Building the future of pharmaceutical drug discovery with a pioneering AI-driven healthcare platform.
Intro
Led by world-renowned longevity scientist David Sinclair, Life Biosciences is pursuing therapies targeting molecular pathways that regulate the biology of aging. The platform approach enables us to develop pharmaceutical treatments with the potential to prevent, treat, and/or reverse multiple aging-related diseases, each with critical unmet needs. I was the product lead, tasked with leading the creation of new solutions.
Problem
Drug discovery is impossibly difficult. The average drug takes 10 years and over 1 billion dollars to get to market, while only 1 out of 12 will actually succeed.
Our initial problem started with having several different laboratories with distributed data sets. Labs typically have their own systems for data and they can be quite archaic, including PDFs, excel sheets and plain emails.
We didn't have a central place to consolidate data, or even a concept to share information across teams for collaboration.
Solution
We wanted to collect all the data into one place, keep its original integrity, but also process it to make further analysis. The goal was to speed up the drug discovery process, which results in potentially millions of dollars of savings. We also hoped that the sharing of data could lead to more collaborative approach to discovery.
We developed an in-house data lake and date warehouse, called Lakehouse. This unique solution allowed us to capture large amounts of lab data, process it and then add an analytical layer powered by AI on the top. The outputs allowed us to speed up the discovery process.
Unfortunately due to a NDA I am not at liberty to provide further details.