laboratorioautomaation

Laboratorioautomaation is the application of automated hardware and software to perform laboratory tasks with minimal human intervention. It covers processes from sample handling to data reporting, aiming to increase throughput, improve accuracy and reproducibility, and enhance safety while reducing labor costs. In multilingual and cross-disciplinary contexts, the term may appear as laboratory automation or related spellings.

Key components include hardware such as robotic arms, liquid-handling systems, plate handlers, autosamplers, incubators, and automated storage; and software such as Laboratory Information Management Systems (LIMS), Electronic Laboratory Notebooks (ELN), workflow-management tools, and instrument-control platforms that coordinate steps and capture results. Systems are typically integrated with analytical instruments via standard interfaces, middleware, and data communication protocols.

Common workflows are organized into pre-analytic steps (sample receipt and labeling), analytic steps (assay setup and execution), and post-analytic steps (data analysis and reporting).

Applications span high-throughput screening in drug discovery, omics sample preparation, clinical chemistry and hematology in automated diagnostics, environmental and food testing, and basic research laboratories.

Benefits include higher throughput, improved precision and reproducibility, better traceability and data integrity, safer handling of hazardous materials, and reduced operator fatigue. Challenges include high upfront and maintenance costs, system validation and regulatory compliance, interoperability between vendors, data governance, and cybersecurity concerns.

Regulatory contexts such as GLP/GxP and electronic records regulations often require rigorous validation and audit trails for automated workflows, and many laboratories adopt standards and best practices aligned with ISO/IEC 17025 and related frameworks.

Over time, laboratory automation has become more modular and scalable, with cloud-enabled data management, AI-assisted analysis, and predictive maintenance shaping future trends.