The rapid growth of systems biology approaches in preclinical research, such as whole-genome sequencing and genome editing, has contributed to the need for high-throughput and reproducible phenotypic screening of genetically engineered animals. The relationship between genotype and phenotype is complex: targeted genes of interest interact with background genes and unknown mutations, as well as epigenetic and environmental factors, to exert specific or collective effects on health and behavior.
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We hypothesize that continuous monitoring of behavioral and physiological parameters will provide additional meaningful data to assess disease and efficacy in genetic rodent models of disease, including SLE. To address this hypothesis, the objectives of this study were: 1) To investigate behavioral and physiological characteristics of MRL/lpr mice using a low-touch, continuous monitoring platform, and 2) To evaluate and compare the effects of standard of care (SOC) compounds on conventional disease measures as well as behavioral and physiological phenotypes in MRL/lpr mice.
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We hypothesize that continuous monitoring of behavioral and physiological parameters will provide clinically relevant data to assess disease in induction rodent models, including the Con A- induced mouse model of liver disease. The objective of this study was to evaluate behavioral and physiological characteristics of Con A-induced mice using different doses of Con A.
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Despite a broad spectrum of anti-arthritic drugs currently on the market, there is a constant demand to develop improved therapeutic agents. Efficient compound screening and rapid evaluation of treatment efficacy in animal models of rheumatoid arthritis (RA) can accelerate the development of clinical candidates. Compound screening by evaluation of disease phenotypes in animal models facilitates preclinical research by enhancing understanding of human pathophysiology; however, there is still a continuous need to improve methods for evaluating disease.
Measurement of overall motion, as well as specific subtypes of activity such as circadian rhythms and particular aspects of locomotion, can be used as an integrated readout for tracking disease progression. Vium's platform enables motion tracking of subjects non-invasively and is used as a measure to track disease progression and treatment in a variety of animal models.
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Measuring changes in breathing rate can lead to the early detection of disease and is key in evaluating the safety profile of novel therapeutics. A range of conditions including exercise, stress, lung disorders, cardiovascular disease, metabolic acidosis, drug overdose, and central nervous system abnormalities can all manifest in detectable alterations in breathing rate.
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The Vium Digital Vivarium Platform offers two different types of activity metrics, which allow researchers to dissociate overall physical activity and voluntary activity: the Vium Motion metric and the Vium Percentage (%) Time Running on Wheel metric. The Vium Motion metric measures overall activity, which is comprised of both voluntary and involuntary motor movements, including wheel running, asa well as a wide range of complex behaviors, such as eating drinking and grooming. In contrast, the Vium % Time Running on Wheel metric specifically captures free running on the wheel, which accounts for voluntary activity. A number of factors are known to differentially alter overall physical activity and voluntary wheel running activity.
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The Vium Arthritis Index enables researchers to evaluate the efficacy and safety of therapeutic interventions in rodent models of RA through near realtime measurements and data analysis. Our use of physiological measurements combined with advanced analytics provides a highly sensitive readout of arthritis induction, as well as clinically relevant measures of therapeutic response.