ABSTRACT
This chapter starts with a theory of how data management should operate from a biostatistician’s perspective. It distinguishes two major settings: the big pharma model, and the small pharma model or academic research. The chapter provides example of the extreme case: the biostatistician is a member of a small research team. It describes small pharma, as in academic research, the extreme case, but generally there could be a spectrum of possibilities between the “extreme case” and “minimally sufficient involvement”. There are a couple of aspects that could make things for an aspiring biostatistician in small pharma even more challenging than in academic research. The first issue is very rigorous requirements for data collection, analysis and reporting, imposed by the regulatory agencies. The second issue is an incredibly entertaining opportunity to fix some problematic work done by others, while using relatively modest resources. The chapter presents two case studies illustrating these ideas.
