ReviewAnnals of laboratory medicine2025
Revolutionizing Laboratory Practices: Pioneering Trends in Total Laboratory Automation.
Review in Annals of laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- An automatic semen processing system versus a manual method for semen processing: a randomized, single-blind non-inferiority trial.Frontiers in endocrinology · 2026Trial
- Rapid Centrifugation for Coagulation Testing: A Multianalyzer Validation Study Harmonizing Preanalytical Protocols for Total Laboratory Automation.International journal of laboratory hematology · 2026Article
- When Brownian Motion Meets Clinical Laboratory Automation: A DLS-Inspired Autocorrelation Function for Characterizing Workflow Performance in Sample Processing.Diagnostics (Basel, Switzerland) · 2026Article
- Total Laboratory Automation Versus Manual Processing in Urine Culture Inoculation and Interpretation: A Hospital Experience.Diagnostics (Basel, Switzerland) · 2026Article
- Collaborative Robotic Systems for Pre-Analytical Processing of Biological Specimens in a Medical Laboratory.Diagnostics (Basel, Switzerland) · 2026Article
- A Hybrid Qualitative-Quantitative FMEA Model for Risk Management in Clinical Laboratory Automation: A Case Study Integrating ISO 15189:2022.Journal of clinical laboratory analysis · 2026Article
- Article
- Artificial intelligence in experimental and clinical in vitro analysis: applications, limitations, and future directions.Biotechnology notes (Amsterdam, Netherlands) · 2026Review
- Evolving microbiology laboratories: mastering automated culture-based processes and molecular assays, an institutional experience.Frontiers in cellular and infection microbiology · 2026Review
- Artificial Intelligence (AI) Adoption, Policies, and Goals in Family Medicine: A Survey of Department Chairs.Journal of the American Board of Family Medicine : JABFM · 2025Article
- Optimization of the Total Testing Process Within the Big Data-to-Big Data Loop.Annals of laboratory medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Total laboratory automation (TLA) is a transformative solution in clinical laboratories that addresses growing demands for operational efficiency, accuracy, and rapid turnaround times in patient care. TLA integrates advanced technologies across pre-analytical, analytical, and post-analytical phases, thereby streamlining workflows, reducing manual intervention, and enhancing QC. TLA adoption is driven by factors such as increasing test volumes, the need for cost reduction and regulatory compliance, and labor shortages. Key benefits of TLA include improved accuracy through error minimization, optimized resource utilization, enhanced staff well-being, and consistent delivery of high-quality results. Leading companies, including Abbott, Roche, Siemens, and Beckman Coulter, dominate the global TLA market with innovative solutions. Recent developments incorporate artificial intelligence (AI), machine learning, robotics, and Internet-of-things technologies, which enable predictive analytics and automated data management. However, challenges remain, including high implementation costs, the need for workforce training, cybersecurity concerns, and system integration complexities. Future trends indicate that TLA will advance through enhanced AI integration, sustainable practices, and big data analytics, fostering continuous improvements in precision diagnostics and clinical outcomes. Moreover, TLA has the potential to revolutionize laboratory operations globally, driving efficiency, accuracy, and sustainability while ultimately improving patient care. Successful adoption of TLA will require strategic planning, interdisciplinary collaboration, and alignment with emerging healthcare needs. In this review, we emphasize that overcoming these challenges through innovation and robust management is essential for ensuring that TLA continues to play a vital role in modern healthcare systems.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.