Partnership Models for R &D in the Pharmaceutical Industry

Abstract

AbstractOver the last decades the complexity of R &D processes in the pharmaceutical industry have resulted in a decline in the efficiency of those processes. Despite financial resources used in R &D have increased over time the number of drugs developed has remained almost constant. The phenomenon is known as “Eroom’s Law”. In order to start growing R &D efficiency again, the business models of companies were reviewed by mainly implementing open innovation models that can simplify and shorten the drug development process. Pharmaceutical companies are increasingly outsourcing activities from the external environment. The R &D tasks that firms choose to outsource include a wide spectrum of activities from basic research to late-stage development: genetic engineering, target validation, assay development, hit exploration and lead optimization (hit candidates-as-a-service), safety and efficacy tests in animal models, and clinical trials involving humans. Terms such as crowdsourcing, innovation centers, R &D collaboration, and open source are becoming more and more common in the sector. Almost all the Big Pharma are striving to create collaborative networks that might allow them to be more efficient. Pharmaceutical companies are called upon to make a “make or buy” decision to determine whether it is more convenient to outsource these activities rather than exploiting internal resources for generating innovation. In a global context in which the stochastic view has become more suitable for interpreting phenomena the aim of this kind of decision is mainly related to decrease uncertainty. The aim of the chapter is to explore this topic by also providing data and examples.