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Review
. 2022 Feb 14:15:758274.
doi: 10.3389/fnbeh.2021.758274. eCollection 2021.

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

Szczepan W Baran  1 , Natalie Bratcher  2 , John Dennis  3 , Stefano Gaburro  4 , Eleanor M Karlsson  5 , Sean Maguire  6 , Paul Makidon  7 , Lucas P J J Noldus  8   9 , Yohann Potier  10 , Giorgio Rosati  4 , Matt Ruiter  11 , Laura Schaevitz  12 , Patrick Sweeney  13   14 , Megan R LaFollette  15
Affiliations
Review

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

Szczepan W Baran et al. Front Behav Neurosci. .

Abstract

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.

Keywords: 3Rs (reduce replace refine); digital biomarkers; drug discovery and development; home cage; preclinical; rodents; translation.

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Conflict of interest statement

SB is employed by Novartis Pharmaceuticals Corporation. NB and PM are employed by AbbVie Inc. NB and PM also own AbbVie stock. SG and GR are employed by Tecniplast S.p.A. EK is employed by Calico Life Sciences LLC. SM is employed by GlaxoSmithKline USA. LN is employed by Noldus Information Technology BV. YP is employed by Tessera Therapeutics Inc. MR is employed by Unified Information Devices Inc. LS is employed by Recursion Pharmaceuticals Inc. PS is employed by Actual Analytics Ltd and Naason Science Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Evolution of technologies generating digital biomarkers of rodent behavior and physiology. Each arrow extending over 2020 is a technology that is currently available. Blue rectangles: hardware. Orange rectangles: software. ABR, automatic behavior recognition. Housing: systems that are designed for permanent housing of rodents in the vivarium. Home cage: cages where the animals are housed majority of their lifetime in the vivarium. Bench top cage or technology: cages and technology (experimental test environments) not designed for permanent housing but where the animals are housed for a short (from hours up to few days) period of time.
FIGURE 2
FIGURE 2
Data Science is an interdisciplinary field focused on extracting knowledge from data. It requires a combination of skills, mainly statistics and mathematics, information technology understanding, and domain knowledge.
FIGURE 3
FIGURE 3
Example timeline for a pharmaceutical company from decision to engage with a scalable digital biomarker technology to running a first study.
FIGURE 4
FIGURE 4
Value propositions for translational digital biomarkers within drug discovery and development.
FIGURE 5
FIGURE 5
Scalable digital biomarker technologies present an opportunity to digitize the collection of traditional biomarkers and measure novel digital biomarkers (Wang et al., 2016).
FIGURE 6
FIGURE 6
Multiple measurements collected continuously and remotely within animals’ home environment can provide a holistic view of an in vivo model including objective assessment of disease development and burden.
See this image and copyright information in PMC

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