Inductive Bio – a technology company developing a machine learning (ML) platform designed to accelerate the compound optimization process dramatically – recently emerged from stealth with $4.3 million in funding. The seed round was co-led by Andreessen Horowitz (a16z) Bio + Health and Lux Capital, with participation from Character, Bessemer Venture Partners, Alleycorp, and others.
Half of the time and money is spent on small molecule preclinical drug discovery and is focused on optimizing compounds to effectively balance potency with Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties. And Inductive’s platform maps the drivers of small molecule ADMET by pairing a proprietary dataset with state-of-the-art ML – helping scientists to optimize initial compounds into leads and development candidates faster and with a better balance of ADMET properties.
Inductive Bio was co-founded by Josh Haimson and Ben Birnbaum – who had previously built out the ML organization at Flatiron Health (acquired by Roche in 2018). Wendy Young, Ph.D., a life sciences senior executive and former SVP of small molecule discovery at Genentech, overseeing the discovery and progression of over 25 clinical candidates into development, joined Inductive’s advisory board in the summer of 2022.
One of Inductive’s early partners is Denali Therapeutics – who is leveraging Inductive’s ML capabilities for ADME property predictions. Denali has integrated custom ADME models from Inductive into their small molecule drug design platform to support rapid, data-driven decision-making.
KEY QUOTES:
“We set our sights on compound optimization after talking to dozens of medicinal chemists who all described this process as a complex game of ‘whack-a-mole’ with dramatic consequences for the success or failure of drug programs. From our experience at Flatiron and Google, we knew it would be possible to help chemists leverage vast quantities of data to make better decisions.”
— Josh Haimson, co-founder and CEO of Inductive Bio
“Our deep graph learning algorithms have been tailored to the specific needs of real-world, heterogeneous data and trained on the world’s best-curated ADMET dataset. Traditional QSAR approaches make accurate predictions in novel chemotypes only around 30% of the time, whereas our algorithms are predicting accurately across 80% of novel chemotypes, and that number is continuing to improve as our data set grows.”
— Ben Birnbaum, Ph.D., co-founder and CTO of Inductive Bio
“When we were building out the small molecule discovery organization at Genentech, I pushed for our teams to leverage earlier generations of ML because I saw how impactful they were for focusing our resources on the experiments with the highest chance of success in the lab. I’m excited that at Inductive, we’re building the next-generation technology that the entire biopharma industry can tap into.”
— Wendy Young, Ph.D., a life sciences senior executive and former SVP of small molecule discovery at Genentech
“Having launched and run many biotech companies in my career, I’ve seen the pain of compound optimization first hand – years of intuition-driven science and millions of dollars spent to find one or two compounds that have the right balance of potency and ADMET. When I learned about the platform Inductive is making available to the biopharma industry I was excited to get involved because I know how much this will accelerate our industry’s ability to bring safer and more effective therapies to patients.”
— Ankit Mahadevia, M.D., a serial biotech entrepreneur, former Venture partner at Atlas Ventures, and co-founder of nine therapeutics companies, also joined Inductive’s advisory board
