Clinical trials follow the premise of scientific discovery: there is a hypothesis that a product will perform to an expected
result. An experiment is performed to verify the hypothesis. Results from the experiment refine the hypothesis leading to
theory-driven experiments yielding confirmation that the product performs as expected. Human trials require dual theories;
not only must the product work but it must also be safe.
Does the product work?
Most of us were taught in the beginning of school that we must control the parameters of a science experiment; the beakers
must be sterile, the water distilled, etc., ensuring control of the environment to achieve predicted repeatable results. Similarly,
the clinical trial process looks for control of all inputs. Monitoring processes concentrating on 100% source data verification
were born from these practices. However, it is slowly being recognized that predictable study results require verification
that critical values are correct—not that all variables are correct.
Is the product safe?
If the experiment is controlled and values verified, does this ensure product safety? Or, does it confirm that what we postulated
as risks in study design are appropriate but not what the true safety profile is? If monitoring safety does not affect outcomes
of product effectiveness, then vigilance of information coming in becomes a higher priority.