Late-stage pharmaceutical R&D and pricing policies under two-stage regulation
Journal article, 2016

© 2016 Elsevier B.V.We present a model combining the two regulatory stages relevant to the approval of a new health technology: the authorisation of its commercialisation and the insurer's decision about whether to reimburse its cost. We show that the degree of uncertainty concerning the true value of the insurer's maximum willingness to pay for a unit increase in effectiveness has a non-monotonic impact on the optimal price of the innovation, the firm's expected profit and the optimal sample size of the clinical trial. A key result is that there exists a range of values of the uncertainty parameter over which a reduction in uncertainty benefits the firm, the insurer and patients. We consider how different policy parameters may be used as incentive mechanisms, and the incentives to invest in R&D for marginal projects such as those targeting rare diseases. The model is calibrated using data on a new treatment for cystic fibrosis.

Cost-effectiveness threshold

Optimal sample size

Static and dynamic efficiency

Pharmaceutical pricing and reimbursement

Rare diseases


Sebastian Jobjörnsson

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

M. Forster

University of York

P. Pertile

Verona University

Carl-Fredrik Burman

Chalmers, Mathematical Sciences, Mathematical Statistics

University of Gothenburg

Journal of Health Economics

0167-6296 (ISSN)

Vol. 50 298-311

Subject Categories

Health Care Service and Management, Health Policy and Services and Health Economy

Probability Theory and Statistics


Basic sciences



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