Biomarkers can be powerful tools to guide diagnosis, treatment, and research. However, prudent use of biomarkers requires formal validation efforts. Although the data needed for biomarker validation has traditionally been hard to access, new research initiatives can ease this process.

The FDA's new table of surrogate endpoints used for drug approvals is an important step forward for overseeing the use of biomarkers in clinical trials. Nevertheless, we present several ways in which the table can be improved.

John Worrall and Nancy Cartwright have both argued that randomized controlled trials (RCTs) are “testing the wrong theory.” They claim that RCTs are designed to test inferences about the causal relationships in the study population, but this does not guarantee a justified inference about the causal relationships in the more diverse population in clinical practice. In this article I argue that the epistemology of theory testing in trials is more complicated than either Worrall’s or Cartwright’s accounts suggest. I illustrate this more complex theoretical structure with case studies in medical theory testing from Alzheimer’s research and anticancer drugs in personalized medicine.

The concordance of results that are “robust” across multiple scientific modalities is widely considered to play a critical role in the epistemology of science. But what should we make of those cases where such multimodal evidence is discordant? Jacob Stegenga has recently argued that robustness is “worse than useless” in these cases, suggesting that “different kinds of evidence cannot be combined in a coherent way.” In this article I respond to this critique and illustrate the critical methodological role that robustness plays as an aim of scientific inquiry.