| Summary: | Randomised controlled trials (RCTs) play a fundamental role in the development and marketing activities of pharmaceutical companies. They are the primary means of evaluating the tolerability, safety and efficacy of a drug, and for providing information relevant for pricing and reimbursement decisions and clinical decision-making. RCTs require a substantial investment by pharmaceutical companies and the financial consequences of poorly or sub-optimally designed trials are potentially substantial. Revenue does not materialise unless a licence to market a product is granted and sales may be restricted if a trial fails to provide evidence of sufficient strength or relevance for those involved in product adoption decisions. From a pharmaceutical company's perspective, the value of RCTs can therefore be judged on the contribution they make to the performance of a drug in the market and hence on their contribution to the performance of the firm. Consequently the design choices made in the planning of RCTs are effectively investment appraisal decisions. However, the application of investment appraisal techniques to RCT design has not previously been proposed. The purpose of this thesis is to consider how private sector investment appraisal methods might be applied to RCT design decision-making and to explore aspects of the practicalities of application. A general investment appraisal model is presented and its application to determine profit maximising RCT designs is illustrated. Considering the cost side of the investment appraisal equation, it is shown how decision-makers' requirements for cost-effectiveness evidence derived from trials could have a significant impact on the major determinants of cost (sample size and study duration) depending on their specific preferences for evidence defined over key components of RCT design. Considering the revenue side of the investment appraisal equation, it is shown how discrete choice analysis could be used to incorporate decision-makers' preferences for RCT designs into the planning of studies. Specifically, it is shown how the predicted probabilities derived from the application of this technique could be used within an investment appraisal framework. Directions for future research into the application of investment appraisal to RCT design are proposed.
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