Collaboration aims to enable discovery of first-in-class therapeutic candidates
NEW YORK & SHANGHAI–(BUSINESS WIRE)–Schrödinger, Inc. (Nasdaq: SDGR) and Viva Biotech Holdings (1873.HK) today announced a strategic collaboration to expand the reach of structure-based drug discovery by generating de novo crystal structures of high-value targets.
Under the terms of the collaboration, Schrödinger will identify drug discovery targets for which there are currently no crystal structures in the public domain, including those that could lead to first-in-class therapeutic candidates for its internal pipeline. Viva Biotech will deploy X-ray crystallography designed to structurally enable these targets by generating high-resolution structures with bound ligands. Schrödinger will then leverage its advanced computational platform at scale to explore large portions of chemical space with the goal of designing novel therapeutic candidates for such targets.
“This is an exciting collaboration. We have identified numerous promising targets that are challenging to drug in part because they lack high-resolution crystal structures. Viva Biotech is widely recognized as a world leader in x-ray crystallography, and we believe they will be able to generate high-quality structures that are amenable to our physics-based predictive modeling,” said Karen Akinsanya, Ph.D., Executive Vice President, Chief Biomedical Scientist and Head of Discovery R&D at Schrödinger. “We hope this collaboration will lead to the discovery of therapeutic candidates that can be advanced into human trials in areas with critical unmet medical needs.”
“This collaboration brings together two leaders in the field of structure-based drug discovery,” said Zhixiong Ye, Chief Scientific Officer at Viva Biotech. “Our expertise in x-ray crystallography and in other key related areas enables us to generate de novo structures for previously unsolved targets. Schrödinger’s industry-leading platform enables broad and rapid exploration of chemical space. Together, we hope to create innovative therapeutics with the potential to benefit patients around the world. (Read more…)”
Schrödinger’s industry-leading computational platform to accelerate drug discovery and materials design is deployed by leading biopharmaceutical and industrial companies, academic institutions, and government laboratories worldwide. In addition to this global business, Schrödinger is also applying its computational platform to a robust pipeline of drug discovery programs in collaboration with pharmaceutical companies and has co-founded leading biotech companies. In addition, Schrödinger is using its platform to advance a pipeline of internal, wholly-owned drug discovery programs. Schrödinger’s significant and ongoing investment in basic research continues to drive advances in its computational platform. Founded in 1990, Schrödinger has over 400 employees in its New York City headquarters and around the world. Visit www.schrodinger.com for more information.
About Viva Biotech
Viva Biotech operates a leading structure-based, integrated drug discovery platform, providing drug discovery services to biotechnology and pharmaceutical customers worldwide. Viva Biotech actively combines conventional cash-for-service (CFS) and unique equity-for-service (EFS) approaches to realize a combination of short and long term innovation-driven returns. CFS covers the full spectrum of its customers’ needs for early-stage drug discovery, including target protein expression and structure research, hit screening, lead optimization, and drug candidate determination. As of December 31st, 2019, Viva Biotech has served 438 pharmaceutical customers worldwide, worked on over 1,200 independent drug targets, delivered approximately over 13,700 protein structures, and incubated/invested 46 early-stage biotech startups. Visit www.vivabiotech.com for more information.
Cautionary Note Regarding Forward-looking Statements of Schrödinger
This press release contains forward-looking statements of Schrödinger within the meaning of The Private Securities Litigation Reform Act of 1995 including, but not limited to those regarding Schrödinger’s expectations about the speed and capacity of its computational platform, its ability to expand the reach of structure-based drug discovery, and its ability to leverage its advanced computational platform to potentially design novel therapeutic candidates. Statements including words such as “anticipate,” “believe,” “contemplate,” “continue,” “could,” “estimate,” “expect,” “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 it and on assumptions it 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 factors that are beyond Schrödinger’s control, including its ability to further develop its computational platform, its reliance upon third-party providers of cloud-based infrastructure to host its software solutions, its reliance upon its third-party drug discovery collaborators, the ability to retain and hire key personnel and the direct and indirect impacts of the ongoing COVID-19 pandemic on its business and other risks detailed under the caption “Risk Factors” and elsewhere in its Securities and Exchange Commission filings and reports, including its Quarterly Report on Form 10-Q for the quarter ending March 31, 2020 filed with the Securities and Exchange Commission on May 13, 2020. Any forward-looking statements of Schrödinger 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.
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