The journey of INS018_055 to Phase II trials has been one of continual "firsts." The preclinical candidate was selected in Feb. 2021, just 18 months after the project began. Nine months later the Company announced first-in-human for Phase 1 trials. It was a milestone in drug discovery – from novel target discovery to Phase 1 in under 30 months, about half the time the process would take with traditional drug discovery, thanks to the speed and efficiency provided by AI, and for a fraction of the cost.
To build the initial hypothesis, Insilico scientists trained the target discovery engine PandaOmics
on a collection of omics and clinical datasets related to tissue fibrosis, annotated by age and sex. PandaOmics performed sophisticated gene and pathway scoring and found relevant targets via deep feature synthesis, causality inference, and de novo pathway reconstruction. The target novelty and disease association scoring was assessed by a natural language processing (NLP) engine, which analyzes data from millions of data files, including patents, research publications, grants, and databases of clinical trials. PandaOmics revealed 20 targets for validation, and one novel intracellular target – "Target X" – was prioritized for further analysis.
Next, scientists applied Chemistry42
, the generative AI chemistry engine, to this novel target. The engine uses 500 predictive pre-trained models, including transformer-based, GANs and genetic algorithms, which reward and punish generated molecules based on how well they meet the necessary conditions – including hitting the target, metabolic stability, and penetrability. Ultimately, scientists selected 79 molecules to synthesize. They chose the 55th molecule which showed promise in improving fibrosis and good safety profile in mouse models.