Selection of animal models for drug efficacy

A major hurdle in drug development is the limited benefit of efficacy data in animals for use in the clinic. For each patient (sub)group or disease, many different animal models exist to provide insight into drug efficacy. However, it is often unclear how predictive the outcomes of drugs tested in these models are for the clinic, and on what basis researchers select a specific model. The main goal of this thesis is to gain insight into the selection of animal models for drug efficacy. We studied the extent of the low value of animal models for predicting efficacy. Then, we analyzed underlying causes of this low value. To this end, we studied the role of different stakeholders in the selection process, such as researchers, local and national ethics committees, and funding agencies. Finally, we present an instrument that supports the evaluation of similarities between animal models and patients: the Framework to Identify Models of Disease (FIMD). FIMD provides a solution to assess the value of animal models for efficacy. We applied FIMD to validate two animal models of cow's milk allergy in young children. We demonstrated that the instrument contributes to validating animal models for drug efficacy and thus can facilitate appropriate animal model selection. When applied, this instrument provides a scientific basis for policy recommendations and changes, which can lead to a more responsible use of animals in drug development.