Linked pharmacometric-pharmacoeconomic modelling (also known as pharmacokinetic-pharmacodynamic-pharmacoeconomic - PKPDPE - modelling) has emerged as a potential means of facilitating early economic evaluations to enhance decision making during drug development. The methodology proposes that PKPD models, developed from early phase trials, are used to generate inputs to pharmacoeconomic models via simulation. There are few published applications of this methodology and these have typically focussed on late, or post-marketing, decision problems such as early prediction of cost effectiveness, regimen selection and phase 3 go/no-go decisions. The aim of this thesis was to widen the scope of linked pharmacometric-pharmacoeconomic modelling by demonstrating novel applications of this methodology from the early to late stages of drug development.
A case study of urate-lowering therapies for the treatment of hyperuricemia in gout patients was chosen for developing and demonstrating the application of the methodology. Pharmacokinetic models for several urate-lowering therapies were obtained from the literature and a semi-mechanistic multi-compartment pharmacodynamic model was developed in collaboration with pharmacometricians at Pfizer. The first application of the pharmacometric model is a study into the potential implications for drug safety of adherence patterns characterised by repeated drug holidays. A pharmacoeconomic model is subsequently developed which uses the pharmacometric model outputs, serum uric acid concentrations, as inputs to predict clinically relevant outcomes and costs. The linked set of models were used to study the impact of imperfect medication adherence on treatment effectiveness and subsequently, cost effectiveness, in a study that could potentially be relevant from both an industry and reimbursement authority perspective.
Further applications of the linked pharmacometric-pharmacoeconomic model were examined, which included informing early phase candidate selection and phase 3 trial design decisions. The early phase application considers the decision of whether to invest in early drug development based on the valuation of hypothetical pharmacological profiles in terms of their predicted maximum reimbursement prices. This could serve to guide candidate selection for progression into clinical phases. The application in trial design uses a pharmacometric based clinical trial simulation and a pharmacoeconomic pricing model to compare trial designs in terms of return on investment. This combines the drug pricing perspectives of both the pharmaceutical company, setting minimum prices needed to obtain an adequate return on investment, and the reimbursement authority, setting cost effectiveness thresholds which imply a maximum price for a given benefit.
This thesis has gone beyond previous work in this area, which primarily focussed on early estimates of cost-effectiveness or estimates of the impact of protocol deviations in clinical trials, to applications in early development decisions and clinical trial design incorporating value of information methods. It concludes with a discussion of how the iterative application of this methodology within a Model-Informed Drug Discovery and Development framework may enhance drug development efficiency and communication of product value to external decision-makers.