The Potential of Microphysiological Systems for Artificial Intelligence Assisted Rapid Drug Discovery

Authors

  • Arun Asif Department of Mechatronics Engineering, Jeju National University, Jeju-si, Jeju-do, Republic of Korea, 63243
  • Abdul Rahim BioSpero Inc., Jeju Science Park, Jeju-si, Jeju-do, 63243 Republic of Korea
  • Zaroon Ricky Microbiology Department ,UiT The Arctic University of Norway, Tromso, Norway

Keywords:

Microphysiological Systems, artificial intelligence, drug discovery, mini review, deep learning

Abstract

The continuous evolution of deep learning tools with expanded applications in biology presents a great opportunity to improve drug analysis. The recent emergence of microphysiological tools has revolutionized the field of drug analysis owing to its human mimicking capacity. The convergence of artificial intelligence with automated microphysiological systems (MPS) may open the scope for speed-boosting drug discovery and development. Organ on a chip technology application at large scale will reduce the cost and time for the discovery of lead compounds for yet uncured diseases. The rapidly accumulated data from MPS-based analysis for new drug compounds with their initial indication will help in the elimination of the potentially irrelevant drugs at the earliest stage possible.

Author Biography

Arun Asif, Department of Mechatronics Engineering, Jeju National University, Jeju-si, Jeju-do, Republic of Korea, 63243

 

 

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Published

2022-05-22

How to Cite

Asif, A., Rahim Chethikkattuveli Salih , A., & Ricky, Z. (2022). The Potential of Microphysiological Systems for Artificial Intelligence Assisted Rapid Drug Discovery. Journal of Intelligent Pervasive and Soft Computing, 1(01), 16–19. Retrieved from http://journals.aipspub.com/index.php/jipsc/article/view/5

Issue

Section

Computer Science and Multidisciplinary research