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Insilico Medicine expands synthetic lethality portfolio with nomination of a preclinical candidate targeting MAT2A for the treatment of MTAP-deleted cancers
  • India - English


News provided by

Insilico Medicine

May 05, 2022, 11:00 ET

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NEW YORK, May 5, 2022 /PRNewswire/ -- Insilico Medicine ("Insilico"), a clinical-stage end-to-end artificial intelligence (AI)-driven drug discovery company, today announced that the company has nominated a preclinical candidate (PCC) targeting methionine adenosyltransferase 2A (MAT2A) from AI-designed molecules for the treatment of methylthioadenosine phosphorylase (MTAP)-deleted cancers. The PCC is part of Insilico's growing portfolio of synthetic lethality assets in development.

MTAP deletion is one of the most common gene deletions seen in cancers including lung, bladder, and pancreatic cancer, and is associated with poor prognosis. MAT2A is defined as a synthetic lethality target in MTAP-deleted cancers and plays an essential role in producing S-adenosylmethionine (SAM), a molecule involved in cell function and survival. Inhibitors of MAT2A lead to a selective anti-proliferative effect on MTAP-deleted cancer cells by reducing the level of SAM to affect PRMT5-Dependent mRNA splicing, inducing DNA damage.

Insilico's PCC is a potent and selective MAT2A inhibitor. It demonstrated excellent drug-likeness with good solubility and permeability, good activity at low doses in animal models, and a favorable safety profile in preclinical studies. Insilico is progressing the PCC in IND-enabling studies and anticipates IND filing in early 2023.

"Powered by AI, the MAT2A program team was able to discover the PCC molecule with high selectivity of MTAP-deleted cancer cells over wide-type cells, which we believe provides key differentiation compared to reported MAT2A inhibitors," said Feng Ren, PhD, Chief Scientific Officer of Insilico Medicine. "This is the second PCC in our growing synthetic lethality pipeline, and we are progressing the molecule in IND-enabling studies towards clinical trials for the treatment of MTAP-deleted cancers."

Insilico has built a strong portfolio of synthetic lethality assets supported by scientists with deep drug discovery expertise and its AI-driven small molecule design and generation engine, Chemistry42. The company announced its first synthetic lethality PCC, which targets USP1 for tumors with homologous recombination deficiency, in mid-April. Continuing this success, Insilico delivered the PCC for the MAT2A program approximately 12 months after its initiation.

"This PCC continues the expansion of our synthetic lethality portfolio, driven by our end-to-end AI drug discovery platform," said Insilico founder and CEO Alex Zhavoronkov, PhD. "With this latest discovery, we continue to utilize the power of AI to treat the most aggressive cancers with the highest unmet needs."        

Insilico is developing a growing portfolio in frontier areas. In just over 12 months, it has delivered 7 PCCs, including AI-discovered therapeutics of novel targets with novel structures and AI-designed therapeutics of known targets with desired properties. It also successfully completed a Phase 0 microdose trial and entered a Phase I clinical trial with its first internally developed program for fibrosis.

About Insilico Medicine

Insilico Medicine, a clinical stage end-to-end artificial intelligence (AI)-driven drug discovery company, 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 to discover novel targets and to design novel molecular structures with desired properties. Insilico Medicine is delivering breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system (CNS) diseases and aging-related diseases.

For more information, visit www.insilico.com

For media inquiries, contact [email protected]

SOURCE Insilico Medicine

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