Inductive Bio

If you're interested in the intersection of AI x biology, come drop by the "Rise of the AI Scientist" panel for SF Tech Week. I'm looking forward to discussing the present and future of AI x biology with Zak Doric, PhD from Andreessen Horowitz, Ashu Singhal from Benchling, Josh Haimson from Inductive Bio, and Stefano Quintini from Fenwick & West! Register here: https://lnkd.in/gHTzhE9y?

We're bringing the AI Drug Discovery ecosystem together. Join high-profile guests from tech, pharma, startups & academia to discuss the future. Some of the perspectives we’re excited to feature: ➡️ Josh Haimson (Inductive Bio) ➡️ Mike Marlow (Boehringer Ingelheim) ➡️ Margie Sutton (MD Anderson) We will dive into what AI-native biology looks like in practice. Data, collaboration, and lab-in-the-loop R&D. Datapoints Summit 2025. Sept 9th. Boston Seaport. Space is just about full. Check out the agenda and request an invite here: https://lnkd.in/gxqgV8ic

At Inductive Bio, we believe the future of drug discovery lies in a tight integration between the dry lab and the wet lab. That’s why we’re partnering with Ginkgo Datapoints and Tangible Scientific to create a lab-in-the-loop workflow that brings these pieces together. By combining AI chemistry models, rapid ADME profiling, and seamless compound logistics, this collaboration helps researchers reduce costs, shorten discovery timelines, and design higher quality development candidates. It’s a step toward a world where new medicines move from idea to the clinic faster than ever before. Read more in the link in the comments.

Can AI help overcome one of drug discovery’s most persistent bottlenecks? At Inductive Bio, we believe it can, by enabling more efficient ADMET optimization. Our Amodels provide chemists with real-time, molecular-level insights before synthesis begins, reducing failed compounds and speeding up decision-making. In this new Drug Target Review feature, our CEO and Co-founder, Josh Haimson, shares how Inductive Bio is: • Replacing ADMET "whack-a-mole" with targeted, predictive modeling • Building a secure, pre-competitive data consortium • Partnering with biotechs like Nested Therapeutics to accelerate lead optimization • Delivering intuitive tools chemists can use without a machine learning background Read how our platform is helping drug discovery teams work faster and smarter: https://lnkd.in/gn_4yCQs

We’re thrilled to announce that our latest generation of Beacon-1 ADMET models secured first place in the recent Polaris ASAP blinded prediction challenge focused on ADMET properties. This exciting competition, organized by Polaris - Benchmarks for methods that matter, ASAP Discovery, and OpenADMET, used real antiviral program data from ASAP’s MERS-CoV and SARS-CoV-2 efforts. The setup mirrored real-world conditions, with chronologically split training and test sets and blinded outcomes, offering an opportunity to benchmark competing ML approaches in a realistic drug discovery scenario. Our post-win analysis revealed two key takeaways. First, bringing in additional ADMET data consistently enhanced accuracy. Second, our analysis of additional programs showed that the relative performance of ML methods can vary meaningfully across programs, underscoring the importance of benchmarks that truly reflect the diverse chemical space of drug discovery. A huge thank you to Polaris for organizing this valuable benchmark. We look forward to more initiatives that raise the bar for ML evaluation in drug discovery. Link to our full blog post in the comments.

We’re thrilled to welcome Nicolas Pabon as the newest member of the Inductive team!

Thanks to Brian Gormley for featuring Inductive Bio in The Wall Street Journal's VC Daily newsletter today! We appreciate the opportunity to share how our pre-competitive data consortium approach is helping address the complex balancing act of drug optimization. By bringing together biopharma organizations to collaborate on ADMET data, we're enabling AI predictions that help chemists design better molecules more efficiently. Grateful to our partners and investors who are supporting our mission to accelerate the discovery of life-changing therapies. Read here: https://lnkd.in/gjSuZQZB #DrugDiscovery #AI #MachineLearning #Biotech

We just closed our Series A and we're expanding our team! Inductive is growing rapidly and we have some exciting announcements coming soon. If you’re interested in working with our talented, ambitious, and kind team to combine medicinal chemistry, AI, and software to accelerate drug discovery across the industry, please reach out! We are hiring across a number of different roles, including the following titles: - Head of Medicinal Chemistry - ML Engineer - Frontend Engineer - Full Stack Engineer - Product Designer - Growth Marketer - Partnerships Lead To learn more and apply, visit our careers page here:

Excited to share BiotechTV's interview with our CEO, Josh Haimson, diving into how Inductive is helping improve the speed and quality of small-molecule drug discovery.

We’re excited to announce that Inductive has raised $25M in Series A funding, led by Obvious Ventures with participation from a16z Bio + Health, Lux Capital, S32, Character Capital, Amino Collective, and leading angel investors. AI is not a silver bullet for drug discovery, but it is a powerful tool in the drug hunter’s toolbox. This milestone enables us to expand our mission of democratizing AI tools that transform small-molecule drug discovery. At the heart of Inductive is our pre-competitive data consortium, bringing together anonymized datasets across biopharma in a secure, IP-protected environment. This data powers Compass, our AI platform that predicts ADMET properties before synthesis - helping medicinal chemists design better molecules, faster. Since launching last year: • Compass has supported dozens of drug discovery programs • Over 1 million molecule designs have been explored on the platform • Our models placed 1st in the Polaris ADMET challenge, outperforming 38 global AI and computational chemistry groups from leading companies and academic labs In a time when speed, efficiency, and quality are more important than ever, we're building tools that help drug discovery scientists navigate chemical space more confidently to discover the next generation of life-changing therapies, faster. We’re just getting started. 🔗 Learn more: https://lnkd.in/gt3yAa_E #DrugDiscovery #AI #SeriesA #Biotech #Pharma #LifeSciences #InductiveBio