Reports of a reproducibility crisis combined with a high attrition rate in the pharmaceutical industry have put animal research increasingly under scrutiny in the past decade. Many researchers and the general public now question whether there is still a justification for conducting animal studies. While criticism of the current modus operandi in preclinical research is certainly warranted, the data on which these discussions are based are often unreliable. Several initiatives to address the internal validity and reporting quality of animal studies (e.g., Animals in Research: Reporting In Vivo Experiments (ARRIVE) and Planning Research and Experimental Procedures on Animals: Recommendations for Excellence (PREPARE) guidelines) have been introduced but seldom implemented. As for external validity, progress has been virtually absent. Nonetheless, the selection of optimal animal models of disease may prevent the conducting of clinical trials, based on unreliable preclinical data. Here, we discuss three contributions to tackle the evaluation of the predictive value of animal models of disease themselves. First, we developed the Framework to Identify Models of Disease (FIMD), the first step to standardise the assessment, validation and comparison of disease models. FIMD allows the identification of which aspects of the human disease are replicated in the animals, facilitating the selection of disease models more likely to predict human response. Second, we show an example of how systematic reviews and meta-analyses can provide another strategy to discriminate between disease models quantitatively. Third, we explore whether external validity is a factor in animal model selection in the Investigator’s Brochure (IB), and we use the IB-derisk tool to integrate preclinical pharmacokinetic and pharmacodynamic data in early clinical development. Through these contributions, we show how we can address external validity to evaluate the translatability and scientific value of animal models in drug development. However, while these methods have potential, it is the extent of their adoption by the scientific community that will define their impact. By promoting and adopting high quality study design and reporting, as well as a thorough assessment of the translatability of drug efficacy of animal models of disease, we will have robust data to challenge and improve the current animal research paradigm.

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IntroductionThe immune modulatory role of estrogens in inflammation is complex. Both pro- and anti-inflammatory effects of estrogens have been described. Estrogens bind both estrogen receptor (ER)α and β. The contribution of ERα and ERβ to ER-mediated immune modulation was studied in delayed type hypersensitivity (DTH) and in experimental arthritisMethodsER-mediated suppression of rat adjuvant arthritis (AA) was studied using ethinyl-estradiol (EE) and a selective ERβ agonist (ERB-79). Arthritis was followed for 2 weeks. Next, effects of ER agonists (ethinyl-estradiol, an ERα selective agonist (ERA-63) and a selective ERβ agonist (ERB-79) on the development of a tetanus toxoid (TT)-specific delayed type hypersensitivity response in wild type (WT) and in ERα - or ERβ-deficient mice were investigated. Finally, EE and ERA-63 were tested for their immune modulating potential in established collagen induced arthritis in DBA/1J mice. Arthritis was followed for three weeks. Joint pathology was examined by histology and radiology. Local synovial cytokine production was analyzed using Luminex technology. Sera were assessed for COMP as a biomarker of cartilage destruction.ResultsEE was found to suppress clinical signs and symptoms in rat AA. The selective ERβ agonist ERB-79 had no effect on arthritis symptoms in this model. In the TT-specific DTH model, EE and the selective ERα agonist ERA-63 suppressed the TT-specific swelling response in WT and ERβKO mice but not in ERαKO mice. As seen in the AA model, the selective ERβ agonist ERB-79 did not suppress inflammation. Treatment with EE or ERA-63 suppressed clinical signs in collagen induced arthritis (CIA) in WT mice. This was associated with reduced inflammatory infiltrates and decreased levels of proinflammatory cytokines in CIA joints.ConclusionsERα, but not ERβ, is key in ER-mediated suppression of experimental arthritis. It remains to be investigated how these findings translate to human autoimmune disease.

National and international laws and regulations exist to protect animals used for scientific purposes in translational and applied research, which includes drug development. However, multiple animal models are available for each disease. We evaluated the argumentation behind the selection of a specific animal model using thematic content analysis in project applications issued in 2017-2019 in the Netherlands. In total, 125 animal models for translational and applied research from 110 project applications were assessed. Explanations to select a specific model included: the model's availability (79%); the availability of expertise (62%); and the model showing similar disease pathology/symptoms (59%) to humans. Therefore, current selection of a specific animal model seems to be based on tradition rather than its potential predictive value for clinical outcome. The applicants' explanations for the implementation of the 3R principles (replacement, reduction and refinement) as to the animal model were unspecific. Replacement was achieved by using data from prior in vitro studies, reduction by optimal experimental design and statistics, and refinement by reducing discomfort. Additionally, due to the stated need for a test model with high complexity (47%) and intactness (30%), the full replacement of animal models with alternative (non-live animal) approaches was thought unachievable. Without a clear, systematic and transparent justification for the selection of a specific animal model, the likelihood of poorly translatable research remains. It is not only up to the researcher to demonstrate this, as ethical committees and funding bodies can provide positive stimuli to drive this change.

Introduction Poor translation of efficacy data derived from animal models can lead to clinical trials unlikely to benefit patients–or even put them at risk–and is a potential contributor to costly and unnecessary attrition in drug development. Objectives To develop a tool to assess, validate and compare the clinical translatability of animal models used for the preliminary assessment of efficacy. Design and results We performed a scoping review to identify the key aspects used to validate animal models. Eight domains (Epidemiology, Symptomatology and Natural History–SNH, Genetic, Biochemistry, Aetiology, Histology, Pharmacology and Endpoints) were identified. We drafted questions to evaluate the different facets of human disease simulation. We designed the Framework to Identify Models of Disease (FIMD) to include standardised instructions, a weighting and scoring system to compare models as well as factors to help interpret model similarity and evidence uncertainty. We also added a reporting quality and risk of bias assessment of drug intervention studies in the Pharmacological Validation domain. A web-based survey was conducted with experts from different stakeholders to gather input on the framework. We conducted a pilot study of the validation in two models for Type 2 Diabetes (T2D)–the ZDF rat and db/db mouse. Finally, we present a full validation and comparison of two animal models for Duchenne Muscular Dystrophy (DMD): the mdx mouse and GRMD dog. We show that there are significant differences between the mdx mouse and the GRMD dog, the latter mimicking the human epidemiological, SNH, and histological aspects to a greater extent than the mouse despite the overall lack of published data. Conclusions FIMD facilitates drug development by serving as the basis to select the most relevant model that can provide meaningful data and is more likely to generate translatable results to progress drug candidates to the clinic.

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Immunoglobulin E (IgE)-mediated allergy against cow’s milk protein fractions such as whey is one of the most common food-related allergic disorders of early childhood. Histone acetylation is an important epigenetic mechanism, shown to be involved in the pathogenesis of allergies. However, its role in food allergy remains unknown. IgE-mediated cow’s milk allergy was successfully induced in a mouse model, as demonstrated by acute allergic symptoms, whey-specific IgE in serum, and the activation of mast cells upon a challenge with whey protein. The elicited allergic response coincided with reduced percentages of regulatory T (Treg) and T helper 17 (Th17) cells, matching decreased levels of H3 and/or H4 histone acetylation at pivotal Treg and Th17 loci, an epigenetic status favoring lower gene expression. In addition, histone acetylation levels at the crucial T helper 1 (Th1) loci were decreased, most probably preceding the expected reduction in Th1 cells after inducing an allergic response. No changes were observed for T helper 2 cells. However, increased histone acetylation levels, promoting gene expression, were observed at the signal transducer and activator of transcription 6 (Stat6) gene, a proallergic B cell locus, which was in line with the presence of whey-specific IgE. In conclusion, the observed histone acetylation changes are pathobiologically in line with the successful induction of cow’s milk allergy, to which they might have also contributed mechanistically.

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