The Structure of Clinical Translation: Efficiency, Information, and Ethics

The so-called “drug pipeline” is not really about drugs and is not much like a pipeline. It is really about the production of information, and it is much more like a web. Not surprisingly, the misunderstanding leads to a poor understanding of what’s wrong with it and how it can be improved.

The last two decades have witnessed a crescendo of allegations that clinical translation is rife with waste and inefficiency. Patient advocates argue that excessively demanding regulations delay access to life-saving drugs, research funders claim that too much basic science languishes in academic laboratories, journal editors allege that biased reporting squanders public investment in biomedical research, and drug companies (and their critics) argue that far too much is expended in pharmaceutical development.

But how should stakeholders evaluate the efficiency of translation and proposed reforms to drug development? Effective reforms require an accurate model of the systems they aspire to improve—their components, their proper functions, and their pathologies. However, there is currently no explicit and well-developed model of translation for evaluating such criticisms.

In what follows, we offer an explicit model of clinical translation. Many discussions of clinical translation and its pathologies presume that its main output is tangible: new drugs, vaccines, devices, and diagnostics. We disagree. We argue that the principal output of clinical translation is information—in particular, information about the coordinated set of materials, practices, and constraints needed to safely unlock the therapeutic or preventive activities of drugs, biologics, and diagnostics. To develop this information calls for a process far different from a simple linear progression of clinical trials; it requires exploratory sampling of many different elements in this set. Our model points to some limitations and liabilities of influential proposals for reforming research. It also reveals some underrecognized opportunities for improving the efficiency of clinical translation.