Towards personalized treatment of pain using a quantitative systems pharmacology approach.

Abstract

Pain is a complex biopsychosocial phenomenon of which the intensity, location and duration depends on various underlying components. Treatment of pain is associated with considerable inter-individual variability, and as such, requires a personalized approach. However, a priori prediction of optimal analgesic treatment for individual patients is still challenging. Another challenge is the assessment and treatment of pain in patients unable to self-report pain. In this mini-review, we first provide a brief overview of the various components underlying pain, and their associated biomarkers. These include clinical, psychosocial, neurophysiological, and biochemical components. We then discuss the use of empirical and mechanism-based pharmacokinetic-pharmacodynamic modelling to support personalized treatment of pain. Finally, we propose how these concepts can be extended to a quantitative systems pharmacology (QSP) approach that integrates the components of clinical pain and treatment response. This integrative approach can support predictions of optimal pharmacotherapy of pain, compared with approaches that focus on single components of pain. Moreover, combination of QSP modelling with state-of-the-art metabolomics approaches may offer unique possibilities to identify novel pain biomarkers. Such biomarkers could support both the personalized treatment of pain and translational drug development of novel analgesic agents. In conclusion, a QSP approach will likely improve our ability to predict pain and treatment response, paving the way for personalized treatment of pain.

• Authors: Sebastiaan C Goulooze, Elke H J Krekels, Monique van Dijk, Dick Tibboel, Piet H van der Graaf, Thomas Hankemeier, Catherijne A J Knibbe, J G Coen van Hasselt
• Journal: European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences (Eur J Pharm Sci) Vol. 109S Pg. S32-S38 (Nov 15 2017) ISSN: 1879-0720 [Electronic] Netherlands
• PMID: 28506867 (Publication Type: Journal Article, Review)
• Copyright: Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Chemical References

• Analgesics
• Biomarkers

Topics

• Analgesics (therapeutic use)
• Biomarkers (metabolism)
• Humans
• Metabolomics (methods)
• Models, Biological
• Pain (drug therapy, metabolism)
• Precision Medicine (methods)