How Genomic Data Improves Drug Development Timelines and Success

Genomic data is rapidly reshaping drug development—but not all data delivers the same value. For biopharma teams, the ability to accurately identify patients, understand disease burden, and make confident development decisions depends on integrating clinically validated genomic insights with real-world data.

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In this webinar, you’ll see how integrating clinical-grade genomic data with longitudinal insights can fuel drug discovery, accelerate precise clinical trials, advance HEOR research, and generate evidence to deliver value across the drug development lifecycle.

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Many current approaches rely heavily on claims data, which often lack the specificity needed to accurately define genetically driven diseases. This can result in misidentified patient populations, incomplete understanding of disease burden, and missed opportunities in clinical development. By contrast, clinically derived genomic data, paired with longitudinal insights, enables a more precise, end-to-end view of patient populations and their real-world experiences, along with molecular depth only available via genomics.

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In this session, GeneDx will show how integrating clinical-grade genomic data with longitudinal patient insights enables a more precise, end-to-end view of patient populations. We’ll introduce GeneDx Infinity^TM, one of the world’s largest genomic datasets with over 2.5M genetic tests and 1M exomes and genomes. Infinity includes over 8M phenotypic datapoints and now includes claims data to support more accurate and actionable insights across the drug development lifecycle. Infinity is ever-growing and with foundation models and multimodal AI, it can enable biomarker discovery, genetic target validation, and natural history progression modeling.

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Through a structured, three-pillar framework, we will demonstrate how this integrated approach enhances key areas of drug development. First, we will explore payer mix, highlighting differences in coverage, access, and patient demographics. Next, we will examine healthcare resource utilization, including hospitalizations and emergency visits. Finally, we will analyze cost of care, illustrating the financial impact of rare and genetic diseases with high accuracy.

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To bring these insights to life, we will walk through a live demo of the Infinity dataset, showing how genetics-informed analysis can improve patient identification, strengthen evidence generation, and support more confident development decisions.