The Fifth Face of Fair Subject Selection: Population Grouping

The article by MacKay and Saylor (2020) claims that the principle of fair subject selection yields conflicting imperatives (e.g. in the case of pregnant women) and should be understood as "a bundle of four distinct sub-principles" (i.e. fair inclusion, burden sharing, opportunity, distribution of third-party risks), each having conflicting normative recommendations (MacKay and Saylor 2020). The authors also offer guidance as to how we should navigate between subprinciples that may conflict with each other. The problem is a crucial one since fair subject selection is one of the principles regulating clinical research that produces generalizable knowledge with the potential of improving people’s health. Therefore, there may be cases where the way in which participants are selected directly influences the generalizability (or its lack) of the clinically relevant knowledge and its value (if any) to different groups. In my commentary article, written from the philosophical perspective, I notice a number of interrelated problems which I believe have not been discussed thoroughly in the target article: (1) the precise way in which health care priority setting should influence the content of health research priority setting and fair inclusion principles; (2) the distinction between group and individual benefits and burdens from clinical research; (3) the reference class problem in medical research.