OBJECTIVES:

There is a lack of robust models allowing to forecast the economic impact of Gene Therapies (GTx). This research aims to build a forecasting model of all GTx marketed or in development over the period 2022-2036, and to assess their impact on France’s pharmaceutical budget.

METHODS:

Clinicaltrials.gov and ct.catapult.org.uk were searched to identify all active and completed clinical studies of GTx, defined as treatments seeking to modify the expression of a gene for therapeutic use. Data were filtered to remove duplicates, dormant programs, and those with insufficient information. Indication, study population, technology, phase of development, and timing (study start and expected completion dates) were systematically extracted. Prevalence and incidence data for target indications were sought from the literature. Timing to first commercial patient were estimated from historical GTx development data. Attrition rates were obtained from MIT’s project ALPHA. For each indication, a probability of success (PoS) was estimated based on the individual PoS of each asset in development and the number of assets in development. Price estimates and annual treatment penetration rates among each addressable patient population were benchmarked on previously launched products. The model was built in Excel 365 with VBA 7.1.

RESULTS:

According to the model’s base case scenario, by 2036, more than 31,000 patients could be treated annually in France by a gene therapy, which would represent 3.5% of the total addressable population. Leading indications would include haematological cancers, cardiovascular diseases, and solid tumours with 9,600, 8,200, and 6,600 annual patients, respectively. At a 75% PoS threshold, 34 new treatments are expected to reach the market between 2022 and 2036, with up to 8 in a single year (2027).

CONCLUSIONS:

Our model outlines the acceleration of GTx uptake, pointing out to a potential need to rethink the financing model for these disruptive innovations.