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Insilico nominates an AI-designed obesity pill with a safety edge

The Hong Kong-listed biotech used its generative chemistry platform to design ISM1354, a small-molecule GIPR antagonist built for obesity and Type 2 diabetes.

MedSpark Staff
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msadmin
MedSpark Staff
Bymsadmin
Medical, Healthcare, & Biotech/Pharma AI News
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Published: October 3, 2026
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Insilico Medicine has nominated ISM1354, an AI-designed small molecule aimed at the glucose-dependent insulinotropic polypeptide receptor, as a preclinical candidate for obesity and Type 2 diabetes.

The compound came out of Chemistry42, Insilico’s generative chemistry platform. The company leaned on protein-ligand structures, an early liver-injury prediction filter and free energy perturbation modeling across repeated design cycles.

Preclinical work showed oral bioavailability of 75% to 104% across mice, rats, dogs and monkeys. At the same dose, the compound produced at least 18 times greater plasma exposure than a clinical-stage benchmark, Insilico said.

Safety data also looked differentiated. The company reported weaker OATP1B1 inhibition than the benchmark and a wider hepatocyte safety margin, with little effect on cell viability up to 200 micromolar. Non-GLP monkey toxicology showed roughly a 45-fold safety margin.

Why pair a GIPR drug with the blockbuster GLP-1 class? The hope is that combining them strips fat without eroding lean muscle, a priority for societies facing more frailty in old age.

TAGGED:AI Drug Discoverygenerative chemistryGIPRInsilico Medicinemetabolic diseaseobesitypreclinical
SOURCES:Drug Target ReviewThe Manila Times
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