AI powered drug discovery
Pharma R&D efficiency is decreasing steadily, while the cost of new drug discovery is increasing exponentially. Vast amounts of structured data are being generated using high throughput technologies in drug discovery/development. However, the analysis and interpretation of this data for meaningful outcomes has been a challenge.
Peptris has developed a platform technology to enhance efficiencies across the drug discovery/development cascade using Artificial Intelligence/Machine Learning
Peptris’ proprietary AI platform integrates unsupervised learning and generative AI to design optimized molecules, significantly reducing the need for wet lab testing. The automated platform streamlines this process, designing potent, safe, selective, and biologically active drug candidates. The platform has been used to discover Novel Chemical Entities (NCE), to repurpose or reposition approved drugs, and rescue molecules that have been proven safe in the clinic. We have a pipeline of preclinical assets that have been discovered, validated in vitro and in vivo disease models.
Peptris operates virtually, focusing on AI-driven discovery while outsourcing wet lab work to CROs and biotech partners. Revenue comes from licensing deals, milestone payments, and royalties, with partnerships across academia, biotech and pharma companies and rare disease organizations
Generate novel scaffolds and molecules that can be sythesised, with superior activity, selectivity and optimal drug like properties
Repurpose approved drugs and molecules with proven clinical safety to find solutions for unmet medical needs and rare disease indications. This will help reach the patient early as it fast tracks the preclinical and clinical development process.
Identify novel molecular targets and disease indications for clinically safe molecules that have passed Phase I or later stages but not developed further due to reasons including efficacy in primary disease indication or lack of commercial potential
Our proprietary technology leverages cutting edge neural network architectures found in Natural Language Processing, Large Language Models and Image processing research areas.
Peptris has created an array of AI models to understand the chemical space and generate novel molecules and predict varied parameters that are critical for a molecule to be considered a potential drug candidate. The power of the Peptris platform is derived from a foundational unsupervised learning algorithm to understand the vast chemical space. It uses a large language model built on a novel and proprietary molecule language syntax. The foundational model learns from ultra-large and diverse purchasable compound libraries and predicts various drug-like properties with precision
Our proprietary generative AI algorithms can also design novel molecules with superior physicochemical properties and drug target activity. The models are orchestrated by an automated process that prunes large purchasable compound datasets and creates de novo variations of compounds that are predicted to be novel, potent, safe, selective, and biologically active. Our neural network models when benchmarked for various molecule property predictions, show a high generalization power enabling faster candidate identification.
Generates diverse, patentable and synthesizable molecules that are potent, selective, safe and biologically active
Leverages the power of unsupervised learning to rapidly screen ultra large diverse virtual chemical libraries
Predict with accuracy various parameters that are critical for a molecule to be considered a potential drug candidate
Ensures that the number of molecules to be tested in a wet lab are small, making the discovery process cost effective
Specialist in Algorithms. Expertise in building large systems and software. Keen Observer and a great leader
Expert in Image and Video processing and Deep Learning Architectures. The creative thinker and eternal optimist
Experienced drug hunter with 18 clinical candidates and one drug in the market. The visionary strategist with a deep mastery of his craft
Specialist in fundamental algorithms and prototyping, the analytical thinker passionate about science