Characterizing and Communicating Uncertainty in the Assessment of Benefits and Risks of Pharmaceutical Products Workshop Summary (2014) / Chapter Skim
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4 Basic Methodologies and Applications for Understanding and Evaluating Uncertainty
4 Basic Methodologies and Applications for Understanding and Evaluating Uncertainty
Pages 31-42
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From page 31... ...
to clarify and examine trade-offs. • Bayesian approaches to evaluating clinical trial data have the potential to facilitate more robust characterization of inferences drawn from studies.
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From page 32... ...
For example, as suggested by one workshop participant, an expert elicitation in the drug review process might quantify expert judgment about the relative likelihood that alternative models of pharmacokinetic or pharmacodynamic processes correctly describe a given biological process. Morgan provided three cautions with respect to the application of expert elicitation: (1)
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Before an RCT begins, the Bayesian approach instead calculates a probability distribution of the plausible values of the treatment effect. This probability distribution excludes evidence from the current RCT and forms the "prior distribution." Then, based on emerging information from the current RCT, a plausible value of the treatment effect is generated, or "likelihood." Applying Bayes rule and Bayesian methodology, the prior distribution is combined with the likelihood to determine the "posterior distribution" that is ultimately a combination of historical assessments of a treatment effect and current opinion about the treatment effect in the active RCT.
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From page 34... ...
Application of a disciplined Bayesian approach could offer opportunities to characterize and accommodate uncertainty in clinical trials. APPLYING DECISION THEORY APPROACHES TO REGULATORY DECISION MAKING Several speaker presentations generally addressed decision theory techniques and the scientific basis for incorporating patient and other stakeholder preferences.
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From page 35... ...
However, Mandel noted, such approaches do little to reduce the vagueness associated with the selected terms and there is no guarantee that decision makers will keep the prescribed rank ordering in mind when reading reports. A more radical proposal, he said, would be to assign numbers to words that communicate uncertainty (see Figure 4-1 for two examples of verbal probability terms)
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From page 36... ...
SOURCE: Adapted from Mandel, 2007. and Economy, University of Calgary, stated that decision theory provides a structured approach for gauging the influence of individual perspectives, including a scientific rationale for incorporating stakeholder input in benefit–risk considerations.
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Arvai cited publications (see Appendix C for additional resources) that explicate several methods by which structured, deliberative processes can combine stakeholder input with analysis.
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From page 38... ...
Well-managed regulatory approval decisions consider the available alternatives to the proposed drug and the consequences of not approving it. The central valuation question that drives a risk management process, said McDaniels, is this: Given the estimated impacts of the alternatives on these objectives, is it worthwhile for society to accept the trade-offs in going from "do not approve" to "approve" for one of the alternatives?
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In addition, noted McDaniels, FDA makes good use of its advisory committee structure as a forum for combining analysis and reflection on values. FDA APPROACHES TO DECISION MAKING In addition to McDaniels' previous comments on FDA's decision processes, individual workshop participants also noted a number of FDA attributes and processes that currently incorporate, or could be enhanced to incorporate, the methods and approaches of decision science for making decisions under uncertainty.
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is a proposed limited-use approval pathway for drugs developed in an expedited manner to meet unmet medical needs in a clearly defined subpopulation. One workshop participant noted that the pathway was proposed in part to take into account that certain severely affected subpopulations with few treatment options might be willing to accept greater uncertainty and greater risk.
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Manski suggested broadening the set of approval options beyond yes or no, by empowering FDA to institute what he termed adaptive partial approval, similar in concept to "adaptive licensing" proposals made by others in the field (Eichler et al., 2012)
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