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Based on AI-powered De novo Generation, Insilico Medicine nominates ISM1745 as preclinical candidate targeting PRMT5

A potentially best-in-class small molecule inhibitor for the treatment of MTAP-deleted cancers

Based on AI-powered De novo Generation, Insilico Medicine nominates ISM1745 as preclinical candidate targeting PRMT5
2025-01-02
(Press-News.org) Since 2021, Insilico Medicine has successfully nominated 22 preclinical candidates (PCCs) with the help of its proprietary Pharma.AI platform, among which 5 were nominated just the year of 2024. The novel scaffold of ISM1745 is based on de novo generation results of Insilico’s Chemistry42, the generative AI platform combining more than 40 generative models. With in vivo anti-tumor activity validated in multiple cancer models, the candidate compound showed robust in vivo efficacy as monotherapy as well as combination potential with chemotherapies, targeted agents including MAT2A inhibitor, and immunotherapies.

CAMBRIDGE, Mass., January 2, 2025 — Insilico Medicine (‘Insilico’), a clinical-stage generative artificial intelligence (AI)-driven drug discovery and development company, today announced the nomination of ISM1745, a potentially best-in-class MTA cooperative PRMT5 inhibitor with AI-powered novel scaffold, as preclinical candidate (PCC) for the treatment of MTAP-deleted cancers. Based on de novo design results of Chemistry42, ISM1745 marks the fifth PCC nomination achieved by the Insilico team in the year of 2024, bringing the total number since 2021 to 22.

Protein arginine methyltransferase 5 (PRMT5) regulates essential cellular processes, including RNA splicing, DNA damage repair, and translation, and elevated PRMT5 expression is observed in various cancers and correlates with poor prognostic outcomes. In MTAP-deleted tumor cells, the accumulating methylthioadenosine (MTA) increases sensitivity to PRMT5 inhibition, while binding with PRMT5 to form a novel MTAP-deleted cancer specific target, showing PRMT5’s potential as a synthetic lethality target.

"MTAP (methylthioadenosine phosphorylase) deletion occurs in about 15% of human cancers, with higher frequency in later line patients suffering from resistance to standard therapies, highlighting great unmet needs," said Feng Ren, PhD, Co-CEO and Chief Scientific Officer of Insilico Medicine. "The novel scaffold of ISM1745 powered by Chemistry42 enables unique interaction with the specific target for MTAP deleted cancers. With promising preclinical results, we look forward to further evaluation of ISM1745 as another Insilico AI-driven program."

Leveraging the structure-based generation strategy, Insilico scientists started with de novo molecule design outputs of Chemistry42, the AI-powered generative chemistry engine. After AI-supported molecule evaluation based on pharmacophores, druglikeness, developability and other factors, ISM1745 was selected as a preclinical candidate following rounds of optimization.

According to the preclinical data, ISM1745 demonstrated robust in vivo efficacy at a low dosage in multiple animal models, with promising potency as monotherapy and broad potential in combination with chemotherapies, targeted agents, and immunotherapies. The combination potential with MAT2A inhibitor has been validated in both in vitro and in vivo tests. Additionally, the compound shows excellent selectivity over MTAP WT cell lines, minimized drug-drug interaction (DDI) risk, and favorable Drug Metabolism and Pharmacokinetics (DMPK) profiles.

"As the fifth PCC nomination solely in 2024, the achievement further proves the reproducibility of Insilico's programs," said Alex Zhavoronkov, PhD, Founder and CEO of Insilico Medicine. "Since the foundation of Insilico in 2014, our Pharma.AI platform has been growing nonstop, from algorithms in the papers to the comprehensive AI toolbox today. We want to make sure that generative AI accelerates the costly and lengthy process of drug discovery and development, so more people could live longer and healthier lives."

In 2016, Insilico first described the concept of using generative AI for the design of novel molecules in a peer-reviewed journal, which laid the foundation for the commercially available Pharma.AI platform. Since then, Insilico keeps integrating technical breakthroughs into Pharma.AI platform, which is currently a generative AI-powered solution spanning across biology, chemistry, medicine development and science research. Powered by Pharma.AI, Insilico has nominated 22 preclinical candidates in its comprehensive portfolio of over 30 assets since 2021 and has received IND clearance for 10 molecules. 

In early 2024, Insilico published a Nature Biotechnology paper presenting the entire R&D journey from AI algorithms to Phase II clinical trials of ISM001-055, the company's lead drug pipeline with AI-discovered target and AI-designed structure. Following that, Insilico has recently announced positive preliminary results from a Phase IIa trial (NCT05938920), where ISM001-055 showed favorable safety and tolerability across all dose levels, as well as dose-dependent response in forced vital capacity (FVC), after only 12 weeks of dosage.

 

About Insilico Medicine 

Insilico Medicine, a global clinical stage biotechnology company powered by generative AI, is connecting biology, chemistry and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers and other modern machine learning techniques for novel target discovery and the generation of novel molecular structures with desired properties. Insilico Medicine is developing breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system diseases, infectious diseases, autoimmune diseases, and aging-related diseases.

www.insilico.com

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[Press-News.org] Based on AI-powered De novo Generation, Insilico Medicine nominates ISM1745 as preclinical candidate targeting PRMT5
A potentially best-in-class small molecule inhibitor for the treatment of MTAP-deleted cancers