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Engineering Steps for Mobile Point-of-Care Diagnostic Devices
Ayden Malekjahani1, Shrey Sindhwani1, Abdullah Muhammad Syed1
1Institute of Biomaterials and Biomedical Engineering (IBBME) , University of Toronto , 164 College St , Toronto , ON M5S 3G9 , Canada.
Mobile phone diagnostics offer great potential for point-of-care testing. This review outlines strategies to overcome development challenges and accelerate the creation of new diagnostic tools for global health.
Area of Science:
- Biomedical Engineering
- Medical Diagnostics
- Mobile Health Technology
Background:
- Mobile phones offer advanced capabilities for point-of-care diagnostic development.
- Despite academic progress, few mobile diagnostics have achieved field testing, commercialization, or regulatory approval.
Purpose of the Study:
- To address challenges in mobile diagnostic development and propose strategies for researchers.
- To provide a resource for accelerating the development and approval of new mobile diagnostics.
Main Methods:
- Review of published mobile phone diagnostics and lessons learned.
- Inclusion of recommendations from regulatory and public health agencies (e.g., FDA, WHO).
- Outlining a four-step development process: Needs Assessment, Technology Development, Preclinical Verification, and Clinical Validation.
Main Results:
- Identified common pitfalls in mobile diagnostic development, including misaligned technical parameters with clinical impact and reliance on lab resources.
- Emphasized the need for equipment-free, mobile-agnostic devices and simulating field conditions during laboratory verification.
- Stressed the importance of field testing in conditions matching intended use and focusing on fundamental research principles.
Conclusions:
- The future of mobile point-of-care diagnostics is promising but requires addressing fundamental research and development challenges.
- Adherence to a structured development process with a focus on needs assessment and realistic validation is crucial.
- Implementing the suggested strategies can streamline development, increase productivity, and lead to more approved diagnostics, ultimately reducing global disease burden.
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