Quantification of the Pharmacodynamic Interaction of Morphine and Gabapentin Using a Response Surface Approach

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

The combination of morphine and gabapentin has shown to be promising for managing postoperative pain but finding the right dose for the combination has proven to be a challenge. The purpose of this study was to quantitatively characterize the pharmacodynamic interaction between the two drugs and to identify the optimal concentration–effect relationship of the combination. Information regarding plasma concentrations and von Frey withdrawal thresholds following incisional surgery on Sprague Dawley rats, after administration of morphine, gabapentin, or their combination was available from published studies. The combined pharmacodynamic effect of morphine and gabapentin was analyzed and linked to drug plasma concentrations via a response surface approach using non-linear mixed-effect modeling. Full reversal of withdrawal thresholds for the pain stimulation to presurgery values was estimated at morphine plasma concentration of 435.1 ng/mL. Co-administration of up to 40 μg/mL of gabapentin led to a reduction of the needed morphine concentration down to 307.5 ng/mL (~ 29% reduction). Combination of concentration ranges of gabapentin between 20 and 40 μg/mL with any morphine concentrations between 100 and 600 ng/mL were found to lead up to 50% increased effect relatively to the effect attained by morphine alone. This study highlights the importance of finding the right combination in multimodal analgesia and demonstrates the usefulness of the response surface approach for the study of pharmacodynamic interactions. The proposed pharmacokinetic–pharmacodynamic model may provide the basis for a rational clinical trial design with the aim to identify the optimal dose combination ratios in humans.

OriginalsprogEngelsk
TidsskriftAAPS Journal
Vol/bind19
Udgave nummer6
Sider (fra-til)1804–1813
Antal sider10
ISSN1550-7416
DOI
StatusUdgivet - 1 nov. 2017

ID: 184286456