Published online by Cambridge University Press: 19 January 2018
With this economic and management background we are now ready to turn to some case studies of how the biomedical discovery process has actually functioned – whether managed explicitly by firms or government, or indirectly by market interactions as exemplified by some key efforts to bring useful products to market. As might be expected, we will see some behaviors that largely agree with the predictions these theories make, but also some that do not – usually because of the role of chance or personality in defining the outcomes of individual real world cases. The stories will be fascinating in themselves but also instructive in showing the variety of ways the underlying economic and managerial forces play out.In these cases we pay particular attention to the intricacies underlying life sciences research and the inevitable uncertainties and frustrations that investigator–inventors experience while at the same time balancing the findings made in terms of earlier discoveries made in the basic sciences that established the foundations upon which the work described was based.Case analysis, especially when compared to randomized controlled trials, is the weakest of research methods. Epidemiology courses teach that individual (anecdotal) cases seldom if ever demonstrate anything. So what is the value of such an approach in general, and for this volume in particular? Well, the answer to that question is that case studies are much more than just accounts of what happened – they are also extensively researched depictions, albeit approximations, of social events and the context in which they occur. As such, they attempt to explain “how” and “why” things happened when and in the way they did – explanations that are not easily captured empirically. That is why extensive empirical analyses are often complemented by the findings that come from intensive case studies of this type. If nothing else, these case studies serve to define and sharpen research questions, and generate hypotheses for future research. The cases here pay attention not only to the business and managerial details of discoveries, but also to the scientific complexity inherent to the process by which they are made. Most business texts on scientific innovation rarely appreciate, let alone confront, the complexity of the science itself, which is what we hope to accomplish in what follows.