As I drive up to San Francisco on US-101, I look to my right, and see large complexes with unfamiliar names – Mission Bio, Kezar Life Sciences, Ultragenyx. Drive into Stanford and you might pass Varian Medical Systems, Genencor International, or Stanford Genome Technology Center. The Bay Area landscape is still covered with large tech companies and countless tech startups, but the map is increasingly dotted with biotech startups. Big players, too, are constantly moving in. DuPont, in addition to owning Genencor, just opened their DuPont Silicon Valley Innovation Center in 2018 in Sunnyvale. Apple is making constant strides in healthcare – so much so that Tim Cook even said, “I do think there will be a day we look back and say Apple’s greatest contribution to mankind has been in healthcare.” And believe it or not, Google’s DeepMind is leading the field in protein engineering.
A revolution is brewing, and the game is changing.
That much was evident at Stanford’s AI in Healthcare panel featuring a few of the faces at the frontlines of the biotech startup industry.
Sometimes scientific investigation yields something more than meaningful insights into the world. Mathematical models in biology can be fascinating and aesthetically pleasing, and some computer games, apart from being very addictive, can educate people and advance research. Mathematical models and games are deeply interconnected, because in biology we often want to model using computers different types of “games” happening in nature – the competition for various resources (food, mating partners, etc.) being the obvious example.
In this article, we will examine a few notable biological games. The first two examples are not really games as we usually think of them – you don’t play, but rather watch what happens as the game plays itself! This is exactly how we think of life, where organisms live, evolve, and die without outside intervention. Games can help us see how complex patterns and behaviors emerge from a set of seemingly simple rules.
Our ability to read and write DNA from a lab bench is another human capability that feeds into what has been coined the Fourth Industrial Revolution. Har Gobind Khorana first artificially synthesized DNA in 1972 and machines for de novo gene synthesis entered the market by 1991. The cost of DNA sequencing, the act of reading DNA, has rapidly declined as the machines advanced. For DNA synthesis, the act of writing DNA, we can expect a similar trend as those machines advance and the technologies proliferate. The ability to write DNA brings enormous upside for minimizing the financial and human capital needed to produce small molecule drugs, rapidly develop and test vaccines, and create novel gene therapies. However, specific events clearly highlight the risks, which are often called dual-use implications in the biosecurity world, of de novo DNA synthesis. For example, in 2017, a team of Canadian researchers created horsepox from scratch - a virus in the same family as smallpox. This event raised questions about free speech and academic publishing; however, as it becomes easier for people to write and make their own DNA sequences, we must think about if our current understanding of free speech prepares us for that world.
As genetic engineering technologies rapidly become more accessible, fears surrounding genetic modification that once seemed like science-fiction are soon becoming reality. Just earlier last year, He Jiankui made headlines when he unveiled the birth of the first-ever CRISPR-edited twins to the world.
Scientific advancements have dominated much of the 21st century, making it impossible to ignore the ethical implications of advancing genetic procedures. In 2017, the United States spent a whopping518 million dollars on genetic research alone. Unsurprisingly, new advances in these fields often reach far beyond the scope of existing ethical and legal regulations. This is a dire but often understated problem: rampant, unrestricted genetic engineering projects can threaten both public health and social equality. Thus, the international ratification of a robust, consistent set of genetic engineering guidelines is critical to the safe and ethical advancement of the technology.
If you cracked open a dictionary and looked up the word “couch potato” prior to me coming to Stanford, my name would have been written all over the page. So when I joined Stanford Women in Rugby and realized I could only run .2 seconds until fading from existence, I decided to start running everyday. I own an Apple Watch (thanks Costco sales!) and love tracking how many miles I have run and how many calories I burn from it. But I started to wonder just how much should I believe my watch…
What do investors look for in medical device start-ups? What value do they provide to entities like CBID, a biodesign research center and provider of a cutting-edge master’s program in biodesign? To gain more insight into where academia meets bio-innovation, I spoke to Professor Yazdi.
Plants have a sophisticated machinery to convert solar energy from sunlight into chemical energy and food. The visual system of organisms, based on photosensitive proteins and transduction, helps organisms find food and survive. Jellyfish bioluminescence improve survival and reproduction. Thus, optogenetics, a new frontier in light-activated therapies, is just an extension of light as a driving force in natural evolution.
Sound Machines 2.0 is not a techno punk rock band. It’s not even a human music group – it’s a self-playing, auto-composing robot quintet, designed by the engineering firm Festo. By using advanced artificial intelligence technology, this “band” analyzes the acoustic fingerprints of existing musical pieces and then generates and executes its own original compositions.
Dr. Rhiju Das (Ph.D., ‘05) is currently an Associate Professor of Biochemistry at Stanford University. He helped create EteRNA, an online videogame that uses crowdsourcing and collective intelligence to probe players who uncover the mechanisms of RNA folding machinery.