Literature DB >> 33866355

Pharmacometabonomics: data processing and statistical analysis.

Jianbo Fu1, Ying Zhang1, Jin Liu1, Xichen Lian1, Jing Tang2, Feng Zhu1.   

Abstract

Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Keywords:  analytical technique; data processing; pharmacometabonomics; precision medicine; statistical analysis

Year:  2021        PMID: 33866355     DOI: 10.1093/bib/bbab138

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  3 in total

1.  Pharmacokinetic-Pharmacometabolomic Approach in Early-Phase Clinical Trials: A Way Forward for Targeted Therapy in Type 2 Diabetes.

Authors:  Khim Boon Tee; Luqman Ibrahim; Najihah Mohd Hashim; Mohd Zuwairi Saiman; Zaril Harza Zakaria; Hasniza Zaman Huri
Journal:  Pharmaceutics       Date:  2022-06-15       Impact factor: 6.525

2.  Diagnosis and prognosis of COVID-19 employing analysis of patients' plasma and serum via LC-MS and machine learning.

Authors:  Alexandre de Fátima Cobre; Monica Surek; Dile Pontarolo Stremel; Mariana Millan Fachi; Helena Hiemisch Lobo Borba; Fernanda Stumpf Tonin; Roberto Pontarolo
Journal:  Comput Biol Med       Date:  2022-05-21       Impact factor: 6.698

Review 3.  A Review of Performance Prediction Based on Machine Learning in Materials Science.

Authors:  Ziyang Fu; Weiyi Liu; Chen Huang; Tao Mei
Journal:  Nanomaterials (Basel)       Date:  2022-08-26       Impact factor: 5.719

  3 in total

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