PK-PD model of morphine, pregabalin and their combination to assess the opioid-sparing effect
Monir Bertayli (1,2), Wouter Bakker (2), Geert Jan Groeneveld (2,3), Jeroen Elassaiss-Schaap (1)
(1) PD-value B.V., the Netherlands, (2) Centre for Human Drug Research, the Netherlands, (3) Leiden University Medical Center, the Netherlands
Introduction: Chronic pain (CP) causes major discomfort and is highly prevalent [1]. Opioids are currently the most effective class of analgesics, but lead to a plethora of adverse effects. Therefore there is a strong need for improved treatments. As part of the QSPainRelief consortium our goal is to identify novel analgesic drug combinations that are complementary or synergistic with each other and could be superior to current treatments. To that end a clinical trial was performed to study combining morphine and pregabalin for the treatment of pain. Treatment effect was assessed by multiple nociceptive tests, among which the ‘cold pressor test’ where subjects placed their hand for 2 minutes in a 35°C water bath followed by a 1.0°C bath. A pharmacodynamic (PD) endpoint is the time in seconds from immersion to hand withdrawal from the water bath indicating that the pain is no longer tolerable (pain tolerance threshold, PTT).
Objectives:
-
Describe the clinical trial results by a PK-PD model
-
To determine if the combined treatment effect is antagonistic, additive or synergistic
Methods:
Clinical trial:
Clinical trial design and power analysis based simulations were previously supported by us [2]. Combined treatment effect of morphine and pregabalin was assessed in a double-blind, placebo controlled clinical trial in 12 healthy male and 15 female volunteers. In four identical study periods with 7 days wash-out in-between, subjects (20-64years) received a single oral dose of 300mg pregabalin, 3mg + 7mg morphine as a bolus infused intravenously, a combination of these two (double-dummy) or placebo in randomized order.
Model development:
The effect of morphine and pregabalin on ColdPTT was previously modelled by Dahan et al. [3] and van Esdonk et al. [4]. We took these models as starting point for our modelling process using NONMEM 7.5.1. Pharmacokinetic (PK) interactions, while not expected, was assessed through diagnostic plots to decide on using PK data from the combined treatment for the individual PK models. Between occasion variability (BOV) was examined for both PK and PD models. Model selection was based on objective function value (OFV), diagnostic plots, model stability and relative standard error (RSE), among others.
Results: Morphine PK was best described by a two-compartment model where the M3 method was applied because 24h time points had a significant portion of BLQ measurements. Pregabalin PK was fitted by a two-compartment model with a depot compartment, lag time and allometric scaling on V1, V2, CL and Q. Adding BOV on KA and CL improved the OFV by 117. No PK interactions were apparent in diagnostic plots and thus drug PK data from the combined treatment was used for individual PK model development.
Individual PD models of morphine and pregabalin were described by a turnover model. BOV on the baseline ColdPTT improved the OFV over 100 points for both models. Adding a declining slope of the baseline (acquired from the placebo occasion) further improved description of data.
To describe the combined treatment effect with the three other treatment arms, the individual PD compartments were folded into a single PD compartment with an estimated ColdPTT baseline of 13.98 seconds. A single turnover - kout was estimated for both morphine and pregabalin. Multiple variations were examined to fit the combined treatment effect. Best fit was achieved by modulation of the pregabalin effect when morphine and pregabalin were present within the system. The estimated modulation indicated a 2.1-fold increase of the pregabalin effect with an RSE of 15%. In conclusion, treatment combination of morphine and pregabalin leads to a synergistic analgesic effect with a drop in OFV of 25 points for one additional parameter in this study using nociceptive stimuli in healthy subjects.
No biological conclusions on the mechanism of synergism can be drawn on the basis of these results as modulation of morphine instead of pregabalin gave similar fits.
Conclusions: Both PK and PD models described data adequately. Combining morphine and pregabalin indicated a synergistic analgesic effect on the ColdPTT test associated with a significant improvement of model fit statistics. These results suggest that pain patients could benefit from the combined treatment of pregabalin and morphine, allowing for lower doses of the opioid morphine to achieve the same treatment effect, and therefore to an important reduction in opioid-induced side effects and abuse potential.
References:
[1] Fredheim, O. M. S., et al. "Chronic non‐malignant pain patients report as poor health‐related quality of life as palliative cancer patients." Acta Anaesthesiologica Scandinavica 52.1 (2008): 143-148.
[2] Bertayli, Monir, et al. PAGE 30 (2022) Abstr 10216 [www.page-meeting.org/?abstract=10216]
[3] Dahan, Albert, et al. "Benefit and risk evaluation of biased μ-receptor agonist oliceridine versus morphine." Anesthesiology 133.3 (2020): 559-568.
[4] van Esdonk, Michiel J., et al. "Population Pharmacokinetic/Pharmacodynamic Analysis of Nociceptive Pain Models Following an Oral Pregabalin Dose Administration to Healthy Subjects." CPT: pharmacometrics & systems pharmacology 7.9 (2018): 573-580.
