Issue 5, 2024

Optimization of liquid handling parameters for viscous liquid transfers with pipetting robots, a “sticky situation”

Abstract

Automated air-displacement pipettes have become a standard equipment for the transfer of liquids in laboratory settings. However, these tools fail to perform accurate and precise transfers of liquids with viscosities greater than 100 cP. In this study, we report a systematic protocol for optimizing the liquid-handling parameters of automated pipettes to achieve accurate and precise transfers of viscous liquids (within 5% of percentage transfer error) with viscosities as high as 1275 cP using minimal transfer times. The protocol is based on the iterative gravimetric testing of different combinations of aspiration and dispense rates obtained by a Multi-Objective Bayesian Optimization (MOBO) algorithm. We demonstrate that optimal solutions obtained through MOBO can match or outperform solutions derived from human intuition, showing a consistent performance even when different pipetting equipment and tip geometries are used. Finally, we demonstrate that the protocol can be performed in a fully automated, closed-loop fashion by integrating an automated mass balance, increasing the manpower efficiency of the method. This offers a valuable advancement in the accurate manipulation of highly viscous liquids, with broad applications for the automation of various laboratory experiments.

Graphical abstract: Optimization of liquid handling parameters for viscous liquid transfers with pipetting robots, a “sticky situation”

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Article information

Article type
Paper
Submitted
29 Dec 2023
Accepted
14 Apr 2024
First published
17 Apr 2024
This article is Open Access
Creative Commons BY-NC license

Digital Discovery, 2024,3, 1011-1020

Optimization of liquid handling parameters for viscous liquid transfers with pipetting robots, a “sticky situation”

P. Quijano Velasco, K. Y. A. Low, C. J. Leong, W. T. Ng, S. Qiu, S. Jhunjhunwala, B. Li, A. Qian, K. Hippalgaonkar and J. J. W. Cheng, Digital Discovery, 2024, 3, 1011 DOI: 10.1039/D3DD00255A

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