The pharmaceutical industry faces decreasing R&D efficiency and exponentially increasing drug discovery costs. Analyzing and interpreting the vast amounts of structured data generated by high-throughput technologies presents a significant challenge in identifying meaningful outcomes.

Peptris Technologies addresses these challenges with its AI-powered preclinical drug discovery platform. The platform integrates unsupervised learning and generative AI to design optimized molecules, significantly reducing the need for extensive wet lab testing. This automated process streamlines the design of potent, safe, selective, and biologically active drug candidates. Peptris' platform facilitates the discovery of Novel Chemical Entities (NCEs), repurposes approved drugs, and rescues clinically safe molecules for new indications. The company operates virtually, focusing on AI-driven discovery and partnering with CROs and biotech companies for wet lab work.

Proprietary AI platform leveraging unsupervised learning and generative AI to understand chemical space and generate novel molecules.

Large language model built on a novel and proprietary molecule language syntax.

AI models predict critical parameters for potential drug candidates, including drug-like properties, target activity, and physicochemical properties.

Automated pipeline prunes large purchasable compound datasets and creates de novo variations of compounds.

Models are benchmarked for molecule property predictions, demonstrating high generalization power for faster candidate identification.

Capabilities include generating novel, patentable, and synthesizable molecules, repurposing approved drugs, and rescuing clinical candidates.

Peptris' primary customers are pharmaceutical and biotech companies, as well as rare disease organizations, seeking to enhance their drug discovery and development pipelines.

Peptris generates revenue through licensing deals, milestone payments, and royalties from partnerships across academia, biotech, and pharma companies.