2023 - A Coruña - Spain

PAGE 2023: Drug/Disease Modelling - Other Topics
Aude Coumau

Population pharmacokinetic modelling to characterize (es)citalopram exposure in a large cohort of psychiatric patients

Aude Coumau123, Chantal Csajka123, C.B Eap1234, Monia Guidi125

1Centre for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. 2Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Geneva, Switzerland. 3School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland. 4Unit of Pharmacogenetics and Clinical Psychopharmacology, Center of Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland. 5Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Objectives: Citalopram is the racemic combination of R and S-citalopram (escitalopram), the latter being the active form. Both enantiomers are mainly metabolized by CYP2C19 (≈37%) and to a minor extent by CYP3A4 (≈35%) and CYP2D6 (≈28%) (1). Citalopram and escitalopram are widely prescribed for depression with or without anxiety (2). About 30-50% of patients suffering from depression do not respond properly to their antidepressant treatment (3). In 2018, a study found a relationship between CYP2C19 genotype, escitalopram exposure and treatment failure in a large cohort of patients (4).

The objective of this study was to characterize the pharmacokinetics (PK) of escitalopram in a large cohort of psychiatric patients, to quantify the impact of CYP2C19 polymorphisms and identify other sources of variability.

Methods: The analysis was performed on steady-state escitalopram plasma concentrations collected in 1744 patients enrolled in an ongoing pharmacogenetic study (PsyMetab) (5) conducted at the Departments of Psychiatry of the Lausanne and of the Geneva University Hospitals and in a private mental health care center (Les Toises; Lausanne, Switzerland) or included in the clinical follow-up study (PsyClin) at the Department of Psychiatry of the Lausanne University Hospital. The population PK (popPK) analyses were performed using the NONMEM program. At first, a base popPK model was built to describe the typical concentration-time profile and the variability in the psychiatric population comparing models of increasing complexity. Due to the paucity of data within a few hours after drug administration, the absorption constant rate (ka) was fixed at 0.8 h-1 according to the literature (6, 7). Second, the effect of covariates, namely age, sex and bodyweight, were investigated on clearance (CL). Finally, a sub-analysis on CYP2C19 genotyped patients tested the influence of genetics (*1, *2, *3 and *17 alleles) on escitalopram PK. Five phenotypic groups (poor metabolizers (PM), intermediate metabolizers (IM), normal metabolizers (NM), rapid metabolizers (RM) and ultra-rapid metabolizers (UM)) were predicted using genetics.

Results: A total of 2201 escitalopram concentrations (median (range) of 1 (1-22) blood samples per patient) were available for the analysis. The median (range) escitalopram maintenance dose was 20 mg (4 - 60 mg) once daily. A one-compartment model with first-order absorption and elimination best described the escitalopram PK. The base model typical parameter estimates with interindividual variability (IIV, CV%) were: CL, 17.4 L/h (65 %); volume of distribution, 2410 L and ka, 0.8h-1. None of the studied covariates showed any significant effect on CL.

The reduced model conducted on CYP2C19 genotyped patients (n=328) showed an influence of CYP2C19 polymorphisms on CL. Analyses of the influence of each of the five genetic groups indicated a CL of 12.6 L/h in PM (n=9), of 17 L/h in IM (n=99), of 22.4 L/h in NM (n=133), of 22.1 L/h in RM (n=77) and of 19.8 L/h in UM (n=10). No statistical difference was observed between the NM, RM and UM groups and these data were reduced into a single group. The final model estimated a significant reduction of 43% and 23% in CL between PM (12.6 L/h) and IM (17.1 L/h), respectively, compared to NM, RM and UM (22.2 L/h). The CYP2C19 genetic polymorphism explained 5.4% of the initial observed variance on CL.

Conclusions: Our popPK model conducted in a large cohort of unselected psychiatric patients is in line with previously published models developed on psychiatric or non-psychiatric patients (6, 8, 9). This analysis confirms the high interpatient variability in escitalopram concentrations described in previous studies (9, 10) and the strong influence of CYP2C19 polymorphism on its elimination (4, 9). As observed in a previous study, this analysis did not show an influence of age, sex and weight on escitalopram CL (10), which is in contradiction with the findings of another study showing an influence of age and weight (9). Despite the wide recommended concentration targets for this drug (11), some poor metabolizer patients might be overdosed in case of high dosage regimens and are thus at higher risk of therapeutic failure. Our results support the recommendation of a 50% dosage reduction in poor metabolizer (12).



References:

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  2. Lindsley CW. The top prescription drugs of 2011 in the United States: antipsychotics and antidepressants once again lead CNS therapeutics. ACS Chem Neurosci. 2012;3(8):630-1.
  3. Thase ME, Haight BR, Richard N, Rockett CB, Mitton M, Modell JG, et al. Remission rates following antidepressant therapy with bupropion or selective serotonin reuptake inhibitors: a meta-analysis of original data from 7 randomized controlled trials. J Clin Psychiatry. 2005;66(8):974-81.
  4. Jukić MM, Haslemo T, Molden E, Ingelman-Sundberg M. Impact of CYP2C19 Genotype on Escitalopram Exposure and Therapeutic Failure: A Retrospective Study Based on 2,087 Patients. Am J Psychiatry. 2018;175(5):463-70.
  5. Dubath C, Delacrétaz A, Glatard A, Vollenweider P, Preisig M, Richard-Lepouriel H, et al. Evaluation of Cardiometabolic Risk in a Large Psychiatric Cohort and Comparison With a Population-Based Sample in Switzerland. J Clin Psychiatry. 2020;81(3).
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  7. Søgaard B, Mengel H, Rao N, Larsen F. The pharmacokinetics of escitalopram after oral and intravenous administration of single and multiple doses to healthy subjects. J Clin Pharmacol. 2005;45(12):1400-6.
  8. Liu S, Xiao T, Huang S, Li X, Kong W, Yang Y, et al. Population pharmacokinetics model for escitalopram in Chinese psychiatric patients: effect of CYP2C19 and age. Front Pharmacol. 2022;13:964758.
  9. Jin Y, Pollock BG, Frank E, Cassano GB, Rucci P, Müller DJ, et al. Effect of age, weight, and CYP2C19 genotype on escitalopram exposure. J Clin Pharmacol. 2010;50(1):62-72.
  10. Courlet P, Guidi M, Glatard A, Alves Saldanha S, Cavassini M, Buclin T, et al. Escitalopram population pharmacokinetics in people living with human immunodeficiency virus and in the psychiatric population: Drug-drug interactions and probability of target attainment. Br J Clin Pharmacol. 2019;85(9):2022-32.
  11. Hiemke C, Bergemann N, Clement HW, Conca A, Deckert J, Domschke K, et al. Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology: Update 2017. Pharmacopsychiatry. 2018;51(1-02):9-62.
  12. PharmGKB. Annotation of CPIC Guideline for citalopram,escitalopram and CYP2C19 2023 [Available from: https://www.pharmgkb.org/chemical/PA10074/guidelineAnnotation/PA166127638.

Reference: PAGE 31 (2023) Abstr 10338 [www.page-meeting.org/?abstract=10338]
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