Inductive Bio Announces Publication of Successful Drug Optimization Collaboration with Nested Therapeutics

NEW YORK, July 29, 2024 /PRNewswire/ — Inductive Bio, a leader in leveraging machine learning (ML) to accelerate compound optimization for small molecule drug discovery, announces the publication of the approach and findings from their recent collaboration with Nested Therapeutics, a biotechnology company pioneering a next-generation precision medicine platform to address hard-to-treat cancers. The publication in ACS Medicinal Chemistry Letters highlights the pivotal role of ML models for ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) alongside computational potency predictions for prioritizing synthetic targets and enhancing design quality.

“Integrating Inductive Bio’s ADMET models into Nested’s predictive platforms helped us to prioritize designs with optimal drug like properties.”

Yongxin Han, EVP and Head of Drug Discovery at Nested Therapeutics

Multi-parameter optimization of small molecules is an expensive, time-intensive, and high-stakes process in which potency must be balanced with ADMET properties to achieve a viable drug candidate. The two companies combined Inductive’s ADMET foundation models, which leverage state-of-the-art deep learning methods trained on proprietary ADMET datasets, with Nested’s computational platform for predicting the potency of compounds in cryptic pockets. This collaborative approach allowed Nested to reduce the number of compounds synthesized and accelerate the lead optimization process.

“Integrating Inductive Bio’s ADMET models into Nested’s predictive platforms helped us to prioritize designs with optimal drug like properties,” said Yongxin Han, EVP and Head of Drug Discovery at Nested Therapeutics. “This allowed us to rapidly iterate and optimize lead compounds and address critical ADMET challenges.”

“We are very proud of the outcome from our collaboration with Nested Therapeutics,” said Josh Haimson, co-founder and CEO of Inductive Bio. “This publication underscores the impact of ML models for ADMET in accelerating drug optimization and offers a practical framework for others aiming to undertake similar approaches. We look forward to continuing to support our partners in achieving their drug discovery goals.”

For more information on this collaboration, read the full publication here: pubs.acs.org/doi/10.1021/acsmedchemlett.4c00290

About Inductive Bio

Inductive Bio is a technology company with a machine learning (ML) platform that dramatically accelerates 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.

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