AI, Deep Learning and Big Data are Eating the Biotech World
The biotech world is not the same as it was just five years ago. Technologies like artificial intelligence, deep learning and big data have paved the way for the industry to enter a golden age of medical research and discovery.
How exactly are these technologies impacting the biotech world, and what trends should we expect to see in the coming years?
We examined these questions in depth at an event co-organized by the French-American Chamber of Commerce of San Francisco (FACCSF) and French Tech San Francisco, where we had three expert panelists weigh in.
Our first panelist was Julien Mamet, founder and board member at Adynxx, Inc. He founded Adynxx in October 2007 and currently serves as Chief Scientific Officer. Julien has extensive pharmaceutical experience in the areas of neuroscience and drug discovery and is the inventor of the AYX technology platform. Prior to Adynxx, he worked at the SCRIPPS Research Institute and Novartis Genomics Institute in San Diego, California.
Our second panelist was Carolina Reis, a biotechnology entrepreneur and co-founder/CEO of OneSkin Technologies. She holds a biochemistry degree and a Ph.D in stem cell and tissue engineering. As CEO of OneSkin, her main goal is to disrupt the skincare market by finding molecules that are able to reverse skin aging with a proven effect on 3D skin models.
Our final panelist was Laura Smoliar, founding partner of the Berkeley Catalyst Fund, which is focused on the vibrant startup ecosystem around UC Berkeley, Lawrence Berkeley National Laboratory and UC San Francisco, as well as associated incubators, accelerators and alumni throughout the San Francisco Bay Area. Initiated in close collaboration with UC Berkeley’s College of Chemistry and the UC Berkeley Foundation, the fund is committed to sharing its returns with the College of Chemistry.
The panel was moderated by Reza Malekzadeh, General Partner at Partech Ventures. Malekzadeh is a former successful marketing executive, turned investor. His expertise spans from early-stage startups to multi-billion dollar companies, over many industries. Partech Ventures is a transatlantic venture capital fund that invests in technology companies from seed to growth.
With their diverse backgrounds, each of these panelists brought a unique perspective to the discussion, but agreed on the following points:
1. Hire the right team that is strong on both the scientific and the engineering side.
In an age where software is eating the world, as Marc Andreessen famously quipped, it’s not enough to have talented scientists and biologists. You need to make sure you have the right software engineers, too. Equally important, both sides must be able to work together seamlessly and speak the same language. Smoliar added that, from the perspective of an investor, strong team dynamic is one of the most critical things they look for.
2. Artificial intelligence and machine learning are allowing biotech companies to speed up the data analysis process.
The life sciences industry is especially challenging in that it involves a much longer lead cycle than software would. Technologies like artificial intelligence and machine learning are helping to narrow the gap, allowing for the development of new types of solutions that require quicker data analysis. Reis commented that the market is ready, and that AI and ML are enabling biotechnology companies to establish a better data analysis process that will pave the way for a new array of biotech products like personalized treatments.
3. Artificial intelligence, machine learning and computing technologies are making drug discovery cheaper and quicker.
Julien Mamet’s company, Adynxx, developed a new treatment to address the pain patients feel post-surgery and during rehabilitation. He is particularly interested in seeing how the evolution of biotechnology impacts drug discovery. Thanks to AI and ML, biotech companies can learn from previously conducted studies to better inform future experiments so that researchers have a better idea of any possible missteps taken in previous trials and can ultimately determine better designations for drugs.
We are making great strides towards a better future in healthcare. Advancements in biotechnology are cutting down the cost of new drugs and reducing the amount of time it takes to get new medicines approved down to just a few processing cycles. But AI and deep learning are still relatively new concepts in the biotech world. There is a lot of education and a few structural changes in the approval process that still need to happen before we can leverage these technologies to their full potential.
