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Abstract:
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In drug discovery and development, the majority of the cost occurs in the phase 2 and 3 clinical development stages. The improvement in the probability of success of the drug in phase 2 and 3 programs will improve the overall development efficiency, and more importantly, expedite the regulatory approval and benefit the patient health in a timely manner. The major reason of the phase 2 and 3 failures is probably the candidate drugs are not well selected. Therefore, the early phase development to select the appropriate candidate drugs to move to next stage is critical. In this paper, I will discuss the approaches on how to improve the decision-making in the early phase drug development from three aspects: model-assisted study design and data analysis, adjusting for the bias for promising small proof-of-concept study, and systematically tracking and evaluating the performance of model prediction and decision-making.
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