An Automated, Home-Cage, Video Monitoring-based Mouse Frailty Index Detects Age-associated Morbidity in C57BL/6 and Diversity Outbred Mice.

Frailty indexes (FIs) provide quantitative measurements of nonspecific health decline and are particularly useful as longitudinal monitors of morbidity in aging studies. For mouse studies, frailty assessments can be taken noninvasively, but they require handling and direct observation that is labor-intensive to the scientist and stress inducing to the animal. Here, we implement, evaluate, and provide a refined digital FI composed entirely of computational analyses of home-cage video and compare it to manually obtained frailty scores in both C57BL/6 and genetically heterogeneous Diversity Outbred mice. We show that the frailty scores assigned by our digital index correlate with both manually obtained frailty scores and chronological age. Thus, we provide an automated tool for frailty assessment that can be collected reproducibly, at scale, without substantial labor cost.

Emerging Role of Translational Digital Biomarkers Within Home Cage Monitoring Technologies in Preclinical Drug Discovery and Development.

In drug discovery and development, traditional assessment of human patients and preclinical subjects occurs at limited time points in potentially stressful surroundings (i.e., the clinic or a test arena), which can impact data quality and welfare. However, recent advances in remote digital monitoring technologies enable the assessment of human patients and preclinical subjects across multiple time points in familiar surroundings. The ability to monitor a patient throughout disease progression provides an opportunity for more relevant and efficient diagnosis as well as improved assessment of drug efficacy and safety. In preclinical in vivo animal models, these digital technologies allow for continuous, longitudinal, and non-invasive monitoring in the home environment. This manuscript provides an overview of digital monitoring technologies for use in preclinical studies including their history and evolution, current engagement through use cases, and impact of digital biomarkers (DBs) on drug discovery and the 3Rs. We also discuss barriers to implementation and strategies to overcome them. Finally, we address data consistency and technology standards from the perspective of technology providers, end-users, and subject matter experts. Overall, this review establishes an improved understanding of the value and implementation of digital biomarker (DB) technologies in preclinical research.

Combined evaluation of commonly used techniques, including PCR, for diagnosis of mouse fur mites.

Our study evaluated and compared the false-negative rates (FNR) of a wide array of fur-mite diagnostic tests, including 2 postmortem tests (pelt exam and sticky paper) and 3 antemortem tests (adhesive tape, fur pluck, and PCR). Past publications examining fur-mite diagnostic techniques primarily used paired comparisons, evaluating tests by their level of agreement with only one other test. However, different combinations or pairs of diagnostics are used in the different studies, making the results of these comparisons difficult to interpret across all available diagnostics. In the current study, mice from a conventionally maintained colony endemic for Myobia musculi were identified as positive based on at least one positive diagnostic test. From this pool of positive animals, the FNR of all tests were quantified. The PCR assay and the pelt exam performed the best, with 0% and 2% FNR respectively, whereas tape, fur-pluck, and sticky-paper tests showed 24%, 26%, and 36% FNR, respectively. Our study shows that for mice in a colony naturally infested with Myobia musculi, PCR testing can be used for reliable antemortem detection, and pelt exam performed by experienced examiners is reliable for postmortem detection.