Toxicity Profile, Pharmacokinetic, and Drug-Drug Interaction Study of Citalopram and Sertraline Following Oral Delivery in Rat: An LC-MS/MS Method for the Simultaneous Determination in Plasma

Investigation of Pharmacokinetic and Pharmacodynamic Interactions between Citalopram and Duloxetine: An Integrated Analytical, Computational, Behavioral, and Biochemical Approach

Despite the prevalent utilization of antidepressant combinations in clinical settings, concerns persist regarding heightened side effects and potential drug-drug interactions (DDI). In response, this study investigates the interaction between citalopram (CIT) and duloxetine (DUL) using a multifaceted approach encompassing analytical, computational, behavioral, and biochemical techniques. Notably, the absence of published analytical methods tailored for studying antidepressant interactions underscores the novelty of our endeavor. We present the development and validation of a robust and sensitive assay, coupling liquid chromatography-tandem mass spectrometry. This method facilitates the simultaneous determination of DUL, a serotonin-norepinephrine reuptake inhibitor (SNRI), and CIT, a selective serotonin reuptake inhibitor (SSRI), in rat plasma following oral administration. Successful pharmacokinetic and DDI monitoring of DUL and CIT in rat plasma post a single oral dose of 120 mg/kg is achieved using this method. Our findings reveal DUL's influence on CIT's pharmacokinetic parameters, resulting in an increased area under the concentration-time curve (AUC) by 4-fold, peak plasma concentrations (C max) by 20-fold, maximum plasma concentration-time (T max) by 4-fold, and oral clearance (Cl/F) of CIT by 1.3-fold upon coadministration. Furthermore, our investigation explores the behavioral and biochemical ramifications of coadministering CIT and DUL through the sucrose preference test (SPT), forced swimming test (FST), and enzyme-linked immunosorbent assay (ELISA). We observe potential exacerbation of serotonin concentration and serotonin syndrome in rat models. Molecular modeling studies indicate that DUL may competitively inhibit CYP2D6, the principal enzyme responsible for CIT metabolism, as well as P-glycoprotein (P-gp), which extrudes CIT back to the intestinal lumen. These findings emphasize the imperative of further research into potential DDIs in psychiatric patients undergoing chronic treatment with DUL and CIT to mitigate adverse effects and serotonin syndrome.

Recent Advances in Analytical Techniques for Antidepressants Determination in Complex Biological Matrices: A Review

Depression is one of the most prevalent but severe of mental disorders, affecting thousands of individuals across the globe. Depression, in its most extreme form, may result in self-harm and an increased likelihood of suicide. Antidepressant drugs are first-line medications to treat mental disorders. Unfortunately, these medications are also prescribed for other in- and off-label conditions, such as deficit/hyperactivity disorders, attention disorders, migraine, smoking cessation, eating disorders, fibromyalgia, pain, and insomnia. This results in an increase in the use of antidepressant medications, leading to clinical and forensic overdose cases that could be either accidental or deliberate. The findings revealed that people who used antidepressants had a 33% greater chance of dying sooner than expected, compared to those who did not take the medications. Analytical techniques for precisely identifying and detecting antidepressants and their metabolic products in a variety of biological matrices are greatly needed to be developed and made available. Hence, this study attempts to discuss various analytical techniques used to identify and determine antidepressants in various biological matrices, which include urine, blood, oral fluid (saliva), and tissues, which are commonly encountered in clinical and forensic science laboratories.