Learn about the innovative approach of Menten AI in developing peptide therapeutics. Patrick Finneran shares insights on drug development process. Explore the challenges faced by startups in drug discovery. Understand the advantages of peptides in therapeutic applications and the balance between technology and biology in computational drug discovery.
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Quick takeaways
Peptides with 3-30 amino acids offer unique therapeutic properties, contrasting with proteins in drug development.
Machine learning accelerates drug development timelines, aiding in target identification, clinical trials, and FDA reviews.
Deep dives
Proteins and Peptides in Drug Development
Proteins and peptides play crucial roles in cell functions, with peptides having 3 to 30 amino acids, distinct properties useful in therapies. Menton AI employs generative methods for peptide therapeutics development, backed by prominent investors. Patrick Finneran, the company's Associate Director of Biochemistry, discusses drug development, managing biological data noise, forming hybrid engineering-biology teams, and more.
Drug Discovery Process Overview
Drug development involves a lengthy 10-15 year timeline, with initial phases identifying target proteins, preclinical development to optimize drug candidates, clinical trials in humans, rigorous FDA reviews, and post-market studies. Machine learning aids in accelerating timelines and drug approval processes.
Challenges and Solutions in Preclinical Development
Preclinical development timelines vary from 1 to 4 years involving pharmacology, pharmacokinetics, toxicology, and chemistry control aspects. Challenges include solubility of peptides and lack of understanding compared to antibodies. Computational tools assist in managing complex multivariable problems in preclinical drug development.
Innovations in Peptide Therapeutics
Peptides, smaller versions of proteins, offer benefits over traditional small molecules and biologics in drug delivery. Leveraging peptides with small molecule properties enables oral administration and bridging the gap between existing drug modalities. Computational tools empower the design and optimization of novel peptide-based therapeutics.
Proteins are nanomachines inside cells and perform the incredible array of tasks required for cells to function. They are composed of a chain of hundreds to thousands of amino acid “building blocks”. Peptides are similar to proteins, but have only about 3 to 30 amino acids. Their smaller size gives them distinct properties that are useful in therapeutic applications.
Menten AI is using cutting-edge generative methods to engineer new peptide therapeutics, and are backed by Y Combinator, Khosla Ventures, and others.
Patrick Finneran is the Associate Director of Biochemistry at Menten. He joins the show to tell us about the drug development process, handling noisy biological data, building a hybrid team of software engineers and biologists, and more.
Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer .