Serinus Biosciences is tackling one of the toughest problems in cancer treatment: creating combination therapies to override treatment resistance. We leverage cutting edge technology to design a fully explainable AI platform primed with decades of system biology knowledge. Uniquely powered for biological inference, our AI engine uncovers how cancer cells evolve treatment resistance and identifies molecules to overcome resistance escape routes. We design combinations that are safer, more effective, and can get to patients quickly. Founded by MIT PhDs and supported by a scientific advisory board of top academics from the Broad Institute, Dana-Farber, and UCSD, Serinus is powered by Y Combinator and other top investors to revolutionize precision medicine.
Prior to founding Serinus, Adam gained over 10 years of entrepreneurship experience including a Microsoft R&D Fellowship and Flagship Pioneering Ideation Fellowship. Adam is passionate about developing advanced AI models for biological research that will bring medicine to scale. Adam received his PhD and MS in computer science from MIT, MSc in computer science and mathematics from the Weizmann Institute of Science, and dual major BSc in computer science and neuroscience from Bar-Ilan University.
After five years as a paramedic, Max left clinical medicine to develop new treatments for the millions of patients without access to effective medications. He studied applied math and biology at Brown University, statistics at Cambridge University, and is completing his PhD in computational biology at MIT. His research has appeared in prestigious journals including Science, Nature Biotechnology, and Nature Neuroscience and has been recognized with national and international awards.
We're Adam and Max, the founders of Serinus Biosciences 💊💻🤓
At Serinus, we develop drugs that are effective against multiple types of cancer, and because cancer patients need solutions now, we do it in months instead of years!
Currently, more than 80% of cancer patients are not eligible for targeted cancer therapies - the most efficient and least toxic cancer treatments. Why? Because the proteins driving cancer in one patient are often different than those driving cancer in another patient.
Here's where the economics comes in. The cost of bringing a new cancer drug to market is currently >$2.5 BILLION. Developing a drug against a protein that only causes cancer in a small number of patients each year is just not economically viable with traditional drug development.
While building AI tools to understand the causes of cancer during our PhDs at MIT, we had a realization: all the different cancer-causing proteins disrupt the same cellular systems. We shut down these shared dysfunctional systems.
How? We look for the support proteins that keep the system functioning. Think about a telephone system ☎️ If you want to bring it down, you should find the small number of relay stations that route messages across the network instead of hitting the individual phones. We find the relay stations of cancer cells and bring them down ☠️☠️☠️
Since cancer systems are widely shared across patients, the relays that support those systems are widely shared across patients. Our current pipeline could help more than 100K PATIENTS PER-YEAR!
We met on the very first day of our PhDs at MIT. It was a cancer-fighting match made in heaven. Adam comes from an AI/ML background, Max comes from a biology and statistics background, having given up his place in medical school so he could develop new treatments for patients in need by merging biology, mathematics, and computer science.
Oh, and did we mention that Adam is a former Navy SEALs commander and Max spent five years as a paramedic.
How can you help?
Our platform is churning out way more ways to kill cancer than we can pursue ourselves. If you or someone you know works at another therapeutics company that might be interested in co-developing a drug with us, give us a shout on email@example.com