Collaborative Robotics, Mobile Platforms, and Total Laboratory Automation in Clinical Diagnostics

Area of Science:

• Clinical diagnostics
• Laboratory automation
• Robotics in healthcare

Background:

• Clinical diagnostic labs face pressure from high test volumes, complex testing, workforce shortages, and cost demands.
• Total laboratory automation (TLA) has improved efficiency in high-volume labs, reducing turnaround times and errors.
• Significant pre-analytical and post-analytical workflows remain manual, hindering overall laboratory efficiency.

Purpose of the Study:

• To explore the integration of TLA with emerging robotics technologies.
• To discuss the technical, regulatory, operational, and business aspects of hybrid automation.
• To present the case for flexible, modular robotic systems in clinical laboratories.

Main Methods:

• Review of current TLA systems and their impact on laboratory performance.
• Analysis of advancements in collaborative robotics (cobots) and autonomous mobile robots (AMRs).
• Integration of technical, regulatory (CLIA, FDA), operational, and business perspectives.

Main Results:

• TLA significantly reduces turnaround time, error rates, and labor needs in high-volume labs.
• Cobots offer precision for fine motor tasks, while AMRs excel at logistical transport.
• Existing mobile manipulators demonstrate real-world success in hospital supply delivery.

Conclusions:

• Hybrid automation ecosystems combining TLA, cobots, AMRs, and AI are emerging.
• Flexible, modular robotic systems working alongside humans will augment the strained laboratory workforce.
• This shift enhances laboratory reliability, scalability, and allows staff to focus more on patient care.