A standardised framework to identify optimal animal models for efficacy assessment in drug development

Abstract

17Introduction -Poor translation of efficacy data derived from animal models is a potential contributor to 18 costly and unnecessary attrition in clinical trials. 19Objectives -To develop a tool to assess, validate and compare the clinical translatability of animal 20 models used for the preliminary assessment of efficacy. 21Design and Results -We conducted an exploratory literature search to identify the key aspects to 22 validate animal models. Eight aspects (Epidemiology, Pathophysiology, Genetic, Biochemistry, 23 Aetiology, Histology, Pharmacology and Endpoints) were identified for which questions were drafted to 24 evaluate the different faces of the human disease simulation. Features of the framework include 25 standardised instructions, a weighting and scoring system to compare models as well as contextualising 26 factors regarding model similarity and evidence uncertainty. We included a quality assessment of the 27 internal validity of drug intervention studies included in the Pharmacological validation section for both 28 effective and ineffective drugs in humans. A web-based survey was conducted with experts from 29 different stakeholders to gather input on the framework. Finally, we present a case study of a preliminary 30 2 validation and comparison of two animal models for Duchenne Muscular Dystrophy (mdx mouse and 31 GRMD dog) and Diabetes Type 2 (ZDF rat and db/db mouse). We show that there are significant 32 differences between the mdx mouse and the GRMD dog, the latter mimicking the human condition to a 33 greater extent than the mouse despite the considerable lack of published data. In DT2, both the ZDF 34 rat and the db/db mouse are comparable with minor differences in pathophysiology. 35Conclusions -FIMD facilitates drug development by serving as the basis to select the most relevant 36 model that can provide meaningful and translatable results to progress drug candidates to the clinic. 37

Levelling the Translational Gap for Animal to Human Efficacy Data

“…To address the lack of standardisation and the necessity of a multidimensional appraisal of animal models of disease, we developed the Framework to Identify Models of Disease (FIMD) [ 21 , 22 ]. The first step in the development of FIMD was the identification of the core parameters used to validate disease models in the literature.…”

“…The pitfalls of using animals to simulate human conditions, such as different aetiology and lack of genetic heterogeneity, have been widely recognised for a long time [ 1 , 10 , 19 , 20 ]. Nonetheless, the few efforts to address external validity to the same extent as internal validity are still insufficient [ 21 , 22 ].…”

New Developments in Behavioral Pharmacology

“…Since screening tests rely mostly on predictive validity, current approaches to modeling in behavioral pharmacology view them as limited. Moreover, producing models which show good construct validity in at least some domains (i.e., epidemiology, symptomatology and natural history, genetics, biochemistry, etiology, histological alterations, or endpoints) has been proposed as a way to indirectly increase predictive validity [46], as drugs which improve performance in a test that simulates at least some aspects of the target disorder.…”

Introductory Chapter: Behavioral Pharmacology - From Basic to Clinical Research

“…Behavioral pharmacology is a multidisciplinary field of science focused on exploring and understanding the effects of chemical substances, hormones, and drugs on the behavior of humans and experimental animals, all with the final objective of understanding the neurobiological substrate of behavior and contributing in the development of therapeutic agents or pharmacologic tools for research in neurosciences [1]. The relative new popularity and accelerated growth of neurosciences have simultaneously led to an exponential growth on the scientific literature on this area that has been produced every day [2][3][4][5][6]. That makes necessary new strategies to be ready in a field that has been constantly actualized; for example, years ago, students with different backgrounds, who are graduates of psychology, medicine, or chemistry, had to study postgraduate trainings to specialize in the field of neurosciences.…”