Creating the next generation of peptide-based drugs powered by machine learning.
Physics-Based Design meets Machine Learning
The Menten AI platform overcomes historical limitations by developing machine learning-based methods that leverage first principle physics-based methods for molecular modeling. The platform is able to create its own data from first principles and apply machine learning to guide the design and optimization of novel peptides. The advantage of this approach is that we can create truly new chemical matter not seen before. This contrasts with current state-of-the-art methods for protein and peptide design require computationally expensive simulations and are limited by the power of their sampling approach and by the accuracy of their simulations, hitting an accuracy wall that prevents them from de novo design of potent drug molecules.
The Menten platform enables the design of potent drug-like peptide macrocycles in the nM range with desirable in vitro and in vivo properties and enables a new chemical modality for hard-to-drug targets.
Backed by top-tierVCs including Uncork Capital, Khosla Ventures, Social Impact Capital, and Y-Combinator, Menten AI is enabling a new type of drug for currently undruggable targets using machine learning. The Menten AI platform designs peptide macrocycles in a larger chemical space (1050 compared to 109 for high throughput platforms) and in record time (8 weeks vs 1-2 year in industry). This equates to 10,000x greater sampling power in ⅙ the time with >50% in vitro hit success compared to ~9% in industry. We have validated the platform by creating multiple hit molecules across a variety of drug targets including an anti-viral peptide forCovid-19.
Drug Design Platform
Menten AI’s platform delivers drug-like hit molecules in a single round of design in 8 weeks. The team’s first focus is peptide macrocycles. Peptides are the ideal drug modality for undruggable and hard-to-drug targets which remain beyond the reach of small molecules and biologics.
Validation
Menten AI’s platform has been validated across the preclinical discovery pipeline from in silico, to in vitro and in vivo efficacy with several peptides having already shown drug-like DMPK properties and in vivo efficacy.
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