Pharmacometabonomics and personalized medicine.

Ann Clin Biochem

Medway Metabonomics Research Group, School of Science, University of Greenwich, Chatham Maritime, UK.

Published: November 2013

Background: Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics.

Methods: A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmaco-metabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013.

Results: Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals.

Conclusions: Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.

Download full-text PDF

Source
http://dx.doi.org/10.1177/0004563213497929DOI Listing

Publication Analysis

Top Keywords

personalized medicine
12
pharmacometabonomics
8
drug metabolism
8
drug efficacy
8
efficacy safety
8
drug
7
pharmacometabonomics personalized
4
medicine background
4
background pharmacometabonomics
4
pharmacometabonomics branch
4

Similar Publications

The present study investigated the neuromodulatory substrates of salience processing and its impact on memory encoding and behaviour, with a specific focus on two distinct types of salience: reward and contextual unexpectedness. 46 Participants performed a novel task paradigm modulating these two aspects independently and allowing for investigating their distinct and interactive effects on memory encoding while undergoing high-resolution fMRI. By using advanced image processing techniques tailored to examine midbrain and brainstem nuclei with high precision, our study additionally aimed to elucidate differential activation patterns in subcortical nuclei in response to reward-associated and contextually unexpected stimuli, including distinct pathways involving in particular dopaminergic modulation.

View Article and Find Full Text PDF

Technological advances in clinical individualized medication for cancer therapy: from genes to whole organism.

Per Med

January 2025

Department of Clinical Pharmacy, Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet.

View Article and Find Full Text PDF

Despite significant advancements in achieving high recanalization rates (80%-90%) for large vessel occlusions through mechanical thrombectomy, the issue of "futile recanalization" remains a major clinical challenge. Futile recanalization occurs when over half of patients fail to experience expected symptom improvement after vessel recanalization, often resulting in severe functional impairment or death. Traditionally, this phenomenon has been attributed to inadequate blood flow and reperfusion injury.

View Article and Find Full Text PDF

Metastasis continues to pose a significant challenge in tumor treatment. Evidence indicates that choline dehydrogenase (CHDH) is crucial in tumorigenesis. However, the functional role of CHDH in colorectal cancer (CRC) metastasis remains unreported.

View Article and Find Full Text PDF

Study Question: How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?

Summary Answer: AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.

What Is Known Already: Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!