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10.1016_j.biopha.2023.114784.pdf (5.52 MB)

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology

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submitted on 2024-01-18, 07:18 and posted on 2024-01-18, 12:36 authored by Ajay Vikram Singh, Vaisali Chandrasekar, Namuna Paudel, Peter Laux, Andreas Luch, Donato Gemmati, Veronica Tisato, Kirti S. Prabhu, Shahab Uddin, Sarada Prasad Dakua

More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, the promotion of non-animal testing has fueled the computational toxicogenomics as a pivotal part of the next-gen risk assessment paradigm. Artificial Intelligence (AI) has the potential to provid new ways analyzing the patient data and making predictions about treatment outcomes or toxicity. As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. AI can process and integrate a multitude of data including genome data, patient records, clinical data and identify patterns to derive predictive models anticipating clinical outcomes and assessing the risk of any personalized medicine approaches. In this article, we have studied the current trends and future perspectives in personalized medicine & toxicology, the role of toxicogenomics in connecting the two fields, and the impact of AI on personalized medicine & toxicology. In this work, we also study the key challenges and limitations in personalized medicine, toxicogenomics, and AI in order to fully realize their potential.

Other Information

Published in: Biomedicine & Pharmacotherapy
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.biopha.2023.114784

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Medical Corporation
  • Hamad General Hospital - HMC
  • Academic Health System - HMC
  • Interim Translational Research Institute - HMC