Relative impact of CYP2D6 phenotype, physiological changes and hepatic extraction ratio on drug exposure during pregnancy
Karen Rowland Yeo
Certara UK Ltd
Title: Relative impact of CYP2D6 phenotype, physiological changes and hepatic extraction ratio on drug exposure during pregnancy
Author: Karen Rowland Yeo1, Eva Gil-Bergland2, Paola Coppola3
Institution: Certara UK Ltd (Simcyp Division) (1), Certara NL Ltd (2), Certara Italy Srl (3)
Introduction: Pregnancy and associated physiological changes can affect the pharmacokinetics (PK) of selective serotonin reuptake inhibitors (SSRIs) which are first-line treatment for depression. During pregnancy, SSRIs exhibit extensive PK variability that may influence their tolerability and efficacy [1]. The risk of discontinuing antidepressants during pregnancy is nearly 4-fold higher in CYP2D6 slow metabolizers (poor or intermediate metabolizers; PM or IMs) than those with a faster metabolism rate (normal or ultrarapid metabolizers; EM or UM) [2]. On the other hand, compared with slow metabolizers, a significantly higher proportion of women in the fast metabolizer group had depressive symptoms in the first trimester [2]. Physiologically based pharmacokinetic (PBPK) modelling has been used to predict changes in exposure of fluvoxamine [3] and fluoxetine [4] during pregnancy throughout gestation to term according to CYP2D6 phenotype. Limited clinical data were available. For drugs with significant first pass metabolism, CYP2D6-mediated changes are likely to be more pronounced than for low extraction drugs. Here we demonstrate this using the CYP2D6 probe substrate metoprolol [5]; clinical data are available for the drug in pregnant and non-pregnant women following intravenous (IV) and oral administration [6].
Objectives:
- To elucidate the relative impact of CYP2D6 phenotype, pregnancy-related changes and first pass metabolism on metoprolol exposure during gestation
Methods: Simulations were run using the Simcyp Simulator (V23) to estimate metoprolol clearance values and bioavailability in pregnant and non-pregnant women and were verified using clinical data [6]. Thereafter, simulations were run to estimate metoprolol clearances during early and mid to late pregnancy for CYP2D6 UM, EM and IM subjects. Where possible, predicted values were compared against observed data [7].
Results: Following IV and oral administration, the ratio of predicted clearances in pregnant (37 weeks) to non-pregnant women were 2.60 and 6.88, respectively; observed values were 2.64 and 6.93, respectively. Predicted changes in first pass metabolism (2.64-fold increase) or decrease in bioavailability (0.38 to 0.14) during pregnancy, which are consistent with observed data, are significant. In CYP2D6 EM subjects, predicted clearances (L/h/kg) were within 1.25-fold of observed data in mid to late pregnancy and post-partum. Predicted clearance ratios for UM/IM subjects increased from 4.61 to 5.65 over the gestational period and for EM/IM subjects from 2.61 to 2.83.
Conclusion: These results demonstrate that PBPK modelling can be used to elucidate key factors contributing to the variability in exposure of CYP2D6 drugs during pregnancy. In addition, for drugs with similar PK characteristics (fluvoxamine and fluoxetine), it may be possible to use the relative CL changes generated here for metoprolol to describe the PK of the drug in pregnant women of differing CYP2D6 phenotypes.
References:
[1] Poweleit EA et al. Front Pharmacol. 2022 Feb 25;13:833217. doi: 10.3389.
[2] Bérard A et al. Front Pharmacol. 2017 Jul 17;8:402. doi: 10.3389/fphar.2017.00402. PMID: 28769788; PMCID: PMC5511844.
[3] Burhanuddin K, Badhan R. Metabolites. 2022 Dec 16;12(12):1281. doi: 10.3390/metabo12121281. PMID: 36557319; PMCID: PMC9782298.
[4] Coppola P et al. J Clin Pharmacol. 2023 Jun;63 Suppl 1:S62-S80. doi: 10.1002/jcph.2266. PMID: 37317504.
[5] Abduljalil K et al. J Pharmacokinet Pharmacodyn. 2020 Aug;47(4):361-383. doi: 10.1007/s10928-020-09711-2. Epub 2020 Aug 25. PMID: 32840724.
[6] Högstedt S et al. Eur J Clin Pharmacol. 1983;24(2):217-20. doi: 10.1007/BF00613820. PMID: 6840170.
[7] Ryu RJ et al. J Clin Pharmacol. 2016 May;56(5):581-9. doi: 10.1002/jcph.631. Epub 2015 Dec 4. PMID: 26461463; PMCID: PMC5564514.