Forecasting Gene Therapy Candidates Using Claims Data and Other Sources

More than 30 gene therapies are currently approved by the FDA, with more than 2,000 others in development. Many have high list prices at the time of FDA approval, making it difficult for payers to know which are affordable and can be made accessible. A presentation at AMCP Nexus 2023 offered a strategy to forecast potential candidates using various information, including patient-level data, details from the manufacturer, financial market insights, and FDA reports.

The FDA defines gene therapy as a technique that modifies a person’s genes to treat or cure disease. The mechanism may involve replacing a disease-causing gene, inactivating a disease-causing gene, or introducing a new or modified gene (known as gene editing).

A forecasting report can help health insurers make informed business decisions about this growing and complex market, said speakers Pat Gleason, PharmD, assistant vice president of health outcomes research at Prime Therapeutics, and Landon Z. Marshall, PharmD, PhD, principal health outcomes researcher at Prime Therapeutics. They outlined four “Gene Therapy Forecast Operational Steps” payers can use. The process requires a team that includes a clinical pharmacist, data scientist, and epidemiologist, they advised.

The first step involves gathering an understanding of basic product details, such as administration, curative intent, and anticipated price point. Second, the presenters recommend checking regulatory status by reviewing investor reports, manufacturer and clinical reports, the FDA pathway that will be used for review and approval, and the approximate date when a final decision on drug approval can be expected (also known as the PDUFA date).

The third step of the process involves developing and deploying algorithms to identify which members are likely to use the gene therapy. Useful data for these algorithms include diagnosis and procedure codes, other prescriptions, health care utilization, gender, and age. The final step is a forecasting report that identifies potential candidates, potential demand, and market capacity, they said.

To illustrate the process, the speakers presented a case study in Duchenne muscular dystrophy, highlighting several challenges that may occur along the way. Among the challenges are limitations inherent in medical and pharmacy claims data, nonspecific diagnosis code(s), and a lack of published information for rare diseases often targeted by gene therapies.


Gleason P, Marshall LZ. Gene Therapies: Forecasting Potential Candidates Using Integrated Medical and Pharmacy Claims Data. Session W6. Presented at AMCP Nexus 2023; Oct. 16‒19, 2023; Orlando, Fla.