Baran Szczepan W, Bratcher Natalie, Dennis John, Gaburro Stefano, Karlsson Eleanor M, Maguire Sean, Makidon Paul, Noldus Lucas P J J, Potier Yohann, Rosati Giorgio, Ruiter Matt, Schaevitz Laura, Sweeney Patrick, LaFollette Megan R
Novartis Institutes for BioMedical Research, Cambridge, MA, United States.
Office of Global Animal Welfare, AbbVie, North Chicago, IL, United States.
Front Behav Neurosci. 2022 Feb 14;15:758274. doi: 10.3389/fnbeh.2021.758274. eCollection 2021.
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 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.
在药物研发过程中,对人类患者和临床前研究对象的传统评估是在潜在压力环境(即诊所或测试场地)中的有限时间点进行的,这可能会影响数据质量和研究对象的福祉。然而,远程数字监测技术的最新进展使得能够在熟悉的环境中对人类患者和临床前研究对象进行多个时间点的评估。在疾病进展过程中对患者进行全程监测,为更相关、高效的诊断以及改进药物疗效和安全性评估提供了机会。在临床前动物模型中,这些数字技术允许在动物的生活环境中进行连续、长期和非侵入性监测。本文概述了用于临床前研究的数字监测技术,包括其历史和发展、通过实际应用案例的当前应用情况,以及数字生物标志物(DBs)对药物发现和3R原则的影响。我们还讨论了实施过程中的障碍以及克服这些障碍的策略。最后,我们从技术提供商、终端用户和主题专家的角度探讨了数据一致性和技术标准。总体而言,本综述增进了人们对数字生物标志物(DB)技术在临床前研究中的价值和应用的理解。