Are some animal models more equal than others? A case study on the translational value of animal models of efficacy for Alzheimer's disease

Veening-Griffioen, Désirée H.; Ferreira, Guilherme S.; Meer, Peter J.K. van; Boon, Wouter; Wied, Christine C. Gispen‐de; Moors, Ellen H.M.; Schellekens, Huub

doi:10.1016/j.ejphar.2019.172524

Cited by 42 publications

(29 citation statements)

References 57 publications

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“…Guidance on model selection for efficacy assessment in drug development is nonetheless available in the literature [32,33]. However, very few retrospective assessments of their predictive validity [34] have actually been carried out. Quality of prediction can nonetheless be improved by estimating the relationship between drug efficacy data in humans and animal models quantitatively.…”

Section: Discussionmentioning

confidence: 99%

Assessing Scientific Soundness and Translational Value of Animal Studies on DPP4 Inhibitors for Treating Type 2 Diabetes Mellitus

Franco

Miranda

Kovács

et al. 2021

Biology

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Although there is a wide range of animal models of type 2 diabetes mellitus (T2DM) used in research; we have limited evidence on their translation value. This paper provides a) a comparison of preclinical animal and clinical results on the effect of five dipeptidyl peptidase-4 (DPP4) inhibitors by comparing the pharmaceutical caused glucose changes, and b) an evaluation of methodological and reporting standards in T2DM preclinical animal studies. DPP4 inhibitors play an important role in the clinical management of T2DM: if metformin alone is not sufficient enough to control the blood sugar levels, DPP4 inhibitors are often used as second-line therapy; additionally, DPP-4 inhibitors are also used in triple therapies with metformin and sodium-glucose co-transporter-2 (SGLT-2) inhibitors or with metformin and insulin. In our analysis of 124 preclinical studies and 47 clinical trials, (1) we found no evidence of species differences in glucose change response to DPP4 inhibitors, which may suggest that, for this drug class, studies in mice and rats may be equally predictive of how well a drug will work in humans; and (2) there is good reporting of group size, sex, age, euthanasia method and self-reported compliance with animal welfare regulations in animal studies but poor reporting of justification of group size, along with a strong bias towards the use of male animals and young animals. Instead of the common non-transparent model selection, we call for a reflective and evidenced-based assessment of predictive validity of the animal models currently available.

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Section: Discussionmentioning

confidence: 99%

Assessing Scientific Soundness and Translational Value of Animal Studies on DPP4 Inhibitors for Treating Type 2 Diabetes Mellitus

Franco

Miranda

Kovács

et al. 2021

Biology

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“…Thus, we need to focus on understanding the animal pathophysiology to the degree that allows us to assess for what kind of research a disease model is suitable. Especially for complex multifactorial conditions (e.g., Alzheimer's disease), the use of multiple models that simulate different aspects is likely to provide a more detailed and reliable picture [42]. For instance, Seok and colleagues have shown that human and mouse responses to inflammation vary significantly according to their aetiology [43].…”

Section: Levelling the Translational Gap For Animal To Human Efficacymentioning

confidence: 99%

Levelling the Translational Gap for Animal to Human Efficacy Data

Ferreira

Veening-Griffioen

Boon

et al. 2020

Animals

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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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“…Additionally, Tg animals expressing FAD genetic variants (Table S1), despite showing amyloids, NFTs, gliosis, and synaptic alterations, often do not undergo significant neuronal loss, and the amyloid peptides they generate appear to be different from those identified in the human brain [80]. Another relevant aspect is that animal models of AD generally do not reflect the pathology as observed in humans [16,81], and do not develop the typical co-morbidities observed in AD patients, such as metabolic syndrome, cardiovascular disease, inflammation, and immunological disorders [15]. Notably, different murine strains show remarkably different lifespans, often premature mortality, along with sex differences in the expected lifespan, as summarized by Rae and Brown [82].…”

Section: Alzheimer's Diseasementioning

confidence: 99%

Alzheimer’s Disease, and Breast and Prostate Cancer Research: Translational Failures and the Importance to Monitor Outputs and Impact of Funded Research

Herrmann

Bernasconi

McCarthy

et al. 2020

Animals

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Dementia and cancer are becoming increasingly prevalent in Western countries. In the last two decades, research focused on Alzheimer’s disease (AD) and cancer, in particular, breast cancer (BC) and prostate cancer (PC), has been substantially funded both in Europe and worldwide. While scientific research outcomes have contributed to increase our understanding of the disease etiopathology, still the prevalence of these chronic degenerative conditions remains very high across the globe. By definition, no model is perfect. In particular, animal models of AD, BC, and PC have been and still are traditionally used in basic/fundamental, translational, and preclinical research to study human disease mechanisms, identify new therapeutic targets, and develop new drugs. However, animals do not adequately model some essential features of human disease; therefore, they are often unable to pave the way to the development of drugs effective in human patients. The rise of new technological tools and models in life science, and the increasing need for multidisciplinary approaches have encouraged many interdisciplinary research initiatives. With considerable funds being invested in biomedical research, it is becoming pivotal to define and apply indicators to monitor the contribution to innovation and impact of funded research. Here, we discuss some of the issues underlying translational failure in AD, BC, and PC research, and describe how indicators could be applied to retrospectively measure outputs and impact of funded biomedical research.

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Are some animal models more equal than others? A case study on the translational value of animal models of efficacy for Alzheimer's disease

Cited by 42 publications

References 57 publications

Assessing Scientific Soundness and Translational Value of Animal Studies on DPP4 Inhibitors for Treating Type 2 Diabetes Mellitus

Assessing Scientific Soundness and Translational Value of Animal Studies on DPP4 Inhibitors for Treating Type 2 Diabetes Mellitus

Levelling the Translational Gap for Animal to Human Efficacy Data

Alzheimer’s Disease, and Breast and Prostate Cancer Research: Translational Failures and the Importance to Monitor Outputs and Impact of Funded Research

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