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Multi-objective optimisation of polymerase chain reaction continuous flow systems.

Foteini Zagklavara1, Peter K Jimack2, Nikil Kapur3

  • 1School of Computing, University of Leeds, Leeds, LS2 9JT, United Kingdom. fotizagl@hotmail.com.

Biomedical Microdevices
|March 22, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for optimizing continuous flow Polymerase Chain Reaction (CFPCR) systems using machine learning and simulations. The approach enhances DNA amplification efficiency and reduces costs by optimizing device design and operating parameters.

Keywords:
COMSOL®Design of ExperimentsMicrochannelMulti-objective OptimisationPCRPareto Front

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Area of Science:

  • Biotechnology
  • Microfluidics
  • Computational Science

Background:

  • Continuous flow Polymerase Chain Reaction (CFPCR) systems offer potential for rapid DNA amplification.
  • Optimizing CFPCR devices requires balancing multiple performance objectives, such as amplification efficiency, time, volume, and pressure drop.
  • Existing optimization methods may not adequately address the complex interplay of design parameters in CFPCR systems.

Purpose of the Study:

  • To develop and present a surrogate-enabled multi-objective optimization methodology for CFPCR systems.
  • To explore the impact of PCR protocols and channel geometry on key performance metrics.
  • To provide designers with a tool for achieving optimal compromises between competing objectives in CFPCR design.

Main Methods:

  • Integration of high-fidelity conjugate heat transfer (CHT) simulations with Machine Learning to build accurate surrogate models.
  • Development of a surrogate model covering DNA amplification efficiency, residence time, substrate volume, and pressure drop.
  • Application of single and multi-objective optimization techniques to a sigmoid-shaped microfluidic CFPCR device.

Main Results:

  • Single-objective optimizations demonstrated significant potential improvements: up to 5.7% in DNA concentration, 80.5% in pressure drop reduction, 17.8% in residence time, and 43.2% in substrate volume.
  • Multi-objective optimization results, presented as a Pareto surface, illustrate trade-offs between objectives.
  • Cost reductions through miniaturization and reduced power consumption were shown to be achievable with minimal impact on DNA amplification efficiency.

Conclusions:

  • The developed methodology effectively optimizes CFPCR systems by balancing multiple performance criteria.
  • DNA amplification efficiency is strongly correlated with residence time in the extension zone.
  • The findings enable informed design decisions for cost-effective and efficient CFPCR devices.