The use of mechanistic evidence in drug approval.

The role of mechanistic evidence tends to be under-appreciated in current evidence-based medicine (EBM), which focusses on clinical studies, tending to restrict attention to randomized controlled studies (RCTs) when they are available. The EBM+ programme seeks to redress this imbalance, by suggesting methods for evaluating mechanistic studies alongside clinical studies. Drug approval is a problematic case for the view that mechanistic evidence should be taken into account, because RCTs are almost always available. Nevertheless, we argue that mechanistic evidence is central to all the key tasks in the drug approval process: in drug discovery and development; assessing pharmaceutical quality; devising dosage regimens; assessing efficacy, harms, external validity, and cost-effectiveness; evaluating adherence; and extending product licences. We recommend that, when preparing for meetings in which any aspect of drug approval is to be discussed, mechanistic evidence should be systematically analysed and presented to the committee members alongside analyses of clinical studies.

Robustness and evidence of mechanisms in early experimental atherosclerosis research.

This article considers the evaluation of experimental evidence for a causal relation between cholesterol and atherosclerosis from the beginning of the 1900s until the late 1950s. It has been argued that the medical community failed to see the implications of this early research, and at first unjustifiably rejected a causal link between cholesterol and atherosclerosis. This article argues to the contrary that the medical community was justified to conclude based on the experimental evidence that cholesterol (dietary or blood) is probably not an effective target for preventive treatment. However, the evidence would have been sufficient to ascribe to cholesterol a contributing causal role in atherosclerotic heart disease. This view is argued for based on a rational reconstruction of the researchers' evaluation of evidence, specifically, the robustness of evidence for a manipulable dependence between cholesterol and atherosclerosis on the one hand, and the evidence for a mediating mechanism on the other. The case study is used to illustrate that robustness is a feasible methodological principle even when evidence is discordant, and evidence of mechanism should be evaluated on a par with evidence of statistical dependence in establishing causal claims.

Causation in evidence-based medicine: in reply to Kerry et al.

Kerry et al. criticize our discussion of causal knowledge in evidence-based medicine (EBM) and our assessment of the relevance of their dispositionalist ontology for EBM. Three issues need to be addressed in response: (1) problems concerning transfer of causal knowledge across heterogeneous contexts; (2) how predictions about the effects of individual treatments based on population-level evidence from RCTs are fallible; and (3) the relevance of ontological theories like dispositionalism for EBM.

Causal knowledge in evidence-based medicine. In reply to Kerry et al.'s causation and evidence-based practice: an ontological review.

In Causation and evidence-based practice: an ontological review, Kerry et al. argue that evidence-based practice (EBP) should revise its understanding of causation, and take on board a dispositionalist ontology. We point out that the challenges from complexity discussed by Kerry et al., are not properly addressed by their proposed ontology. Rather, the difference making views of causation Kerry et al. criticize, spell out the relevant aspects of causation, and have a range of advantages compared to dispositionalist accounts. We explore some of these here, with a special focus on the role of causal assumptions in inferences from scientific evidence to clinical decisions. A philosophical account should help us explicate the assumptions that go into causal inference in EBM. In doing so, it enables an understanding of the various ways in which these assumptions might fail, and of how they can be justified.

Synthetic biology and genetic causation.

Synthetic biology research is often described in terms of programming cells through the introduction of synthetic genes. Genetic material is seemingly attributed with a high level of causal responsibility. We discuss genetic causation in synthetic biology and distinguish three gene concepts differing in their assumptions of genetic control. We argue that synthetic biology generally employs a difference-making approach to establishing genetic causes, and that this approach does not commit to a specific notion of genetic program or genetic control. Still, we suggest that a strong program concept of genetic material can be used as a successful heuristic in certain areas of synthetic biology. Its application requires control of causal context, and may stand in need of a modular decomposition of the target system. We relate different modularity concepts to the discussion of genetic causation and point to possible advantages of and important limitations to seeking modularity in synthetic biology systems.