Pharmacokinetic variations in cancer patients with liver dysfunction: applications and challenges of pharmacometabolomics

Abstract

Purpose

In cancer patients, pharmacokinetic variations between individuals and within individuals due to impairments in organs' function and other reasons such as genetic polymorphisms represent a major problem in disease management, which can result in unpredictable toxicity and variable antineoplastic effects. Addressing pharmacokinetic variations in cancer patients with liver dysfunction and their implications on anticancer and analgesic drugs, in addition to the use of advanced analytical techniques such as metabolomics and pharmacometabolomics, to monitor altered kinetic and discover metabolic biomarkers during therapeutic intervention will help in understanding and reducing pharmacokinetic variations of drugs in cancer patients as a step forward towards personalised medicine.

Methods

Reviewing published literature addressing and/or related to complications resulting from altered pharmacokinetics (PKs) in cancer patients with liver dysfunction, anticancer and analgesic drugs, evaluating recent advances of pharmacokinetic detection using metabolomics/pharmacometabolomics and the challenges that are currently facing these techniques.

Results

The current situation presents a pressing need to reduce pharmacokinetic variations of drugs in cancer patients. Although most of the omics technologies are not entirely focussed on the study of pharmacokinetic variations and some studies are met with uncertainty, the use of pharmacometabolomics combined with other omics technology such as pharmacogenomics can provide clues to personalised cancer treatments by providing useful information about the cancer patient's response to medical interventions via identification of patients' dependent variables, understanding of correlations between individuals and population PKs, and therapy outcomes to achieve optimum therapeutic effects with minimum toxicity. We also propose an approach for PKs' evaluation using pharmacometabolomics.

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