Simulations Plus, Inc. (“Simulations Plus”), a leading provider of cheminformatics, biosimulation, simulation-enabled performance and intelligence solutions, and medical communications to the biopharma industry, announced that experimental results of its artificial intelligence-driven drug design (AIDD) collaboration with the Institute of Medical Biology of the Polish Academy of Sciences (IMB PAS) have been published in the American Chemical Society (ACS) Medical Chemistry Letters .
Simulations Plus and IMB PAS launched their collaboration in 2023 to use the AIDD module in ADMET Predictor® to design novel RORγ/RORγT ligands, molecules that impact gene expression related to inflammation and immune responses. Within three months, the two teams had developed models to predict RORγ/RORγT ligand potency, designed potential ligands simultaneously optimized for potency, in vivo absorption, synthesizability, and ADMET risk, synthesized compounds, and completed initial in vitro potency and toxicity testing. The recently published results show that the vast majority of compounds tested had strong potency for the target that was close to or better than the values predicted by ADMET Predictor.
“Among the 27 compounds we tested, an impressive 70% demonstrated significant inhibition of RORγT activity, with our lead compound exhibiting potent inverse agonist activity and a novel indolizine scaffold not previously reported for this target,” said Rafal A. Bachorz, Senior Principal Applied Scientist at Simulations Plus and lead author of the publication. “Importantly, this compound displayed strong efficacy in cellular assays, no significant cytotoxicity, and effectively suppressed the expression of proinflammatory Th17 cytokines in human T cells. In vitro ADMET profiling of our most potent compound showed that this molecule possesses favorable drug-like properties, as predicted by ADMET Predictor, supporting its potential as a promising lead for further optimization. These findings highlight the power of AI-driven, multi-parameter optimization in accelerating drug discovery and underscore the potential of our approach to deliver innovative therapies for patients across the globe.”
“We are delighted to see the validation of our models and ADMET Predictor platform,” said Viera Lukacova, Chief Scientific Officer at Simulations Plus. “ADMET Predictor and the AIDD module provide our clients with a first-to-invent advantage by harnessing artificial intelligence and machine learning (AI/ML) to design and optimize compounds for specific targets. We are particularly pleased to collaborate with the scientists at IMB PAS to advance their research on RORγ/RORγT receptors and their potential role in cancer progression, and we look forward to extending this partnership through further rounds of scaffold optimization based on the promising results achieved to date.”
