Schrödinger Launches Initiative to Significantly Expand Application of Computational Tools for Predictive Toxicology

Rhea-AI Summary

Schrödinger (NASDAQ: SDGR) has launched an initiative to expand its computational platform for predictive toxicology in drug discovery. The project aims to develop tools to improve drug candidates' properties and reduce development failures due to off-target protein binding. Funded by a $10 million grant from the Bill & Melinda Gates Foundation, the initiative will leverage Schrödinger's physics-based platform and NVIDIA's AI technologies.

The resulting technology will be available to Gates Foundation grantees, Schrödinger's software customers, and for the company's drug discovery programs. This initiative addresses a significant challenge in drug development, as safety issues are a frequent cause of delays and failures. The project aligns with the FDA's Predictive Toxicology Roadmap and has the potential to accelerate drug discovery while reducing toxicity risks in preclinical and clinical studies.

Positive

• $10 million grant received from Bill & Melinda Gates Foundation
• Expansion of computational platform to include predictive toxicology
• Potential to reduce drug development failures and costs
• Collaboration with NVIDIA for AI technologies
• Technology will be available to multiple stakeholders, including Gates Foundation grantees and Schrödinger's customers

Negative

• None.

Insights

Financial Analyst

Schrödinger's initiative to expand its computational platform for predictive toxicology represents a significant strategic move with potential long-term implications for the company's financial performance. The $10 million grant from the Bill & Melinda Gates Foundation provides immediate funding, reducing the company's initial R&D burden. However, the true value lies in the potential market expansion and competitive advantage this technology could offer.

If successful, this initiative could:

• Increase Schrödinger's software licensing revenue by offering a highly valuable tool to pharmaceutical companies
• Enhance the company's drug discovery collaborations, potentially leading to more lucrative partnerships
• Improve the success rate of Schrödinger's proprietary drug discovery programs, reducing costs and increasing the likelihood of marketable drugs

While the immediate financial impact may be , the long-term potential for revenue growth and cost reduction in drug development is substantial. Investors should monitor the progress of this initiative closely, as successful implementation could significantly boost Schrödinger's market position and financial outlook in the highly competitive drug discovery space.

Medical Research Analyst

Schrödinger's initiative to develop predictive toxicology tools represents a potential paradigm shift in drug discovery. The focus on early prediction of off-target binding and associated toxicity addresses a critical pain point in the pharmaceutical industry. Currently, approximately 90% of drug candidates fail in clinical trials, with toxicity being a major contributor to these failures.

Key potential impacts of this technology include:

• Significant reduction in late-stage drug failures, potentially saving billions in R&D costs
• Acceleration of the drug discovery process by identifying safer candidates earlier
• Improved safety profiles for drugs that do reach clinical trials and the market

The collaboration with NVIDIA to leverage AI technologies is particularly promising, as it could enhance the accuracy and speed of predictions. However, it's important to note that developing accurate predictive models for complex biological systems is challenging. The success of this initiative will depend on the quality and breadth of data used to train these models, as well as the ability to validate predictions in real-world settings.

If successful, this technology could revolutionize drug discovery, potentially leading to safer, more effective drugs reaching patients faster and at lower costs. The involvement of the Gates Foundation also highlights the potential global health impact, particularly for neglected diseases affecting low- and middle-income countries.

Tech Expert

Schrödinger's initiative to expand its computational platform for predictive toxicology represents a significant advancement in the application of physics-based modeling and AI to drug discovery. This project leverages several cutting-edge technologies:

• Physics-based computational modeling: Schrödinger's core strength, allowing for accurate prediction of molecular interactions
• AI and machine learning: Collaboration with NVIDIA suggests the use of advanced AI algorithms, likely including deep learning models
• High-performance computing: Necessary for running complex simulations and AI models at scale

The technical challenges are substantial. Accurately predicting toxicity requires modeling complex biological systems and their interactions with drug molecules. This demands not only powerful computational resources but also sophisticated algorithms that can integrate diverse data types and account for the inherent variability in biological systems.

The success of this initiative could position Schrödinger as a leader in AI-driven drug discovery. It also has the potential to create a new standard in the industry, possibly leading to increased demand for high-performance computing resources in pharmaceutical research.

From a broader perspective, this project exemplifies the growing trend of using AI and physics-based modeling to solve complex biological problems. If successful, it could accelerate similar applications in other areas of life sciences and materials science.

Initiative initially funded by $10 million grant from the Bill & Melinda Gates Foundation

NEW YORK--(BUSINESS WIRE)-- Schrödinger, Inc. (Nasdaq: SDGR), whose physics-based computational platform is transforming the way therapeutics and materials are discovered, today announced that it is embarking on an initiative to expand its computational platform to predict toxicology risk early in drug discovery. The goal of the initiative is to develop a computational solution designed to improve the properties of novel drug development candidates and reduce the risk of development failure associated with binding to off-target proteins, which can be associated with serious side effects. This initiative is an expansion of Schrödinger’s “predict first” digital laboratory and will leverage its physics-based platform and NVIDIA’s AI technologies. Broad deployment of predictive toxicology has the potential to accelerate progress from target to drug development candidate and reduce the risk of toxicity in preclinical or clinical studies. Safety issues are a frequent cause of drug development delays and failures and are the focus of the U.S. Food and Drug Administration's Predictive Toxicology Roadmap.

The initiative will be funded by a $10 million grant from the Bill & Melinda Gates Foundation to accelerate the scientific research underlying this initiative for the first year of the project. Once developed, the technology will be available to the Gates Foundation’s grantees around the world to help speed the development of new drugs against diseases that disproportionately affect people in low- and middle-income countries. These tools will also be available to Schrödinger’s software customers and will be used to advance Schrödinger’s proprietary drug discovery programs and collaborations.

“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. 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,” stated Ramy Farid, Ph.D., chief executive officer at Schrödinger. “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,” stated Trevor Mundel, president, global health, at the Gates Foundation. “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.”

“With its world-leading physics-based platform, Schrödinger has spearheaded the last two decades of computational drug and materials discovery,” said Kimberly Powell, vice president of healthcare at NVIDIA. “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 already generated several computational predictive models of off-target drug activity. The company’s recent advances characterizing the structure of safety-related proteins such as hERG (recently published in Cell) and cytochrome P450 enzymes are examples of these efforts.

About Schrödinger

Schrödinger is transforming the way therapeutics and materials are discovered. Schrödinger has pioneered a physics-based computational platform that enables discovery of high-quality, novel molecules for drug development and materials applications more rapidly and at lower cost compared to traditional methods. The software platform is licensed by biopharmaceutical and industrial companies, academic institutions, and government laboratories around the world. Schrödinger’s multidisciplinary drug discovery team also leverages the software platform to advance a portfolio of collaborative and proprietary programs to address unmet medical needs.

Founded in 1990, Schrödinger has approximately 850 employees and is engaged with customers and collaborators in more than 70 countries. To learn more, visit www.schrodinger.com, follow us on LinkedIn and Instagram, or visit our blog, Extrapolations.com.

Cautionary Note Regarding Forward-Looking Statements

This press release contains forward-looking statements within the meaning of The Private Securities Litigation Reform Act of 1995 including, but not limited to those statements regarding Schrödinger’s expectations about the speed and capacity of its computational platform, the long-term potential of its business, its ability to improve and advance the science underlying its platform, including the ability to predict off-target activity, its ability to improve drug discovery and the timing during which the initiative’s technology will become available to software customers and collaborators, as well as expectations related to the use of its cash, cash equivalents and marketable securities. Statements including words such as “aim,” “anticipate,” “believe,” “contemplate,” “continue,” “could,” “estimate,” “expect,” “goal,” “intend,” “may,” “might,” “plan,” “potential,” “predict,” “project,” “should,” “target,” “will,” “would” and statements in the future tense are forward-looking statements. These forward-looking statements reflect Schrödinger’s current views about its plans, intentions, expectations, strategies and prospects, which are based on the information currently available to the company and on assumptions the company has made. Actual results may differ materially from those described in these forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and important factors that are beyond Schrödinger’s control, including the demand for its software platform, its ability to further develop its computational platform, its reliance upon third-party providers of cloud-based infrastructure to host its software solutions, factors adversely affecting the life sciences industry, fluctuations in the value of the U.S. dollar and foreign currencies, its reliance upon its third-party drug discovery collaborators, the uncertainties inherent in drug development and commercialization, such as the conduct of research activities and the timing of and its ability to initiate and complete preclinical studies and clinical trials, whether results from preclinical studies will be predictive of the results of later preclinical studies and clinical trials, uncertainties associated with the regulatory review of IND submissions, clinical trials and applications for marketing approvals, the ability to retain and hire key personnel and other risks detailed under the caption “Risk Factors” and elsewhere in the company’s Securities and Exchange Commission filings and reports, including its Quarterly Report on Form 10-Q for the quarter ended March 31, 2024, filed with the Securities and Exchange Commission on May 1, 2024, as well as future filings and reports by the company. Any forward-looking statements contained in this press release speak only as of the date hereof. Except as required by law, Schrödinger undertakes no duty or obligation to update any forward-looking statements contained in this press release as a result of new information, future events, changes in expectations or otherwise.

View source version on businesswire.com: https://www.businesswire.com/news/home/20240726774411/en/

Jaren Madden

Schrödinger, Inc. (Investors)

617-266-6264

Matthew Luchini (Investors)

Schrödinger, Inc.

matthew.luchini@schrodinger.com

917-719-0636

Allie Nicodemo (Media)

Schrödinger, Inc.

allie.nicodemo@schrodinger.com

617-356-2325

Source: Schrödinger

FAQ

What is the purpose of Schrödinger's new initiative announced on May 16, 2023?

Schrödinger's new initiative aims to expand its computational platform to predict toxicology risk early in drug discovery, potentially reducing development failures associated with off-target protein binding and improving drug candidate properties.

How much funding did Schrödinger (SDGR) receive for its predictive toxicology initiative?

Schrödinger received a $10 million grant from the Bill & Melinda Gates Foundation to fund the first year of the predictive toxicology initiative.

Who will have access to the predictive toxicology technology developed by Schrödinger (SDGR)?

The technology will be available to Gates Foundation grantees, Schrödinger's software customers, and will be used in Schrödinger's proprietary drug discovery programs and collaborations.

How does Schrödinger's (SDGR) predictive toxicology initiative align with FDA goals?

The initiative aligns with the U.S. Food and Drug Administration's Predictive Toxicology Roadmap, addressing safety issues that are a frequent cause of drug development delays and failures.