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.
Contact
media@inductive.bio
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SOURCE Inductive Bio, Inc.