Join us for a deep dive into DeepMind’s newest foundation model for regulatory genomics - and where it goes next. AlphaGenome is DeepMind’s boldest step yet in decoding the regulatory genome. A single deep learning model that predicts thousands of functional genomic outputs - from gene expression and splicing to 3D genome structure - based on just 1 Mb of DNA sequence. It’s already setting new benchmarks:
But what does that mean for biomedical researchers? And what’s still missing?
We’ll break down where AlphaGenome excels, where gaps remain, and how tools like curated knowledge graphs, structured biological context, and Elucidata’s AI Co-Scientist help translate model outputs into real-world discoveries.
Join us for a deep dive into DeepMind’s newest foundation model for regulatory genomics - and where it goes next. AlphaGenome is DeepMind’s boldest step yet in decoding the regulatory genome. A single deep learning model that predicts thousands of functional genomic outputs - from gene expression and splicing to 3D genome structure - based on just 1 Mb of DNA sequence. It’s already setting new benchmarks:
But what does that mean for biomedical researchers? And what’s still missing?
We’ll break down where AlphaGenome excels, where gaps remain, and how tools like curated knowledge graphs, structured biological context, and Elucidata’s AI Co-Scientist help translate model outputs into real-world discoveries.
Scaling clinico-genomic data integration: Large pharmaceutical organizations working with external data providers used Polly to build interoperable clinico-genomic data products 6x faster.
Although purchased datasets are often labeled as "clean," they still lack interoperability—Polly's pipelines bridge this gap with robust integration and harmonization.
Information Retrieval: Drug safety monitoring teams used Polly's Knowledge Graph powered co-scientist to conversationally retrieve the right cohorts & assess drug response—cutting discovery time by 70%.
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How AlphaGenome helps uncover non-coding variants that drive complex disease-and reveals new drug targets.
Learn how high-impact variant prediction fuels CRISPR, AAV, and synthetic biology pipelines.
Explore pharmacogenomic use cases for patient stratification and therapeutic response.
See how AlphaGenome supports the design of tissue-specific regulatory elements and circuits.
Understand how shared variant-driven pathways suggest new indications for approved drugs.
If you’re working with complex biological data, you may be asking:
Can generative AI truly assist in scientific reasoning, not just data analysis?
What does it mean for hypothesis generation, literature review, or even designing experiments?
Could this accelerate—not replace—my discovery pipeline?
Whether you're skeptical, curious, or already experimenting with AI in your lab—this is a session designed to ground your understanding in evidence, not speculation.
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