Humankind 2.0

a book in progress...
Meditations on the future of technology and society... be published in China in 2016

These are raw notes taken during and after conversations between piero scaruffi and Jinxia Niu of Shezhang Magazine (Hangzhou, China). Jinxia will publish the full interviews in Chinese in her magazine. I thought of posting on my website the English notes that, while incomplete, contain most of the ideas that we discussed.
(Copyright © 2016 Piero Scaruffi | Terms of use )

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Biotech: History, Trends and Future

(See also the slide presentation)

Narnia: How important is biotech for today's Silicon Valley?


It is hard to believe that now the Bay Area alone (according to AngelList) has more biotech startups than the rest of the USA combined, which basically means about 30% of the world's startups. The history of biotech repeats the script of computer technology. It is a typical story of how a technology invented somewhere else, and an industry dominated by European and East Coast multinationals, ends up migrating to the Bay Area. The double-helical structure of DNA was discovered in Britain (by Francis Crick and James Watson), and the Human Genome Project was largely an East Coast enterprise. The big pharmaceutical companies are mostly in Europe (Novartis and Roche in Switzerland, GlaxoSmithKline and AstraZeneca in Britain, Bayer in Germany) or on the East Coast (Pfizer and Bristol-Myers Squibb in New York, and Merck, Johnson & Johnson, Wyeth, Sanofi and Organon in New Jersey), with the exception of Abbott (Chicago) and Lilly (Indiana). There was no major pharmaceutical company in California. The first biotech startup of the Bay Area, Cetus, was founded in 1971 by Donald Glaser, a Nobel-winning nuclear physicist at UC Berkeley who had switched to molecular biology, but for a humble niche of business. Then in 1973 Stanford University's Stanley Cohen and UC San Francisco's Herbert Boyer discovered how to make "recombinant DNA" (DNA made in a lab). The scientific community viewed it as an exciting experiment, but not many saw that it would create a whole new industry. Boyer himself didn't see much of a business opportunity in their discovery. Robert Swanson, a 29-years old employee of the legendary venture capital firm Kleiner Perkins, was the first man to truly appreciate the business potential of recombinant DNA. In 1976 he convinced Herbert Boyer to form Genentech, and the rest is history: in 1978 Genentech cloned human insulin (approved for sale in 1982), and in 1979 they cloned a human growth hormone (they would start selling growth hormone for children in 1985). In 1980 Genentech's IPO was the first biotech IPO. Calgene was formed in 1980 by UC Davis scientists, and Chiron was formed in 1981 by scientists from UC San Francisco and UC Berkeley. On the East Coast, the MIT began spawning Boston-based startups like Integrated Genetics, also founded in 1981. The other interesting story of that early age happened in southern California. Convinced that biotech promised stellar returns, another venture capitalist, William Bowes, founded Amgen (Applied Molecular Genetics) in 1980 in Los Angeles and hired bright young bioengineers. One of them, Taiwanese-born Fu-Kuen Lin cloned the erythropoietin gene, an experiment that led to the development in 1983 of one of the most successful drugs in biotech history, Epogen (for the treatment of anemia), which was approved for sale in 1989. Meanwhile, Larry Souza cloned a substance called G-CSF, leading in 1985 to the drug Neupogen (for the treatment of neutropenia), approved in 1991. By 1992 Amgen had become a billion-dollar pharmaceutical giant. The major difference between Genentech and Amgen is that, from the beginning, Genentech was looking for buyers, and eventually sold to Swiss giant Roche in 1990.

The interesting story is, clearly, that the pharmaceutical corporations were based around New Jersey and New York, and the MIT and Harvard are world-class institutions in chemistry, engineering and biology; but nonetheless the biotech industry as we know it today boomed in California. Obviously the spirit of risk-taking and "think different" was more important than money and number of scientists. Venture capitalists and big companies can create biotech startups anywhere, but then they have to attract bright young engineers. The Bay Area attracts young people from all over the world. Big companies are very good at marketing a product, but not very good at coming up with new ideas. Bay Area startups are very good at coming up with new ideas. Genentech set an important precedent: it created a new idea, but then partnered with a giant corporation to market that idea to the world. This is a pattern that keeps repeating in biotech.

To be fair, there are many startups in the Boston area. Harvard's professor George Church alone co-founded Knome, Alacris, AbVitro, Pathogenica, Veritas Genetics, Joule, Gen9, Editas, Egenesis, enEvolv, WarpDrive... It is only recently that the Bay Area has dwarfed Boston in biotech.

Later, another startup, Gilead Sciences, succeeded quietly thanks to a different model, and it is interesting that most people don't think of Gilead as the biggest biotech success of the Bay Area (but it is). It was founded in 1987 in Foster City by a 29-years old employee of the venture capital firm Menlo Ventures, Michael Riordan, originally to work on gene therapy. Riordan switched business in 1991 to the development of antiviral drugs, realizing the enormous potential of the field. Gilead lost money until 2003, but in 1999 Roche started selling the anti-influenza drug Tamiflu (Oseltamivir), a Gilead invention, and in 2005 the US president George W. Bush requested emergency funding to fight an influenza pandemic and 15% of these funds were spent to buy Tamiflu. It probably helped that Gilean's board included politicians who were close to the Bush administration, and that in 2005 Gilead's former chairman Donald Rumsfeld was Secretary of Defense in the Bush administration. A second Gilead success was Tenofovir (better known as Viread), an anti-AIDS drug that the FDA approved in 2001. In 2009 Gilead was ranked one of the fastest growing companies by Fortune magazine, and in 2013 Gilead hit the market with another success, Sovaldi (Sofosbuvir), for the treatment of hepatitis C, one of the most expensive drugs of all times. In 2015 Gilead was the largest biotech company, with a market value of $150 billion, larger than more established "big pharma" multinationals such as GlaxoSmithKline, AstraZeneca and Bristol-Myers Squibb. Certainly Gilead was blessed with relatively quick approval of its drugs by the FDA during the Bush reign, but Riordan was a business genius when he decided to focus on fighting viruses (harder than fighting bacteria) to treat chronic and global diseases (AIDS, hepatitis C and the flu).

Today the Bay Area has at least nine incubators of biotech startups, including QB3 or "California Institute for Quantitative Biosciences" (opened in 2000 by the Univ of California), Berkeley Biolabs (founded in 2014 by Jayaranjan Anthonypillai), IndieBio (an emanation of SOSVentures launched in 2014 in Ireland), as well as one of Bayer's CoLaborators and one of Johnson & Johnson's JLabs. The main Bay Area centers for biotech are South San Francisco (where Genentech was born in 1976), Emeryville (between Oakland and Berkeley, a natural location for UC Berkeley spinoffs) and the Mission Bay district of San Francisco (where a new medical campus of UC San Francisco opened in 2003). So it is not really a Silicon Valley phenomenon (Silicon Valley is south of South San Francisco), although some of the companies that use software technology to automate biotech are based in Silicon Valley (notably Affymetrix, the startup that invented the "DNA chip", and 23andMe).

In the first half of 2015 the Bay Area witnessed the biggest bubble in biotech since the 1990s, with a record influx of venture capital for biotech startups. In just the second quarter of 2015 Bay Area biotech firms raised $926 million of venture capital. But it wasn't only the Bay Area. The biotech bubble was all over the USA. Among the star attractions of 2015 were Denali Therapeutics (San Francisco, neurodegenerative diseases), Melinta Therapeutics (New Haven, antibiotics discovery), CytomX Therapeutics (Santa Barbara, tumor-targeting antibodies), Regenexbio (Maryland, gene therapy), Dimension Therapeutics (Boston) and Voyager Therapeutics (Boston). The year 2015 was also a record year for mergers and acquisitions in biotech, just like the previous year had been a record year for IPOs (74 IPOs in one year). During the second quarter of 2015 there were 14 biotech IPOs, notably Aduro Biotech (formerly called Oncologic, Berkeley, cancer immunotherapy) and ProNAi Therapeutics (Vancouver, cancer drugs).

After four crazy years of booming biotech, the wake-up call came in the Fall of 2015. By the end of september the Nasdaq Biotech Index had lost 27% of its value from its peak in July. Some financial specialists said that it was simply a consequence of the general drop in the stock market; nothing to worry about. They point out that the biotech boom was fueled by a simple statistical data: in the USA there are 80 million "baby boomers" about to retire over the next 20 years, presumably causing a boom in health care. Those statistics have not changed. These financial analysts also point out that big pharmaceutical companies are developing (or have acquired startups that are developing) exciting drugs to reduce cholesterol, for cancer treatment, to improve the cognitive skills of elderly people afflicted by dementia, etc; all of which are "miracle drugs".

Personally, i think that the success of one specific drug explains the enthusiasm of investors. In 1996 Pfizer introduced the cholesterol-lowering drug Lipitor. By 2012 this had become the world's best-selling drug of all time: it had fetched more than $125 billion in sales (more than the GDP of the country of Tanzania).

I think that some scandals and dubious behaviors show endemic problems in the biotech bubble. During the boom a young man named Martin Shkreli bought the rights to Daraprim, a drug used to treat patients with weakened immune systems caused by HIV. He then started the ghost company Turing Pharmaceuticals, and increased the price of Daraprim from $13.50 to $750 a pill. De facto, he condemned many HIV victims to death. He defended himself as just a businessman (and publicly boasted of his lavish lifestyle). But he was arrested in December 2015 on fraud charges for a previous financial transaction, proving that he was not exactly the kind of person that the public trust with their health, and the kind of person that the investors trust with their money. There are also too many cases that any person with common sense would call "speculation" instead of "health care". For example, the biggest IPO of 2015 was Axovant. First of all, Axovant had only ten employees (the founder's mother and brother plus some friends), but Axovant was immediately valued at three billion dollars. Secondly, Axovant was founded (just a few months earlier) by a young man named Vivek Ramaswamy, who was a former hedge-fund manager (not a scientist) and had founded (just one year earlier) Roivant Sciences, another biotech company. Thirdly, Axovant, like many other biotech startups that went public in the previous year, only had one product. On top of that, this specific drug, an Alzheimer cure, was a drug that Axovant acquired from Glaxo because Glaxo didn't think it was worth anything, If you think that maybe Glaxo made a blunder, Pfitzer was developing a similar drug and it halted development for the same reason: no benefits to patients. Axovant's value has collapsed since IPO.

Theranos, founded in 2003 by a very young woman, Elizabeth Holmes, who never completed her degree at Stanford, promised a new kind of blood test that would be simpler and cheaper. Theranos became a unicorn, which at the peak was worth almost ten billion dollars, and Holmes was hailed by the media as the next Steve Jobs, but in 2015 an article in the respected Wall Street Journal revealed dubious practices at the company and in 2016 a 100-page report by the Department of Health of the USA stated that their practices are simply dangerous to their patients.

Narnia: Is biotech similar to IT?


No, completely different. In fact, the venture capitalists that invest in biotech are typically not the ones who invest in computer technology, and viceversa. The big ones invest in everything, but the smaller ones specialize in either one or the other. The product cycle is very different. First of all, a biotech startup needs much closer ties to the scientific community. Biotech is very much about science, whereas software is mostly about finding an app that goes viral, and hardware is mostly about packing more transistors on a chip. Biotech startups are typically founded by older people. Software startups can be founded by teenagers, but biotech is a complex industry that requires skills that teenagers often don't have. A biotech venture is a complex project that requires skills in chemistry, biology, engineering, marketing, and even skills in dealing with the government agency that approves drugs (the FDA) and with the big pharmaceutical companies (that have the power to sell a new drug worldwide). The cost to develop a new "product" is colossal compared with software. Just the clinical study can easily cost $10 million. According a report published in 2014 by the Tufts Center for the Study of Drug Development, the total cost to develop a new drug (from laboratory research to clinical study to marketing) now exceeds 2.5 billion dollars. The cost to develop a new software app is not even one million dollars. There are strict rules and regulations to obey that don't exist in software. At most, the hardware industry has to worry about not polluting, but the biotech industry has to worry that its new drug does not harm millions of patients. The development of a new biotech drug usually takes between 5 and 10 years: 6-7 years is the norm for the clinical study, and FDA approval can take up to 2 years. The research behind it can take anywhere between 2 and 6 years. The actual production of the drug takes only one year, but what came before the production is a lengthy and costly process. There is nothing in biotech like a hackathon that delivers a prototype. Product development in biotech is slow and painful. It is also harder to compete with established products: you can invent a better aspirin, but how to do convince millions of people to ditch aspirin for your new pill? Marketing a new drug is tougher than marketing a software application: drugs don't go viral the way a software app goes. Drugs don't run on smartphones, don't spread via social media like Facebook. Thousands of new software apps and gadgets are launched every year, but instead very few new drugs are approved every year by the FDA, way less than 100. In general, the risk for the biotech industry is much higher than the risk for the computer industry. But (and this is a big "but") the payback can be astronomical. A new drug can generate billions of dollars of revenues for a long time.

2014 and 2015 were golden years for the pharmaceutical industry because the FDA approved an unusually large number of new drugs: 44 in 2014 (the most since 1996), 51 in 2015 (the most since 1950). The top three companies are always the same (J&J, Glaxo and Novartis), but more than 50% of the new drugs were not developed by "big pharma"; and the share of "biologicals" keeps increasing: 22% in 2013, 35% n 2014 (16 out of 44), 39% in 2015.

Narnia: Is personal genomics the main business of biotech?


There are all sorts of biotech startups. But certainly genomics has attracted a lot of capital and brains. Illumina, that is probably number one in machines that sequence genomes, predicted a market of $20 billions by 2020, but that was before the prices started collapsing. The cost of a personal genetic test-kit was $3 billion in 2003, and there was only one: the Human Genome Project. In 2009 the cost had decreased to $48,000 (Illumina's package). By the end of 2009 only about 100 human genomes had ever been sequenced. Today the four big ones, namely 23andMe (the most famous of genomic startups), Generations Network's AncestryDNA (launched in October 2007), National Geographic's Genographic Project (launched in 2005) and Family Tree DNA (that acquired the technology from the German company DNA-Fingerprint), have already genotyped millions of people. 23andMe genotyped its first customer in November of 2007, and genotyped its millionth customer in June 2015. That's because the cost of genome testing has fallen dramatically. The Human Genome Project (the first analysis of the human genome) had cost an estimated at $2.7 billion over a decade. 23andme was the first startup to commercialize a system to sequence the genome for ordinary consumers. The price of its package is now only $200. In 2014 Illumina announced a genomic test for $1,000.

The story is a bit more complex. First of all, the cost of genome testing keeps falling because the cost of the machines keeps falling. The gene-sequencing market is dominated by three companies: San Diego-based Illumina (that had acquired the sequencing technology of Solexa in 2007), Silicon Valley-based Applied Biosystems (acquired in 2014 by Thermo Fisher Scientific), and 454 Corporation (founded by Jonathan Rothberg in 1999 in Connecticut and acquired by Roche in 2007. Illumina has about 70% of the market. As their machines get cheaper, the product sold to the customers also get cheaper.

That's the good news: DNA testing is getting cheaper and cheaper. The bad news is that it is not very useful: the results of the DNA test are not "actionable", e.g. it doesn't tell you what you should do to reduce the risk of a disease. In fact, often the price does not include an analysis of the results. Neither 23andMe nor Illumina included the "interpretation" of the data with their cheapest genome testing. Competitors of 23andme have multiplied all over the world, but only a few of these "personal-genomic" startups provide comprehensive reports, reports that a health-care specialist can use to make real predictions. What we need now is personal genomics for "predictive" medicine. Two leaders in "actionable" reports are Boston-base Knome (that was the first startup to introduce a commercial human genome sequencing in 2007, which is now part of Utah-based Tute Genomics) and Illumina; but they charge more than $10,000 for this kind of reports. In 2015 Maryland-based Veritas Genetics, which has a research center in Hangzhou, a startup founded in 2014 by George Church (the director of Harvard's Personal Genome Project), announced a package that includes both "sequencing" and "interpretation" of the genome for $1,000. In 2016 Las Vegas-based Sure Genomics, founded in 2014 by people who have no background in biological sciences, announced a way for its customers to do the tests at home with a single saliva test) and receive a more comprehensive DNA test than the one they can get from 23andme. The price is higher than 23andme's package ($2,500) but its report is supposed to be much better.

The next revolution in gene-sequencing will come when we have portable gene-sequencers. That day is very near. In 2012 Oxford Nanopore (founded in 2005 by a professor of Chemical Biology at the University of Oxford, Hagan Bayley) began testing a portable gene sequencer called Minion. It was immediately used by doctors to "read" the genomes of Ebola viruses in Guinea during the epidemics that killed 20,000 people. You can plug the Minion into the USB port of a laptop so it will display the results in real time. It is even better than a "lab-on-a-chip": it is a "lab-on-a-USB-drive". The first release only worked well with short genomes, not with genomes as long and complex as the human genome, but in the near future portable devices like the Minion will come to the market. A biologist can pack it in her backpack and take it with her into the jungle to sequence the DNA of some rare animal; the police can use it to quickly identify unknown organisms that could be biological weapons; NASA can use it to test the surface of Mars for signs of life.

There are many possible applications of genomics. You may want to find out if you have any European ancestors. Or you may want to find out whether you are likely to have Alzheimer. Or what sports you are more likely to succeed in. Boston-based startup Good Start Genetics tells parents if their children are likely to have a serious genetic disease like cystic fibrosis. These are different genomic "apps". When you buy a book on Amazon, Amazon suggests other books. Helix will be able to suggest other "apps" that can give you important information about your DNA. Helix, a 2015 San Francisco-based Illumina spinoff, wants to create the first "app store" for genetic information. The customer of a genetic application will have the choice to share the genetic information delivered by that application with other genetic applications.

Narnia: genomics will make us live longer?


The goal of genomics is, of course, longevity. We want to prevent diseases, and we want to figure out which genes make some people live to a very old age. In 2013 Google funded Calico (which is nicknamed "Google's longevity lab" in Silicon Valley) and hired Arthur Levinson, a former Genentech executive to run it. He was Genentech's chief scientist and from 1995 its CEO until Roche acquired the company in 2009. Levinson hired others from Genentech, notably David Botstein, a geneticist from Princeton University and former vicepresident at Genentech. He hired Cynthia Kenyon, the UC San Francisco biologist who in 1993 discovered that removing a gene doubled the lifespan of worms and that injections of sugar shortened their lifespan. He hired Shelley Buffenstein, a specialist at the University of Texas in animals with exceptionally long lifespans. Calico also acquired access to Ancestry's massive datasets.

Craig Venter founded Human Longevity Inc in San Diego in 2013, a company that has been studied genetic data and already found some correlations between genetic variations and longevity. Ambrosia, a startup in Monterey founded by Jesse Karmazin, has begun experimental transfusions of younger blood to older people because Stanford's scientist Tony Wyss-Coray discovered that rats live longer when given the blood of younger rats.

For me the science of longevity really begins in 1993. In 1993 Cynthia Kenyon at UC San Franisco discovered that partially disabling a gene called Daf-2 can double the life of a worm (to one month instead of two weeks). This became known as the sugar problem because eating sugar basically is equivalent to activating (instead of disabling) Daf-2, and in fact sugar shortens the life of the worm (Kenyon famously warned that "sugar is the new tobacco"). After that experiment many other experiments focused on genes and chemicals of all types that seem to affect the lifespan of animals and plants.

A few years later (1999) Leonard Guarente at the MIT found a gene that increased the lifespan of yeast, SIR2. SIRT1 is the equivalent gene in mammals and the family of these genes, "sirtuin", became known as "the anti-aging gene". Guarente and Cynthia Kenyon founded Elixir Pharmaceuticals in 1999 to make anti-aging products. In 2003 Fritz Muller's team at the University of Fribourg in Switzerland discovered that suppressing an enzyme called TOR (Target of Rapamycin) increased the lifespan of worms. Zelton Dave Sharp at the University of Texas proved that the same is true in mice: give them rapamycin (the inhibitor of TOR) and they live longer lives. In 2007 Guarente's pupil David Sinclair showed that the two substances (sirtuin and rapamycin) target the same "longevity pathway". Biologists started searching for "sirtuin activators" and "TOR inhibitors". There was one obvious TOR inhibitor, rapamycin, but no obvious sirtuin activator. In 2003 Sinclair had proposed resveratrol as sirtuin activator, a substance that is found in red wine, and had founded Sirtris in 2004 to make anti-aging drugs based on resveratrol. In 2008 GlaxoSmithKline bought Sirtris, but now the scientific consensus is that resveratrol doesn't work, especially after a study conducted in 2014 by Richard Semba's team of Johns Hopkins University. On the other hand, rapamycin (known as "rapamune" by pharmacies around the world) definitely works on mice. It was confirmed by another study in 2009 led by Richard Miller of the University of Michigan but conducted by three separate teams in three different universities. These studies are interesting but we should never forget that dying is not really a disease. What happens to everybody is not a disease: it is the norm. Everybody dies, so that is not a disease in the sense that diabetes or malaria are diseases. When we look for a drug to cure malaria, we are looking for a drug to turn malaria victims into normal people. When we look for a drug to make us immortal, we are looking for a drug to turn people into something else, not people anymore.

The search for longevity, and possibly even immortality, has led scientists to a tiny polyp, the hydra. This is the only animal that does not age and therefore does not die of old age. It would be immortal if no predator killed it. What makes the hydra "immortal" is that its stem-cells keep proliferating. In 2012 Thomas Bosch at Kiel University discovered that this property of the hydra is due to the so-called FoxO gene, which all animals have but only in some individuals it works overtime. Scientists have long suspected that this gene is important for longevity because a 2008 study by David Curb's team (mainly Bradley Willcox) at the University of Hawaii showed that this gene seems to be particularly active in centenarians. Some day with a bit of genetic manipulation it may be someday possible for humans to regenerate stem-cells and increase longevity. (Bad news for tall people: in 2014 a study by the same team showed that FoxO3 was "inversely associated with height", i.e. the taller you are the shorter your life expectancy. But good news for tea drinkers: the same team showed that drinking tea helps activate FoxO gene expression, i.e. live longer lives. But, don't panic, all these studies are very preliminary).

Another interesting animal for the study of longevity is the jellyfish called "turritopsis". It is the only known animal that can reverse its life cycle and rejuvinate. This animal is not immortal (it does die) but for brief periods it can get younger, and that's certainly something that many elderly people would like to do.

A chemical called NRF-2 became famous when in 2010 Rochelle Buffenstein at the University of Texas showed that it is a key actor in the aging process while protecting the body from diseases. In 2016 Linda Partridge of University College London lithium prolongs the life of fruit flies because (as known since 1996) it blocks a chemical called GSK-3 (that is suspected of being involved in the aging process) while at the same time stimulating that famous NRF-2. In 2016 Manfred Kayser in the Netherlands discovered that a gene called MC1R is responsible for "looking older".

Potentially, this is big business, so no surprise that Craig Venter opened Human Longevity Inc (in San Diego in 2013) and Jesse Karmazin started Ambrosia (in Monterey in 2016) to investigate the finding by Tony Wyss-Coray at Stanford University that a transfusion of younger blood makes old mice live longer. Anti-aging treatments are offered by hundreds of clinics but here are all unregulated therapies. Meanwhile the record of longevity still belongs to Jeanne Calment, who died in 1997 at the age of 122. Nobody has managed to live longer╬Ý╬§.

Potentially, this is big business, so no surprise that Craig Venter opened Human Longevity Inc (in San Diego in 2013) and Jesse Karmazin started Ambrosia (in Monterey in 2016) to investigate the finding by Tony Wyss-Coray at Stanford University that a transfusion of younger blood makes old mice live longer. Anti-aging treatments are offered by hundreds of clinics but here are all unregulated therapies. Meanwhile the record of longevity still belongs to Jeanne Calment, who died in 1997 at the age of 122. Nobody has managed to live longer.

Narnia: does genomics create another problem for privacy?


Privacy is not necessarily at stake, just like your doctor knows a lot about you but that remains confidential.

The fact that may disturb you is that these DNA testing companies make money out of your genes. Genomic companies are ammassing a treasure: the genomes of their customers. The customer of 23andMe or Ancestry is paying for the DNA test in two pays: with some money and with information about her genome. Genomic companies carefully collect the genomes of all their customers: that will be valuable information to analyze who has the "best" genes for some application. Everybody's favorite application is longevity. Companies that are looking for the longevity genes need to collect genetic samples from millions of people and then check which genes are prevalent in the people who live to be 100. The media paid a lot of attention when in 2012 Amgen purchased the genomes of 160,000 inhabitants of Iceland, but that's nothing compared with the database of genomes that have been amassed by Ancestry and by 23andMe, which has more than one million genomes. And of course when Google entered the fray with Calico people immediately thought of Google's ability to collect "big data".

There is already a gold rush for "rare genes", for genetic mutations that give some individual some advantages that others may want. For example, some individuals were publicized by the news media in the USA because they don't feel pain. That's actually a disease, because their lives are constantly in danger: pain is a useful signal from our body that something is wrong, and you can die if you don't get that signal; but, if we could understand which genetic mutation causes that "disease", we would be able to create a new family of pain-killers. Those "rare genes" are worth millions. They belong to people who took the DNA test and who will not receive a penny from the inventions due to their rare genes.

On the other hand, the information about our genomes can be valuable to save lives. Rare genes are interesting, but also important is to study "rare diseases". Rare diseases are not well understood because few people have them. If these people volunteer their genomes, scientists can work on a much bigger dataset.

Let's face it: if you get your genome sequenced, you can do very little with it. You do it mainly for fun. It is "entertainment", not "health care". The reason that it is not very useful is that scientists know too little about the correlation between genes and diseases. We need to have millions of genomes and for each one we need data about the person's health. Only then will we be able to find meaningful and useful correlations. This has become a "chicken and egg" problem. My motivation to get my genome sequenced is very low because i know that it is not very useful; but it is not very useful because we have very few genomes sequenced and data about these people's health. At this point i think that protecting my privacy is not a high priority. The high priority is to convince me to get my genome sequenced and then provide information about my health for the rest of my life, so that i can help scientists find correlations and make the test more useful in the future. At this point society should invest more in motivating people to get their genome sequenced than in protecting their privacy.

In 2012 Britain launched the 100,000 Genomes Project via a company called Genomics England: people with rare diseases can upload their genomes via an app, PanelApp, to help scientists who study the genetics of rare diseases.

Scientists are increasingly interested in studying populations of genomes, not just individual genomes. The Human Genome Project was a big success and delivered a "blueprint" of how the human software works; but we are all different: there are genetic variations between person and person. Those genetic variations can make the difference between living a healthy life and dying of cancer at a young age.

The Personal Genome Project is an interesting merger of crowd-sourcing and biotech ideas. Originally launched in 2005 by George Church at Harvard University, its goal was to enroll thousands of volunteers willing to have their complete genomes and medical records published on the Internet, so that researchers all over the world could study them and find correlations among genes, environment and diseases. By 2015 the project had enrolled more than 16,000 volunteers.

In 2008 David Altshuler of the Broad Institute of Boston, which is a joint laboratory of the MIT and Harvard University, and the National Human Genome Research Institute (NHGRI) in Maryland launched the 1000Genomes project ( to study human genetic variation. Several laboratories helped, including BGI-Shenzhen. This project collected the genomes volunteered by 1,000 people from all over the world and analyzed the differences. But 1,000 is really a drop in the ocean when we know that millions of people have already sequenced their genomes. In 2014 one of the project's scientists, the Israeli-born computational biologist Yaniv Erlich, moved from the MIT to the New York Genome Center, a spin-off of Columbia University, where in 2015 he and Joe Pickrell launched (, another non-profit project to collect people's genomes and study genetic variation. This time it was truly a case of "crowdsourcing": asking people from all over the world to upload their DNA so that scientists can study it. In 2015 Yaniv Erlich published the paper "A Vision for Ubiquitous Sequencing" in the Genome Research magazine.

The crowdsourcing experiment then migrated to the West Coast, where people started talking about the "Internet of DNA" or "Internet of Living Beings" (in contrast with the "Internet of Things"). The hero in California is David Haussler of the University of California in Santa Cruz, who in 2013 partnered with David Altshuler of the Broad Institute to create the Global Alliance for Genomics and Health. The idea is to set up a peer-to-peer network of scientists and volunteers to work together on understanding genetic variations. In 2015 the MIT Technology Review had an article about this project: "A global network of millions of genomes could be medicine's next great advance."

And finally in 2016 a big pharmaceutical company, AstraZeneca, launched a project to sequence 2 million genomes (in collaboration with Venter's new startup Human Longevity, Britain's Wellcome Trust Sanger Institute, and Finland's Institute for Molecular Medicine).

A simple example of the benefits of these databases came in 2016. From 2006 until 2010 British scientists have collected blood, urine and saliva samples from 500,000 adult volunteers for the project UK Biobank, hosted at the University of Manchester and directed by Rory Collins of the University of Oxford. The scientists keep monitoring the health of these volunteers. Using those data, in 2016 the University of Edinburgh identified two genetic variants that can shorten a person's life by 3 years. This finding affects about 3 in 1000 people.

In 2011 the National Research Council of the USA published a report titled "Toward Precision Medicine - Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease." In 2015 the US government launched the "Precision Medicine Initiative", whose goal is to catalog the genomes of one million people. Precision medicine is about customizing treatment based on individual genes. The goal is "pharmacogenomics": the right drug for the right patient at the right time and at the right dose. The idea behind it is that some genes cause a predisposition to some diseases. The only way to find out if this theory is correct is to find the genes shared by people with certain diseases. It has been more than ten years since the human genome was sequenced, but we don't really have a success story in precision medicine. In 2012 the USA approved a drug by Vertex, Ivacaftor, for curing cystic fibrosis, one of the most expensive drugs ever developed by the pharmaceutical industry, but the results have been disappointing: other (more traditional) treatments that cost a fraction of ivacaftor seem to achieve the same results. Precision medicine needs big data that today are still missing. The 2011 report encouraged two new repositories: an "Information Commons" that will make data on large populations of patients available to all scientists; a "Knowledge Network" that will highlight inter-relationships. An important tool is the GWAS (Genome-wide Association Study), that tries to relate common genetic variants in different individuals to traits. The GWA catalog (originally maintained by the National Human Genome Research Institute or NHGRI, but now hosted by the European Molecular Biology Laboratory-European Bioinformatics Institute or EMBL-EBI) was set up in 2008. It is a database that associates "single nucleotide polymorphisms" or SNPs to traits.

Precision medicine could also help "predictive" medicine. Today most of the money spent by the health-care system is spent after people get sick; and most of the cost to the government and to society happens after people get sick. It would be nice to reverse this statistic, and get to the point when most of the money is spent in preventing the disease. That will be possible when we know which genetic variations are more likely to cause a disease.

We also need a more fair sample of genomes. The vast majority of people who have had their genomes sequenced so far are of European ancestry. Therefore, the millions of genomes available to the genomic startups are not very useful to understand non-white people.

In 2016 Mark Zuckerberg donated $600 million to BioHub, that hired Stephen Quake of Stanford University as president. BioHub's goal is to create a map of the millions of cells in the human body.

Narnia: What kind of progress is happening in the laboratory machines?


More than machines. We are putting the entire laboratory on a chip. Laboratory automation is a big thing. Genomics would not be getting cheaper without it. The Bay Area now is home to many startups specializing in automation for biotech laboratories. The traditional "automation" of a laboratory replaced the eyes and hands of the technicians with automated workstations; but today "automation" really means a new type of laboratory.

Affymetrix introduced the first "DNA chip" in 1994, the GeneChip, based on photolithography, thanks to the 1991 breakthrough by its founder Stephen Fodor when the company was still called Affymax. Affymetrix introduced the first DNA chip in 1994, the GeneChip. Pat Brown and Mark Schena at Stanford University worked on a different method (a robotic method) and in 1995 introduced the term "DNA microarray". Edwin Southern at Oxford University (and the founder of Oxford Gene Technology in 1995) was working on a technique based on inkjet printing, and so did Alan Blanchard at the University of Washington, who in 1996 invented the technique adopted by Agilent. Nimblegen Systems adopted an improved version of Affymetrix's technique. Illumina adopted the method invented by David Walt at Tufts University in 1998. They all wanted to leverage techniques originally developed for silicon semiconductors in order to improve the speed at which DNA tests could be performed. Their microarrays made it possible to simultaneously test thousands of molecules. The microarrayers that performed such DNA tests were descendants of the first array robots built in 1987 by Hans Lehrach at the the Imperial Cancer Research Fund in England.

The next step in biotech automation after the DNA chip/microarray was the "lab on the chip". Since the 1960s there had been a lot of progress in "micro-electro-mechanical systems" (MEMS). These devices were already around before the invention of the microprocessor. In 1964 Harvey Nathanson at Westinghouse made the first MEMS, and the first success story of MEMS was the "thermal inkjet" technology that Hewlett Packard debuted in 1979, followed in 1993 by Analog Devices' micro-accelerometer (widely used in many industries today, for example in airbags). In 1983 Richard Feynman delivered one of his famous lectures, this one titled "Infinitesimal Machinery". Initially MEMS simply exploited the fabrication technologies of the semiconductors industry, but in 1999 Lucent introduced the all-optical router and triggered the boom of optical MEMs of the 2000s. But the enabling technology was "microfluidics", the ability to make millions of microchannels ("micro" in the sense that they measuring micrometers in diameter) that handle very tiny quantities of fluids. This was the result of a US military program: the Defense Advanced Research Projects Agency (DARPA) wanted a system to quickly detect biological and chemical weapons and so in 1997 created a program called "Microflumes" to fund research in microfluidics. In 1978 James Angell at Stanford had already been working on "micromachines" and one of his students, Stephen Terry, in 1979 had unveiled what can be considered as the first "lab on a chip", a device for separating, identifying and analyzing the components of a gas (originally, it was commissioned by NASA and meant to analyze the atmosphere of Mars. But progress in MEMS and in microfluidics led to today's "lab-on-a-chip" products. In 1999 Hewlett-Packard's spinoff Agilent introduced the first commercial "lab-on-a-chip" product, the 2100 Bioanalyzer. Even more important was the Agilent 5100 of 2004. These were the vanguard of systems that enabled biotech startups to conduct analysis of thousands of DNA and protein samples per day. After the success of the Human Genome Project, the goal shifted to putting the whole human genome on a microarray. In 2002 Wilhelm Ansorge at the European Molecular Biology Laboratory (EMBL) in Germany succeeded.

In 2004 the first commercial microarrays with the whole human genome became available from Affymetrix (whose GeneChip was still dominating the market for microarrays), Agilent (that still relied on the technique based on inkjet printing), Applied Biosystems and Illumina (all based in California, the first three in the Bay Area). Technically speaking, the first company to offer a whole-human-genome microarray was probably Wisconsin-based NimbleGen Systems in 2003. Then the battle began for lower prices and for better "annotation" of the genes. In 2009 Arrayit, founded in 1993 as TeleChem International in Sunnyvale by Rene Schena and Todd Martinsky, introduced the H25K.

There is probably going to be more progress because interest in "labs on a chip" is enormous both in the industry and in the government. For example, in 2011 DARPA launched another program, this time to create "human-on-chip" platforms, i.e. more comprehensive and evolved "labs on a chip".

For most biotech tasks we still need to handle liquids in a real-world laboratory. This can be done by an expensive human, who works only some hours and on some days, or by a robot, who works nonstop. There are already robots that can do what a biologist does manually, but they cost $100,000 and more. The goal now is to lower that cost so that small laboratories can afford it. OpenTrons is an interesting story. It was founded in 2013 by Will Canine, a graduate from New York University who was also an activist of the anti-capitalist "Occupy" movement and a "biohacker" at the Do-It-Yourself biotech space Genspace, with the Chinese robotics expert Chiu Chau and the software engineer Nick Wagner. OpenTrons was incubated in Shenzhen in 2014 by Haxclr8tr and initially funded via a Kickstarter campaign. It is now based in New York, Their goal is to build an affordable robot for performing biotech experiments. Their project is clearly inspired by the software hackers of Silicon Valley: it is open-source and provides a form of "rapid prototyping", except that they are not prototyping software but life forms. OpenTrons' robot is built around an open-source Raspberry Pi computer (originally conceived in Britain in 2012 for schoolchildren by a charitable organization based around Cambridge University) and open-source software. They hope to make it cheaper than a laptop computer so that the DIY community can use it.

The other promising technology is the cloud. Cloud-based biotech completely eliminates the laboratory for the customer. Transcriptic, founded by Duke University graduate Max Hodak in 2012 in Palo Alto, conducts laboratory tests using robots on behalf of scientists who can be located anywhere in the world. They have the robots, they have the laboratory, they handle all the computation. You simply submit the specifications of your experiment and they perform it on your behalf.

Narnia: What is the status of Synthetic Biology?


The first international conference of Synthetic Biology was held in 2004 at the MIT, but the field was still in its prehistory. I think that "history" truly begins for Synthetic Biology in 2005 when Jay Keasling's team at UC Berkley produced artificially the acid needed to produce an anti-malarial drug called artemisinin (the one for which Zhejiang scientist Youyou Tu was awarded the Nobel Prize in 2015). The plant Artemisia Annua, used for centuries in China, grows very slowly, but science was now able to manufacture the anti-malarian drug in the laboratory. All the new malaria pills use this substance. This was the first time that an experiment of Synthetic Biology had an impact on the world. In 2006 there was another success story, although less publicized: Chris Voigt's team at UC Berkeley engineered a bacterium to target cancer cells in the human body. In 2007 Craig Venter's team in Maryland carried out a full-genome transplant: they transplanted the genome of a bacterium (Mycoplasma Mycoides) into the cytoplasm of a different bacterium (Mycoplasma Capricolum). In 2010 Hamilton Smith's team at the Craig Venter Institute reprogrammed a bacterium's DNA. That bacterium's parent was a computer. This experiment told the world that science could now design custom bacteria on a computer and then build them in the laboratory.

We can envision a day when individuals will be able to program a living organism on a smartphone, upload the design to the cloud and order the living organism from a laboratory that will download the design from the cloud and use robots to manufacture the living organism.

If you think like a computer scientist, by 2010 biotech had reached a point where it was easy to read the genetic data (DNA sequencing) and easy to write new genetic data (DNA synthesis) but it was still difficult to edit genetic dada (the genome). One of the earliest methods, the ZFN method, was exclusively owned by Sangamo Biosciences. The TALEN method invented in 2011 by Dan Voytas of the University of Minnesota and by Adam Bogdanove of Iowa State Univ was much faster, and hailed as dramatic progress. But in just one year an even better, easier, cheaper and faster technology emerged: Jennifer Doudna's laboratory at UC Berkeley and Emmanuelle Charpentier's laboratory in Sweden invented the CRISPR technique. CRISPR startups, offering "genome-editing platforms", started popping up everywhere. The first one, in 2011, was Rachel Haurwitz's and Martin Jinek's Caribou Biosciences, a spinoff of Doudna's lab at UC Berkeley, but within a few years similar startups spread from Switzerland (CRISPR Therapeutics, founded in 2013) to Boston (Editas Medicine, a 2013 spin-off of the Broad Institute, and Intellia Therapeutics, founded in 2014 by Caribou itself). In 2015 scientific journals published more than 1,300 papers on CRISPR.

DNA synthesis itself is being revolutionized by the combined forces of miniaturization, automation and software. All the companies that want to do "rapid prototyping" in polymerase chain reaction (PCR) or gene sequencing need some raw materials called oligonucleotides. These are short DNA molecules that machines can use to test hypotheses. A traditional limit was the cost of these "oligos". A hot startup in San Francisco is Twist Bioscience, founded in 2013 by Emily Leproust, a veteran of Agilent, by Complete Genomics's hardware engineer Bill Banyai and by Bill Peck, who worked at both Complete Genomics and Agilent. They want to produce synthetic DNA on a massive scale using a silicon-based method to make oligos. In 2015 Twist Bioscience got an order of 100 million base pairs of DNA (the equivalent of millions of oligos) from Ginkgo Bioworks that was about 10% of the world's global gene market. In 2016 they acquired Israel's Genome Compiler that has a technology to design genes, so now Twist can let people design genes and then it can print them on demand. Meanwhile, the largest gene-synthesis supplier in the world is Nanjing-based GenScript that provides custom gene-synthesis for scientists thanks to a sort of assembly line for oligo synthesis. Right now synthetic biology is still using "cut and paste" technology to create new organisms; but, as costs continue to decline, some day it might be more effective to print a new genome rather than edit an existing one.

In 2014 a team led by Jef Boeke at Johns Hopkins University for the first time succeeded in synthesizing (creating) a chromosome in a complex organism (only yeast, but still a major step towards creating living organisms). The final goal is to create the world's first artificial genome, the genome of the yeast (16 chromosomes for a total of about 5,000 genes). The project is now distributed around the world. For example, Junbiao Dai, Boeke's collaborator at Tsinghua University, is synthesizing the 12th chromosome, the largest of the 16th and the one They have developed new techniques that could be more important than their official goal. For example, they invented "gene scrambling", which is a mix of synthesis and editing: it creates a new organism out of the same genes. This can be useful to simulate what happens when some genes are not in the right place. Boeke's collaborator Patrick Cai at the University of Edinburgh is trying to add a 17th chromosome to the 16, a chromosome that should add a new function to the yeast. Boeke's student Jingchuan Luo is trying to pack all 16 chromosomes in just one. It is not clear if these things are possible: is there a minimum number of chromosomes for the yeast? is it possible to add a function to an existing organism? The genome of the jumper ant of Australia (myrmecia pilosula) is made of just one chromosome. The blue butterfly (polyommatus atlanticus) is the species with the highest chromosome number: at least 223. Why some animal species have only one chromosome and some have hundreds?

Narnia: The most famous application of biotech is genetically-modified food. Are you scared of it?


Some people call it the "Food 2.0 Revolution". First of all, we have been "genetically engineering" plants and animals for a long time. Almost all the fruit that we eat today is genetically engineered: it didn't exist thousands of years ago. Almost all the dogs are genetically engineered. The British kept experimenting until they produced dozens of dog varieties that didn't exist in nature. Farmers have always experimented with crops. They kept improving them with traditional methods of breeding. There are obvious differences when you do the same in a laboratory, but it is important to realize that there are many more similarities than differences. When people don't want to eat something because it is not "natural", they are lying to themselves: most of the food that they eat is not "natural", in the sense that it was created by humans over many generations of "genetic" experimentation.

GMO also suffers from another form of bad publicity: it has helped the big chemical corporations make billions of dollars.

The obvious advantage of creating new food in the laboratory is that it takes only a few months instead of 10-20 years. By definition, the plant created inside the laboratory is also more "scientific" than the plant created by the farmer by "trial and error": the scientist knows why the plant grows, whereas the farmer only knows that his experiment either it worked or didn't work, but doesn't really understand why.

This is also what scares people. People assume that the traditional process, precisely because it takes so long to create a new variety of potatoes or tomatoes, is less dangerous: there is enough time to test it, a little bit at a time. This may be true, but there is a simple reason why we cannot afford to wait 10-20 years to improve our plants. Climate change is happening faster and faster. We need to adapt our crops and fruit to the rapid fluctuations of climate change, and genetic engineering can do that. Climate change is bringing higher temperatures to places where plants need a cold season, and too much rain to places where plants cannot defend themselves against the parasites and diseases that spread with humidity. There seems to be evidence that catastrophic storms are becoming more frequent. Climate scientists tell us that extreme weather will become a common occurrence, not a rarity. For a farmer this means that the weather is becoming too unpredictable. David Lobell at Stanford and Wolfram Schlenker at Columbia University have published studies about the effects of climate change on food production, such as "Climate Trends and Global Crop Production Since 1980" (2011) that showed a decline to corn and wheat production due to climate change. Think of rice, that is the main ingredient of the diet of about 40% of the world's population. If rice succumbs to climate change, we will have starvation again in countries like India and China. In 2009 British scientist Paul Quick from the University of Sheffield was appointed to run the "C4 Rice Project" at the International Rice Research Institute (IRRI), a consortium of 12 laboratories in 8 countries. This project, funded by the Bill & Melinda Gates Foundation. This project aims to improve rice with a technique called "C4 photosynthesis". Meanwhile, Eduardo Blumwald, a scientist from UC Davis, is experimenting in California's Central Valley, one of the world's most productive agricultural regions that has recently experienced extreme drought and heat conditions. Blumwald wants to engineer plants like rice that can tolerate extreme variations in heat and drought, and that can grow in soils with high salinity.

In California there is also a "green" movement to redesign the food supply so that it uses less land, water and energy. It turns out that meat is the worst food that humans can possibly eat in terms of land use, water use and energy use. So there is also research into creating plant-based substitutes for animal-agriculture products, in other words "fake meat". A startup that became very popular in San Francisco is Hampton Creek, founded in 2011 by social worker Josh Tetrick and animal-rights activist Josh Balk. Their animal-free replacement for the chicken egg is sold in many stores and their egg-free "Just Mayo" mayonnaise is used in many sandwich places. They were viciously attacked by some big lobbies and corporations, but they won their legal battles. Egga are a big market: $60 billion in the USA alone. Venture capitalists are now funding several food-related startups. Hampton Creek is not a biotech company because it simply looks for a vegetarian way to provide the same nutritional value and taste of animal products, but its success story has inspired biotech companies to achieve the same results in the laboratory; and it has convinced venture capitalists that people will switch to plant-based substitutes if that option is available.

The fear of genetically-engineered food remains, but it is largely based on superstition. Very few things have been subjected to so many studies like genetically-modified food. And yet, in more than 15 years, no transgenic crop has been found dangerous for humans. The majority of corn, soybeans and cotton produced in the USA have been created in laboratories using a gene from a bacterium. 81% of the soybeans of the world are genetically modified. 96% of India's cotton is genetically modified. Even better: the new TALEN and CRISPR techniques can modify a plant without the addition of genes that come from other living beings. They offer an easy and precise way to edit (alter) the plant's genes so that it will be drought-resistant or something else. In theory, this should reduce the chances of "transgenic" catastrophes. If you object to editing the genes of a plant, then you should also object to gene therapy for humans. They are, ultimately, the same process.

In fact, the US Department of Agriculture is still undecided whether crops created with the CRISPR and TALEN technique should be considered GMOs (Genetically Modified Organisms). I am sure that many groups will pressure the USA to classify these foods as GMO, but the fact that it is not so clear tells you that even the traditional reasons to fear GMOs are not there anymore.

Using genome-editing tools like TALEN and CRISPR, scientists can "genetically engineer" a lot more vegetables. For example, in 2014 Gao Caixia in China used both TALEN and CRISPR to create a strain of wheat that is fully resistant to powdery mildew. This experiment was followed by genetic engineering of tomatoes, soybeans, rice and potatoes.

But for farmers a "gene drive" technique might be even more important than a "gene-modification" technique. Genetic changes usually take many years of even millennia to spread in a population. A "gene drive" is a mechanism to spread a genetic change quickly inside a population. A "gene drive" could be used by farmers to wipe out undesired weeds. For example, we can (theoretically) genetically-change mosquitoes so that they will not spread malaria or genetically-change ticks so that they will not spread lyme disease, but then we have no way to make sure that this genetic change (these "good genes") will spread to all mosquitoes and all ticks of those dangerous species. Mendel's classical rules say that this is impossible in nature, but genome-editing changes the rules. The first experiments that seem to have succeeded in creating a "gene drive" was carried out in southern California. At the end of 2014 Ethan Bier and Valentino Gantz at UC San Diego used the CRISPR technique to trigger a gene drive in fruit flies. That was just a conceptual experiment, but a few months later Anthony James at UC Irvine in southern California used their experiment to introduce a "malaria-blocking" gene in a mosquito so that this new gene will spread to almost all its offspring. This scientist has spent 20 years of his life trying to create anti-disease mosquitoes in the laboratory.

Of course, this sounds even more terrifying to those who are afraid of genetic engineering. What is more terrifying to the mothers who live in places infested with malaria is that their children might die of malaria.

Before we criminalize genetically-modifed foods, let's remember that our foods today are not natural at all. Only chemical engineers can understand the labels of the foods at the supermarket. Read the labels, and you will find mysterious ingredients such as: butylated hydroxyanisole, butylated hydroxytoluene, polysorbate, sodium benzoate, sulfites, potassium sorbate, nitrates, etc. Our supermarket foods are full of artificial colors that make foods look pretty, artificial flavors that mimic the taste of natural ingredients, preservatives that prolong the shelf life of foods, and replacements for sugar like high-fructose corn syrup and calorie-free sweeteners. Some of these are possible carcinogens, some may weaken the immune system, some may cause allergies and possibly infertility, and some may even cause DNA damage. You would never eat these things if i asked you to eat them, but millions of people eat them every day. Since 1983 most cheese in the USA and Britain is made using chymosin (rennet) that has been genetically engineered, a much more humane method than the traditional method of obtaining it from the stomach of calves (a method still practiced in continental Europe). And, if you eat meat, you mostly eat animals that have been grown in industrial facilities and fed industrial food. Being afraid of genetically-modified foods when our diets are basically chemical experiments is a bit funny.

Narnia: What are the other applications of synthetic biology?


These genome-eiditing technologies can have an even bigger impact beyond food. Perhaps the first successful application of the CRISPR technique was the experiment in 2014 by Chad Cowan and Derrick Rossi at the Harvard Stem Cell Institute. They took some human cells (some stem-cells that form blood and some "T-cells" that contribute to the immune system), edited them with the CRISPR technique, and then introduced the gene-edited cells into HIV patients. These "genetically engineered" cells are designed to fight the HIV. There is something in human cells that is vulnerable to HIV: remove that "something" and you get an HIV-resistant immune system. At the same time Daniel Anderson's team at the MIT used CRISPR (in mice) to correct a genetic mutation that causes a serious disease called "tyrosinaemia5" in mice. In 2015 JuanCarlos Izpisua-Belmonte's team at the Salk Institute in San Diego used CRISPR to remove HIV from infected cells before it could start replicating. Gene editing on a human being with CRISPR-Cas9 was first performed by Lu You at Sichuan University in Chengdu. These are the first steps towards using CRIPSR technology for gene therapy. Of course it will take years before these techniques are approved for use on human beings. Nobody today can predict the side effects.

There are a number of startups working on genetically-modified bacteria that humans could just swallow. In 2000 MIT's scientist James Collins turned a bacterium into the equivalent of an electronic "flip-flop" switch. Basically, he reprogrammed a bacterium the way a software engineer programs a computer. The startup that Collins founded in Boston, Synlogic, is engineering a bacterium capable of destroying ammonia. Ernest Pharmaceuticals (Boston) and GenCirq (San Diego) are engineering bacteria to treat cancer. Trayer Biotherapeutics (Maryland) is redesigning yogurt bacteria to treat a rare disease. ActoGenix (Belgium), acquired in 2015 by Intrexon, is engineering bacteria to treat allergic and autoimmune diseases.

We can even use these biotechnologies to create new materials. Without using these new technologies (that are still out of the reach of the average laboratory) several biotech startups have already created materials that didn't exist before. Refactored Materials (later renamed Bolt Threads), a 2009 spinoff of UC San Francisco (scientists Dan Widmaier, David Breslauer and Ethan Mirsky) manipulates bacteria to manufacture spider silk, stronger than steel but very light, that can be used for making clothes. Zymergen, founded in 2013 in Emeryville by two Amyris alumni, Jed Dean and Zach Serber, had discovered a way to insert DNA into bacteria, and to create microbes that can create new materials. Modern Meadow, started in New York in 2011 by Gabor Forgacs of the Univ of Missouri, wants to "print" meat and leather without killing animals.

The startup that makes synthetic biologists dream is Ginkgo Bioworks, founded in 2008 in Boston by MIT's synthetic biology pioneer (and iGem co-founder) Tom Knight with other MIT alumni (Jason Kelly, Reshma Shetty, Barry Canton, and Austin Che), that calls itself "the world's first organism-engineering foundry". A foundry is usually a place where semiconductor chips are manufactured on behalf of companies like Intel. Intel sends the design, and the foundry delivers the electronic chip. Ginkgo Bioworks opened a "foundry" to make living organisms: the customer sends the design, and Ginkgo delivers the organism. So far it has produced synthetic perfumes, cosmetics and foods. Both Zymergen and Ginkgo want to become biotech factories that can produce all sorts of consumer goods in their robotic laboratories. This could revolutionize the chemical industry. Today a lot of materials are obtained via chemical engineering from fossil fuels. Basically, the chemical industry "re-engineers" natural materials (like petroleum) to become artificial materials (like plastic) that are useful to humans Unfortunately this process is not "green": it generates a lot of pollution; and it builds materials that are not "green", i.e. that do not decompose (like plastic). Ginkgo could potentially produce materials that are "green" and using a "green" process.

There are applications of biotech that are not easy to imagine until someone tries them. For example, one classical problem of medicine is how to operate on the brain. Our body is designed to minimize the risks of infection and attacks from the outside, especially inside the skull. The brain is isolated from the blood stream in order to avoid that "attackers" can use the bloodstream to attack the brain. This is a great line of defense, but makes it impossible for doctors to deliver medicines to the brain via the bloodstream. The only way for doctors to help the brain is brain surgery. It would be an improvement if doctors had a way to enter the brain and deliver genes into the nuclei of brain cells in order to reprogram them. For example, doctors could deliver genes that create antibodies inside the brain. In 2015 Ben Deverman's team at Caltech took a harmless virus named AAV9, created millions of genetic variants of it (through the "polymerase chain reaction" or PCR, invented in 1983 by Kary Mullis and still widely used in laboratories), and invented a new technique to test these millions of variants. This was natural selection at lightining speed: their technique selects the variants that are capable of entering the brain brain and of delivering genes to brain cells. Imagine if we could do something like this for all the cases in which today surgery is required to repair a body organ.

Narnia: What is the future of regenerative medicine?


This is another field that has had many false "starts". The appeal is obvious: a future in which we can grow replacement tissues (for example, to replace skin that we burned) and body organs. Every year 1.2 million people suffer from an organ that is collapsing. Only 10-20% get an organ transplant. Regenerative medicine can save over one million people annually.

This is a field that was born in 1981 when, independently, Martin Evans at Cambridge Univ and Gail Martin at UC San Francisco isolated embryonic stem cells of the mouse. Stem cells are the mothers of all the cells of our body. Once they specialize in a specific job, they cannot be used to make cells of a different kind, but, before they specialize, when they are still "pluripotent", they can develop into all cell types. The stem cells of the embryo are pluripotent. The stem cells of your nose are adult stem cells: they can develop into nose cells, not into liver cells. For more than a decade these studies were limited to other animals, but then scientists started studying the human embryonic stem cells. William Haseltine coined the expression "regenerative medicine" in 1992. It wasn't until 1998, though, that James Thomson at the University of Wisconsin isolated human embryonic stem cells. This step made it possible for scientists to generate all the building blocks of our body in a laboratory. At this point there was enough commercial interest in the possibilities of regenerative medicine that several companies were created all over the world. In retrospect, some of the most influential were: Cellectis (France, 1999), Mesoblast (Australia, 2004), Capricor Therapeutics (Los Angeles, 2005) and Pharmicell (Germany, 2006). In 2004 the state of California launched a California Institute for Regenerative Medicine that has been helping research in the field. Another decade went by, with a lot of controversy about the ethical aspects of stem-cell research, and in 2007 Shinya Yamanaka at Kyoto University in Japan converted adult human cells into pluripotent stem cells. His seminal paper was titled "Induction of Pluripotent Stem Cells" and that became the term for the technology of genetically reprogramming cells to become pluripotent: "Induced Pluripotent Stem" cells or iPS cells. These cells are very similar to embryonic stem cells. We don't need to get embryonic stem cells from humans, we can create them in the laboratory. Cellectis immediately licensed Yamanaka's patents In 2011 Pharmicell got approval for the first stem-cell drug, called "Hearticellgram-AMI". Today Mesoblast, that uses its own proprietary kind of cells, is probably the best known actor in regenerative medicine.

Madeline Lancaster at Cambridge University is using pluripotent human cells to grow three-dimensional tissues ("cerebral organoids") that she uses to model how the human brain develops (see her paper "Cerebral Organoids Model Human Brain Development And Microcephaly", 2013).

This field had its share of scandals. Two rank among the biggest scientific scandals of the last century. In 2004 a Korean scientist, Hwang Woo Suk, announced that he had cloned human embryonic stem-cells, but an investigation by his university found that he was lying. In 2014 a young Japanese scientist, Haruko Obokata, announced that she had discovered a way to turn adult cells back into stem-cells, the so called "stimulus-triggered acquisition of pluripotency" (STAP) cells. Her employer, Riken, investigated and found that it was not true. So we need to be cautious about the announcements that come from stem-cell startups.

When we mix gene therapy and stem-cell research, we obtain tools that look promising for the regeneration of tissues and body parts. They use different approaches, but this kind of research is going on in several laboratories around the world: Ying Liu at the University of Texas at Houston; Guangbin Xia at the University of Florida; Joshua Hare at the University of Miami; Malin Parmar at Lund University in Sweden; etc.

A terrible disease called "severe combined immunodeficiency" (SCID) was the first disease to be treated with gene therapy. Children who have SCID (sometimes called "bubble children") are basically without an immune system. In 1990 William French Anderson at the National Institutes of Health (NIH) in Maryland introduced a gene called ADA (Adenosine Deaminase) into the immune cells of a four-year-old girl, Ashanti DeSilva, who was suffering from SCID. It didn't really work well, but that was the first case of gene therapy. The first big success story came in 2009, when an eight-year-old boy, Corey Haas, who was going blind (a form of blindness caused by mutations in the gene RPE65) regained normal vision thanks to gene therapy performed by Jean Bennett at the Children's Hospital of Philadelphia. In 2013 this hospital spun off the company Spark Therapeutics. Research on "bubble children" continued and after more than 20 years Anderson's original intuition started working. In 2013 Bobby Gaspar at the Great Ormond Street Hospital at University College London reported success in treating children suffering from SCID with genetically-engineered stem cells, and in 2014 Donald Kohn at UCLA cured 18 children born with SCID by introducing the ADA gene into their cells. The first gene-therapy treatment approved in Western countries was Alipogene Tiparvovec, marketed since 2012 as Glybera by the Dutch company UniQure. It treats a very rare condition and it costs more than one million dollars, the most expensive medicine in the world. Obviously it was not a commercial success. But soon (2017?) a second gene-therapy treatment should be approved in Europe: a gene-therapy treatment to treat those "bubble children" born with SCID. It was developed at San Raffaele Institute in Italy and will be marketed by GlaxoSmithKline as Strimvelis.

In 2015 the big success story was Layla Richards, a one-year-old girl who was cured of an "incurable" cancer (acute lymphoblastic leukaemia, the most common form of childhood leukaemia) at Great Ormond Street Hospital . The baby did not have enough of the T-cells that search and destroy the leukaemia cells. Cellectis scientists using TALENS edited T-cells from healthy donors and created T-cells for her. It is relatively easy to inject outside T-cells into the body, but there are two problems: the foreign T-cells don╬Ú╬¸t recognize the body as their own and start killing all sorts of cells in the body that they are supposed tosave, and the body does not recognize the T-cells so it starts fighting them with its own antibodies (like it fights a transplanted organ). Cellectis edited out two genes from the donor╬Ú╬¸s T-cells in order to disable both processes. The result is a T-cell called UCART that is "universal", i.e. that can work in any body: UCART stands for Universal Chimeric Antigene Receptor T-cells. The ones used for leukaemia are UCART19 and will be sold by Servier and Pfizer. In 2016 a second baby condemned by the same cancer was cured by the same UCART19 at the same hospital.

Children with epidermolysis bullosa are condemned to a horrible and painful death: their skin literally disintegrates. Doctors in Holland killed two of these so-called "butterfly children" in order to stop their suffering. This disease is caused by a defective gene that does not produce the protein (type-7 collagen) that holds skin layers together. In 1997 Paul Khavari at a medical center in Palo Alto had published a paper titled "Cutaneous Gene Therapy" that explained how gene therapy could help. Almost twenty years later in 2016 a team at Stanford University, where Khavari now leads a laboratory, has used gene therapy to inject the correct gene into stem cells of the child and to grow healthy skin that can then be grafted on the child's wounds. The gene therapy will be commercialized by a Ohio startup called Abeona Therapeutics (acquired in 2015 by Texas-based PlasmaTech), which is a 2013 spinoff of the Nationwide Children's Hospital in Ohio. The problem is that our body sheds most of its cells every year, so this gene therapy has to be renewed almost every year. It is not a solution, but an improvement over killing the child!

In 2016 Elizabeth Parrish, who has her own startup in Seattle called Bioviva, performed gene therapy on herself and improved her "telomere score", which is higher among young people and low among older people. She managed to recover the equivalent of 20 years of telomere decline. This telomere decline is only one of the many aspects of the overall aging process, but she also performed other gene therapies on herself to reverse other factors. Time will tell if her "younger blood" really helped her live longer, but gene therapy is certainly becoming more real. In 2016 Robert MacLaren of Oxford University led a successful experiment of gene therapy to restore sight in a rare case of eye disease ("choroideremia"): he added a working gene to the cells of the retina in order to compensate for the defective gene that causes the disease. In 2016 Dusan Bogunovic at Mount Sinai in New York showed that people without the gene ISG15 (about 1 in 10 million people) have a stronger immune system that can fight almost all known viruses: maybe removing that gene will solve forever the problem of pandemics and make vaccines a relic of the past.

There are also scientists who think that they can just "print" tissues and organs. The idea of applying 3D Printing technology to living tissues sounds appealing, and the first company to try it commercially was Organovo, co-founded in 2007 by Gabor Forgacs of the University of Missouri. Now there are 3D Bioprinting startups in Asia, like Cyfuse (Japan) and Regenovo (Hangzhou, China). But 3D Bioprinting is still mostly studied in universities, particularly at Wake Forest University in North Carolina and by Jeremy Mao at Columbia University. The human body is not as good as other animals at regrowing organs. It is pretty good at healing itself, but not when it comes to tendons, ligaments and cartilage like the meniscus. The meniscus is a body part that millions of people have injured all over the world and usually is not repaired. In 2015 Jeremy Mao showed a machine that can bioprint a human meniscus, and in 2016 scientists at Wake Forest University unveiled a printer designed to print skin cells onto burn wounds.

Narnia: Is this related to the idea of "organ on a chip"?


No, those are simulations. Those organs on a chip are not meant to be used inside the human body. They are meant to be used in the laboratory. In 2010 Donald Ingber from the Wyss Institute developed a chip (the size of your thumb-drive) that simulates a lung, the first "organ on-a-chip". The Wyss Institute spun off the startup Emulate to sell the chip. Until now the world's scientists have used animals to study their theories, and each year millions of animals are harmed and killed in laboratories by scientists who are studying new theories; but from now on the scientists will also have an alternative: use the organ simulated by a chip.

Narnia: What about immune therapy?


The immune system is one of the smartest organs of our body. It is made of several cell types that defend the body against viruses and cancer. The problem of cancer is that sometimes these cells are switched off. One way to switch them on again is to use gene-editing techniques to create "improved" immune cells. The first success story in "immune therapy", based on research by James Allison at UC Berkeley, was Ipilimumab for the treatment of skin cancer. Officially introduced in 2011, this substance activates the part of the immune system that can recognize and destroy cancer cells. Wendell Lim at UCSF, who is also the founder of startup Cell Design Labs, focuses on "T cells", immune cells that identify other cells infected by a virus or a cancer (The latest paper is "Precision Tumor Recognition by T cells with Combinatorial Antigen-sensing Circuits" in Cell magazine, 2016). Several start-ups are specializing in creating "improved" T cells, notably Cellectis, founded in 1999 in France, whose technology is used by John Lin's team at Pfizer's San Francisco laboratory, and AbVitro (acquired by Juno Therapeutics in 2015). In 2015 the US government approved the immunotherapy drug Opdivo manufactured by Bristol-Myers Squibb, a cancer medicine that helps the immune system fight the spread of cancer cells. It only works with skin cancer, it has adverse side-effects, it is very expensive, and it is not always successful, but it is a first practical step. Verily (Google's biotech unit) is holding frequent seminars on the idea of engineering cells to boost the immune system. In 2016 Facebook's first president, Sean Parker, donated 250 million dollars to study how to engineer the immune system so it can fight cancer, and hired Jeffrey Bluestone of UC San Francisco to lead this effort.

The first success story of immunotherapy to fight cancer was announced in 2016 by Steven Rosenberg at the National Cancer Institute. Rosenberg's experiments started in 1985 when he led the first trial on humans of IL-2. IL-2 makes T cells grow. These are then used to infiltrate the tumor (basically, they are transplanted into the region attacked by the cancer) with a procedure called "adoptive cell transfer". In 1996 he improved his procedure thanks to new information about the genes that represent tumor antigens. In 2006 Rosenberg had tried his procedure on 684 cancer patients and was reporting some success in slowing down or even shrinking the tumor. In 2016 he announced that a woman who had colon cancer was free of cancer. For the first time we have healed someone of cancer.

Narnia: Who contributes most to progress in, for example, cancer treatment:


Governments certainly contributed a lot of bureaucracy. Big corporations (so called "big pharma") certainly invest a lot of money. But both failed to solve the problem of cancer. The single biggest challenge for medicine is to defeat cancer. The story of the "war on cancer" is actually very educational. US president Richard Nixon launched the "war on cancer" in 1971. He created a bureaucracy to study and fight cancer, and he appointed two politicians in charge of it. Nixon promised that the cure for cancer would be found in 5 years. Of course, no cure was found, but the budget for the bureaucracy centered around the National Cancer Institute increased. In 1984 Vincent DeVita, the director of the National Cancer Institute, promised a 50% reduction of cancer-related deaths by 2000. The reduction was only 17%. In 2003, a new director of the National Cancer Institute, Andrew von Eschenbach, promised to cure cancer by 2015. In 2015 in the USA alone there were 1.5 new million cases of cancer and 590,000 people died of cancer. Not cured at all. In fact, since Nixon's 1971 speech, the rate of cancer cases in the USA has increased, from less than 500 per 100,000 people to more than 500. The deaths from cancer have decreased a little bit only because medicine found ways to keep people alive for a little longer; but sometimes a longer life with cancer is not really a solution. This is what i consider a big failure. However, at the same time the scientists who study cancer have understood a lot more about cancer. In 1971 Nixon's experts were convinced that cancer was caused by a virus. They spent millions of dollars trying to find the virus of cancer. Today we know that cancer is caused by oncogenes, that oncogenes can be activated by external factors (like radioactivity or toxins) and by internal factors (random mutations), and that some other genes are supposed to "suppress" oncogenes but sometimes don't do their job. The most important discovery of recent years is that a tumor undergoes constant genetic change, which makes it really difficult to target it. Cancer is "protean". That is what i call "success". During the same period some scientists were very successful in understanding cancer while other scientists were very unsuccessful at finding a cure. DeVita published a book in 2015 titled "The Death of Cancer" that explains the difference: the bureaucracy failed, the distributed community of scientists succeeded. The bureaucracy was a top-down hierarchy that simply created more and more bureaucracy. The worldwide distributed community of scientists "competed" to study cancer and every year discovered a new fact. Each discovery by one scientist leads to the discovery by another scientist.

The lesson learned is clear: in general big bureaucracies don't solve problems, they simply use problems to get funding for themselves and pay their salaries. Big corporations have made a lot of money out of the existence of cancer, so let me be cynical and suspect that their motivation to eliminate cancer is not as high as the motivation to develop drugs for people who HAVE cancer.

For the future i believe that an important contribution will come from communities of independent researchers like UC Berkeley's Rosetta@home, the World Community Grid (run by IBM) and Australia's DreamLab, people who are pooling together their computers or smartphones to allow scientists to carry out independent research on cancer. There are also "big data" projects that are collecting billions of data about cancer patients, such as CancerLinQ, launched in 2013 by the American Society of Clinical Oncology, and the Genomics Evidence Neoplasia Information Exchange (GENIE) project, launched in 2015 by the American Association for Cancer Research.

Narnia: What role can "biohackers" play?


This is always the most interesting story: how some young, independent, eccentric rebels start experimenting with a new technology in ways that no big corporation or government agency would do. And usually this is a sign that a boom of startups is about to happen.

In 2005 a young biologist, Rob Carlson, left the non-profit research laboratory Molecular Sciences Institute in Berkeley (founded by Nobel Prize winner Sydney Brenner and continued his biological experiments at home, and founded his own garage startup, Biodesic. In 2008 Jason Bobe and Mac Cowell founded the DIYbio organization on the East Coast, which is usually considered the beginning of the "do-it-yourself" movement in synthetic biology.

In 2009 four talented young New Yorkers (molecular biologist Ellen Jorgensen, bioengineer Oliver Medvedik, freelance journalist Daniel Grushkin and interdisciplinary artist Nurit Bar-Shai) established the nonprofit organization Genspace to promote biohacking, and the following year opened a shared and public biotech laboratory. In 2009 Angela Kaczmarczyk and others founded the Boston Open Science Lab (BossLab).

Silicon Valley responded with BioCurious, another volunteer-run non-profit organization. It was established in 2010 by a group of young independent biologists (Eri Gentry, Raymond McCauley, Tito Jankowski, Joseph Jackson, Josh Perfetto, Kristina Hathaway). It aimed at providing a "hackerspace for biotech" at its Sunnyvale offices. It marked the rise of a community of worldwide hobbyists taking advantage of public-domain databases of genetic parts. European biohackers had Open Wetlab in Amsterdam and La Paillasse in Paris. In 2010 UCLA organized a symposium titled "Outlaw Biology?" at which biohacker Meredith Patterson delivered the speech "A Biopunk Manifesto". Rob Carlson published a book titled "Biology is Technology" (2010), that became the motto of this movement.

In 2010 two of BioCurious' founders, Tito Jankowski and Josh Perfetto, founded OpenPCR in San Francisco to manufacture a machine that could bring biotech to the desktop, basically a copy machine for DNA. Most genetic applications (such as DNA detection and sequencing) required a machine to perform Polymerase Chain Reactions (PCRs), i.e. to amplify sections of DNA. OpenPCR dramatically lowered the price of these PCR "printers" and made them affordable for individuals. In 2010 Austen Heinz founded Cambrian Genomics in San Francisco to manufacture the first "laser printer for living beings", a machine capable of rapidly and accurately producing DNA. Arcturus BioCloud, founded in 2014 in San Francisco, makes it even easier: it wants to be a virtual bio-foundry for rapid prototyping microorganisms using the cloud to communicate with its users.

In 2003 MIT's professor Tom Knight envisioned a catalog of standardized "biobricks" that synthetic biologists could use to create living organisms. His model clearly mirrored the way the personal-computer industry got started, with hobbyists ordering kits from catalogs advertised in magazines and then assembling the computer in their garage.

In 2003 researchers from MIT, Harvard, and UCSF had unveiled the MIT Registry of Standard Biological Parts, which later folded into iGEM, the International Genetically Engineered Machine. Both iGEM and the BioBricks Foundation were Drew Endy's brainchildren. By 2014 the repository would contain 20,000 biological parts (biobricks). "Open-source" biotech was starting a global grassroots revolution in synthetic biology. Every year the iGEM Jamboree, first held in 2004 in Boston, gathered young bioengineers from all over the world to create new life forms, mostly microbes for useful applications. There would be 2,500 competitors from 32 countries in 2014.

The nonprofit organization AddGene, started in 2004 by MIT's student Melina Fan, helps synthetic biologists share their discoveries, i.e. their biological parts. For example, it ships the DNA material needed for gene-editing to any laboratory that wants to experiment with the CRISPR technique.

It is also interesting that we see the emergence of an "open source" movement in biotech. Sage Bionetworks, a nonprofit organization in Seattle founded by Stephen Friend and Eric Schadt, is clearly inspired by GitHub, the most famous repository for open-source software. Friend got it started in 2009 with a donation of know-how and tools from his old company Merck. Their mission talks about the importance of "open networks of contributors to solve complex scientific problems".

What was still needed was the equivalent of Computer-Aided Design (CAD) for synthetic biology. In 2010 Chris Anderson at UC Berkeley delivered Clotho, an open-source "bioCAD" platform to design organisms. In 2014 Autodesk launched Project Cyborg, a cloud-based platform of design tools for DNA designers.

This worldwide community of biohackers is thriving. As prices get lower and lower, we can expect to see amazing achievements by individuals.

Narnia: Can AI help biotech?


These days we see applications of "deep learning" to everything, so it is no surprise that scientists are testing if this A.I. technique can help their job. The vast majority of the data collected by health-care professionals are images, frequently those generated by X-Ray machines or by MRI machines or by Computed Tomography (CT); so image analysis is a natural application. Thousands of people who work in radiology, cardiology and oncology departments of the world's hospitals spend thousands of hours checking medical images to detect problems in their patients as soon as possible.

San Francisco-based Enlitic is using deep learning to detect lung cancer in CT images. Lung cancer is one of the hardest forms of cancer to detect, which is why it is usually detected when it's too late.

Arterys, a spinoff of Stanford University's StartX accelerator, has developed an application based on deep learning for General Electric's MRI scanners to detect cardiovascular disorders.

Dell has millions of medical images on its cloud, coming from more than 1,000 health-care providers, and is using the deep learning software from Israel's Zebra Medical Vision to provide automated analysis of those images.

Philips is working with Hitachi on an image analysis system because it has an even bigger repository of images, with more than 135 billion medical images. Its health-care devices (X-ray scans, CT scans and MRI scans) generate more than 2 million medical images per week.

IBM is applying its Watson machine-learning system (and the technology acquired in 2015 from Merge Healthcare) to medical image management, but also to diabetes diagnostics (in partnership with Medtronic, Johnson & Johnson and Apple) and to cancer diagnostics (in partnership with several hospitals), which are being packaged as Watson Genomic Analysis. At the same time IBM is encouraging the collection of patient data via smartphones and their upload to its cloud, where Watson can carry out its learning chores. In 2015 IBM opened in Boston the headquarters of a new division called Watson Health, directed by Deborah DiSanzo, former CEO of Philips Healthcare,

Biogen, a Boston company formed in 1978 by Phillip-Allen Sharp of the MIT, Walter Gilbert of Harvard University and a group of European biologists, is the third largest biotech company in the world. It is planning to generate automated "risk reports" from the 1.6 billion records of genomic data that it owns.

Toronto-based startup A4L (Analytics 4 Life) is using billions of data collected in Canada to develop an algorithm for heart disease.

Unfortunately, i don't think we're replacing radiologists and cardiologists any time soon, but the dream is to store all medical images in a cloud and have the equivalent of Google's or Baidu's "spider robots" crawl this cloud and check each new image for signs of trouble. This will happen automatically, without any need to "request" an image analysis. And new "releases" of the spider robots will automatically re-check all images based on whatever new medical knowledge has become available.

A.I. techniques can also be applied to other aspects of health care. For example, in 2016 AiCure announced a system that uses a smartphone camera, facial recognition software and motion-sensing software to remind a patient of medication and to check that the patient takes the medication.

Narnia: How do Biotechnology and Nanotechnology fit together?


I think that the use of DNA as a material for computation and robotics is the one of the most exciting stories or our times.

Let's start with DNA as a computer. DNA is a natural substance for computing because it uses a code and that code obeys strict rules of logic. The pioneer of "DNA computing" was Leonard Adleman at the University of Southern California, who in 1994 created a DNA computer capable of solving one mathematical problem. He found a way to encode a string of data in the sequence of nucleotides and then used the chemical properties of DNA to do the calculation. (For the record, one decade earlier Adleman had coined the expression "computer virus" and one of his students, Fred Cohen, had created the world's first computer virus). But the sensational news came one year later, in 1995, when Richard Lipton at Princeton University showed huge potential for computation in the inherent parallelism inherent of DNA-based computing. This parallelism can help solve some mathematical problems much faster than with electronic computers. A few months later Lipton's students Dan Boneh and Chris Dunworth showed that a DNA computer could break the data encryption system developed by the National Security Agency (NSA) of the USA. That "application" definitely captured the attention of the media. All sorts of mathematicians, computer scientists and biologists became interested in the computational power of DNA. In 1999 computer scientist Mitsunori Ogihara and biologist Animesh Ray at the University of Rochester published the paper "Simulating Boolean Circuits on a DNA Computer" and Ehud Shapiro at the Weizmann Institute in Israel published "A Blueprint for a Biomolecular Computer" (he built the first one in 2001). The first practical DNA computer was unveiled in 2002 and used for gene analysis by Olympus in Japan (a collaboration with Akira Suyama's team of the University of Tokyo), but not much progress was achieved in the following ten years because DNA computers are difficult and expensive to make. Then in 2013 Drew Endy at Stanford unveiled a simple "biocomputer", a computer operating inside a living cell. This computer can only answer "true/false", but the question can be important: it could detect a disease that cannot be detected with today's equipments. The main difference between a biocomputer and an electronic computer is that the biocomputer can interact naturally with the cells of the body. A biocomputer is slow but it can operated in places where electronics cannot be deployed. When biocomputers become practical, we will be able to deploy computation everywhere inside the body. Endy's biocomputers can even communicate with each other: his team worked out a way for transmitting genetic data from a cell to another cell. A sort of Internet is coming to the cells of your body.

Now let's analyze DNA as a nanotech material. Living beings are self-assembling structures. They are not built in a factory: they assemble themselves, cell by cell. The resulting structures are pretty amazing. Think of the human brain: we still cannot design and build in a laboratory anything remotely similar to the human brain, which self-assembles in a mother's womb in 9 months and will keep self-assembling for the rest of the person's life. Nanotech uses two approaches to build new materials: top-down and bottom-up. Top-down is done in many laboratories where the scientists put together molecules or even atoms with painstaking precision, hoping to achieve a stable material. Bottom-up is done when scientists find a structure that will keep growing by itself. Bottom-up is what life does: life is a bottom-up process, i.e. it self-assembles. DNA is an excellent nano-construction material because because we know that it works: it constructs billions of living organisms every single day.

The first man who saw the analogy was probably Nadrian Seeman at New York University. In 1982 he published a paper about constructing 3D structures from DNA that is considered the beginning of DNA Nanotechnology. Nothing happened for 20 years because the machines to "synthesize" (create artificially) DNA structures were very limited. In 2005 Seeman wrote the paper "From genes to machines - DNA nanomechanical devices" realizing that these ideas were becoming feasible. In fact, in 2006 the breakthrough came, although it came from the other side of the country: Paul Rothemund at CalTech showed how DNA molecules can be folded into two-dimensional structures and how DNA structures can be programmed to form larger DNA structures. "DNA origami" (as the technique came to be known) was the cover story of Nature magazine on March 16 of 2006. So the bottom-up approach became popular and John Pelesko published the book "Self Assembly" (2007). Research in DNA nanotech picked up dramatically in 2009, when William Shih's team at Harvard, and Tim Liedl's team at the University of Munich in Germany published techniques to fold DNA that generate self-assembling origamis.

Hiroshi Sugiyama at Kyoto University started working on "DNA origami technology for biomaterials applications" (as his paper of 2012 titles). In 2011 Shawn Douglas of Shih's lab at Harvard founded the BioMod competition to encourage students from all over the world to experiment with DNA origami.

In 2012 two of George Church's students at Harvard University, namely the same Shawn Douglas and Ido Bachelet, developed nanorobots made of DNA with the intention that they could be programmed to target specific cells in the body, for example to seek out cancer cells and program them to self-destruct.

All of this progress was enabled by better machines to "synthesize" DNA (like Agilent machines). It quickly became apparent that these mathematicians and biologists were using DNA to "design" robots the same way that architects use software to design objects. The software to design objects is called CAD (Computer-Aided Design), and the most popular CAD software comes from Autodesk. Similar software was introduced (especially at Harvard) for biologists who want to design DNA robots. CADnano was developed in 2009 by Shih when he was at the Dana-Farber Cancer Institute, and later improved by Church's group and by (not surprisingly) Autodesk. CADnano provides biologists with a way to do what software engineers call "rapid prototyping", except that in this case it is rapid prototyping of three-dimensional DNA origami structures. In 2009 Hao Yan at Arizona State University developed Tiamat, a three-dimensional editing tool for DNA structures. In 2011 Mark Bathe at the MIT developed CanDo (a name that stands for "Computer-aided engineering for DNA origami"), a software that can convert a two-dimensional DNA origami blueprint into a complex three-dimensional structure. In 2016 Chris Voigt's group at the MIT released a programming language called Cello that allows biologists to rapidly design DNA circuits. It is based on Verilog, the language that hardware designers have used for 30 years to design electronic chips. Cello automatically designs the DNA sequence required to implement the DNA circuit. In other words, you can build living cells with this programming language. And so on: these are open-source software for DNA origimi.

Douglas then moved to UC San Francisco in 2012 and Bachelet to Bar-Ilan University in Israel, founding two important schools of DNA origami. In 2013 Bachelet published his own method of making DNA molecules that can be programmed to reach specific places in the body and carry out "special missions" in those places. Basically, the DNA origami was becoming a tiny computer that can travel inside the human body. These DNA computers can perform the same kind of logic operations (zero and one logic) as today's silicon-based computers. Right now they are much less powerful, comparable to the first computers of the 1950s, but at least they are already very tiny.

In 2014 Bachelet in collaboration with Daniel Levner at Harvard inserted such DNA nanocomputers into a living being, a cockroach, and let them travel inside its body. You can envision a day in which these DNA robots will be able to interact with the cells of the body that they "inspect" and also to interact with each other, just like computers can be connected in a communication network. In 2015 Ido Bachelet began the first human trial of DNA nanobots (to fight cancer) and Pfizer invested in his ideas.

Living beings (bodies) are collections of molecular objects that move and interact all the time. Think for example of your blood cells. When they collide, the cells of our body perform sophisticated chemical processes. And these chemical processes, in turn, control the collisions. Bachelet, Douglas and their former colleagues at Harvard are creating artificial kinds of such molecular objects.

The next question, of course, is how much information you can store in the "memory" of these DNA computers. One gram of DNA can hold about 10 to the 14th power Mbytes of data. In 2012 George Church encoded his latest book into DNA. In 2013 Ewan Birney's team at the European Bioinformatics Institute encoded all 154 of Shakespeare's sonnets, an audio recording of Martin Luther King's famous speech "I Have a Dream", and a picture of their office in a string of DNA (a total of 739 kilobytes). In 2015 Sri Kosuri, a member of the Harvard team that had encoded Church's book into DNA, encoded a rock song by the band OK Go into DNA, the first music to be released on DNA. In 2016 Microsoft encoded 200 megabytes of data into DNA, including 100 classic novels. These memories are very slow compared with silicon memories, but they can last a lot longer... literally, tens of thousands of years. The problem is the cost of storing data in DNA. Agilent synthesized the DNA for free, but it would normally cost more than $12,000 per megabyte using Agilent's machines that cost millions of dollars. My 16Gbyte flash drive that i keep in my pocket cost $20, and it costs zero to rewrite the data on it. Nonetheless, the storage ability of DNA is impressive: everything that human civilization has produced in writing (50 billion megabytes of text) can be stored in the DNA of the palm of your hand.

You can envision a day when you will have tiny DNA origami robots traveling nonstop around your body and communicating with each other; and maybe they will become so powerful that you can run some A.I. program on them so that they can monitor and interpret what is happening inside your body in real time.

Narnia: What are the dangers?


I am personally more afraid of plastic than of genetically-modified organisms. I don't have problems eating a genetically-modified tomato. I do have problems storing it in a plastic container. The biggest structure of the century was not a high-rise office building but the Fresh Kills landfill of New York: not a place for workers, but a place for garbage.

The dangers are of course real, and scientists themselves have done much to protect the science from horrible mistakes; but of course bad people and stupid people abound, and we have to be prepared for the worst every time a new technology is introduced.

I hope that biotech has not forgotten one important lesson from the 1990s. In 1990 William French Anderson carried out the first gene therapy at the National Institutes of Health (NIH). In the following years the expectations for a boom of gene therapy were high. Then in 1999 a teenager, Jesse Gelsinger, died during a clinical trial of gene therapy at the University of Pennsylvania. This tragic event killed gene therapy for two decades. All it takes is one mistake and an entire field comes to a halt.

The other danger is that the biohackers may create something that will not be easily "undone". The "undo" command doesn't exist in biotech. In 2014 George Church, the influential Harvard bioengineer, and Kenneth Oye, a political scientist at the MIT, published an article in Science magazine that gene-editing techniques and gene-drive techniques are too dangerous when they leave the scientific laboratory. Maybe we should enact a new law mandating that biotech companies introduce a new product only when it is clear what the "undo" process is. If they don't know how to "undo" something that they are doing in the laboratory, then they should keep it in the laboratory.

I also think that philosophers and psychologists are not spending enough time thinking through the fundamental issue of "who am i?" We haven't really spent much time thinking of what happens to "me" when you change one of my genes or reprogram one of my cells. When i teach the class on Neuroscience, i ask my students whether they would be willing to replace their skin. What i really want to know is how much they care for their brain, but before i ask them complicated questions about brain operations, i test them by asking the same questions about something as simple as the skin. The human skin is not a great material: it gets cut and burned very easily. How about i replace your skin with some metallic material like stainless steel that does not break and does not burn? You don't have to worry about scratches, bleeding, bruises, cuts, and burns: happy? And this new material even insulates you from cold weather. Are you willing to replace your skin with this new skin? After thinking about it, most students reply "no". The psychology behind that "no" is simple: "I" (note the "I") prefer to stick to "my" skin (note the "my") because that is "me". If you change my skin, i am not sure that i am still "me". My instinct tells me that i become a cyborg, some strange kind of living being, probably more efficient, but i lose my identity. Now the bigger question is: can i improve your brain to make you smarter? That is a big question because that "improved" brain would be someone else's brain: you would become another person, a more intelligent person, but not "you". I know that i am not the most intelligent person in the world, and maybe i am the most stupid person in the world, but that's "me" and if you change "me" to some other brain, it is just like killing me. Thanks, but i don't want to die, so i'll keep my stupid brain. So... the same question about genes and cells. We are not spending enough time discussing what happens to "me" when you change one of my genes or when you change the program in one of my cells. The goal is to make me healthier, but are you changing "me"? You are definitely changing one of the organs of my body, and therefore my body: is the result still "me"? There are profound philosophical issues related to meddling with someone's genome. Just like we wouldn't like a brain transplant (someone else's brain in my body is not "me"), maybe we shouldn't want a genome transplant (an operation that alters "my" genome).

But the biggest danger, perhaps, is to feel too confident about our understanding of genetics. For example, we all know that the DNA has the structure of a double helix. Our genome is expressed as a sequence of base letters, and this sequence is physically encoded in a double helix. But that is true only in cells that are at rest, which mostly happens when they are dead. In living cells usually the shape is more complex because the helix twists and loops in irregular geometric ways. When cellular biologists discovered techniques to read the sequence of the base letters (such as TALEN and CRISPR techniques), we entered the age of gene-sequencing, and scientists largely stopped studying the meaning of the changing shapes of the double helix. In information terms, we contented ourselves with studying the lower-order structure of DNA (the double helix) and ignored DNA's higher-order structure, which is actually what biologists find in most living processes. The dogma of lower-order cellular biology is that some special proteins attach to DNA and trigger gene replication or gene expression, and that's the essence of cellular life. But in reality those same processes of replication and expression can take place even without the active role of proteins. When the double helix swings, it can achieve the same effects. At a higher level it becomes apparent that DNA and proteins influences each other. There is a whole field of "DNA topology" that is still largely unexplored.

There are many mysteries in the way the genome works. Craig Venter's team simplified as much as possible the genome of a bacterium and in 2016 published the smallest set of genes that can still be a living organism: 473 genes. If you remove any of those 473 genes, the organism cannot survive. The problem is that we don't understand the function of more than 150 of those genes.

In 2016 Stephen Friend of Seattle-based nonprofit organization Sage Bionetworks and Eric Schadt of Mount Sinai published a report that demonstrates how little know about the human genome. There are millions of healthy people who, according to their genes, should be very unhealthy. These are people whose genomes contain genetic mistakes which are known to cause devastating illnesses. But they are perfectly healthy. Jillian Banfield's team at UC Berkeley is using the genomes of animals to re-design the tree of living beings, and it is not the one we knew.

There are even bigger mysteries in the way the genome translates into a living being. The human genome contains 25,000 genes, but rice contains 50,000. So a grain of rice is more complex than me?

In 2016 Steven McCarroll's team at the Broad Institute in Boston announced the discovery of the genes involved in schizophrenia, and a few months later Serena Nik-Zainal's team at the Sanger Institute in England published the genes involved in breast cancer. We have to be very careful to use these data. There have been many cases when society trusted science too soon. For example, in the 1920s eugenics was a very popular scientific topic in the universities of the USA: a few years later eugenics was used by Hitler to justify the extermination of Jews and by Japan to justify mass murder and rape in China. For example, psychiatry was very popular in the USA until recently, and psychiatrists came to dominate many psychology departments in the main universities, but most of Freud's theory has been proven wrong by modern neuroscience.

In conclusion, i hope that biotechnicians realize how little we know about life. After all, this is a very young science. It has only been 60 years since we discovered the double helix of the DNA.

But there is also the opposite risk: that society will be too slow to accept the progress in biotechnology. The US agency in charge of approving new drugs, the FDA, does not "scale up": it cannot approve 1,000 or 2,000 new organisms per year. It takes several years to analyze a new biological product, and only 40-50 are approved any year. On one hand, the public is scared and wants to be protected by strict and tough regulations. On the other hand, biotechnology can deliver a lot more than it does today and these regulations hamper progress that could save the lives of millions of people and these regulations also make it very expensive to conduct research and development. There is zero tolerance for errors in biotech because governments are scared that an error could kill many people, but sometimes the result of this zero-tolerance policy is to let millions of people die of diseases that could be cured and another result is to make all drugs very expensive. The country that figures out how to reform regulations and make it easier and cheaper to introduce new organisms in the world will have a huge advantage over the rest of the world.

Then I am also afraid of the pharmaceutical industry, an industry that missed the manufacturing revolution of the 20th century. "Continuous" manufacturing has become the norm in almost all manufacturing industries since Oliver Evans built his flour mill more than 200 years ago. The pharmaceutical industry is the exception: it is still living in the world of "batch" manufacturing. It can take one month to manufacture a drug that could be made in two days. In 2007 Novartis created the Center for Continuous Manufacturing at the MIT, which in 2012 spawned the startup Continuous, and in 2016 the MIT showed the first portable machine that can make a drug starting with the raw ingredients. The future of "pharma" could be "portable drug making".

Narnia: In conclusion, is progress in synthetic biology desirable and inevitable?


The story of the human species (and of most animals) is the story of coexisting with tools. One of the most influential scientists of our time, Richard Dawkins, wrote a book titled "The Extended Phenotype" (1982) in which he argued that our body does not end at the skin but extends beyond the skin into all the tools that we use to survive; and this is true of all living beings. The beaver builds dams, the spider builds spiderwebs, the bees build beehives, and so on. Each living being "extends" its body into the environment in order to survive. A spider would not survive without a spiderweb, a bird would not survive without a nest, and so on. Humans are unique in the astrononimal number of tools that we build, i.e. in the infinite ways in which we extend our body. I think that the marriage of the natural and the artificial, i.e. of biology and tools, is inevitable. We are genetically programmed to extend our phenotype. And today the most impressive way in which we are extending our phenotype is by developing technology to transform life itself. The marriage of the organic world and of the synthetic world is the future just like the marriage of human workers and robots is the future.

People used to starve to death for lack of food or die of cold for lack of warm housing. We solve the problem of starvation with the agricultural revolution. We solve the problem of housing with the industrial revolution. The 2016 report by the World Health Organization (WHO) showed that cases of diabetes have nearly quadrupled since 1980: more than 400 million people have diabetes now. And each year 3.7 million people around the world die of diabetes. If this trend continues, soon 1 in 10 people of the planet will have diabetes. The same organization estimates that cases of cancer (that already kills 8 million people each year) will increase by about 70% over the next 2 decades. There is still one big problem to solve that neither the agricultural nor the industrial revolutions solved: diseases. That requires the "biological revolution" that is going on today. Centuries from now the historians will write books about the biological revolution of the 21st century.

This interview was complemented with these additional interviews:

Rob Carlson, author of "Biology is Technology" and president of the Bioeconomy Capital

Andrew Endy, Professor of Bioengineering at Stanford University, co-founder of the BioBricks Foundation and of the International Genetically Engineered Machines ( competition

John Cumbers, founder of Synbiobeta and former NASA scientist

Eric Gordon, inventor and venture capitalist of Skyline Ventures

Emily Leproust, founder of Twist Bioscience

Max Hodak, founder of Transcriptic

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