Lack of effect of a single dose of ketoconazole on the pharmacokinetics of citalopram

Escitalopram Personalized Dosing: A Population Pharmacokinetics Repository Method

Escitalopram (SCIT) represents a first-line antidepressant and antianxiety medication. Pharmacokinetic studies of SCIT have demonstrated considerable interindividual variability, emphasizing the need for personalized dosing. Accordingly, we aimed to create a repository of parametric population pharmacokinetic (PPK) models of SCIT to facilitate model-informed precision dosing. In November 2022, we searched PubMed, Embase, and Web of Science for published PPK models and identified eight models. All the structural models reported in the literature were either one- or two-compartment models. In order to investigate the variances in model performance, the parameters of all PPK models were derived from the literature published. A representative virtual population, characterized by an age of 30, a body weight of 70 kg, and a BMI of 23 kg/m2, was generated for the purpose of replicating these models. To accomplish this, the rxode2 package in the R programming language was employed. Subsequently, we compared simulated concentration-time profiles and evaluated the impact of covariates on clearance. The most significant covariates were CYP2C19 phenotype, weight, and age, indicating that dosing regimens should be tailored accordingly. Additionally, among Chinese psychiatric patients, SCIT showed nearly double the exposure compared to other populations, specifically when considering the same CYP2C19 population restriction, which is a knowledge gap that needs further investigation. Furthermore, this repository of parametric PPK models for SCIT has a wide range of potential applications, like design miss or delay dose remedy strategies and external PPK model validation.

Drug Interactions of Psychiatric and COVID-19 Medications

INTRODUCTION

Coronavirus disease 2019 (COVID-19) has become a pandemic with 1771514 cases identified in the world and 70029 cases in Iran until April 12, 2020. The co-prescription of psychotropics with COVID-19 medication is not uncommon. Healthcare providers should be familiar with many Potential Drug-Drug Interactions (DDIs) between COVID-19 therapeutic agents and psychotropic drugs based on cytochrome P450 metabolism. This review comprehensively summarizes the current literature on DDIs between antiretroviral drugs and chloroquine/hydroxychloroquine, and psychotropics, including antidepressants, antipsychotics, mood stabilizers, and anxiolytics.

METHODS

Medical databases, including Google Scholar, PubMed, Web of Science, and Scopus were searched to identify studies in English with keywords related to psychiatric disorders, medications used in the treatment of psychiatric disorders and COVID-19 medications.

RESULTS

There is a great potential for DDIs between psychiatric and COVID-19 medications ranging from interactions that are not clinically apparent (minor) to those that produce life-threatening adverse drug reactions, or loss of treatment efficacy. The majority of interactions are pharmacokinetic interactions via the cytochrome P450 enzyme system.

CONCLUSION

DDIs are a major concern in the comorbidity of psychiatric disorders and COVID-19 infection resulting in the alteration of expected therapeutic outcomes. The risk of toxicity or lack of efficacy may occur due to a higher or lower plasma concentration of medications. However, psychiatric medication can be safely used in combination with COVID-19 pharmacotherapy with either a wise selection of medication with the least possibility of interaction or careful patient monitoring and management.

Escitalopram population pharmacokinetics in people living with human immunodeficiency virus and in the psychiatric population: Drug-drug interactions and probability of target attainment

AIMS

The aims of this study were to characterize escitalopram pharmacokinetic profile, to identify factors influencing drug exposure, notably drug-drug interactions with antiretrovirals, and to simulate expected exposure under standard dosage regimen.

METHODS

A population pharmacokinetic analysis was performed using NONMEM. A total of 159 plasma concentration measurements were obtained from 39 human immunodeficiency virus (HIV)-infected and 71 uninfected psychiatric patients. The influence of age, weight, sex, HIV and psychiatric cohorts, racemic citalopram treatment, and comedications on oral clearance was examined. Simulations served to calculate the percentage of patients expected to be under- or over-exposed, considering established therapeutic targets (15-80 ng/mL).

RESULTS

A 1-compartment model with first-order absorption and elimination described the data adequately. The average escitalopram clearance and volume of distribution were 23.1 L/h (interindividual variability 51%), and 920 L, respectively. Escitalopram disposition did not differ between HIV-infected and uninfected patients, and was not affected by antiretroviral treatments. Coadministration of at least 1 proton-pump inhibitor (CYP2C19 inhibitor) modestly influenced escitalopram elimination (clearance decreased by 19%), with limited clinical relevance. Model-based simulations showed that, under a standard regimen of 10 mg once daily, a significant proportion of patients (56%) might be under-exposed.

CONCLUSION

The variability in escitalopram disposition is large and poorly explained by demographic, clinical and environmental covariates, thus suggesting a role for dosage individualization based on therapeutic drug monitoring in case of poor clinical response. Escitalopram disposition is modestly impacted by comedications and therefore no a priori dosage adjustments are needed in patients receiving antiretroviral treatments, including boosted regimens.

Drug-drug interactions and clinical considerations with co-administration of antiretrovirals and psychotropic drugs

Psychotropic medications are frequently co-prescribed with antiretroviral therapy (ART), owing to a high prevalence of psychiatric illness within the population living with HIV, as well as a 7-fold increased risk of HIV infection among patients with psychiatric illness. While ART has been notoriously associated with a multitude of pharmacokinetic drug interactions involving the cytochrome P450 enzyme system, the magnitude and clinical impact of these interactions with psychotropics may range from negligible effects on plasma concentrations to life-threatening torsades de pointes or respiratory depression. This comprehensive review summarizes the currently available information regarding drug-drug interactions between antiretrovirals and pharmacologic agents utilized in the treatment of psychiatric disorders-antidepressants, stimulants, antipsychotics, anxiolytics, mood stabilizers, and treatments for opioid use disorder and alcohol use disorder-and provides recommendations for their management. Additionally, overlapping toxicities between antiretrovirals and the psychotropic classes are highlighted. Knowledge of the interaction and adverse effect potential of specific antiretrovirals and psychotropics will allow clinicians to make informed prescribing decisions to better promote the health and wellness of this high-risk population.

Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations

AIMS

Citalopram (CT) and escitalopram (S-CT) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder (MDD). We applied a genome-wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S-CT and their metabolites in MDD patients treated with CT or S-CT.

METHODS

Our genome-wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within-subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single-nucleotide polymorphisms (SNPs) were modelled as additive allelic effects.

RESULTS

Genome-wide significant associations were observed for S-CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10(-9) ) and with S-didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10(-16) ), supporting the important role of these cytochrome P450 (CYP) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation.

CONCLUSIONS

In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome-wide association study performed in MDD patients treated with CT or S-CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors.

Inhibitory metabolic drug interactions with newer psychotropic drugs: inclusion in package inserts and influences of concurrence in drug interaction screening software

BACKGROUND

Food and Drug Administration (FDA) regulations mandate that package inserts (PIs) include observed or predicted clinically significant drug-drug interactions (DDIs), as well as the results of pharmacokinetic studies that establish the absence of effect.

OBJECTIVE

To quantify how frequently observed metabolic inhibition DDIs affecting US-marketed psychotropics are present in FDA-approved PIs and what influence the source of DDI information has on agreement between 3 DDI screening programs.

METHODS

The scientific literature and PIs were reviewed to determine all drug pairs for which there was rigorous evidence of a metabolic inhibition interaction or noninteraction. The DDIs were tabulated noting the source of evidence and the strength of agreement over chance. Descriptive statistics were used to examine the influence of source of DDI information on agreement among 3 DDI screening tools. Logistic regression was used to assess the influence of drug class, indication, generic status, regulatory approval date, and magnitude of effect on agreement between the literature and PI as well as agreement among the DDI screening tools.

RESULTS

Thirty percent (13/44) of the metabolic inhibition DDIs affecting newer psychotropics were not mentioned in PIs. Drug class, indication, regulatory approval date, generic status, or magnitude of effect did not appear to be associated with more complete DDI information in PIs. DDIs found exclusively in PIs were 3.25 times more likely to be agreed upon by all 3 DDI screening tools than were those found exclusively in the literature. Generic status was inversely associated with agreement among the DDI screening tools (odds ratio 0.11; 95% CI 0.01 to 0.89).

CONCLUSIONS

The presence in PIs of DDI information for newer psychotropics appears to have a strong influence on agreement among DDI screening tools. Users of DDI screening software should consult more than 1 source when considering interactions involving generic psychotropics.

Age-related changes in antidepressant pharmacokinetics and potential drug-drug interactions: a comparison of evidence-based literature and package insert information

BACKGROUND

Antidepressants are among the most commonly prescribed psychotropic agents for older patients. Little is known about the best source of pharmacotherapy information to consult about key factors necessary to safely prescribe these medications to older patients.

OBJECTIVE

The objective of this study was to synthesize and contrast information in the package insert (PI) with information found in the scientific literature about age-related changes of antidepressants in systemic clearance and potential pharmacokinetic drug-drug interactions (DDIs).

METHODS

A comprehensive search of two databases (MEDLINE and EMBASE from January 1, 1975 to September 30, 2011) with the use of a combination of search terms (antidepressants, pharmacokinetics, and drug interactions) was conducted to identify relevant English language articles. This information was independently reviewed by two researchers and synthesized into tables. These same two researchers examined the most up-to-date PIs for the 26 agents available at the time of the study to abstract quantitative information about age-related decline in systemic clearance and potential DDIs. The agreement between the two information sources was tested with κ statistics.

RESULTS

The literature reported age-related clearance changes for 13 antidepressants, whereas the PIs only had evidence about 4 antidepressants (κ < 0.4). Similarly, the literature identified 45 medications that could potentially interact with a specific antidepressant, whereas the PIs only provided evidence about 12 potential medication-antidepressant DDIs (κ < 0.4).

CONCLUSION

The evidence-based literature compared with PIs is the most complete pharmacotherapy information source about both age-related clearance changes and pharmacokinetic DDIs with antidepressants. Future rigorously designed observational studies are needed to examine the combined risk of antidepressants with age-related decline in clearance and potential DDIs on important health outcomes such as falls and fractures in older patients.

Clinically relevant pharmacokinetic drug interactions with second-generation antidepressants: an update

BACKGROUND

The second-generation antidepressants include selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and other compounds with different mechanisms of action. All second-generation antidepressants are metabolized in the liver by the cytochrome P450 (CYP) enzyme system. Concomitant intake of inhibitors or inducers of the CYP isozymes involved in the biotransformation of specific antidepressants may alter plasma concentrations of these agents, although this effect is unlikely to be associated with clinically relevant interactions. Rather, concern about drug interactions with second-generation antidepressants is based on their in vitro potential to inhibit > or = 1 CYP isozyme.

OBJECTIVE

The goal of this article was to review the current literature on clinically relevant pharmacokinetic drug interactions with second-generation antidepressants.

METHODS

A search of MEDLINE and EMBASE was conducted for original research and review articles published in English between January 1985 and February 2008. Among the search terms were drug interactions, second-generation antidepressants, newer antidepressants, SSRIs, SNRIs, fluoxetine, paroxetine, fluvoxamine, sertraline, citalopram, escitalopram, venlafaxine, duloxetine, mirtazapine, reboxetine, bupropion, nefazodone, pharmacokinetics, drug metabolism, and cytochrome P450. Only articles published in peer-reviewed journals were included, and meeting abstracts were excluded. The reference lists of relevant articles were hand-searched for additional publications.

RESULTS

Second-generation antidepressants differ in their potential for pharmacokinetic drug interactions. Fluoxetine and paroxetine are potent inhibitors of CYP2D6, fluvoxamine markedly inhibits CYP1A2 and CYP2C19, and nefazodone is a substantial inhibitor of CYP3A4. Therefore, clinically relevant interactions may be expected when these antidepressants are coadministered with substrates of the pertinent isozymes, particularly those with a narrow therapeutic index. Duloxetine and bupropion are moderate inhibitors of CYP2D6, and sertraline may cause significant inhibition of this isoform, but only at high doses. Citalopram, escitalopram, venlafaxine, mirtazapine, and reboxetine are weak or negligible inhibitors of CYP isozymes in vitro and are less likely than other second-generation antidepressants to interact with co-administered medications.

CONCLUSIONS

Second-generation antidepressants are not equivalent in their potential for pharmacokinetic drug interactions. Although interactions may be predictable in specific circumstances, use of an antidepressant with a more favorable drug-interaction profile may be justified.

Phenotype-genotype relationship and clinical effects of citalopram in Chinese patients

Although the relationship of CYP2C19 polymorphism to citalopram disposition has been studied in healthy subject, this relationship in combination with dynamic effects (clinical adverse effect of citalopram) has not been well studied in patients. We carried out the present study to investigate the CYP2C19 genotype-phenotype relationship and potentially relate such relationship to the clinical effect (specifically adverse effects) of citalopram in Chinese patients who are known to have relatively high prevalence of poor metabolizers (PMs) of CYP2C19. Fifty-three Chinese adult patients were recruited. One to 2 blood samples at 4 to 24 hours postdose were collected after a minimum of 2 weeks of citalopram administration. The CYP2C19 genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism, and the plasma concentrations of citalopram and desmethylcitalopram were determined by a liquid chromatography-tandem mass spectrometry method. The clinical adverse effects associated with citalopram were assessed according to Toronto Side Effects Scale (TSES). A population pharmacokinetic model was used to analyze the citalopram concentrations. Among 53 patients, 21 were homozygous extensive metabolizers (EMs) (CYP2C19*1/*1), 25 heterozygous EMs (CYP2C19*1/*2 or *1/*3), and 7 PMs (CYP2C19*2/*2 or *2/*3 or *3/*3). The metabolic ratios (plasma concentration of desmethylcitalopram to citalopram) were found to be 0.20 +/- 0.07, 0.15 +/- 0.05, and 0.07 +/- 0.03 in the homozygous EMs, heterozygous EMs, and PMs, respectively (P < 0.001, 1-way analysis of variance). On the basis of the results from our population pharmacokinetic modeling analysis, the citalopram oral clearances in the PMs were 42.9% and 33.3% (both P < 0.05) lower compared with the homozygous and heterozygous EMs, respectively. Statistically significant correlation was observed between the oral clearance and TSES scores in individual patients (rs = -0.37, P = 0.012). The mean TSES score also tended to be higher in PM than EM patients, but the difference was not statistically significant (P = 0.234). The study demonstrated a significant CYP2C19 genotype-phenotype relationship in Chinese patients receiving citalopram treatment. Such a relationship also tended to correlate with the clinical adverse effects of the drug. These results provide important pharmacogenetic implications for citalopram therapy in the Chinese population in whom relatively high frequency of CYP2C19 PM phenotype exists.

The population pharmacokinetics of citalopram after deliberate self-poisoning: a Bayesian approach

Defining the pharmacokinetics of drugs in overdose is complicated. Deliberate self-poisoning is generally impulsive and associated with poor accuracy in dose history. In addition, early blood samples are rarely collected to characterize the whole plasma-concentration time profile and the effect of decontamination on the pharmacokinetics is uncertain. The aim of this study was to explore a fully Bayesian methodology for population pharmacokinetic analysis of data that arose from deliberate self-poisoning with citalopram. Prior information on the pharmacokinetic parameters was elicited from 14 published studies on citalopram when taken in therapeutic doses. The data set included concentration-time data from 53 patients studied after 63 citalopram overdose events (dose range: 20-1700 mg). Activated charcoal was administered between 0.5 and 4 h after 17 overdose events. The clinical investigator graded the veracity of the patients' dosing history on a 5-point ordinal scale. Inclusion of informative priors stabilised the pharmacokinetic model and the population mean values could be estimated well. There were no indications of non-linear clearance after excessive doses. The final model included an estimated uncertainty of the dose amount which in a simulation study was shown to not affect the model's ability to characterise the effects of activated charcoal. The effect of activated charcoal on clearance and bioavailability was pronounced and resulted in a 72% increase and 22% decrease, respectively. These findings suggest charcoal administration is potentially beneficial after citalopram overdose. The methodology explored seems promising for exploring the dose-exposure relationship in the toxicological settings.

An evaluation of the potential for pharmacokinetic interaction between escitalopram and the cytochrome P450 3A4 inhibitor ritonavir

BACKGROUND

Depression often coexists with a number of disease states, and patients with a diagnosis of depression often receive multiple medications. Thus, it is desirable to avoid coadministration of agents that have a potential for drug interactions in these patients. Although escitalopram and its metabolites are weak to negligible inhibitors of the cytochrome P450 (CYP) 3A4 isozyme and are therefore unlikely to affect plasma concentrations of ritonavir (a CYP3A4 substrate and prototype CYP3A4 inhibitor), ritonavir may potentially affect plasma concentrations of escitalopram, as CYP3A4 is partially responsible for conversion of escitalopram to its major metabolite, S-demethylcitalopram (S-DCT).

OBJECTIVES

The aim of this study was to investigate the potential for pharmacokinetic interaction between escitalopram and ritonavir after concomitant administration of a single dose of each in healthy young subjects.

METHODS

In this single-center, randomized, open-label, 3-way crossover study, subjects received each of the following: a single dose of escitalopram 20 mg, a single dose of ritonavir 600 mg, and single doses of both escitalopram 20 mg and ritonavir 600 mg. Blood was collected and plasma was analyzed for the pharmacokinetic parameters (maximum plasma concentration [C(max)], time to C(max) [T(max)], area under the plasma concentration-time curve, plasma elimination half-life, oral clearance, and apparent volume of distribution) of escitalopram, S-DCT, and ritonavir.

RESULTS

Of 21 subjects (11 men, 10 women; mean [SD] age, 28.4 [4.4] years) who were enrolled, 18 completed the study. After concomitant administration of escitalopram and ritonavir, no statistically significant differences were noted in the pharmacokinetics of escitalopram, with the exception of apparent volume of distribution, which was reduced by approximately 10% (P < 0.001). The pharmacokinetics of S-DCT were unaffected by coadministration of ritonavir, with the exception of T(max), which was increased in the presence of ritonavir. The pharmacokinetic parameters of ritonavir were also unaffected by coadministration of escitalopram.

CONCLUSION

In general, no pharmacokinetic interaction was observed between escitalopram and ritonavir in the present study.

Review of pharmacokinetic and pharmacodynamic interaction studies with citalopram

Citalopram is a selective serotonin reuptake inhibitor that is N-demethylated to N-desmethylcitalopram partially by CYP2C19 and partially by CYP3A4 and N-desmethylcitalopram is further N-demethylated by CYP2D6 to the likewise inactive metabolite di-desmethylcitalopram. The two metabolites are not active. The fact that citalopram is metabolised by more than one CYP means that inhibition of its biotransformation by other drugs is less likely. Besides citalopram has a wide margin of safety, so even if there was a considerable change in serum concentration then this would most likely not be of clinical importance. In vitro citalopram does not inhibit CYP or does so only very moderately. A number of studies in healthy subjects and patients have confirmed, that this also holds true in vivo. Thus no change in pharmacokinetics or only very small changes were observed when citalopram was given with CYP1A2 substrates (clozapine and therophylline), CYP2C9 (warfarin), CYP2C19 (imipramine and mephenytoin), CYP2D6 (sparteine, imipramine and amitriptyline) and CYP3A4 (carbamazepine and triazolam). At the pharmacodynamic level there have been a few documented cases of serotonin syndrome with citalopram and moclobemide and buspirone. It is concluded that citalopram is neither the source nor the cause of clinically important drug-drug interactions.

Citalopram: a comprehensive review

Citalopram is a selective serotonin re-uptake inhibitor that has demonstrated antidepressant efficacy in numerous controlled clinical trials. Additional studies have shown that the drug benefits patients with other illnesses that are related in some way to serotonergic dysfunction, including anxiety, panic disorder, obsessive-compulsive disorder, premenstrual dysphoria, alcohol dependence and the behavioural disturbances of dementia. This paper reviews the full spectrum of citalopram's clinical efficacy, as well as its safety and tolerability, in a range of patients.