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RationaleTreatments with the serotonergic psychedelic psilocybin are being investigated for multiple neuropsychiatric disorders. Because many patients with these disorders use selective serotonin reuptake inhibitors (SSRIs), understanding interactions between psilocybin and SSRIs is critical for evaluating the safety, efficacy, and scalability of psilocybin-based treatments. Current knowledge about these interactions is limited, as most clinical psilocybin research has prohibited concomittant SSRI use.ObjectivesWe aimed to explore potential interactions between psilocybin and SSRIs by characterizing peoples' real-world experiences using psilocybin mushrooms and SSRIs together.MethodsWe conducted a systematic search of Reddit for posts describing psilocybin mushroom and SSRI coadministration. We identified 443 eligible posts and applied qualitative content analysis to each.Results8% of posts reported negative physical or psychological effects resulting from coadministration. These included 13 reports that may reflect serotonin toxicity, and 1 concerning for a psychotic/manic episode. 54% of posts described reduced intensity of the acute psilocybin experience, but 39% reported unchanged intensity with SSRI coadministration.ConclusionsPsilocybin's interactions with SSRIs are likely complex and may depend on multiple factors. Prospective studies are needed to evaluate whether psilocybin treatments are reliably safe and effective in the setting of SSRI use.

Ruxolitinib (RUX), a Janus kinase 2 (JAK2) inhibitor, and lenalidomide (LEN), an immunomodulatory agent, have recently been proposed as a combined treatment for myelofibrosis (MF). This combination has demonstrated improved efficacy, safety, and tolerability compared to monotherapy. To further refine these findings, an efficient analytical tool is needed to simultaneously determine RUX and LEN concentrations in blood plasma. This tool would enable the study of their pharmacokinetics, drug-drug interactions, and therapeutic monitoring during MF therapy. Unfortunately, such a method has not been existed in the literature. This study presents the first HPLC method with UV detection for the simultaneous quantitation of RUX and LEN in plasma. The method was validated according to the ICH guidelines for bioanalytical method validation. It exhibited linearity in the concentration ranges of 10 to 3150 ng mL− 1 for RUX and 80 to 5200 ng mL− 1 for LEN. The limits of quantitation were determined to be 25 and 90 ng mL− 1 for RUX and LEN, respectively. All other validation parameters were satisfactory. The HPLC-UV method was successfully employed to study the pharmacokinetics and drug-drug interactions of RUX and LEN in rats following oral administration of single doses. The results demonstrated that the pharmacokinetics of both drugs were changed substantially by their coadministration. LEN exhibited synergistic effects on the maximum plasma concentration (Cmax) and total bioavailability of RUX, meanwhile it exhibited diminishing effect on the values of volume of distribution (Vd) and clearance (CL). Additionally, RUX decreased the Cmax and total bioavailability of LEN, meanwhile it increased its Vd and CL. These data suggest that the use of RUX, as a combination with LEN, is a better therapeutic approach for MF, compared with RUX as a monotherapy. The effects of LEN on the pharmacokinetics of RUX should be considered and can be useful in determining the appropriate RUX dosage and dosing regimen to achieve the desired therapeutic effect when used as a combination therapy with LEN. The method's environmental friendliness was confirmed through three comprehensive tools. This method represents a valuable tool for determining the appropriate dosage and dosing regimen of RUX in combination therapy with LEN to achieve the desired therapeutic effect. Furthermore, it can aid in predicting drug distribution in different patients and assessing the drug accumulation or insufficient drug levels in specific body compartments. [ABSTRACT FROM AUTHOR]

Background: Bleeding complications following intramuscular (IM) injections are generally considered rare with reported incidence of 0.06%. However, evidence on safety of IM injections among anticoagulated hospitalized patients is lacking. The objective of the current study was to examine the incidence of injection site bleeding complications following IM injection among anticoagulated hospitalized patients. Methods: A retrospective comparative study comprised of all hospitalized patients ≥ 18 years old that were treated with ≥ 1 IM injection between 2009 and 2019 in a large tertiary medical center. Bleeding complications were defined as focal hematoma, local bleeding, intramuscular bleeding or compartment syndrome. Each case with IM injection was searched for ICD9 codes (e.g., hematoma, hemorrhage or compartment syndrome) and for indirect evidence suggestive of potential bleeding: hemoglobin drop ≥ 2 g/dl, AST or CPK increase, packed red blood cell transfusion, or abrupt cessation of the anticoagulation. These case were then verified for true injection-site bleeding by natural language processing model and manual review of the electronic medical record. Results: A total of 71,710 patients were treated with 236,406 IM injections. Mean age 53 (± 22) and 63% were females. Concomitant anticoagulation (Heparins: 90.3%, warfarin: 6.8% and DOACs: 4.7%) occurred in 40,819 IM injections (8189 patients). Suspected bleeding complications at the IM injection site were identified among 7,111 patients following 23,089 IM injections, the majority were unrelated to the IM injection-site (e.g., gastrointestinal bleeding, retroperitoneal, etc.). Two cases were verified as true injection site bleeding complication, both in the anticoagulated group (2/8189, 0.02%). Conclusion: Bleeding complications at site of IM injections among anticoagulated hospitalized patients are rare, and their risk is probably not higher compared to patients without anticoagulation. [ABSTRACT FROM AUTHOR]

Objective: Most patients with alcohol use disorder (AUD) regularly take medication. Alcohol interacts negatively with many commonly prescribed medications. Little is known about whether the risk of potential alcohol-medication and drug-drug interactions increases or decreases in patients with AUD during inpatient withdrawal treatment. The aim of our study was to determine the prevalence and characteristics of potential alcohol-medication and drug-drug interactions in patients with AUD before and after withdrawal treatment in an addiction unit. Design: Prospective monocentric quasi-experimental pre-post study. Methods: Medication records before and after withdrawal treatment were analyzed and screened for potential alcohol-medication (pAMI) and drug-drug interactions (pDDI) using the drugs.com classification and the AiDKlinik® electronic interaction program, respectively. Results: We enrolled 153 patients with AUD who were treated in an addiction unit of a university hospital in Germany. Of these, 67.3% experienced at least one pAMI before and 91.5% after withdrawal treatment. In total, there were 278 pAMIs classified as "mild," "moderate," or "severe" before and 370 pAMIs after withdrawal treatment. Additionally, there were 76 pDDIs classified as "moderate," "severe," or "contraindicated combinations" both before and after withdrawal treatment. Conclusion: The risk of exposure to pAMIs and pDDIs increases during inpatient withdrawal treatment in patients with AUD. Improvements in the quality of prescribing should particularly focus on the use of antihypertensives and opioids. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusion Clomipramine (CLOMI) has shown effectiveness in treating premature ejaculation but is linked to erectile dysfunction and reduced libido. Yohimbine (YOH), by contrast, is effective in treating erectile dysfunction and may improve libido. Combining CLOMI and YOH could potentially leverage the benefits of both drugs. This study aimed to investigate the interactions between these drugs and to evaluate their safety profile.A prospective, open‐labelled, single‐centre, pharmacokinetic (PK) drug–drug interaction study was performed in 15 healthy male subjects. Single‐dose and steady‐state PK were investigated using noncompartmental analysis after mono‐ and combination therapy of the 2 orally applied drugs. Plasma sampling was performed at baseline, 0.5 (YOH), 1, 1.5 (YOH), 2, 3, 4, 5, 6, 8, 12 and 24 h (CLOMI). Differences in the area under the curve after multiple dosing (MD) were determined using an equivalence boundary of 80–125%.The geometric mean ratio of the area under the curve up to 12 h for MD CLOMI (combination vs. monotherapy) was 112% (90% confidence interval: 104–120%), whereas for MD YOH this ratio was 137% (90% confidence interval: 112–168%). The study drugs were safe and well tolerated as mono‐ and combination therapy, with no major adverse events reported.A PK assessment of clomipramine and yohimbine indicated a clinically significant drug–drug interaction for MD YOH in combination with CLOMI. This might be explained by competitive, CLOMI‐related inhibition of YOH metabolism, probably mediated by cytochrome P450 2D6. However, according to European Medicines Agency guidelines, the effect can be classified as interaction absent (<1,25 fold) or minor (>1.25–<2‐fold). Given the complimentary mechanisms of action and the favourable safety profiles, the findings pave the way for future efficacy studies. [ABSTRACT FROM AUTHOR]

This study introduces a deep learning framework based on SMILES representations of chemical structures to predict drug–drug interactions (DDIs). The model extracts Morgan fingerprints and key molecular descriptors, transforming them into raw graphical features for input into a modified ResNet18 architecture. The deep residual network, enhanced with regularization techniques, efficiently addresses training issues such as gradient vanishing and exploding, resulting in superior predictive performance. Experimental results show that StructNet-DDI achieved an AUC of 99.7%, an accuracy of 94.4%, and an AUPR of 99.9%, demonstrating the model's effectiveness and reliability. These findings highlight that StructNet-DDI can effectively extract crucial features from molecular structures, offering a simple yet robust tool for DDI prediction. [ABSTRACT FROM AUTHOR]

Background: Drug-drug interactions (DDIs) can result in unexpected pharmacological outcomes, including adverse drug events, which are crucial for drug discovery. Graph neural networks have substantially advanced our ability to model molecular representations; however, the precise identification of key local structures and the capture of long-distance structural correlations for better DDI prediction and interpretation remain significant challenges. Results: Here, we present DrugDAGT, a dual-attention graph transformer framework with contrastive learning for predicting multiple DDI types. The dual-attention graph transformer incorporates attention mechanisms at both the bond and atomic levels, thereby enabling the integration of short and long-range dependencies within drug molecules to pinpoint key local structures essential for DDI discovery. Moreover, DrugDAGT further implements graph contrastive learning to maximize the similarity of representations across different views for better discrimination of molecular structures. Experiments in both warm-start and cold-start scenarios demonstrate that DrugDAGT outperforms state-of-the-art baseline models, achieving superior overall performance. Furthermore, visualization of the learned representations of drug pairs and the attention map provides interpretable insights instead of black-box results. Conclusions: DrugDAGT provides an effective tool for accurately predicting multiple DDI types by identifying key local chemical structures, offering valuable insights for prescribing medications, and guiding drug development. All data and code of our DrugDAGT can be found at https://github.com/codejiajia/DrugDAGT. [ABSTRACT FROM AUTHOR]

Graft‐versus‐host disease (GVHd) remains a significant challenge following allogeneic hematopoietic stem cell transplantation (HSCT). Prevention of GVHd relies mainly on the use of calcineurin inhibitors, notably ciclosporin that exhibits complex pharmacokinetics influenced by many factors including drug‐drug interactions (DDIs). Due to the downregulation of drug metabolizing enzymes and transporters, it has been postulated that inflammation may be a contributing factor to the variability observed in ciclosporin pharmacokinetics.This study aimed to assess the impact of inflammation, as indicated by C‐reactive protein (CRP) levels, on the metabolism of ciclosporin in adult allogeneic HSCT recipients. A retrospective observational study was conducted at Rennes University Hospital involving 71 adult HSCT patients. The relationship between the intensity of inflammation (no‐to‐mild, moderate, and severe), and the metabolism of ciclosporin (estimated by the concentration/dose ratio) was assessed. Severe inflammation significantly decreased the metabolism of ciclosporin, as evidenced by higher concentration/dose ratios. Thanks to the daily dose adjustment, inflammation did not influence the blood levels of ciclosporin. Interestingly, DDIs did not emerge as a significant covariate in influencing ciclosporin metabolism. This is likely because the CYP3A4 inhibitory potential of interacting drugs may be masked in HSCT patients where metabolism is already upstream downregulated by inflammation.The study highlights the intricate relationship between inflammation and ciclosporin pharmacokinetics in HSCT patients. This underscores the necessity for therapeutic monitoring and the potential adjustment of dosage strategies based on the inflammatory status. These insights could contribute to the development of more personalized, optimized, and effective management strategies for HSCT recipients. [ABSTRACT FROM AUTHOR]

Objective Background Methods Results Conclusions Reported here are the results of four rimegepant phase I studies, in healthy participants, aimed at determining the in vivo potential of rimegepant (75 mg) for cytochrome P450 (CYP) 3A4‐related drug–drug interactions (DDIs).Rimegepant orally disintegrating tablet (Pfizer Inc., New York, NY, USA) is a calcitonin gene‐related peptide receptor antagonist approved for acute treatment of migraine and preventive treatment of episodic migraine. People with migraine commonly use multiple drug treatments, with the potential for DDIs.Each study was an open‐label, single‐arm, single‐sequence, crossover study. Rimegepant was tested as a victim drug by separate co‐administration of itraconazole (a strong CYP3A4 inhibitor and P‐glycoprotein inhibitor) in Study 1, rifampin (a strong CYP3A4 inducer and moderate CYP2C9 inducer) in Study 2, and fluconazole (a strong CYP2C9 inhibitor and moderate CYP3A4 inhibitor) in Study 3, and as a perpetrator drug by co‐administration with midazolam (a CYP3A4 substrate) in Study 4.Mean values of single‐dose rimegepant maximum concentration (Cmax) and area under the curve from time 0 to infinity (AUC0–inf) increased with itraconazole co‐administration (n = 22) by 1.42‐fold (90% confidence interval [CI] 1.25–1.61) and by 4.14‐fold (90% CI 3.87–4.44), respectively, and decreased with rifampin co‐administration (n = 21) to 36% (90% CI 31.2–41.4%) and to 19% (90% CI 16.3–21.4%), respectively. Co‐administration with fluconazole (n = 23) increased rimegepant mean AUC0–inf by 1.80‐fold (90% CI 1.68–1.93), with no impact on Cmax (1.04‐fold; 90% CI 0.94–1.15). Co‐administration of rimegepant single dose (300 mg; n = 14) or multiple doses (150 mg/day; n = 14) increased the mean Cmax of midazolam by 1.38‐fold (90% CI 1.13–1.67) and 1.53‐fold (90% CI 1.32–1.78), respectively, and the AUC0–inf of midazolam by 1.86‐fold (90% CI 1.58–2.19) and 1.91‐fold (90% CI 1.63–2.25), respectively.Based on the magnitude of DDIs, these studies indicate the following: co‐administration of rimegepant with a strong CYP3A4 inhibitor should be avoided; during co‐administration with a moderate CYP3A4 inhibitor, another dose of rimegepant within 48 h should be avoided; co‐administration of rimegepant with a strong or moderate CYP3A4 inducer should be avoided; CYP2C9 does not play a meaningful role in rimegepant metabolism; and there is no clinically meaningful CYP3A4 inhibition by rimegepant. [ABSTRACT FROM AUTHOR]

Aim: Given that metformin is often recommended for the management of type 2 diabetes mellitus, it is clinically significant to consider the potential interactions between metformin and other medications. In this study, we aimed to identify potential drug-drug interactions associated with metformin by retrospectively analyzing the prescriptions of patients taking metformin. Materials and Methods: Metformin-containing prescription data of five independent community pharmacies in Konya province for the year 2023 were analyzed retrospectively. Medscape®, Drugs® and LexiComp® software programs were used to detect potential drug-drug interactions. As a result of power analysis with the G Power program, 400 patients were included in the study with an effect size of 0.25, type 1 error of 0.05 and confidence interval of 0.95. Results: Kendall's W value indicating the agreement between Medscape®, Drugs®and LexiComp® software programs was calculated as 0.061. In terms of potential drug-drug interactions of metformin, the agreement between the software programs was observed to be slight. The highest agreement between the programs was observed between Medscape® and LexiComp® (Kappa coefficient=0.44). Conclusion: Since potential drug-drug interactions are common in prescriptions for patients taking metformin, these interactions should be carefully monitored. Clinicians should use multiple interaction programs to identify potential drug-drug interactions of metformin. [ABSTRACT FROM AUTHOR]

Background/Objectives: Plasma levels of 4β-hydroxycholesterol (4β-OHC), a CYP3A-specific metabolite of cholesterol, are elevated after administration of CYP3A inducers like rifampicin and carbamazepine. To simulate such plasma 4β-OHC increase, we developed a physiologically based pharmacokinetic (PBPK) model of cholesterol and 4β-OHC in the Simcyp PBPK Simulator (Version 23, Certara UK Ltd.) using a middle-out approach. Methods: Relevant physicochemical properties and metabolic pathway data for CYP3A and CYP27A1 was incorporated in the model. Results: The PBPK model recovered the observed baseline plasma 4β-OHC levels in Caucasian, Japanese, and Korean populations. The model also captured the higher baseline 4β-OHC levels in females compared to males, indicative of sex-specific differences in CYP3A abundance. More importantly, the model recapitulated the increased 4β-OHC plasma levels after multiple-dose rifampicin treatment in six independent studies, indicative of hepatic CYP3A induction. The verified model also captured the altered 4β-OHC levels in CYP3A4/5 polymorphic populations and with other CYP3A inducers. The model is limited by scant data on relative contributions of CYP3A and CYP27A1 pathways and does not account for regulatory mechanisms that control plasma cholesterol and 4β-OHC levels. Conclusion: This study provides a quantitative fit-for-purpose and framed-for-future modelling framework for an endogenous biomarker to evaluate the DDI risk with hepatic CYP3A induction. [ABSTRACT FROM AUTHOR]

As the most common psychiatric symptom, depression represents a subject of high interest for the medical community. Background/Objectives: International guidelines consider selective serotonin reuptake inhibitors (SSRIs) the first-line treatment of depression. Although having better efficacy and tolerability in comparison to tricyclic antidepressants or monoamine oxidase inhibitors, the diversity and potential severity of adverse effects and interactions manifested by SSRIs, combined with the frequency of prescriptions, lead to the necessity of evaluating real-world data. The aim of this study was to identify and evaluate the drug interactions reported in EudraVigilance (EV) for the six SSRIs representatives that are authorized in Europe: fluoxetine (FXT), fluvoxamine (FVM), citalopram (CIT), escitalopram (ESC), paroxetine (PAR) and sertraline (SER). The entire class of SSRIs was examined as a comparator to identify whether one of the representatives was more prone to reporting. Methods: Descriptive analysis and disproportionality analysis were conducted on data extracted from the EV database. Results: A total of 326,450 adverse reactions (ADRs) were reported for the SSRIs group. Approximately a quarter of these (n = 83,201; 25.46%) were reported for SER and 22.37% (n = 73,131) for PAR. Of the total ADRs reported, 2.12% (n = 6925) represent preferred terms related to drug-drug interactions (DDIs): SER (n = 1474; 22.37%), CIT (n = 1272, 19.86), and FXT (n = 1309, 19.83%). Specific ADRs related to inhibitory activity represent 0.98%, and for potentiating activity, 1.89%. Conclusions: Although representing a small value of the total ADRs, DDIs may be related to severe outcomes. Awareness should be raised for this category of ADRs that can be reduced by the joined efforts of physicians and pharmacists. [ABSTRACT FROM AUTHOR]

A patient-tailored therapy of the heterogeneous, neuropsychiatric disorder of Parkinson's disease (PD) aims to improve dopamine sensitive motor symptoms and associated non-motor features. A repeated, individual adaptation of dopamine substituting compounds is required throughout the disease course due to the progress of neurodegeneration. Therapeutic drug monitoring of dopamine substituting drugs may be an essential tool to optimize drug applications. We suggest plasma determination of levodopa as an initial step. The complex pharmacology of levodopa is influenced by its short elimination half-life and the gastric emptying velocity. Both considerably contribute to the observed variability of plasma concentrations of levodopa and its metabolite 3-O-methyldopa. These amino acids compete with other aromatic amino acids as well as branched chain amino acids on the limited transport capacity in the gastrointestinal tract and the blood brain barrier. However, not much is known about plasma concentrations of levodopa and other drugs/drug combinations in PD. Some examples may illustrate this lack of knowledge: Levodopa measurements may allow further insights in the phenomenon of inappropriate levodopa response. They may result from missing compliance, interactions e.g. with treatments for other mainly age-related disorders, like hypertension, diabetes, hyperlipidaemia, rheumatism or by patients themselves independently taken herbal medicines. Indeed, uncontrolled combination of compounds for accompanying disorders as given above with PD drugs might increase the risk of side effects. Determination of other drugs used to treat PD in plasma such as dopamine receptor agonists, amantadine and inhibitors of catechol-O-methyltransferase or monoamine oxidase B may refine and improve the value of calculations of levodopa equivalents. How COMT-Is change levodopa plasma concentrations? How other dopaminergic and non-dopaminergic drugs influence levodopa levels? Also, delivery of drugs as well as single and repeated dosing and continuous levodopa administrations with a possible accumulation of levodopa, pharmacokinetic behaviour of generic and branded compounds appear to have a marked influence on efficacy of drug treatment and side effect profile. Their increase over time may reflect progression of PD to a certain degree. Therapeutic drug monitoring in PD is considered to improve the therapeutic efficacy in the course of this devastating neurologic disorder and therefore is able to contribute to the patients' precision medicine. State-of-the-art clinical studies are urgently needed to demonstrate the usefulness of TDM for optimizing the treatment of PD. [ABSTRACT FROM AUTHOR]

Background: Direct oral anticoagulants (DOACs) are recommended for the management of thrombosis prophylaxis, especially in patients with atrial fibrillation. As substrates of cytochrome P450 (CYP) 3A4 and/or P-glycoprotein, they are implicated in potential drug–drug interactions. NS5A/NS5B inhibitors are direct-acting agents (DAAs) against the Hepatitis C Virus (HCV) infection that exert a mild inhibition of P-glycoprotein without effects on CYP3A4. A DOAC and NS5A/NS5B inhibitor co-administration may lead to an increased risk of bleeding. Real-world data on the concomitant use of DOACs and DAAs are scarce. On this purpose, we perform a retrospective analysis on the risk of vascular adverse events (bleeding and thrombosis) among HCV patients under DOAC/DAA therapy, even in advanced liver disease. Methods: Between May 2015 and April 2023, patients treated with sofosbuvir-based DAA regimens and DOACs were consecutively included in this study from 12 Italian medical centers. Baseline characteristics, especially concerning bleeding risk and liver function, were collected. The occurrence of bleeding events, classified as major and minor, was the primary endpoint. Secondary endpoints were the rate of any thrombotic events and/or the need for discontinuation of one or both treatments. Moreover, a cohort of patients, matched by demographic characteristics (age and sex), that switched to vitamin K antagonists (VKAs) during the antiviral treatment was compared with the DOAC/DAA group. Results: A total of 104 patients were included. Thirty-eight of them (36.5%) were cirrhotic. Atrial fibrillation was an indication for anticoagulation in almost all cases (76%). Rivaroxaban (35.6%) was the most used DOAC, followed by apixaban (26.9%), dabigatran (19.2%) and edoxaban (18.3%). Sofosbuvir/velpatasvir (78.8%) was the most prescribed DAA, and all patients were already on anticoagulant therapy before the start of DAAs. During concomitant DOAC/DAA treatment, no major bleeding events were recorded, while four minor bleeding events occurred, but none resulted in DAA or DOAC discontinuation. At univariate analysis, the only additional risk factor statistically related to bleeding events was the anticoagulant therapy (hazard ratio [HR]: 13.2, 95% confidence interval 1,6-109). Performing an evaluation by a LOGIT binomial analysis with demographic characteristics, the antiplatelet therapy remained statistically associated to bleeding events. No significant differences were found in the rate of clinically relevant bleeding when the main population was compared with the VKA-switched cohort. A single major bleeding event leading to anticoagulation and DAA discontinuation was reported in VKA-switched matched cohort. Conclusions: In our study, the concomitant use of NS5A/NS5B inhibitors with DOAC showed good safety, and the only risk factor associated with bleeding events was the concomitant antiplatelet therapy. These findings support the use of DOACs during sofosbuvir-based HCV treatment, even in advanced liver disease. Replacing DOACs with VKAs does not appear to be of clinical benefit. [ABSTRACT FROM AUTHOR]

Simple Summary: Prostate cancer is most commonly diagnosed in males after the age of 55 years. These patients are also at risk for cardiovascular disease and venous thromboembolism requiring antithrombotic therapy. Prostate cancer treatments, such as androgen receptor axis-targeted therapies (ARATs, i.e., abiraterone acetate, apalutamide, darolutamide, and enzalutamide), may interact with common antithrombotic medications like warfarin, clopidogrel, and the direct oral anticoagulants. However, the data detailing the clinical outcomes of patients treated with these combinations are limited. We undertook a comprehensive review of the literature and modified Delphi process to enable development of an evidence-based consensus document for the co-prescribing of ARATs with antithrombotic medications. Our assessments relied heavily on pharmacokinetic data and extrapolation from drug interaction studies of similarly metabolized drugs, highlighting the need for more research into the clinical impact of drug interactions in prostate cancer patients. Nonetheless, we provide a practical framework to support clinicians in day-to-day therapeutic decision making. Background/Objectives: Abiraterone acetate, apalutamide, darolutamide, and enzalutamide, which make up the androgen receptor axis-targeted therapies (ARATs) drug class, are commonly used in the management of prostate cancer. Many patients on ARATs also receive oral antithrombotic therapy (i.e., anticoagulants or antiplatelets). The concomitant use of ARATs and antithrombotic therapies creates the potential for clinically relevant drug–drug interactions, but the literature regarding the actual consequences of these interactions, and guidance for co-prescribing, is limited. We assembled a multidisciplinary panel of experts and provided them with clinical information derived from a comprehensive literature review regarding the drug–drug interactions between ARATs and antithrombotic therapies. Methods: A three-stage modified electronic Delphi process was used to gather and consolidate opinions from the panel. Each stage consisted of up to three rounds of voting to achieve consensus on which ARAT/antithrombotic therapy drug pairs warrant attention, the possible clinical consequences of drug–drug interactions, and suggested actions for management. Results: The panel achieved consensus to avoid 11 ARAT/antithrombotic therapy drug pairs and modify therapy for eight pairs. Assessments relied heavily on pharmacokinetic data and extrapolation from drug–drug interaction studies of similarly metabolized drugs. Conclusions: This e-Delphi process highlights the need for further research into the clinical impact of ARAT/antithrombotic drug interactions. Nonetheless, the suggested actions aim to provide clinicians with a practical framework for therapeutic decision making. [ABSTRACT FROM AUTHOR]

It has become increasingly common for patients to rely on the use of multiple prescription medications. The management of polypharmacy requires careful consideration for how drugs are metabolized and their potential for interaction with other drugs. Drug–drug interaction (DDI) assessments are typically performed in a stepwise manner during drug development, though knowledge gaps can exist at the time of approval. The US Food and Drug Administration can establish postmarketing requirements (PMRs) or postmarketing commitments (PMCs) to address these knowledge gaps. In this study, we systematically evaluated PMRs and PMCs established to new molecular entities (NMEs) at the time of initial approval between 2009 and 2023, for the assessment of pharmacokinetics‐based DDIs (i.e., drug metabolizing enzyme‐ and transporter‐related DDIs). We found that 22% of NMEs had at least one DDI‐related PMR or PMC, with a total of 263 that were pharmacokinetic based. Of these, 67% were for the assessment of drug metabolizing enzymes, which were established most frequently for their evaluation as a substrate, and 28% for transporters, which were established most frequently for their evaluation as an inhibitor. The 89% of PMRs and PMCs that were considered fulfilled had a revision to the United States prescribing information, the majority of which resulted in updated new instructions for use. This study highlights the value in conducting PMRs and PMCs early in the drug development process allowing broad patient inclusion at the time of initial drug approval. [ABSTRACT FROM AUTHOR]

Erdafitinib, an oral pan‐FGFR inhibitor, is used in locally advanced or metastatic urothelial carcinoma for adults with FGFR3 genetic alterations and whose disease progressed following prior systemic therapy. This drug‐drug interaction substudy evaluated the effect of erdafitinib on the pharmacokinetics of midazolam (cytochrome P450 3A4 substrate), and metformin (organic cation transporter 2 substrate). Twenty‐five patients with advanced solid tumors harboring FGFR gene alterations received pretreatment with single doses of midazolam and metformin, followed by a daily dose of erdafitinib. Drug‐drug interaction assessments were performed at erdafitinib steady state following coadministration of single doses of midazolam and metformin, respectively. Geometric mean ratios for maximum plasma concentration and area under the plasma concentration‐time curve (AUC) from time 0 to the last measurable concentration, and AUC from time 0 to infinity were estimated using linear mixed‐effects models (90% confidence interval within 80%‐125% indicated no interaction). The 90% confidence intervals of geometric mean ratios for maximum plasma concentration, AUC from time 0 to the last measurable concentration, and AUC from time 0 to infinity of midazolam (86.3%, 88.5%, and 82.1%), 1‐OH midazolam (99.8%, 97.4%, and 101.5%), and metformin (108.7%, 119.0%, and 113.9%) were either contained or slightly outside the 80%‐125% interval and not considered clinically meaningful. Adverse events were consistent with the known erdafitinib safety profile; no new safety signals emerged. Thus, repeated dosing of erdafitinib had no clinically meaningful effect on the pharmacokinetics of midazolam or metformin. [ABSTRACT FROM AUTHOR]

The lack of data on drug–drug interactions in pediatrics represents a relevant problem in making appropriate therapeutic decisions. Our study aimed to investigate the incidence and risk factors for potential drug–drug interactions (pDDIs) in pediatric pneumonology units, including cystic fibrosis patients. We performed a 6‐month prospective observational study during which clinical pharmacists, using the Lexicomp Drug Interactions checker, screened medical records to identify pDDIs. Spearman's rank coefficient, logistic regression, and the Mann–Whitney U test were used to identify correlations, analyze risk factors for pDDIs, and compare cystic fibrosis patients with the rest, respectively. Recommendations were provided for the D and X pDDIs categories. Within the 218 patients, 428 pDDIs were identified, out of which 237 were classified as clinically significant. Almost 60% of patients were exposed to at least one relevant interaction. The number of pDDIs correlated with the number of; drugs (rs = 0.53, P <.001), hospitalization length (rs = 0.20, P <.01), and off‐label medicines (rs = 0.25, P <.001). According to the multivariate analysis, at least 6 administered medications (OR = 4.15; 95% CI = 2.21‐7.78), 4 days of hospitalization (OR = 6.41; 95% CI = 2.29‐17.97), and off‐label therapy (OR = 3.37; 95% CI = 1.69‐6.70) were the risk factor for pDDIs. Despite significant differences in the number of medications taken, comorbidities, and off‐label drugs, cystic fibrosis patients were not more exposed to pDDI. Given the lack of data on pDDIs in the pediatric population, the need for close cooperation between clinicians and clinical pharmacists to improve the safety and efficacy of pharmacotherapy is highlighted. [ABSTRACT FROM AUTHOR]

Purpose: A physiologically based pharmacokinetic (PBPK) model for fedratinib was updated and revalidated to bridge a gap between the observed drug–drug interaction (DDI) of a single sub-efficacious dose in healthy participants and the potential DDI in patients with cancer at steady state. The study aimed to establish an appropriate dose for fedratinib in patients coadministered with dual CYP3A4 and CYP2C19 inhibitors, providing quantitative evidence to inform dosing guidance. Methods: The original minimal PBPK model was developed using Simcyp® Simulator v17. The model was updated by substituting a single distribution rate (Qsac) with 2 separate rates (CLin/CLout) and transitioning to v20. Model parameter updates were further informed with 3 clinical studies, and 3 more studies served as independent validation data. The validated model was applied to simulate potential DDIs between fedratinib and a known dual inhibitor of CYP3A4 and CYP2C19 (fluconazole). Results: Coadministration of fedratinib with fluconazole in patients was predicted to increase fedratinib exposure by < 2-fold in all simulated scenarios. For patients with cancer receiving the approved dose of fedratinib 400 mg once daily along with fluconazole 200 mg daily, the model predicted an approximate 50% increase in fedratinib exposure at steady state. Conclusions: The updated PBPK model improved description of the observed pharmacokinetics and predicted a low risk of clinically significant DDIs between fedratinib and fluconazole. The quantitative evidence serves as a primary foundation for providing dose guidance in clinical practice for the coadministration of fedratinib with dual CYP3A4 and CYP2C19 inhibitors. [ABSTRACT FROM AUTHOR]

Drug interactions are a significant and integral part of the concept of medication-related adverse events, whether referring to potential interactions or those currently observed in real-world conditions. The high global consumption of antibiotics and their pharmacokinetic and pharmacodynamic mechanisms make antibiotic-drug interactions a key element that requires continuous study due to their clinical relevance. In the present work, the current state of knowledge on antibiotic-drug interactions, which are less studied than other drug-drug interactions despite their frequent use in acute settings, has been consolidated and updated. The focus was on the interactions of the commonly used antibiotics in clinical practice, on the characteristics of the geriatric population susceptible to interactions, and on the impact of online drug interaction checkers. Additionally, strategies for optimizing the management of these interactions, including spacing out administrations, monitoring, or avoiding certain combinations, are suggested. Sustained research and careful monitoring are critical for improving antibiotic safety and efficacy, especially in susceptible populations, to enhance precision in managing antibiotic-drug interactions. [ABSTRACT FROM AUTHOR]

Background: Currently, there remains substantial controversy in research regarding whether the concomitant use of colchicine and statins increases the occurrence of rhabdomyolysis, warranting further substantiation. Objective: This study aimed to identify the likelihood drug-drug interactions (DDIs) for the co-administration of colchicine and statins resulting in rhabdomyolysis. Methods: A disproportionality analysis was conducted by using data sourced from the US Food and Drug Administration Adverse Event Reporting System (FAERS) to detect rhabdomyolysis signals associated with the combined use of colchicine and statins. The association between (colchicine/statins/colchicine and statins) and rhabdomyolysis were evaluated using information component (IC). DDI signals were calculated based on the Ω shrinkage measure and Bayesian confidence propagation neural network (BCPNN) method. Furthermore, stratification was performed based on colchicine and individual statins agents. Results: In total, 11,119 reports of rhabdomyolysis were identified in the FAERS database, 255 (2.29%) involved both colchicine and statins. Our analysis showed potential DDI signals of rhabdomyolysis (Ω025 = 1.17) among individuals concurrent use of colchicine and statins. Moreover, further drug-specific analysis suggests DDI signals in the colchicine-atorvastatin pair (Ω025 = 1.12), and colchicine-rosuvastatin pair (Ω025 = 1.05), along with a higher proportion of rhabdomyolysis (IC025 = 5.20) and (IC025 = 4.26), respectively. Conclusion: The findings suggest that concomitant use of colchicine and statins may increase the risk of rhabdomyolysis, particularly when combined with atorvastatin or rosuvastatin. Therefore, healthcare professionals should pay special attention to life-threatening AE such as rhabdomyolysis, when co- prescribing colchicine statins. [ABSTRACT FROM AUTHOR]

Palbociclib, an oral inhibitor of cyclin-dependent kinase 4 and 6, is approved for the treatment of metastatic breast cancer. This study investigated the influence of diverse clinical and biological factors--age, renal function, genetic variations, and concomitant medications (pharmacokinetic covariates)--on palbociclib pharmacokinetics. Employing a validated LC-MS/MS method, we analyzed the minimum plasma concentrations (Ctrough) of palbociclib in 68 women and determined the percentage deviations from the median Ctrough for each dosage group. Variations in a panel of absorption, distribution, metabolism, and excretion (ADME) genes were assessed using end-point allele-specific fluorescence detection and pyrosequencing. Two distinct patient cohorts were defined based on median values of age, creatinine, and eGFR, which exhibited statistically significant differences in percentage deviations (p = 0.0095, p = 0.0288, and p = 0.0005, respectively). Homozygous carriers of the PPARA variants displayed larger positive percentage deviations than the other group (p = 0.0292). Similarly, patients concurrently taking CYP3A and P-glycoprotein inhibitors alongside anticancer therapy exhibited significant variations (p = 0.0285 and p = 0.0334, respectively). Furthermore, exploring the drug-drug-gene interactions between inhibitors of CYP3A and P-glycoprotein with their respective genetic variants revealed two patient groups with statistically different percentage deviations (p = 0.0075, p = 0.0012, and p = 0.0191, respectively). These results could help address cases where pharmacokinetic covariates or subclinical conditions impair palbociclib adherence or response, aiming to offer tailored dosing strategies or monitoring for individual patients. [ABSTRACT FROM AUTHOR]

Purpose: While nirmatrelvir/ritonavir (NMV-r) has been positioned as a first-line treatment for mild to moderate COVID-19, it has multiple and significant drug-drug interactions (DDIs). The use of NMV-r in Japan has been limited compared to the United States. This study aimed to describe the distribution of DDIs with NMV-r and their management in patients with COVID-19 under the control of a management system for the appropriate use of NMV-r. Methods: A retrospective observational study was conducted at a Japanese university hospital. The management system included a flowchart for selecting antivirals and a list for reviewing DDI management, based on the National Institutes of Health guidelines and the guidance of the Japanese Society of Pharmaceutical Health Care and Sciences. Patients with mild to moderate COVID-19 and prescribed NMV-r or molnupiravir (MOV) were included. The primary outcome was DDI management practices, including the selected COVID-19 medications. The secondary outcome included the distribution of DDI classification and the 30-day all-cause mortality. Results: This study included 241 patients (median age of 60 years, 112 [46.5%] females), of whom 126 and 115 received NMV-r and MOV, respectively. Of the 241 patients, 145 (60.2%) received concomitant medications that have DDIs with NMV-r. All 30 patients with severe renal impairment or insufficient details on concomitant medications received MOV. Forty-nine patients with concomitant medications required alternative COVID-19 therapy consideration due to DDIs, of whom 42 (85.7%) patients received MOV. Eighty-one patients had concomitant medications requiring temporary adjustment, of whom 44 (54.3%) patients received NMV-r, and 42 of these patients temporarily adjusted these concomitant medications. Five patients with concomitant medications that can continued by monitoring the effects/adverse effects, of whom 4 (80.0%) patients received NMV-r. Seventy-six patients without concomitant medications requiring DDI management, of whom 71 (93.4%) patients received NMV-r. The 30-day all-cause mortality for eligible patients was 0.9% [95% confidence interval, 0.1–3.1]. Conclusions: Most patients received appropriate antivirals according to the classification of DDIs, and most patients with concomitant medications requiring temporary adjustment received the recommended DDI management. Our management system is effective in promoting the use of NMV-r in the appropriate patients and managing problematic DDIs. [ABSTRACT FROM AUTHOR]

Background: Prescribing errors put an enormous burden on health and the economy, claiming implementation of effective methods to prevent/reduce them. Polypharmacy regimens (five or more drugs) are highly prone to unacknowledged prescribing errors, since the complex network of drug-drug interactions, guidelines and contraindications is challenging to be adequately evaluated in the prescription phase, especially if different doctors are involved. Clinical decision support systems aimed at polypharmacy evaluation may be crucial to recognize and correct prescribing errors. Methods: A commercial clinical decision support system (Drug-PIN®) was applied to estimate the frequency of unrecognized prescribing errors in a group of 307 consecutive patients accessing the hospital pre-admission service of the Sant'Andrea Hospital of Rome, Italy, in the period April-June 2023. Drug-PIN® is a two-step system, first scoring the risk (low, moderate or high) associated with a certain therapy-patient pair, then allowing therapy optimization by medications exchanges. We defined prescribing errors as cases where therapy optimization could achieve consistent reduction of the Drug-PIN® calculated risk. Results: Polypharmacy was present in 205 patients, and moderate to high risk for medication harm was predicted by Drug-PIN® in 91 patients (29.6%). In 58 of them (63.7%), Drug-PIN® guided optimization of the therapy could be achieved, with a statistically significant reduction of the calculated therapy-associated risk score. Patients whose therapy cannot be improved have a statistically significant higher number of used drugs. Considering the overall study population, the rate of avoidable prescribing errors was 18.89%. Conclusions: Results suggest that computer-aided evaluation of medication-associated harm could be a valuable and actionable tool to identify and prevent prescribing errors in polypharmacy. We conducted the study in a Hospital pre-admission setting, which is not representative of the general population but represents a hotspot to intercept fragile population, where a consistent fraction of potentially harmful polypharmacy regimens could be promptly identified and corrected by systematic use of adequate clinical decision support tools. [ABSTRACT FROM AUTHOR]

Cytochrome P40 (CYP) enzymes dominate the metabolism of numerous endogenous and xenobiotic substances. While it is commonly believed that CYP-catalysed reactions result in the detoxication of foreign substances, these reactions can also yield reactive intermediates that can bind to cellular macromolecules to cause cytotoxicity or irreversibly inactivate CYPs that create them. Mechanism-based inactivation (MBI) produces either irreversible or quasi-irreversible inactivation and is commonly caused by CYP metabolic bioactivation to an electrophilic reactive intermediate. Many drugs that have been known to cause MBI in CYPs have been discovered as perpetrators in drug-drug interactions throughout the last 20–30 years. This review will highlight the key findings from the recent literature about the mechanisms of CYP enzyme inhibition, with a focus on the broad mechanistic elements of MBI for widely used drugs linked to the phenomenon. There will also be a brief discussion of the clinical or pharmacokinetic consequences of CYP inactivation with regard to drug interaction and toxicity risk. Gaining knowledge about the selective inactivation of CYPs by common therapeutic drugs helps with the assessment of factors that affect the systemic clearance of co-administered drugs and improves comprehension of anticipated interactions with other drugs or xenobiotics. [ABSTRACT FROM AUTHOR]

Objective: The objective of this review is to provide an overview of common drug-drug interactions (DDIs) associated with prostate cancer treatments and outline recommendations for managing polypharmacy. Data sources: A literature search of PubMed, Embase, and CINAHL was carried out to identify pharmacokinetic and pharmacodynamic changes caused by DDIs that are relevant for prostate cancer patients, DDIs between prostate cancer therapies and co-administered medications (both prescription and over-the-counter), and measures to prevent DDIs. Medication package inserts were used to identify the impact of DDI on the prostate cancer therapy and suggested interventions. Data summary: No DDIs are expected for the LHRH agonists leuprolide acetate, histrelin, goserelin, or leuprolide mesylate. However, DDIs have been reported for GnRH antagonists, anti-androgens, PARP inhibitors, and taxanes. Although there are no confirmed DDIs for sipuleucel-T to date, it is not generally recommended to use sipuleucel-T concurrently with immunosuppressive medications. Interventions to prevent DDIs include the use of software that can detect clinically significant DDIs, up-to-date medication reconciliation, the inclusion of dedicated clinical pharmacists in cancer treatment teams, and patient/caregiver education. Conclusions: Prostate cancer patients have a high risk of potential DDIs due to numerous new anti-cancer therapies, the increased use of treatment combinations, and the likelihood of comorbid conditions also requiring drug therapy. Drug-drug interaction screening software, up-to-date medication reconciliation, inclusion of oncology pharmacists on healthcare teams, and patient/caregiver education will aid the development of treatment plans that focus on achieving an optimal risk-benefit profile whilst reducing the risk of DDIs. [ABSTRACT FROM AUTHOR]

Personalized psycho-oncology represents a major challenge for the holistic care of cancer patients. It focuses on individualized psychotherapeutic and psychiatric interventions to address specific psychological needs. This narrative review summarizes the current literature on personalized psycho-oncology and highlights the prevalence and impact of psychiatric/psychological disorders in cancer patients. Personalized approaches, including tailored interventions and interdisciplinary collaboration, have been shown to be effective in improving mental health and overall quality of life. The integration of inflammatory biomarkers into treatment plans is a promising but challenging way to alleviate mental health problems. In addition, there is a need for specific diagnostic tools and treatment guidelines that take into account the specific psychological impact of different types of cancer. Future research should aim to refine these personalized strategies, improve diagnostic accuracy, and evaluate the cost-effectiveness of these interventions to improve both the psychological well-being and treatment outcomes of cancer patients. [ABSTRACT FROM AUTHOR]

Prevention, assessment, and identification of drug–drug interactions (DDIs) represent a challenge for healthcare professionals, especially in nosocomial settings. This narrative review aims to provide a thorough assessment of the most clinically significant DDIs for antibiotics used in healthcare-associated infections. Complex poly-pharmaceutical regimens, targeting multiple pathogens or targeting one pathogen in the presence of another comorbidity, have an increased predisposition to result in life-threatening DDIs. Recognising, assessing, and limiting DDIs in nosocomial infections offers promising opportunities for improving health outcomes. The objective of this review is to provide clinicians with practical advice to prevent or mitigate DDIs, with the aim of increasing the safety and effectiveness of therapy. DDI management is of significant importance for individualising therapy according to the patient, disease status, and associated comorbidities. [ABSTRACT FROM AUTHOR]

As a novel guanylate cyclase stimulator, SGC003F is being developed for the treatment of heart failure with a reduced ejection fraction (HFrEF). This study aimed to assess the effect of P-glycoprotein (P-gp) inhibition on SGC003F exposure in vivo, comparing plasma and tissue levels, and evaluating the role of P-gp in the small intestine, blood–brain barrier (BBB), and kidney in impacting the tissue exposure. Tariquidar, a P-gp inhibitor, was added to monolayer transport assays to observe the changes in the transmembrane characteristics of SGC003F. Rats were given SGC003F with tariquidar via various routes to measure plasma, tissue, urine, and fecal concentrations. The inclusion of tariquidar significantly altered the pharmacokinetics of SGC003F. In LLC-PK1-MDR1 cells, tariquidar reduced the efflux ratio of SGC003F from 6.56 to 1.28. In rats, it enhanced the plasma AUC by 3.05 or 1.61 times, increased the Cmax by 2.13 or 1.07 times, and notably improved bioavailability from 46.4% to 95%. Additionally, co-administration with tariquidar led to a decrease in fecal excretion and an increase in tissue exposure, with only a moderate effect on the partition ratios in the small intestine and brain. P-gp inhibition impacts SGC003F exposure, with plasma levels not fully reflecting tissue levels. P-gp in the small intestine and BBB affects SGC003F's pharmacokinetics, warranting further clinical drug–drug interaction (DDI) studies. [ABSTRACT FROM AUTHOR]

Understanding the interaction between pharmaceuticals and serum proteins is crucial for optimizing therapeutic strategies, especially in patients with coexisting chronic diseases. The primary goal of this study was to assess the potential changes in binding affinity and competition between glipizide (GLP, a second-generation sulfonylurea hypoglycemic drug) and losartan (LOS, a medication commonly prescribed for hypertension, particularly for patients with concurrent diabetes) with non-glycated (HSA) and glycated (gHSAGLC, gHSAFRC) human serum albumin using multiple spectroscopic techniques (fluorescence, UV-visible absorption, and circular dichroism spectroscopy). The results indicated that FRC is a more effective glycation agent for HSA than GLC, significantly altering the albumin structure and affecting the microenvironment around critical amino acid residues, Trp-214 and Tyr. These modifications reduce the binding affinity of LOS and GLP to gHSAGLC and gHSAFRC, compared to HSA, resulting in less stable drug–protein complexes. The study revealed that LOS and GLP interact nonspecifically with the hydrophobic regions of the albumin surface in both binary (ligand–albumin) and ternary systems (ligand–albumin–ligandconst) and specifically saturate the binding sites within the protein molecule. Furthermore, the presence of an additional drug (GLP in the LOS–albumin complex or LOS in the GLP–albumin complex) complicates the interactions, likely leading to competitive binding or displacement of the initially bound drug in both non-glycated and glycated albumins. Analysis of the CD spectra suggests mutual interactions between GLP and LOS, underscoring the importance of closely monitoring patients co-administered these drugs, to ensure optimal therapeutic efficacy and safety. [ABSTRACT FROM AUTHOR]

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The global increase of aging with the related increase of multiple noncommunicable diseases is inevitably accompanied by the associated issue of multimorbidity and polypharmacy. The latter is not without peculiar consequences on health, because it has been shown to be associated with drug-related adverse events, mainly due to poor prescription appropriateness and drug–drug interactions. To contribute to tackle this gigantic problem, a registry of drug dispensation in hospitalized older patient has been initiated in Italy in 2008. Through the last 15 years, data on nearly 11,000 older people have been accrued during their hospital stay in internal medicine and geriatric wards. This review article summarizes the main findings obtained, and how these data contribute to tackle the issue of appropriateness of drug prescription and the need of deprescribing in hospitalized older people affected by the most common noncommunicable diseases. [ABSTRACT FROM AUTHOR]

Abstract Background Bleeding complications following intramuscular (IM) injections are generally considered rare with reported incidence of 0.06%. However, evidence on safety of IM injections among anticoagulated hospitalized patients is lacking. The objective of the current study was to examine the incidence of injection site bleeding complications following IM injection among anticoagulated hospitalized patients. Methods A retrospective comparative study comprised of all hospitalized patients ≥ 18 years old that were treated with ≥ 1 IM injection between 2009 and 2019 in a large tertiary medical center. Bleeding complications were defined as focal hematoma, local bleeding, intramuscular bleeding or compartment syndrome. Each case with IM injection was searched for ICD9 codes (e.g., hematoma, hemorrhage or compartment syndrome) and for indirect evidence suggestive of potential bleeding: hemoglobin drop ≥ 2 g/dl, AST or CPK increase, packed red blood cell transfusion, or abrupt cessation of the anticoagulation. These case were then verified for true injection-site bleeding by natural language processing model and manual review of the electronic medical record. Results A total of 71,710 patients were treated with 236,406 IM injections. Mean age 53 (± 22) and 63% were females. Concomitant anticoagulation (Heparins: 90.3%, warfarin: 6.8% and DOACs: 4.7%) occurred in 40,819 IM injections (8189 patients). Suspected bleeding complications at the IM injection site were identified among 7,111 patients following 23,089 IM injections, the majority were unrelated to the IM injection-site (e.g., gastrointestinal bleeding, retroperitoneal, etc.). Two cases were verified as true injection site bleeding complication, both in the anticoagulated group (2/8189, 0.02%). Conclusion Bleeding complications at site of IM injections among anticoagulated hospitalized patients are rare, and their risk is probably not higher compared to patients without anticoagulation.

Abstract Objective Most patients with alcohol use disorder (AUD) regularly take medication. Alcohol interacts negatively with many commonly prescribed medications. Little is known about whether the risk of potential alcohol-medication and drug-drug interactions increases or decreases in patients with AUD during inpatient withdrawal treatment. The aim of our study was to determine the prevalence and characteristics of potential alcohol-medication and drug-drug interactions in patients with AUD before and after withdrawal treatment in an addiction unit. Design Prospective monocentric quasi-experimental pre-post study. Methods Medication records before and after withdrawal treatment were analyzed and screened for potential alcohol-medication (pAMI) and drug-drug interactions (pDDI) using the drugs.com classification and the AiDKlinik ® electronic interaction program, respectively. Results We enrolled 153 patients with AUD who were treated in an addiction unit of a university hospital in Germany. Of these, 67.3% experienced at least one pAMI before and 91.5% after withdrawal treatment. In total, there were 278 pAMIs classified as “mild,” “moderate,” or “severe” before and 370 pAMIs after withdrawal treatment. Additionally, there were 76 pDDIs classified as “moderate,” “severe,” or “contraindicated combinations” both before and after withdrawal treatment. Conclusion The risk of exposure to pAMIs and pDDIs increases during inpatient withdrawal treatment in patients with AUD. Improvements in the quality of prescribing should particularly focus on the use of antihypertensives and opioids.

Abstract Background Drug-drug interactions (DDIs) can result in unexpected pharmacological outcomes, including adverse drug events, which are crucial for drug discovery. Graph neural networks have substantially advanced our ability to model molecular representations; however, the precise identification of key local structures and the capture of long-distance structural correlations for better DDI prediction and interpretation remain significant challenges. Results Here, we present DrugDAGT, a dual-attention graph transformer framework with contrastive learning for predicting multiple DDI types. The dual-attention graph transformer incorporates attention mechanisms at both the bond and atomic levels, thereby enabling the integration of short and long-range dependencies within drug molecules to pinpoint key local structures essential for DDI discovery. Moreover, DrugDAGT further implements graph contrastive learning to maximize the similarity of representations across different views for better discrimination of molecular structures. Experiments in both warm-start and cold-start scenarios demonstrate that DrugDAGT outperforms state-of-the-art baseline models, achieving superior overall performance. Furthermore, visualization of the learned representations of drug pairs and the attention map provides interpretable insights instead of black-box results. Conclusions DrugDAGT provides an effective tool for accurately predicting multiple DDI types by identifying key local chemical structures, offering valuable insights for prescribing medications, and guiding drug development. All data and code of our DrugDAGT can be found at https://github.com/codejiajia/DrugDAGT .

INTRODUCTION. Pharmacotherapy in elderly and senile patients is associated with multimorbidity and polypharmacy and can lead to adverse drug reactions (ADRs). The growth of the world’s population over 60 makes the practical application of the Beers Criteria for Potentially Inappropriate Medication Use in Older Adults, the key recommendations to optimise prescribing in the geriatric population, increasingly important.AIM. This study aimed to review the history of the Beers criteria, the main changes in the updated 2023 version, and national and international publications on the practical experience of using the criteria in healthcare settings.DISCUSSION. The criteria for assessing the rationality of pharmacotherapy in older patients were developed by Mark Beers in 1991. His recommendations have been regularly reviewed and updated by a panel of experts from the American Geriatrics Society (AGS); version 7 has been in effect since 2023. The criteria are designed to support pharmacotherapy decision making for adults 65 years old and older in all ambulatory, acute, and institutionalised settings of care, except hospice and end-of-life care settings. The criteria are organised into 5 categories: 1) medications that should be avoided in all older adults; 2) medications considered potentially inappropriate in patients with certain diseases or syndromes; 3) medications that should be used with caution; 4) medications that are potentially inappropriate due to the risk of clinically significant drug–drug interactions; 5) medications that should be avoided or require dosage reduction in patients with impaired renal function. Medicines with pronounced anticholinergic effects are categorised as a separate class. The criteria are based on expert grading of the quality of evidence and strength of recommendations. Compared with the previous version (2019), the updated AGS Beers Criteria® (2023) changed the most in terms of recommendations for anticoagulants and sulfonylureas. According to the results of this review, the AGS Beers Criteria® are actively used in healthcare practice in Russia and abroad to reduce the undesirable effects of potentially inappropriate medication use in elderly patients by optimising the selection of medicines and treatment regimens; to train healthcare providers and patients in the principles of rational pharmacotherapy; to reduce the cost of pharmacotherapy; and to assess the quality of medical care.CONCLUSIONS. The AGS Beers Criteria® are an effective tool for identifying potentially inappropriate medications in prescribed therapy and selecting appropriate alternatives. Their practical application in healthcare settings can reduce ADRs, hospital admissions, and mortality rates in elderly and senile patients.

Abstract Background Prescribing errors put an enormous burden on health and the economy, claiming implementation of effective methods to prevent/reduce them. Polypharmacy regimens (five or more drugs) are highly prone to unacknowledged prescribing errors, since the complex network of drug-drug interactions, guidelines and contraindications is challenging to be adequately evaluated in the prescription phase, especially if different doctors are involved. Clinical decision support systems aimed at polypharmacy evaluation may be crucial to recognize and correct prescribing errors. Methods A commercial clinical decision support system (Drug-PIN®) was applied to estimate the frequency of unrecognized prescribing errors in a group of 307 consecutive patients accessing the hospital pre-admission service of the Sant’Andrea Hospital of Rome, Italy, in the period April-June 2023. Drug-PIN® is a two-step system, first scoring the risk (low, moderate or high) associated with a certain therapy-patient pair, then allowing therapy optimization by medications exchanges. We defined prescribing errors as cases where therapy optimization could achieve consistent reduction of the Drug-PIN® calculated risk. Results Polypharmacy was present in 205 patients, and moderate to high risk for medication harm was predicted by Drug-PIN® in 91 patients (29.6%). In 58 of them (63.7%), Drug-PIN® guided optimization of the therapy could be achieved, with a statistically significant reduction of the calculated therapy-associated risk score. Patients whose therapy cannot be improved have a statistically significant higher number of used drugs. Considering the overall study population, the rate of avoidable prescribing errors was 18.89%. Conclusions Results suggest that computer-aided evaluation of medication-associated harm could be a valuable and actionable tool to identify and prevent prescribing errors in polypharmacy. We conducted the study in a Hospital pre-admission setting, which is not representative of the general population but represents a hotspot to intercept fragile population, where a consistent fraction of potentially harmful polypharmacy regimens could be promptly identified and corrected by systematic use of adequate clinical decision support tools.

Abstract Purpose While nirmatrelvir/ritonavir (NMV-r) has been positioned as a first-line treatment for mild to moderate COVID-19, it has multiple and significant drug-drug interactions (DDIs). The use of NMV-r in Japan has been limited compared to the United States. This study aimed to describe the distribution of DDIs with NMV-r and their management in patients with COVID-19 under the control of a management system for the appropriate use of NMV-r. Methods A retrospective observational study was conducted at a Japanese university hospital. The management system included a flowchart for selecting antivirals and a list for reviewing DDI management, based on the National Institutes of Health guidelines and the guidance of the Japanese Society of Pharmaceutical Health Care and Sciences. Patients with mild to moderate COVID-19 and prescribed NMV-r or molnupiravir (MOV) were included. The primary outcome was DDI management practices, including the selected COVID-19 medications. The secondary outcome included the distribution of DDI classification and the 30-day all-cause mortality. Results This study included 241 patients (median age of 60 years, 112 [46.5%] females), of whom 126 and 115 received NMV-r and MOV, respectively. Of the 241 patients, 145 (60.2%) received concomitant medications that have DDIs with NMV-r. All 30 patients with severe renal impairment or insufficient details on concomitant medications received MOV. Forty-nine patients with concomitant medications required alternative COVID-19 therapy consideration due to DDIs, of whom 42 (85.7%) patients received MOV. Eighty-one patients had concomitant medications requiring temporary adjustment, of whom 44 (54.3%) patients received NMV-r, and 42 of these patients temporarily adjusted these concomitant medications. Five patients with concomitant medications that can continued by monitoring the effects/adverse effects, of whom 4 (80.0%) patients received NMV-r. Seventy-six patients without concomitant medications requiring DDI management, of whom 71 (93.4%) patients received NMV-r. The 30-day all-cause mortality for eligible patients was 0.9% [95% confidence interval, 0.1–3.1]. Conclusions Most patients received appropriate antivirals according to the classification of DDIs, and most patients with concomitant medications requiring temporary adjustment received the recommended DDI management. Our management system is effective in promoting the use of NMV-r in the appropriate patients and managing problematic DDIs.

Objective: This cross-sectional study aimed to assess the frequency of potential drug–drug interactions (DDIs) and demographic correlates of moderate and major DDIs among patients with hematologic cancer at a referral hematology hospital in Iran. Methods: In this study, for 6 months, all patients suffering from hematologic cancers admitted to the tertiary oncology hospital, Omid, Isfahan, were considered. Data from all medications prescribed to patients during hospitalization were analyzed using the online Lexicomp® drug interaction checker, recording all interactions classified by risk level: C, D, or X. Findings: A total of 674 DDIs were detected in 109 patients. The prevalence of treatments with at least one clinically relevant interaction was 95%, being 57.9% for those at level C and 31.5% for levels D and X. According to the frequency, the main interaction was between aprepitant and corticosteroids, followed by the interaction between aprepitant and vincristine. The most common interaction between antineoplastic agents was between doxorubicin and cyclophosphamide. In terms of mechanism, most of DDIs (54.9%) were pharmacodynamics. Only the number of administered medications was associated with DDI occurrence. Conclusion: Potential DDIs of moderate to major severity are common among patients with hematologic malignancies. This underscores the importance of implementing different strategies to mitigate this clinically significant risk.

Hyunwook Ryu,1 Hyun Chul Kim,1 Inseung Jeon,1 In-Jin Jang,1 Joo-Youn Cho,1,2 Kyung Tae Kim,3 Jaeseong Oh1,4,5 1Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea; 2Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea; 3Addpharma, Inc., Yongin-si, Gyeonggi-do, Republic of Korea; 4Department of Pharmacology, Jeju National University College of Medicine, Jeju, Republic of Korea; 5Clinical Research Institute, Jeju National University Hospital, Jeju, Republic of KoreaCorrespondence: Jaeseong Oh, Department of Pharmacology, Jeju National University College of Medicine, Jeju, Republic of Korea, Email jaeseong5@jejunu.ac.krBackground: Management of hypertension and hyperlipidemia, which are common comorbid risk factors for cardiovascular diseases, require multiple medications. The development of a fixed-dose combination (FDC) containing ezetimibe, rosuvastatin, telmisartan, and amlodipine aims to enhance patient adherence and persistence, but the potential interactions among the four medications have not been studied. This study aimed to evaluate the pharmacokinetic (PK) interactions between the FDC of ezetimibe/rosuvastatin 10/20 mg (ER) and the FDC of telmisartan/amlodipine 80/5 mg (TA).Methods: An open-label, single-sequence, three-period, three-treatment crossover study was conducted in healthy male subjects. All subjects received ER for 7 days, TA for 9 days and ER combined with TA for 7 days during each treatment period. For PK analysis of total/free ezetimibe, rosuvastatin, telmisartan, and amlodipine, serial blood samples were collected for 24 hours at steady state. Safety profiles were assessed throughout the study.Results: Thirty-eight subjects were enrolled, and 34 subjects completed the study. The systemic exposure to each active ingredient after coadministration of the two FDCs was similar to that after each FDC alone. The geometric mean ratios and 90% confidence intervals for the maximum plasma concentration (μg/L) and the area under the plasma concentration-time curve (h·μg/L) of the combination therapy to monotherapy, assessed at steady state, were as follows: total ezetimibe, 1.0264 (0.8765– 1.2017) and 0.9359 (0.7847– 1.1163); free ezetimibe, 1.5713 (1.2821– 1.9257) and 0.9941 (0.8384– 1.1788); rosuvastatin, 2.1673 (1.7807– 2.6379) and 1.1714 (0.9992– 1.3733); telmisartan, 1.0745 (0.8139– 1.4186) and 1.1057 (0.8379– 1.4591); and amlodipine, 0.9421 (0.8764– 1.0126) and 0.9603 (0.8862– 1.0405). Both combination therapy and monotherapy were well tolerated by the subjects.Conclusion: The coadministration of ezetimibe/rosuvastatin 10/20 mg and ezetimibe/rosuvastatin 10/20 mg was well tolerated in healthy subjects, and the PK interaction between those two FDCs was not clinically significant.Keywords: drug‒drug interactions, pharmacokinetics, fixed-dose combination, ezetimibe, rosuvastatin, telmisartan, amlodipine

Cilofexor, an oral farnesoid X receptor agonist, and firsocostat, an oral, liver‐targeted inhibitor of acetyl‐coenzyme A carboxylase, are being investigated in combination with semaglutide for the treatment of metabolic dysfunction‐associated steatohepatitis (previously known as nonalcoholic steatohepatitis; NCT04971785). The pharmacokinetics and safety profiles of cilofexor (100 mg) and firsocostat (20 mg) were separately investigated in two phase 1 studies, each of which included healthy Japanese participants (n = 20 in the cilofexor study and n = 21 in the firsocostat study) and non‐Japanese participants (n = 20 in the cilofexor study and n = 21 in the firsocostat study). Intensive pharmacokinetic sampling was performed over 96 h following a single‐dose administration of the study drug. Safety was monitored throughout the study. In total, 39 participants completed each study. The plasma exposures of cilofexor and firsocostat (area under the concentration–time curve [AUC] calculated from time 0 to infinity [AUCinf]) in Japanese participants were 1.24‐fold and 1.98‐fold, respectively, of those in non‐Japanese participants. Both study drugs were well tolerated with no clear differences in adverse events or laboratory abnormalities between Japanese and non‐Japanese participants. The approximate 2‐fold exposure difference of firsocostat between Japanese and non‐Japanese participants at the 20 mg dose does not warrant dose reduction given the previously established safety and tolerability of once‐daily doses of firsocostat up to 200 mg. [ABSTRACT FROM AUTHOR]

Patients with psoriasis often take multiple medications due to comorbidities, raising concerns about drug–drug interactions (DDIs) during the development of new medicines. DDI risk assessments of a new small molecule showed risks of CYP3A4 autoinduction and being a sensitive CYP3A4 substrate. We conducted a real‐world evidence (RWE) claims analysis to assess the frequency of prescription claims for up to 12 months from the date of the initial psoriasis diagnosis for drugs that may interact with CYP3A4 substrates. We used 2013 to 2018 patient data from the US Merative MarketScan Research Database. Among patients diagnosed with psoriasis, less than 1% had a claim for a moderate/strong inducer, but up to 15% had a claim for moderate/strong inhibitor. Most prescriptions for CYP3A4 inhibitors or inducers included antibiotics and anticonvulsants. While CYP3A4 inducers were rarely used, those treated received more than >90 days treatment. Then, these RWE data were used to inform the early translational medicine strategy for the new investigational drug by strategically integrating DDI evaluations into a first‐in‐human healthy volunteer trial prior to studies in patients with psoriasis. The resulting DDI substudy showed that the investigational small molecule did not induce midazolam clearance but was sensitive to CYP3A inhibition, leading to the decision to exclude concomitant use of strong CYP3A4 inducers or inhibitors from clinical trials. [ABSTRACT FROM AUTHOR]

Aim Methods Results Conclusions We aimed to assess if dicloxacillin/flucloxacillin reduces the therapeutic efficacy of direct oral anticoagulants (DOACs) and the underlying molecular mechanism.In a randomized, crossover study, we assessed whether dicloxacillin reduces oral absorption of drugs through P‐glycoprotein (P‐gp) during 10 and 28 days of treatment. To study the impact of dicloxacillin/flucloxacillin on intestinal and hepatic expression of P‐gp in vitro, we usd LS174T cells and 3D spheroids of primary human hepatocytes. Finally, we used nationwide Danish health registries and the UK's Clinical Practice Research Datalink to estimate hazard ratios (HRs) for the risk of stroke and systemic embolism following dicloxacillin/flucloxacillin exposure among DOAC users, using phenoxymethylpenicillin and amoxicillin as active comparators.Dicloxacillin reduced the area under the curve of dabigatran to a geometric mean ratio 10 days of 0.67 (95% confidence interval [CI]: 0.42–1.1) and geometric mean ratio 28 days of 0.72 (95% CI: 0.39–1.4), suggesting reduced oral absorption via increased P‐gp expression. In vitro, dicloxacillin raised P‐gp expression in both intestinal and liver cells, while flucloxacillin only affected liver cells. In the pharmacoepidemiologic study, dicloxacillin and flucloxacillin were not associated with increased risk of stroke/systemic embolism (dicloxacillin vs. phenoxymethylpenicillin HR: 0.93, 95% CI: 0.72–1.2; flucloxacillin vs. amoxicillin HR: 0.89, 95% CI: 0.51–1.5).Dicloxacillin increases expression of intestinal P‐gp, leading to reduced oral absorption of dabigatran. However, concomitant use of dicloxacillin/flucloxacillin was not associated with stroke and systemic embolism among DOAC users, suggesting no clinical impact from the drug–drug interaction between dicloxacillin/flucloxacillin and DOACs. [ABSTRACT FROM AUTHOR]

AbstractThis review explores genetic contributors to drug interactions, known as drug-gene and drug-drug-gene interactions (DGI and DDGI, respectively). This article is part of a mini-review issue led by the International Society for the Study of Xenobiotics (ISSX) New Investigators Group. Pharmacogenetics (PGx) is the study of the impact of genetic variation on pharmacokinetics (PK), pharmacodynamics (PD), and adverse drug reactions. Genetic variation in pharmacogenes, including drug metabolizing enzymes and drug transporters, is common and can increase the risk of adverse drug events or contribute to reduced efficacy. In this review, we summarize clinically actionable genetic variants, and touch on methodologies such as genotyping patient DNA to identify genetic variation in targeted genes, and deep mutational scanning as a high-throughput in vitro approach to study the impact of genetic variation on protein function and/or expression in vitro. We highlight the utility of physiologically based pharmacokinetic (PBPK) models to integrate genetic and chemical inhibitor and inducer data for more accurate human PK simulations. Additionally, we analyze the limitations of historical ethnic descriptors in pharmacogenomics research. Altogether, the work herein underscores the importance of identifying and understanding complex DGI and DDGIs with the intention to provide better treatment outcomes for patients. We also highlight current barriers to wide-scale implementation of PGx-guided dosing as standard or care in clinical settings. [ABSTRACT FROM AUTHOR]

Anamorelin, a non-peptide ghrelin analog and growth hormone secretagogue, is a novel oral drug used to treat cancer cachexia. Patients with cancer cachexia frequently use several drugs and anamorelin is a substrate of cytochrome P450 (CYP) 3A4; therefore, drug-drug interactions with CYP3A4 inhibitors and inducers pose a clinical problem. In this study, we aimed to determine the concentration of anamorelin in human plasma using a simple high-performance liquid chromatography-ultraviolet (HPLC-UV)-based method. The analysis involved extracting a 200-µL plasma sample and protein precipitation using solid-phase extraction. Anamorelin was isocratically separated using a mobile phase consisting of 0.5% potassium dihydrogen phosphate (pH 4.5) and acetonitrile (61:39, v/v) on a Capcell Pack C18 MG II column (250 mm × 4.6 mm) at a flow rate of 1.0 mL/min and monitored at a detection wavelength of 220 nm. The calibration curve was linear within a plasma concentration range of 12.5-1,500 ng/mL, with a coefficient of determination of 0.9999. The intra- and inter-day coefficients of variation were 0.37-6.71% and 2.05-4.77%, respectively. The accuracy of the assay and recovery were 85.25-112.94% and > 86.58%, respectively. This proposed HPLC-UV method is simple and can be applied in clinical settings. [ABSTRACT FROM AUTHOR]

This article discusses the drug interaction between trimethoprim-sulfamethoxazole (cotrimoxazole) and folic acid/folinic acid. The interaction is frequently observed in haemato-oncological patients who are receiving trimethoprim-sulfamethoxazole for Pneumocystis Jiroveci Pneumonia (PJP) prophylaxis while also receiving folinic acid supplementation for their haematological condition. The mechanism of this interaction is the inhibition of dihydrofolate reductase (DHFR) by trimethoprim, which affects the metabolism of folic acid into active tetrahydrofolic acid (THF). While there is limited in vitro and in vivo evidence regarding the rationale of this interaction, it is recommended to prioritize folic acid over folinic acid when combining folates with trimethoprim-sulfamethoxazole prophylaxis for safety reasons. [Extracted from the article]

As a selective and potent inhibitor targeting the isocitrate dehydrogenase‐2 (IDH2) mutant protein, enasidenib obtained approval from the US Food and Drug Administration (FDA) in 2017 for adult patients with acute myeloid leukemia (AML) with an IDH2 mutation. In vitro investigations demonstrated that enasidenib affects various drug metabolic enzymes and transporters. This current investigation aimed to assess enasidenib on the pharmacokinetics (PKs) of CYP substrates, including dextromethorphan (CYP2D6 probe drug), flurbiprofen (CYP2C9 probe drug), midazolam (CYP3A4 probe drug), omeprazole (CYP2C19 probe drug), and pioglitazone (CYP2C8 probe drug), in patients with AML or myelodysplastic syndrome. Results showed that following the co‐administration of enasidenib (100 mg, once daily) for 28 days, the PK parameters AUC(0‐∞) and Cmax of dextromethorphan increased by 1.37 (90% confidence interval (CI): 0.96, 1.96) and 1.24 (90% CI: 0.94, 1.65)‐fold, respectively, compared to dextromethorphan alone. For flurbiprofen, these parameters increased by 1.14 (90%CI: 1.01, 1.29) and 0.97 (90% CI 0.86, 1.08)‐fold, respectively, when compared to flurbiprofen alone. Conversely, midazolam exhibited decreases to 0.57 (90% CI 0.34, 0.97) and 0.77 (90% CI 0.39, 1.53)‐fold, respectively, in comparison to midazolam alone. The parameters for omeprazole increased by 1.86 (90% CI: 1.33, 2.60) and 1.47 (0.93, 2.31)‐fold, respectively, compared to omeprazole alone, while those for pioglitazone decreased to 0.80 (90% CI: 0.62, 1.03) and 0.87 (90% CI: 0.65, 1.16)‐fold, respectively, in comparison to pioglitazone alone. These findings provide valuable insights into dose recommendations concerning drugs acting as substrates of CYP2D6, CYP2C9, CYP3A4, CYP2C19, and CYP2C8 when administered concurrently with enasidenib. [ABSTRACT FROM AUTHOR]

Atogepant, an oral calcitonin gene‐related peptide receptor antagonist, is approved for the preventive treatment of migraine. Atogepant is a substrate of P‐glycoprotein (P‐gp), breast cancer resistance protein, organic anion transporting polypeptide transporters, and cytochrome P450 (CYP)3A4 and 2D6. Quinidine is a strong P‐gp and CYP2D6 inhibitor. A phase 1 open‐label study evaluated the effect of P‐gp and CYP2D6 inhibition by quinidine on the pharmacokinetics of atogepant, and the safety and tolerability of atogepant and quinidine gluconate (QG) when co‐administered and when given alone in 33 healthy adults. There was no significant change in the atogepant maximum plasma concentration with QG co‐administration. The overall systemic exposure, the area under the plasma concentration‐time curve (from time 0 to time t or to infinity), of atogepant increased by 25% when co‐administered with QG. However, such an increase was not considered clinically relevant. Atogepant did not alter the mean plasma concentration of quinidine at steady state. The incidence of treatment‐emergent adverse events (TEAEs) was highest when QG was administered alone (42.4%), which was primarily due to QT prolongation. Most TEAEs reported were mild in severity and resolved within 1‐2 days. Co‐administration of atogepant with QG did not result in any unexpected tolerability findings in this phase 1 study in healthy participants. The increase in atogepant exposure during QG co‐administration could be due to inhibition of CYP2D6 (a minor contributor to atogepant clearance) as well as inhibition of P‐gp. [ABSTRACT FROM AUTHOR]

Most medications undergo metabolism and elimination via CYP450 enzymes, while uptake and efflux transporters play vital roles in drug elimination from various organs. Interactions often occur when multiple drugs share CYP450-transporter-mediated metabolic pathways, necessitating a unique clinical care strategy to address the diverse types of CYP450 and transporter-mediated drug-drug interactions (DDI). The primary focus of this review is to record relevant mechanisms regarding DDI between COVID-19 and tuberculosis (TB) treatments, specifically through the influence of CYP450 enzymes and transporters on drug absorption, distribution, metabolism, elimination, and pharmacokinetics. This understanding empowers clinicians to prevent subtherapeutic and supratherapeutic drug levels of COVID medications when co-administered with TB drugs, thereby mitigating potential challenges and ensuring optimal treatment outcomes. A comprehensive analysis is presented, encompassing various illustrative instances of TB drugs that may impact COVID-19 clinical behavior, and vice versa. This review aims to provide valuable insights to healthcare providers, facilitating informed decision-making and enhancing patient safety while managing co-infections. Ultimately, this study contributes to the body of knowledge necessary to optimize therapeutic approaches and improve patient outcomes in the face of the growing challenges posed by infectious diseases. [ABSTRACT FROM AUTHOR]

We conducted this three‐part study in healthy subjects to investigate the pharmacokinetics of tasurgratinib (orally available selective inhibitor of fibroblast growth factor receptor 1–3) and M2 (its major metabolite) under different conditions. In Part A, subjects received tasurgratinib 35 mg either fed with a high‐fat meal or fasted. In Parts B and C, subjects received tasurgratinib 35 mg alone or with either rabeprazole (acid‐reducing agent) 20 mg (Part B) or rifampin (strong CYP3A inducer) 600 mg (Part C). Primary endpoints were maximum concentration (Cmax), and areas under the plasma concentration–time curve to time of last quantifiable concentration (AUC(0–t)) and extrapolated to infinite time (AUC(0–inf)). Forty‐two subjects were enrolled, 14 each into Parts A, B, and C. In Part A, administration of tasurgratinib with a high‐fat meal resulted in 33% reduction in Cmax and ∼23% reduction in AUC(0–t) and AUC(0–inf) of tasurgratinib, and 47% reduction in Cmax with ∼30% reduction in AUC(0–t) and AUC(0–inf) of M2. In Part B, co‐administration of rabeprazole at steady state resulted in no/weak interaction with tasurgratinib (∼8% increase in AUC(0–t) and AUC(0–inf) without an effect on Cmax) and M2 (∼18% increase in AUC(0–t) and AUC(0–inf) without an effect on Cmax). In Part C, co‐administration of rifampin at steady state resulted in a weak interaction with tasurgratinib (∼16% reduction in AUC(0–t) and AUC(0–inf)) and M2 (∼12% reduction in AUC(0‐t) and AUC(0‐inf)). Administration of tasurgratinib with a high‐fat meal appeared to reduce systemic exposure of tasurgratinib, however co‐administration with an acid‐reducing agent or a CYP3A inducer had a minimal impact on pharmacokinetics. [ABSTRACT FROM AUTHOR]