Ulrich R. Luecht (1), Johanna Weber (1), Wolfgang Scholz (2), Stefanie Brune (2), Georg Hempel (1)
(1) University of Muenster, Department for Pharmaceutical and Medicinal Chemistry, Germany (2) ePrax GmbH Munich/Luedenscheid, Germany
Introduction: In clinical and ambulatory care, drugs are often combined to improve the efficacy of the therapy. Especially the combination of psychopharmaceutical drugs can increase the success of the antidepressant or antipsychotic treatment. The problem of adding a drug is that it might influence the other medication, causing an increase or decrease of the others’ plasma concentrations. Particularly the inhibition of enzymes like cytochrome P450 (CYP) oxygenases provokes higher risks for toxic side effects. By using physiologically based pharmacokinetic modelling the possible extent of an interaction can be predicted. These model approaches may state if a dose reduction or a substitution of a drug is useful to decrease the potential risk for negative side effects.
Objectives:
- Creation of a drug-drug interaction physiologically based pharmacokinetic model for pharmacokinetic interaction between mirtazapine and venlafaxine
- Comparison of the model’s predicted area under the curve (AUC) to the results of the SCHOLZ Databank’s multi drug drug interaction (MDDI) tool
- Investigations to evaluate the utility of dose adjustments or substitutions
Methods: For the PBPK-model, samples were collected in the context of a therapeutic drug monitoring (TDM) study [1]. Whole blood was collected from 82 elderly patients via dried blood spot method. The blood concentrations of four psychopharmaceutics – the tetracyclic antidepressant mirtazapine, the atypical antipsychotic risperidone and the selective serotonine reuptake inhibitor citalopram and its eutomer escitalopram – were measured by using liquid chromatography and mass spectrometry detection.
The subjects’ medication plans were analyzed using the software SCHOLZ Databank. This software is a tool to execute medication analyses and to detect medication problems like cumulative side effects or drug interactions. SCHOLZ Databank allows the optimization of the patients’ therapy including substitutions of comparable drugs or dose adjustments [2]. The most frequently displayed pharmacokinetic interaction was between mirtazapine as a substrate of CYP 2D6 and the noradrenaline and serotonine reuptake inhibitor venlafaxine, which inhibits [3] mirtazapine’s metabolism (n=14).
Models for mirtazapine and venlafaxine are created based on their bio- and physicochemical properties using PK-Sim® (BayerAG, Leverkusen, Germany). Evaluation of the models was done by comparison to literature values [4, 5]. Afterwards, both models are combined in an interaction simulation. Plasma concentrations from TDM are used to evaluate the predictability of the interaction model.
Results: If mirtazapine is combined with venlafaxine, there is no measurable change in the AUC of mirtazapine’s plasma concentration curve in the PBPK-interaction model. So, the model, which is validated with TDM data, shows no clinically relevant interaction. SCHOLZ Databank’s MDDI calculator predicts an 8-% higher exposure which is not clinically relevant as well.
Conclusion: In order to better evaluate clinical relevance of DDI there is a need for more clinical research. In addition, more clinical data in the routine setting should be collected including for example renal function and pharmacogenetic data.
References
[1] Weber J, Oberfeld S, Bonse A et al. (2017) Validation of a dried blood spot method for therapeutic drug monitoring of citalopram, mirtazapine and risperidone and its active metabolite 9-hydroxyrisperidone using HPLC-MS. J Pharm Biomed Anal 140: 347–354.
[2] Scholz WU (2016) Zur Pharmakokinetik von Arzneimitteln bei multiplen Interaktionen – Theoretische Überlegungen und praktische Umsetzung. Krankenhauspharmazie 37:497-505.
[3] Ball SE, Ahern D, Scatina J et al. (1997) Venlafaxine: In vitro inhibition of CYP2D6 dependent imipramine and desipramine metabolism; comparative studies with selected SSRIs, and effects on human hepatic CYP3A4, CYP2C9 and CYP1A2. Br J Clin Pharmacol 43(6): 619–626.
[4] Timmer CJ, Sitsen JM, Delbressine LP (2000) Clinical pharmacokinetics of mirtazapine. Clin Pharmacokinet 38(6): 461–474.
[5] Troy SM, Parker VP, Hicks et al. (1997) Pharmacokinetics and Effect of Food on The Bioavailability of Orally Administered Venlafaxine. Journal of clinical pharmacology 37: 954–961.
Reference: PAGE 28 (2019) Abstr 8845 [www.page-meeting.org/?abstract=8845]
Poster: Drug/Disease Modelling - Absorption & PBPK