Data for modelling US projections of product approvals, patients treated, and product revenues for durable cell and gene therapies

Abstract

The recent marketing approval of several durable gene and cell therapies (2017-2020), together with observations that 7,000 monogenic indications and many cancers were potential targets, led to concern about the potential economic impact of such therapies on the US healthcare system. Using a Markov chain Monte Carlo simulation model, driven stochastically by our estimates of the time in phase of clinical trials and each clinical trial phase probability of success, we forecast the pattern of future US regulatory approvals for such therapies currently undergoing clinical trials. Using parameters of those trials, such as inclusion and exclusion criteria, and other epidemiological data we estimate potential treatable patient populations and use these together with pricing estimates to forecast a range for the potential future list price product revenues associated with these therapies.

Keywords

• Markov chain Monte Carlo
• Clinical trials
• Time in phase
• Success probability
• Durable cell and gene therapies
• Incidence and prevalence