Assessment of distress and refinement in animal models for gastrointestinal diseases

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In the first two funding periods, we published 19 manuscripts and reached the following four conclusions: First, telemetry and non-invasive, easy-to-assess methods such as measuring burrowing activity, nesting behaviour, body weight, faecal corticosterone metabolites and evaluating a distress score can be successfully used for analysing distress of animal models. Second, ROC curve analysis is excellent for determining which methods are appropriate to discriminate between specific stress levels. Third, a multifactorial stress analysis by binary logistic regression, k-means-based clustering, or RELSA can define and compare the stress of animal models. Fourth, risk prediction models such as the Cox proportional hazards model are appropriate to define early human endpoints. However, a scientifically based improvement in animal welfare can only be accomplished, if our methods, algorithms and conclusions are robust. Moreover, a broad generalisability of methods and algorithms might be beneficial, when comparing distress levels of various animal models. Thus, it is one major focus during the third funding period to assess the robustness and generalisability of used methods, algorithms and conclusions. For this purpose, we will compare additional data that we are currently collecting with data from our cooperation partners within this DFG research group and with data that we have already published. In addition, we intend to improve the pain management of animals by comparing animal welfare when using different analgesics. In the third funding period, we will focus on the following six specific goals: First, we will validate the reproducibility, robustness, and generalisability of the methods we used to measure stress in mice. Second, we will check the robustness of conclusions derived from the RELSA score and contribute to the creation of a severity map that compares distress between distinct animal models. Third, we want to validate early human endpoints and assess their generalisability. Fourth, together with other FOR 2591 groups, we will describe our experience with different analgesics. Fifth, we will define the pros and cons of using homecage imaging when analysing distress. Sixth, we will test novel analysis methods and algorithms. Thus, the third funding period will enable us to assess whether the burden on mice can be reliably assessed and compared. This funding period will also enable us to make scientifically sound recommendations on the use of analgesics and humane endpoints.