Schrödinger Launches Major Initiative To Enhance Predictive Toxicology Capabilities
Schrödinger improves drug safety with AI-enhanced computational toxicology tools.
Breaking News
Jul 29, 2024
Mrudula Kulkarni

Schrödinger, Inc., known for its innovative physics-based
computational platform that revolutionizes therapeutic and material discovery,
has announced a new initiative aimed at enhancing its platform to assess
toxicology risks in the early stages of drug discovery. This effort seeks to
create a computational tool that will improve the characteristics of new drug
candidates and mitigate the risk of development failures linked to off-target
protein interactions, which can lead to significant adverse effects. This
initiative expands upon Schrödinger’s existing “predict first” digital
laboratory, utilizing its physics-driven platform alongside NVIDIA’s AI
technologies.
Implementing predictive toxicology broadly could expedite
the transition from target identification to viable drug candidates,
significantly lowering the chances of toxicity-related setbacks during
preclinical or clinical trials. Safety concerns are a common cause of delays
and failures in drug development and are a focal point of the U.S. Food and
Drug Administration's Predictive Toxicology Roadmap.
The first year of this project will be supported by a $10
million grant from the Bill & Melinda Gates Foundation, aimed at
accelerating the scientific research integral to this initiative. Once the
technology is fully developed, it will be made available to the Gates
Foundation’s grantees globally, facilitating the rapid advancement of new
treatments for diseases that disproportionately impact individuals in low- and
middle-income countries. Additionally, these tools will be accessible to
Schrödinger’s software clients and will enhance the company’s proprietary drug
discovery programs and partnerships.
Ramy Farid, Ph.D., Chief Executive Officer at Schrödinger,
said in a statement, “Drug discovery is an extremely challenging endeavor, and
off-target toxicity is a significant cause of drug development failure. The
application of our technology, at scale against a broad panel of known
off-target proteins, has the potential to prevent a significant number of these
failures, reducing the potential for safety issues in preclinical and clinical
research, and lowering the cost and risk of drug development.”
He further added, “ Advances in structural biology and
computer performance, coupled with the increasing accuracy of our computational
platform, gives us a unique opportunity to address the need for high quality
computational models for predictive toxicology. We appreciate the support from
the Gates Foundation, which allows us to immediately scale up our efforts
advancing this initiative.”
“Optimizing the safety profile of drug candidates is one of
the most difficult challenges in drug discovery, and computational approaches
have the potential to revolutionize the way we discover drugs by enabling the
prediction of drug toxicity with unprecedented accuracy and efficiency prior to
clinical testing. Leveraging computation to predict the toxicological risk of
drug candidates could ultimately improve productivity across the pharmaceutical
industry and unlock major advances against diseases that continue to plague
low- and middle-income countries,” said Trevor Mundel, president, global
health, at the Gates Foundation.
Kimberly Powell, the Vice President of health at NVIDIA,
also added, “With its world-leading physics-based platform, Schrödinger has
spearheaded the last two decades of computational drug and materials discovery.
Accelerated computing, which introduces many orders of magnitude in discovery
power, combined with generative AI will enhance researchers’ abilities to
tackle complex scientific challenges like predictive toxicology, leading to
faster, more efficient and effective discovery cycles and transformative
medicines for patients.”
Schrödinger has developed multiple computational models that
predict off-target activity of drugs. Notable achievements include their recent
work on safety-related proteins like hERG, detailed in a publication in Cell,
and their studies on cytochrome P450 enzymes, showcasing the company’s
commitment to enhancing drug safety through advanced structural
characterization.