Improving the predictive power of disease models with digital biomarkers

Compound testing in disease models represent an important stage in the drug discovery process, allowing the assessment of  safety and efficacy in complex biological systems or organisms prior to first-in-human trials.  Preclinical studies de-risk first-in-human studies and provide drug developers increased confidence in the potential clinical safety and efficacy of a drug candidate.  While preclinical studies remain invaluable to the drug development process the success rate of translating pre-clinical results into clinical success has been falling not increasing. 

The large attrition rate of compounds (> 90%) in the clinic is due, in part, to the poor predictive power of in vivo safety and efficacy studies.  In assessing the current state of preclinical studies, a number of parameters have been identified to improve predictive power including:

  • Better understanding of the fundamental biology of a disease
  • Refinement of models, and choosing appropriate models to answer scientific questions
  • Better study design (choice of model, protocol, power, endpoints)
  • Improved translation through identification of validated assays in both preclinical and clinical trials
  • Standardization of experimental parameters across laboratories
How can digital biomarkers and the Vium platform improve model predictivity?

Drug discovery researchers seek to develop an advanced understanding of the pathways responsible for the specific disease state of interest in order to and develop strategies to model and then monitor pathways and drug targets during drug candidate efficacy testing.  Biomarkers have become a key component in achieving these goals.

Biomarkers are biochemical, molecular, anatomical, physiological, or behavioral parameters that measure or predict a human’s or an animal’s normal or diseased state, or their response to a drug. To have translational value, preclinical biomarkers must be robust, reproducible, easily measurable, and bridge to biomarkers used in the clinical setting (2,3).

The Vium platform continuously collects digital biomarkers non-invasively using built-in sensors and computer vision algorithms.  Scientists can leverage the platform to identify behavioral and physiological biomarkers that provide specific and sensitive readouts of disease progression and response to treatment.

  1. Denayer T, Stohr T, Van Roy M. (2014) Animal models in translational medicine: Validation and prediction. New Horizons in Translational Medicine 2:5-11.
  3. Pankevich DE, Wizemann TM, Altevogt BM. (2013) Improving the Utility and Translation of Animal Models for Nervous System Disorders. Workshop Summary.

The Vium Discovery Lab

Vium's Discovery Lab performs contract research for clients providing 24/7 remote monitoring of studies and digital metrics utilizing Vium’s Smart Housing™ technology.  Every cage in our facility is digitally enabled with 24/7 video recording and data streaming to the cloud.   Our system allows sponsors to view their studies at any time and watch the study progress in near-real time using our online Research Suite portal with live study views and data analysis.

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