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Development of Analytical Methods

Development of Analytical Methods

An analytical methodology can be divided into four sequential steps: technique, method, procedure, and protocol. A technique is a scientific principle that rationalizes a specific phenomenon through chemical measurements. Adapting a technique for analyzing a sample of interest is termed a method. The procedure outlines the directions for performing the analysis via an analytical method. The protocol is the detailed guidelines on the procedure, which should be strictly followed to obtain the...

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Related Experiment Video

Updated: Dec 29, 2025

Fabrication of Three-dimensional Paper-based Microfluidic Devices for Immunoassays

Fabrication of Three-dimensional Paper-based Microfluidic Devices for Immunoassays

Published on: March 9, 2017

Chemometric challenges in development of paper-based analytical devices: Optimization and image processing.

Vahid Hamedpour¹, Paolo Oliveri², Riccardo Leardi²

¹Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505, Japan; Department of Applied Chemistry, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Japan.

Analytica Chimica Acta

|February 8, 2020

Summary

This summary is machine-generated.

This study shows how design of experiments (DoE) and digital image processing can improve microfluidic paper-based analytical devices (μPADs). These methods aid in optimizing μPADs, potentially accelerating their commercialization.

Keywords:

D-optimal design Design of experiments Image processing algorithm Mathematical morphology recognition (MMR)Microfluidic paper-based analytical devices (μPADs)Optimization

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Published on: September 19, 2017

Area of Science:

Analytical Chemistry
Biomedical Engineering
Materials Science

Background:

Microfluidic paper-based analytical devices (μPADs) show promise but face commercialization challenges.
Limited application of machine learning and chemometrics hinders μPAD design and optimization.
Addressing these limitations is crucial for advancing μPAD technology.

Purpose of the Study:

To demonstrate the utility of chemometric techniques in μPAD development.
To optimize experimental conditions for a colorimetric assay on μPADs.
To showcase the benefits of digital image processing for μPAD analysis.

Main Methods:

Design of Experiments (DoE), specifically D-optimal design, was employed for optimizing experimental factors.
A colorimetric assay for isoniazid, utilizing methyl orange, served as a model system.
Automated digital image processing based on morphological recognition was developed for RGB value analysis.

Main Results:

DoE successfully optimized experimental conditions for the μPAD assay.
Digital image processing significantly accelerated color value analysis and reduced manual selection errors.
The developed algorithm provided repeatable RGB value analysis.

Conclusions:

Chemometric techniques like DoE are vital for efficient μPAD optimization.
Digital image processing enhances the accuracy and speed of μPAD data analysis.
Integrating these methods can overcome key weaknesses in μPAD development, facilitating market entry.