• Expert Rev Clin Pharmacol · Nov 2011

    Review

    Pharmacokinetic-pharmacodynamic modeling in acute and chronic pain: an overview of the recent literature.

    • Christian Martini, Erik Olofsen, Ashraf Yassen, Leon Aarts, and Albert Dahan.
    • Department of Anesthesiology, Leiden University Medical Center, 2330 RC Leiden, The Netherlands.
    • Expert Rev Clin Pharmacol. 2011 Nov 1;4(6):719-28.

    AbstractIn acute and chronic pain, the objective of pharmacokinetic-pharmacodynamic (PKPD) modeling is the development and application of mathematical models to describe and/or predict the time course of the pharmacokinetics (PK) and pharmacodynamics (PD) of analgesic agents and link PK to PD. Performing population PKPD modeling using nonlinear mixed effects modeling allows, apart from the estimation of fixed effects (the PK and PD model estimates), the quantification of random effects as within- and between-subject variability. Effect-compartment models and mechanism-based biophase distribution models that incorporate drug-association and -dissociation kinetics are applied in PKPD modeling of pain treatment. Mechanism-based models enable the quantification of the rate-limiting factors in drug effect owing to drug distribution versus receptor kinetics (since receptor kinetics are nonlinear they are discernable from the linear effect-compartment kinetics). It is a helpful technique in understanding the complex behavior of specific analgesics, such as buprenorphine, but also morphine and its active metabolite morphine-6-glucuronide, especially with respect to the reversal of opioid-induced side effects, most importantly life-threatening respiratory depression. One approach in chronic pain studies is the application of mixture models. Mixture models do not necessarily need to take PK data into account and allow the objective differentiation of measured responses to analgesics into specific response subgroups, and as such, may play an important role in analyzing Phase I and II analgesia studies. Appropriate application of PKPD modeling leads to the improvement of current therapeutics with respect to dose design and outcome, understanding the interaction of analgesics within complex chronic pain disease processes and may play an important role in drug development. In the current article, novel observations using the aforementioned techniques on opioids, NSAIDs, epidural analgesia, ketamine and GABA-ergic drugs in acute and chronic pain are discussed.

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