News
December 13, 2023
Inductive Bio Emerges from Stealth, Unveiling an ML Platform to Accelerate Compound Optimization in Drug Discovery
- Inductive Bio emerged with $4.3M in a seed funding round co-led by a16z Bio + Health and Lux Capital, with participation from Character, Bessemer Venture Partners, Alleycorp, and others.
- Inductive's team has deep expertise building innovative ML products and bringing drugs into the clinic.
NEW YORK, Dec. 13, 2023 /PRNewswire/ — Inductive Bio, a technology company developing a machine learning (ML) platform designed to dramatically accelerate the compound optimization process, emerged from stealth today with $4.3M in funding. Their 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 spent in small molecule preclinical drug discovery is focused on optimizing compounds to effectively balance potency with Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties. 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, which was acquired by Roche in 2018. "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," said Josh Haimson, co-founder and CEO of Inductive Bio. "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."
"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," said Ben Birnbaum, Ph.D., co-founder and CTO of Inductive Bio. "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."
Wendy Young, Ph.D., a life sciences senior executive and former SVP of small molecule discovery at Genentech, where she oversaw the discovery and progression of more than 25 clinical candidates into development, joined Inductive's advisory board in the summer of 2022. "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," said Dr. Young. "I'm excited that at Inductive, we're building the next-generation technology that the entire biopharma industry can tap into."
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.
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. "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," said Dr. Mahadevia. "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."
About Inductive Bio
Inductive Bio is a technology company developing a machine learning (ML) platform designed to dramatically accelerate the compound optimization process, a critical and time-consuming step in developing new therapeutics. By building datasets and state-of-the-art ML models designed to map the drivers of small molecule Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET), Inductive's platform allows scientists to optimize initial compounds into leads and development candidates faster and with a better balance of ADMET properties. For more information, please visit www.inductive.bio.
About Andreessen Horowitz
Andreessen Horowitz ("a16z") is a venture capital firm that backs bold entrepreneurs who are building the future through technology. We invest in companies across multiple sectors, including bio + health, consumer, crypto, enterprise, fintech, games, and companies building toward American dynamism. For more than a decade, our bio + health team has invested in innovative companies leveraging AI and other technologies to drive process efficiencies, usher in the next generation of therapeutics and personalized care delivery, and ensure enduring healthcare for all. We believe the Future is Health.
About Lux Capital
Lux Capital invests in emerging science and technology ventures at the outermost edges of what is possible. They partner with iconoclastic inventors challenging the status quo and the laws of nature to bring their futuristic ideas to life. Over the past two decades, Lux has expanded from its New York City roots to Silicon Valley, and built a $5 billion AUM firm of more than 30 full-time professionals, with the versatility to invest at any stage.
Contact: media@inductive.bio
- QC analytical reports (1H/13C/19F/2D NMR, chiral SFC)
- Propose, visualize, and triage forward and retrosyntheses
- Monitor the synthesis queue and flag stalled targets
- QC assay data as it lands and flag suspicious results
- Prioritize repeats and nominate compounds for downstream assays
- Analyze SAR and identify data gaps
- Evaluate IVIVC and suggest diagnostic experiments
- Design, enumerate, and triage analogs
- Launch and analyze physics-based workflows like docking and FEP
- Project human PK and efficacious dose
- Answer questions about a program’s history (what was learned and when)
- Track team progress against the target candidate profile
- Get new scientists up to speed on a program
- Make meeting-ready slides and figures
Prompt: I’m attaching two files with activity data, one with new data from today and one with historical data. Can you look through the new data and identify any QC issues that I should be aware of? Create a csv where every compound + assay run pair is labeled with any relevant issues.
Prompt: Do a nitrogen walk around the core of this molecule: O=C(NCC1=CC=C(C)C(F)=C1)C2=CC=C3C=C(N4[C@H](C)CCCC4)C=CN32
Prompt: Do an OH walk around this whole molecule: O=C(NCC1=CC=C(C)C(F)=C1)C2=CC=C3C=C(N4[C@H](C)CCCC4)C=CN32
Prompt: Replace the core of this molecule with this set of 5,6-ring systems (file attached): O=C(NCC1=CC=C(C)C(F)=C1)C2=CC=C3C=C(N4[C@H](C)CCCC4)C=CN32
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