A collaborative robotic solution to partly automate SARS-CoV-2 serological tests in small facilities | JoVE Visualize

A collaborative robotic solution to partly automate SARS-CoV-2 serological tests in small facilities

Andrea Maria Zanchettin¹, Federica Facciotti²

¹Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Piazza Leonardo Da Vinci 32, Milano, Italy.

SLAS Technology|January 21, 2022

View abstract on PubMed

Summary

Robotics technology helps automate COVID-19 serological tests, increasing lab throughput by 66% and reducing human pipetting by 62%. This innovation supports healthcare systems during the pandemic.

Area of Science:

Medical Robotics
Clinical Diagnostics
Infectious Disease Management

Background:

The COVID-19 pandemic placed immense strain on global healthcare systems.
Rapid and dependable screening is crucial for controlling viral spread pending widespread vaccination.
Robotics offers potential solutions for enhancing clinical laboratory efficiency.

Purpose of the Study:

To detail a collaborative robotics application for automating SARS-CoV-2 quantitative serological tests.
To assess the impact of this automation on laboratory throughput and human workload.

Main Methods:

Development of a collaborative robotics system in partnership with a hospital and robot manufacturer.
Partial automation of quantitative serological tests for SARS-CoV-2.
Evaluation of throughput increase and reduction in manual pipetting activities.

Main Results:

The implemented robotics application increased overall laboratory throughput by 66%.
Automating parts of the testing process reduced manual pipetting activities by 62%.
The system is particularly beneficial for small laboratories with repetitive tasks.

Conclusions:

Collaborative robotics can significantly enhance the efficiency and safety of clinical diagnostic laboratories.
Automation of SARS-CoV-2 serological testing is a viable strategy to manage pandemic-related healthcare burdens.
This technology can alleviate laboratory technicians from repetitive and potentially harmful tasks.