10 Mar
2025
Shifting sands in evidence quality of medicines and its implications for pharmaco-economic modelling and decision-making
Cost of medicines is on an exponential rise and the pressure towards speedy access to medicines comes from all directions: pharmaceutical industry, patients, clinicians, politicians, and ultimately, the public. In Europe, standard reimbursement of a medicine typically requires efficacy approval from the European Medicines Agency (EMA), clinical and cost-effectiveness assessment of a Health Technology Assessment (HTA) body, and decision by a national regulator. With the intention to provide speedy access, efficacy evidence standards are often lowered in the name of hope that the given medicine may bring about clinically meaningful benefit nonetheless. This shift brings significant uncertainty into clinical and pharmaco-economic assessments, and ultimately into decision-making.
Using the example of a cost-utility analysis of an advance therapy medicinal product (ATMP) for spinal muscular atrophy, I will illustrate a prototypical case of modelling uncertainties. These uncertainties include the use of incomplete data sets, short-term data cut-offs used for long-term extrapolations, or challenges with discounting rates for benefits and costs of chronic conditions. Further challenges include modelling based on data from single arm trials, modelling with numerical values without statistical significance, label approved by EMA for a wider population than included in the clinical trials, or the question of selective approach to the inclusion of indirect costs.
This shift leads to a number of open normative questions such as: who is to pay for the cost of uncertainty? How should we set up willingness-to-pay-thresholds? What will be the role of the new European regulation on HTA (2021/2282)? How to prevent the public from paying thrice: for basic research of medicines, for the actual patented treatment, and for post-market evidence generation?