AWS Health Innovation Podcast

#85, Unlocking the Secrets of Cells with AI, Jonathan Baptista from DeepLife


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Exploring the intersection of AI and biology, this episode features Jonathan Baptista, Co-Founder and CEO of DeepLife. DeepLife uses machine learning to curate and annotate single-cell RNA-seq datasets, enabling downstream bioinformatics analysis and target identification. Host Alex Merwin from AWS learns all about DeepLife's groundbreaking approach to accelerating drug discovery and precision medicine through AI-driven simulations and generative models.

  1. How does DeepLife leverage AI for drug discovery simulations?
    • DeepLife creates digital twins of cells, enabling virtual experimentation and mechanistic modeling to identify potential drug targets without extensive lab testing. Their platform simulates cellular responses to perturbations, providing insights into disease mechanisms and therapeutic opportunities.
    • What inspired Jonathan Baptista's pivot from aerospace to computational biology?
      • Jonathan's background in aerospace engineering inspired applying simulation tools to complex biological systems, inferring "laws" from data using AI/ML techniques instead of defined physics equations. This approach aims to accelerate drug discovery for precision medicine.
      • How does DeepLife map the biomolecular landscape?
        • DeepLife spent years developing pipelines to harmonize and annotate high-quality biomolecular data from public repositories and partners, mapping available datasets to identify therapeutic areas suitable for their AI-driven modeling approach.
        • How does DeepLife leverage generative AI for biomedicine?
          • Leveraging recent advances in generative AI models for text and images, DeepLife improved annotation and simulation of cell states after perturbations, benchmarking and selecting optimal techniques for different drug discovery tasks.
          • What is DeepLife's "collaborative AI" approach?
            • DeepLife's "collaborative AI" approach generates potential biological hypotheses that researchers can validate and explore further, enabling visualization of simulated cells and predicted perturbations to uncover novel mechanistic insights.
            • Learn more about DeepLife here and their mission to build the next generation of system biology.

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