Digital technologies in life sciences: advances and opportunities

Digital advances are fundamentally reshaping the life sciences, with emerging technologies redefining research, diagnostics, agriculture, and biotechnology. This review provides an integrated overview of the key digital innovations shaping the field, including artificial intelligence and machine learning, Internet of Things-based sensing, blockchain, bioinformatics, big data analytics, digital twins, robotics, and social media-driven digital communication. These tools are examined across animal science, medical science, and biotechnology to enable precision agriculture, intelligent disease diagnosis, omics-based discovery, laboratory automation, and continuous real-time monitoring. Through the analysis of recent case studies, it is demonstrated how the combination of sensing, computation, and automation is driving more predictive, efficient, and data-centered life science systems. The review also addresses major challenges related to data governance, interoperability, ethics, and implementation. To identify relevant literature, a structured search was conducted across PubMed, Web of Science, Scopus, and Google Scholar, covering peer-reviewed publications from 2014 to 2026, with emphasis on articles published from 2020 onward. Search terms combined technology-specific concepts (e.g., artificial intelligence, Internet of Things, blockchain, bioinformatics, digital twin, and robotics) with life science application domains (e.g., animal science, medical science, biotechnology, precision livestock farming, and drug discovery). Studies were included if they reported primary findings, systematic reviews, or substantive conceptual analyses relevant to the application of digital technologies in life sciences; non-peer-reviewed sources were incorporated only when they represented major policy or institutional reports. Overall, this synthesis highlights both the transformative potential and the practical constraints of digital technologies in life sciences, offering a forward-looking perspective on the next generation of innovation in biologically informed digital systems.