Just as a stock’s value can be debated with dueling sets of NPV model inputs, a drug’s value can be debated with different inputs and different ways of constructing a cost-effectiveness model. Biotech executives and investors should have command of the inputs into cost-effectiveness math, which include but are not limited to healthcare costs, quality of life, survival, caregiver spillover, productivity, time to loss of exclusivity, future generic price, discount rate, and population risk reduction. Here we provide a guide to wielding that math at various stages of development, because showing the world a drug’s value before declaring its price can prevent a breakthrough medicine from being under-appreciated or unfairly maligned.

Last week’s publication in the Forum for Health Economics and Policy of Valuing the Societal Impact of Medicines and Other Health Technologies: A User Guide to Current Best Practices is a watershed moment for the field of health economics and outcomes research. 

All else being equal, people care more about outcomes that happen in the near future than about outcomes that happen later. The discount rate represents how much timing matters. We sit down with Josh Cohen, Deputy Director of the Center for the Evaluation of Value and Risk in Health (CEVR) at the Institute for Clinical Research and Health Policy Studies at Tufts Medical Center, and Research Professor of Medicine at Tufts University School of Medicine, to learn about how changes to the discount rate can alter how we value medicines.

Traditional cost-effectiveness analyses done by organizations like ICER and NICE overlook much of the value of new drugs, including factors with crucial societal impact like genericization, risk reduction, and community spillover. Peer-reviewed research has made this clear again and again, but these organizations continue to insist on using outdated formulas to determine the value of drugs. With the passage of the IRA and imminent drug pricing “negotiations” (read: price controls), it’s more important than ever to get the math that values our medicines right.