The field of digital and AI-based technologies is rapidly transforming toxicology and safety pharmacology testing in regulatory and pharmcuetical industry. With the advent of portable and affordable digital tools, researchers are increasingly utilizing these technologies to enhance the quality and diversity of clinical trials, especially in the wake of the COVID-19 pandemic. Digital caging technology, in particular, has emerged as a pivotal tool in animal-based research, allowing for continuous, objective, and accurate monitoring of animals within their home cage environment. This innovation facilitates a range of assays for physiological, pharmacological and phenotypic analysis, in vivo drug screening, and safety and risk assessment. Recent advancements in AI software, hardware and infrsructure, automated image processing, and remote sensors have made digital caging systems more practical and impactful. These systems offer non-invasive monitoring capabilities, reducing stress-related confounding factors and enabling real-time measurement and alert of various behavioral and physiological parameters. Despite these advancements, challenges remain in the routine implementation of these technologies, including onboarding, data integration, and operational training.
This Research Topic aims to create a platform for toxicologists, pharmacologists, and veterinarians to share novel findings, issues, and solutions related to digital caging and monitoring technologies in toxicology, risk assessment, and safety pharmacology studies. The goal is to explore new developments and applications of these technologies and their impact on toxicological testing. By fostering communication among researchers, this topic seeks to enhance the understanding and implementation of digital caging technologies, ultimately improving animal welfare and study data quality and preclinic to clinic translatibility.
To gather further insights in the application of digital caging technology in toxicology and safety pharmacology, we welcome articles addressing, but not limited to, the following themes: - Effects of digital caging and monitoring on animals’ well-being, health and toxicological endpoints. - Intelligent monitoring capabilities for remote detection of adverse behavior and physiological effects. - New approaches in collecting, storing, or analyzing automated animal data, such as vocalization and motion tracking. - Data storage, flow, management, and security. - Development of applications for animal monitoring and novel humane experimental endpoints. - Big data potential to promote the 3Rs principle and animal welfare in in vivo research. Manuscripts may include research papers, case reports or reviews.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Clinical Trial
Community Case Study
Conceptual Analysis
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Clinical Trial
Community Case Study
Conceptual Analysis
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy and Practice Reviews
Policy Brief
Review
Study Protocol
Systematic Review
Technology and Code
Keywords: smart cage, digital cage, virtual monitoring diagnosis, remote monitoring, animal welfare, humane endpoints, toxicological endpoints, big data
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.