ABSTRACT
Introduction
A pandemic is the worst-case scenario in the field of infectious diseases. Innovative technologies have the potential to address the challenges associated with the manufacture of personalized drug delivery systems, biosensors, and medical devices during a pandemic. 3D-Printing, microfluidics, and Microelectromechanical systems (MEMS) can provide an important part on this fight, as are cheap, easy to be operated, capable to provide rapid detection and monitoring of a disease, and deliver medicines.
Areas covered
This manuscript answers the question of how these emerging technologies can save lives during a pandemic by avoiding supply chain delays and also by providing rapid diagnostics, disease monitoring, or by offering personalized treatments. The manuscript covers recent approaches in the topic with a focus in manuscripts published in the last year and by emphasising recent regulatory considerations by regulatory agencies in the manufacturing of 3DP systems or other medical devices during COVID.
Expert opinion
New manufacturing techniques are emerging with the ability to address the challenges associated with the development of medical devices or diagnostics, during a pandemic. Are many challenges in order to achieve this and especially in short times that are required under a pandemic attack, which will also be covered in this manuscript.
Article highlights
Emerging technologies have all the potential to be used during a pandemic as are able to address many challenges in short times.
3D-printed systems can be manufactured with rapid and cost-effective manner, and support the supply chain during a pandemic.
MEMS devices and microfluidic systems can provide rapid diagnostics and disease monitoring.
Like many other technologies are barriers that will need to be considered in using innovative technologies.
During a pandemic, the cost and time production of devices are important variables. These can be addressed with the use of emerging technologies such as 3D printing, MEMS or Microfluidics as have all these benefits.
Acknowledgments
The author would like to thank the research group alumni and current members; Erasmus+ students, research visitors, PhD students, and postdoctoral researchers. The author thanks also Queen’s University Belfast (QUB) and all the funders that have supported the lab research during all these years.
Declaration of interest
The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.