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How Genomics Is Personalizing Drug Discovery
Regeneron Genetics Center’s Luca Lotta explains how population-scale genetic evidence can reveal more promising drug targets and open new possibilities for disease prevention
Clinical Scorecard: How Genomics Is Personalizing Drug Discovery
At a Glance
Category
Detail
Condition
Population-scale human genetics and its application to drug discovery and personalized medicine across multiple diseases
Key Mechanisms
Inherited genetic variants can reveal how activating or inactivating biological pathways affects health and disease, supporting target identification and validation.
Target Population
People represented in large-scale genomic and de-identified health datasets; the article discusses potential future use of genomic information to understand individual disease predisposition.
Care Setting
Genetics research and therapeutic development, with potential clinical applications in selected areas of personalized medicine.
Key Highlights
RGC studies use de-identified genomic and health data from more than three million people.
Historically, drug targets supported by human genetics were reported to be two to three times more likely to succeed and eventually be approved.
A study of more than one million DNA samples associated rare FNIP1 mutations with favorable metabolic measures and approximately 60% lower risk of cardiometabolic disease.
Target selection also depends on unmet need and whether a pathway can be specifically targeted with an available or developable modality.
Genetic evidence can be complemented by preclinical models and staged clinical development to build confidence in pharmacology, safety, and proof of concept.
Guideline-Based Recommendations
Diagnosis
The article describes research methods for identifying genetic associations; it does not provide clinical diagnostic recommendations.
Management
The article does not provide treatment recommendations. It describes using genetic findings to inform therapeutic target discovery and development.
Monitoring & Follow-up
The article does not specify clinical monitoring protocols.
Risks
The interview reports that more than 90% of drug development efforts fail.
Genetic association alone is not presented as sufficient proof of therapeutic benefit; confidence is built through preclinical work when feasible and successive clinical development stages.
Patient & Prescribing Data
No prescribing population or patient-level treatment guidance is provided. The article discusses people with naturally occurring genetic variants and large research cohorts.
No drug dosing or prescribing data are provided. The FNIP1 findings are described as a potential basis for therapeutic development, not as an established treatment.
Clinical Best Practices
Use human genetic evidence to investigate whether modifying a biological pathway may affect disease-related outcomes.
Consider unmet need and the feasibility of specifically targeting a pathway when deciding whether to pursue a discovery therapeutically.
Where possible, test pathway modification in preclinical cell or animal models before advancing therapeutic development.
Build confidence through staged clinical development, assessing pharmacology, safety, and proof of concept before large Phase III trials.
