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Abstract:
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Drug development is becoming increasingly costly due to the high attrition rate. Evidence based decision making becomes critical to reduce cost and improve success rate. Key decisions in early drug development include but not limited to 1) do we see enough evidence to confirm proof of mechanism (PoM) 2) do current efficacy and safety support further development? 3) can we modify (stop, accelerate or enroll more patients) an ongoing trial with accumulating data? Traditional decision making relies mostly on an ambiguous process involving subjective expert opinion. Therefore, it is critical to develop a quantitative and evidence-based decision making framework to understand the full picture of benefit and risk. In this presentation, we developed a dual-criterion approach that can not only be used to objectively evaluate pharmacology for PoM declaration, but also can be extended to clinical studies with detection of early signal of efficacy as the objective. In addition, a Bayesian frame work was adopted to incorporate historical data for decision making. Metrics to measure drug modulation effect, efficacy and statistical confidence will also be discussed.
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