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Mathematical Modeling And Pharmaceutical Pricing: Analyses Used To

Abstract. In the face of significant real healthcare cost inflation, pressured budgets, and ongoing launches of myriad technology of uncertain
value, payers have formalized new valuation techniques that represent a barrier to entry for drugs. Cost-effectiveness analysis predominates
among these methods, which involves differencing a new technological intervention’s marginal costs and benefits with a comparator’s, and
comparing the resulting ratio to a payer’s willingness-to-pay threshold. In this paper we describe how firms are able to model the feasible
range of future product prices when making in-licensing and developmental Go/No-Go decisions by considering payers’ use of the costeffectiveness
method. We illustrate this analytic method with a simple deterministic example and then incorporate stochastic assumptions
using both analytic and simulation methods. Using this strategic approach, firms may reduce product development and in-licensing risk.
Keywords: pharmaceutical pricing, R&D investment decision-making, cost-effectiveness analysis, mathematical modeling
1. Introduction
Developmental and in-licensing decision-making in the pharmaceutical,
biotechnology, and medical device industries is
fraught with uncertainty and complexity, arguably unparalleled
in modern corporate experience. The costs and rewards
balanced upon these decisions, including make-buy determinations
about potential compounds that are likely years away
from reaching the marketplace, if ever launched, are enormous.
Previous analyses of drug development decisions have
sought to decompose the uncertainty in predicting net present
value (NPV) [1]. Not surprisingly, the future price a product
will support is a primary driver of variability in its expected
NPV. Because of the important role pricing plays, firm research
efforts to reduce price-related uncertainty increase as
the product moves through the developmental pipeline. This
process often exceeds a decade, beginning...