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Partial Sciatic Nerve Ligation: A Mouse Model of Chronic Neuropathic Pain to Study the Antinociceptive Effect of Novel Therapies
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Potential biomarkers for persistent and neuropathic pain therapy
Marco Sisignano1, Jörn Lötsch1, Michael J Parnham2
1Institute of Clinical Pharmacology, pharmazentrum frankfurt/ZAFES, Goethe - University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany.
Pharmacology & Therapeutics
|February 14, 2019
Summary
Identifying prognostic biomarkers can help personalize pain management. This approach aims to improve treatment efficacy for patients with persistent pain, including neuropathic pain, by predicting optimal pharmacological therapies.
Area of Science:
- Neuroscience
- Pharmacology
- Biomarker Discovery
Background:
- Persistent pain, especially neuropathic pain, impacts millions globally.
- Current analgesic drug response rates are below 50%, necessitating improved treatment strategies.
- Individualized therapy is crucial due to variable patient responses to pain medications.
Purpose of the Study:
- To explore the potential of prognostic biomarkers for predicting optimal pharmacological pain treatment.
- To review recent advancements in identifying and utilizing biomarkers for personalized pain management.
- To discuss the integration of biomarker data with artificial intelligence for tailored pain therapies.
Main Methods:
- Review of recent research on plasma, cerebrospinal fluid (CSF), and genetic biomarkers.
- Inclusion of sensory testing as a diagnostic tool.
- Discussion of machine learning and artificial intelligence (AI) for biomarker data analysis.
Main Results:
- Biomarkers (plasma, CSF, genetic) and sensory tests show promise in predicting treatment response.
- AI and machine learning can integrate diverse biomarker data for personalized therapy recommendations.
- Potential exists for improved patient outcomes through biomarker-guided analgesic selection.
Conclusions:
- Biomarker-based individualized pain therapies offer a promising avenue to enhance treatment efficacy.
- Reliability, clinical utility, and limitations of biomarkers require careful consideration for practical application.
- Future research should focus on validating biomarkers and integrating AI for clinical decision support in pain management.
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