Stochastic modeling of performance-based annuities: increasing gene therapy accessibility by managing the uncertainty of costs and treatment value

Abstract

Durable gene therapies are a new and upcoming form of treatment. They have a high prices and high treatment uncertainty. Payers may feel reluctant to pay for such treatments with traditional financing methods because they are concerned about treatment performance risk, actuarial risk, and payment timing. If payers are unwilling to pay for effective treatments, patients will be left untreated, and developers will be unable to recover their development and manufacturing costs. Performance-based annuities may provide a solution. Although some qualitative studies on performance-based annuities exist, quantitative ones are limited. This thesis provides a basis for quantitatively examining the implications of performance-based annuities and then uses Monte-Carlo simulations to study the behavior of hypothetical performance-based agreements. The results show that performance-based annuities address payers’ concerns by aligning treatment value with costs. When payers are more willing to pay for treatments, developers and patients benefit because the treatments become more available and accessible. The findings support the idea that performance-based annuities can be used as a novel financing method for gene therapies.