Simulations Plus Partners with Large Pharmaceutical Company to Validate AI-Driven Drug Design Capabilities in ADMET Predictor®

Software: ADMET Predictor®
Division: Simulations Plus

 Simulations Plus, Inc. (Nasdaq: SLP), the leading provider of modeling and simulation solutions for the pharmaceutical, biotechnology, chemicals, and consumer goods industries, today announced that it entered into a collaborative research agreement with a large pharmaceutical company to evaluate the new AIDD Module in the recently launched version of ADMET Predictor®.

Per the terms of the collaboration, the partner company has entrusted Simulations Plus with compound structure and activity data from one of their ongoing drug discovery programs. The computational chemists at Simulations Plus worked with the partner’s team to define the multi-objective parameters against which the lead molecule(s) needed to be optimized. The innovative approaches within the AIDD Module are now being unleashed to produce novel libraries of virtual compounds with excellent predicted combinations of the properties we chose. Selected sets of analogs will be synthesized and tested to complement the in-house development program and assess the merits of the AIDD approach, with results expected to be jointly shared.

“Many companies have great interest in the exploratory discovery capabilities that the AIDD Module offers and the role it can play in the inventive step,” said Dr. Eric Jamois, director of business development. “We are excited to work with a major pharmaceutical partner to augment their traditional design activities and ensure the output from our technology goes beyond what can be obtained by relying on intuited guidance alone.”

“Simulations Plus recently published a proof-of-principle antimalarial design study we started several years ago that validates several of the individual steps now automated in the AIDD Module,” added Dr. Robert Clark, senior research fellow and co-PI on the collaboration. “In that project, however, we were limited to filling in a chemistry ‘box.’ The generative chemistry algorithms in the AIDD Module, coupled with ADMET Predictor’s mechanistic pharmacokinetic simulations, now allow scientists to move outside the box and explore a larger, more novel chemistry space.”

John DiBella, Lancaster division president, said: “This collaboration is a perfect example of a ‘win-win’ situation. Our client retains all rights to the new compounds resulting from the collaboration. We can utilize the generated experimental data, which no other commercial software vendor has, to improve the machine learning algorithms in ADMET Predictor in ways that will benefit all our clients. We invite those interested in learning more about the capabilities within the AIDD Module, including new case studies, to join us at our webinar scheduled on Wednesday, September 30th at 8 a.m. PDT.”