Severity assessment in neuroscientific research: generalisability of multidimensional approaches and application to refinement

• Applicant: Professorin Dr. Heidrun Potschka
• Subject Area: Molecular and Cellular Neurology and Neuropathology ; Sensory and Behavioural Biology ; Experimental Models for the Understanding of Nervous System Diseases ; Veterinary Medical Science
• Term: since 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 321137804

During funding phase 1 and 2, a comprehensive set of behavioural, biochemical, and telemetrically-analysed physiological parameters has been assessed in various induced and genetic mouse and rat models of neuropediatric and neurological disorders. A cross-age, -model, -species and -sex validation provided valuable information about generalisability of selected parameter candidates. Respective information was considered for the design and validation of a test battery allowing assessment of cumulative severity across the developmental trajectory of young genetically-modified mice. Moreover, we have further developed, and optimised a bioinformatic workflow for parameter selection and design of multidimensional composite measure schemes. Case studies, focussed on models of epilepsy, neurodevelopmental and neuropsychiatric disorders, demonstrated that the resulting multidimensional schemes take severity assessment to a new level of sensitivity allowing comparative assessment with precise grading of distress levels. Multivariate approaches have also been successfully applied to validate potential refinement measures (e.g., optimised multimodal analgesia; telemetric vs. tethered recordings) for common interventions and techniques in neuroscientific research. Findings from experimental studies and systematic reviews serve as a basis for selecting the most promising parameters for an in-depth intra-laboratory and an overarching inter-laboratory analysis, providing further information about their informative value, sensitivity, replicability, robustness, and generalisability. Along these lines, the bioinformatic workflow for the design of multidimensional composite measure schemes will be applied to datasets from different collaboration partners to confirm its validity for different animal models and identify necessary adaptations. In addition, we will apply RELSA to our data sets to confirm the validity of this multidimensional scoring system for continuous severity monitoring and will support the development of variants for specific study designs. In terms of evidence-based refinement, analysis of intra- and inter-laboratory data and routine use of multimodal perioperative analgesic regimens will inform about the generalisability of such regimens. With data sets recorded during a multicentre study with transmitter implants and from a genetic mouse model, we will contribute to the validation of a new smart home cage system. Based on our findings and discussions with stakeholders, we will provide recommendations for the design and application of multivariate schemes for evidence-based severity assessment and for evidence-based refinement measures.

• DFG Programme: Research Units
• Subproject of: FOR 2591: Severity assessment in animal-based research
• Co-Investigator: Dr. Verena Buchecker