The CSO should drive the deployment and regular use of data platforms within a biotech organization rather than a distinct engineering lead. This is both because the requirements for the platform should be set by the biological goals of the company and adopting such a platform in practice requires strong scientific leadership to change the daily behavior of researchers. The current standard is to delegate this responsibility to a computational lead who is further removed from the scientific goals of the organization by training and detached from the daily behavior and needs of the end users. This has led to the widespread deployment of bloated, buggy, and often disjointed platforms that are never truly adopted by research teams and take many years and resources to stand up. Thus the research productivity gained from a single collaborative environment for access and exploration of all experimental data over time is simply unrealized for many biotech organizations. These general claims are made from observing the internals of hundreds of biotech companies. CSO is used interchangeably with scientific leadership throughout this essay and describes the person or team that plans drug programs.
Great blog Kenny Workman!
Computational biologist
2moVery insightful - I've seen similar challenges building out a data warehouse for bio data. I like the points about science leadership leading requirements gathering, however I think it's still a good idea to add an engineer into the mix who is there to listen/ask questions. I've had the experience that often enough scientists don't consider asking for something bc they don't know what's possible. Once that trust is established, the engineer becomes less important. As you described though, lots of biotech companies are in need of transitioning to the model you propose and that means trust has to be built.