Regeneron Embraces Genetics as Fundamental to Drug Development

Episode Summary

Executive Summary: The interview explores how Regeneron’s Genetic Center uses large-scale human sequencing and deep integration with R&D to improve target discovery, validate therapeutic hypotheses, and reshape drug development. Aris Baras argues genetics should be a core, systematic part of modern drug discovery—helping identify disease drivers, stratify patients, and translate findings into both rare and common disease therapies.

Main Topics: Regeneron Genetic Center model (Priority: 5/5): Baras explains that RGC is an in-house, fully integrated genetics operation with sequencing, primary analysis, and discovery embedded inside Regeneron’s broader R&D engine to accelerate translation of genetic findings into drug programs. Why genetics matters for drug target validation (Priority: 5/5): The conversation emphasizes that one of pharma’s biggest bottlenecks is finding well-validated targets, and large-scale genetics can reveal which genes truly drive disease and which targets may be therapeutically actionable. Scale, collaborations, and data sharing (Priority: 4/5): RGC works with dozens of global partners, combines sequencing with rich clinical data, and shares findings collaboratively to support discovery science, drug development, and genomic medicine. Using multiple cohort strategies (Priority: 4/5): Baras describes a deliberate strategy that spans founder populations, families, disease-specific cohorts, and large biobank-style populations to maximize discovery power and generalizability. From rare disease to common disease (Priority: 5/5): The interview highlights how insights from monogenic or rare conditions can generalize to common diseases, enabling therapies with broad population impact, such as PCSK9-related cholesterol lowering. Talent and organizational change (Priority: 3/5): Large-scale genomics requires new skill sets—quantitative, computational, informatics, biology, and clinical expertise—forcing drugmakers to rethink how discovery teams are built and integrated. Translational challenges ahead (Priority: 4/5): Even strong genetic discoveries often create new questions about gene function, assays, and therapeutic modality, making cross-disciplinary collaboration essential for translation.

Key Arguments: Human genetics at scale is becoming a necessary element of modern drug discovery, not an optional add-on. Drug development suffers from a target-validation bottleneck; genetics can help identify which of the ~20,000 genes are truly implicated in disease. Regeneron chose to build its genetics capability internally because the needed scale and integration were not available through external collaboration alone. Large biobank-style sequencing plus deep electronic health record phenotyping can uncover both rare variants and disease associations. Multiple cohort types are complementary: families and isolates help find high-effect variants, while large populations test generalizability and broader phenotype links. Genetic findings in rare disease can inform common disease therapeutics, as seen with lipid biology and PCSK9, and may extend to pain, asthma, COPD, NASH, liver disease, and psychiatric conditions. Data sharing and publication with collaborators are integral to the model, benefiting science, patients, and industry. The genomics workforce must combine computational and quantitative strength with biological and clinical fluency. Discoveries are not the endpoint; they often create a second phase of work to understand biology, develop assays, and move targets toward therapeutics.

Data Points: Genes in the human genome: ~20,000 - Baras cites this as the approximate number of potential drug-target opportunities. Current drug targets pursued by industry: ~500 to 1,000 - He says most companies are concentrated on a small subset of genes/targets. People sequenced by RGC to date: about 150,000 - Regeneron’s cumulative sequencing across collaborations. Projected annual sequencing rate: 150,000 to 200,000 people/year - RGC’s forward-looking scale of sequencing activity. Number of collaborators: about 35 - Global genetics/sequencing partners working with Regeneron. New collaborations added per year: 12 or more - Annual pace of expanding the collaboration network. Geisinger sequencing milestone: approaching 100,000 people - Example of a large population collaboration used for broad phenotyping. Future large-cohort milestone: a quarter of a million - Potential next scale milestone discussed for population sequencing. IBD mutation prevalence example: 8% to 10% - Baras cites mutations in a specific gene as explaining this fraction of inflammatory bowel disease cases.

Pivotal Quotes: "if you're not doing human genetics, frankly, if you're not doing it in this way, you know, at scale and across your entire pipeline, you're really not doing modern-day drug discovery development" — Aris Baras: His strongest statement on why genetics is now essential to drug development. "we wanted to do something like sequence 100,000 people at Geisinger" — Aris Baras: Explaining the scale Regeneron believed was necessary when it built RGC. "genetics is a key piece of it. So it's not everything" — Aris Baras: A caveat that genetics is powerful but must be integrated with biology and clinical translation.

Implications: Drug developers increasingly need large genetic datasets, strong analytics, and deep biology integration to improve target selection and de-risk pipelines. For listeners, the takeaway is that genetics is moving from discovery support to a central driver of precision medicine and therapeutic strategy.