Insilico adds biological age to virtual cell platform

Insilico Medicine launched its Virtual Aging Cell webpage and previewed a multi-agent platform that treats biological age as a core condition in virtual cell research. The company says the platform is designed to move beyond static cellular snapshots by simulating differentiation, reprogramming, aging and responses to interventions across six biological scales: molecular, intracellular, intercellular, tissue, organ and organism/population.

The VAC platform builds on Insilico’s decade of work in computational aging biology, beginning with its 2014 NVIDIA GTC work and extending through the PreciousGPT model series. Precious1GPT predicted biological age using methylation and transcriptomic data, Precious2GPT generated synthetic multi-omics data with tissue and age characteristics, and Precious3GPT integrated text, tabular data and knowledge graphs across multiple species and omics modalities.

Insilico positioned the platform as a digital testing environment for target identification, cell reprogramming protocol design and anti-aging drug evaluation. The company also cited its broader AI drug discovery record, including developmental candidate nomination in an average of just 12 to 18 months and clinical validation for molecules generated by its Pharma.AI platform, with Rentosertib completing a Phase IIa clinical trial.