Presence Of Drug-drug Interactions Research Articles

Evaluation of second-generation Bruton's tyrosine kinase inhibitors for the treatment of mantle cell lymphoma.

Second-generation Bruton's tyrosine kinase (BTK) inhibitors, acalabrutinib and zanubrutinib, are preferred agents for the treatment of relapsed and/or refractory mantle cell lymphoma (MCL) over first-generation BTK inhibitor, ibrutinib. The comparative safety and efficacy of these two agents have not been studied. Currently, the decision between using one second-generation BTK inhibitor over the other is largely dependent on provider preference, cost, organ dysfunction, presence of drug-drug interactions, adherence considerations, and theorized differences in safety outcomes due to the lack of head-to-head trials in MCL. This retrospective, observational study seeks to provide real-world data on the safety and efficacy of second-generation BTK inhibitors in the setting of relapsed and/or refractory MCL. Thirty-eight patients treated with a second-generation BTK inhibitor were evaluated. Ten percent of patients experienced a select adverse drug event (ADE) in the acalabrutinib group that included hypertension and major hemorrhage with no patients experiencing a select ADE in the zanubrutinib group. Results support historical data that acalabrutinib and zanubrutinib have a more favorable safety profile compared to ibrutinib in MCL.

Prediction of drug-drug interactions between roflumilast and CYP3A4/1A2 perpetrators using a physiologically-based pharmacokinetic (PBPK) approach.

This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict changes in the pharmacokinetics (PK) and pharmacodynamics (PD, PDE4 inhibition) of roflumilast (ROF) and ROF N-oxide when co-administered with eight CYP3A4/1A2 perpetrators. The population PBPK model of ROF and ROF N-oxide has been successfully developed and validated based on the four clinical PK studies and five clinical drug-drug interactions (DDIs) studies. In PK simulations, every ratio of prediction to observation for PK parameters fell within the range 0.7 to 1.5. In DDI simulations, except for tow peak concentration ratios (Cmax) of ROF with rifampicin (prediction: 0.63 vs. observation: 0.19) and with cimetidine (prediction: 1.07 vs. observation: 1.85), the remaining predicted ratios closely matched the observed ratios. Additionally, the PBPK model suggested that co-administration with the three perpetrators (cimetidine, enoxacin, and fluconazole) may use with caution, with CYP3A4 strong inhibitor (ketoconazole and itraconazole) or with dual CYP3A41A2 inhibitor (fluvoxamine) may reduce to half-dosage or use with caution, while co-administration with CYP3A4 strong or moderate inducer (rifampicin, efavirenz) should avoid. Overall, the present PBPK model can provide recommendations for adjusting dosing regimens in the presence of DDIs.

Change of dexmedetomidine and midazolam concentrations by simultaneous injection in an in vitro extracorporeal circuit.

Patient sedation and analgesia are vital for safety and comfort during extracorporeal membrane oxygenation (ECMO). However, adsorption by the circuit may alter drug pharmaco-kinetics and remains poorly characterized. This study is the first to examine the concentrations of DEX and MDZ in the presence of drug-drug interactions using an in vitro extracorporeal circuit system that incorporates a polymer-coated polyvinyl chloride tube, but not a membrane oxygenator. Nine in vitro extracorporeal circuits were prepared using polymer-coated PVC tubing. Once the circuits were primed and running, either a single drug or two drugs were injected as boluses into the circuit with three circuits per drug. Drug samples were drawn following injection at 2, 5, 15, 30, 60, and 120min and at 4, 12, and 24h. They were then analyzed using high-performance liquid chromatography with mass spectrometry. When compared with an injection of DEX alone, the combination of DEX and MDZ is highly changed, with DEX and MDZ affecting the availability of free drugs in the circuit. The change of DEX and MDZ concentrations was confirmed by a combination of both drugs as compared with either single-infusion DEX or MDZ in an in vitro extracorporeal circuit. Drug-drug interactions developed between DEX and MDZ through albumin in an extracorporeal circuit; as a result, the unbounded drugs might change in the circuit.

Do clinical decision support systems for prescribing improve patient safety? a systematic literature review

Clinical decision support systems (CDSS) are developed independently or connected to the electronic health record (EHR) or other computerized systems. The study begins with identification by searching the literature through the Google Scholar, PubMed and ScienceDirect databases. The search results obtained 5,595 articles. Forty-two articles were obtained, which were used further. Most of the research focus is on "CDSS development and evaluation". In terms of impacts, the most common is "reduce prescribing errors". One of the biggest problems reported was the presence of "alert fatigue," which was felt to be disturbing to doctors and pharmacists. CDSS must be supported by a method that is able to indicate the presence of drug-drug interactions (DDI). The use of alerts indicating the presence of a DDI should be interpreted using clinical judgment to determine the risks and benefits of a particular drug for a specific patient. The performance of CDSS is mostly reported to have been able to reduce prescribing errors, which in turn will improve patient safety. However, increased adherence to clinical protocols has not been widely reported. Complaints that are still quite a lot reported are the presence of "alert fatigue", which can interfere with effectiveness.

Pharmacokinetic Modeling of Warfarin І - Model-based Analysis of Warfarin Enantiomers with a Target Mediated Drug Disposition Model Reveals CYP2C9 Genotype-dependent Drug-drug Interactions of S-Warfarin.

The objective of this study is to characterize the impact of CYP2C9 genotype on warfarin drug-drug interactions when warfarin is taken together with fluconazole, a cytochrome P450 (CYP) inhibitor, or rifampin, a CYP inducer with a nonlinear mixed effect modeling approach. A target mediated drug disposition model with a urine compartment was necessary to characterize both S-warfarin and R-warfarin plasma and urine pharmacokinetic profiles sufficiently. Following the administration of fluconazole, our study found subjects with CYP2C9 *2 or *3 alleles experience smaller changes in S-warfarin CL compared with subjects without these alleles (69.5%, 64.8%, 59.7% and 47.8% decrease in subjects with CYP2C9 *1/*1, *1/*3, *2/*3 and *3/*3 respectively). Whereas, following the administration of rifampin, subjects with CYP2C9 *2/*3 or CYP2C9 *3/*3 experience larger changes in S-warfarin CL compared with subjects with at least one copy of CYP2C9 *1 or *1B (115%, 111%, 119%, 198% and 193% increase in subjects with CYP2C9 *1/*1, *1B/*1B, *1/*3, *2/*3 and *3/*3 respectively). The results suggest different dose adjustments are potentially required for patients with different CYP2C9 genotypes if warfarin is administered together with CYP inhibitors or inducers. Significance Statement The present study found a target mediated drug disposition model is needed to sufficiently characterize the clinical pharmacokinetic profiles of warfarin racemates under different co-treatments in subjects with various CYP2C9 genotypes, following a single dose of warfarin administration. The study also found S-warfarin, the pharmacologically more active ingredient in warfarin, exhibits CYP2C9 genotype-dependent drug-drug interactions, which indicates the dose of warfarin may need to be adjusted differently in subjects with different CYP2C9 genotypes in the presence of drug-drug interactions.

Evaluation of the potential drug-drug interactions at orthopedics and traumatology outpatient clinics of a tertiary care hospital

Purpose: The aim of the present study is to determine the frequency and severity of possible drug-drug interactions (DDIs) in the prescriptions of patients who admitted to the orthopedics and traumatology outpatient clinics.
 Materials and Methods: This cross-sectional, retrospective study analyzed the prescription data of patients that admitted to orthopedics and traumatology outpatient clinics of a tertiary care hospital from January 1, 2020 to February 15, 2020. The severity of DDIs was interpreted using the Lexi-comp® drug interaction database. Relationship between the presence of DDIs and the number of prescribed drugs were evaluated. 
 Results: Out of 753 patient data evaluated, a total of 2248 drugs were prescribed. Among 669 polypharmacy patients, 293 (43.8%) patients had one or more potential DDIs. A total of 437 DDIs were detected of which 300 (68.6%) were D, 82 (18.8%) were X, 49 (11.2%) were C and 6 (1.4%) were B risk category interactions. The most common DDIs were between systemic Diclofenac and topical Diclofenac, (14.4%) The presence of potential DDIs was significantly associated with adult age and female gender.
 Conclusion: Although, the severity of the potential DDIs in orthopedics and traumatology outpatient clinics were generally moderate and manageable, it is crutial for physicians to be aware of the interactions between the most frequently prescribed drugs in orthopedics and traumatology outpatient clinics, monitor patients for the safe use of drugs.

Italian Emergency Department Visits and Hospitalizations for Outpatients' Adverse Drug Events: 12-Year Active Pharmacovigilance Surveillance (The MEREAFaPS Study).

BackgroundAdverse drug event (ADEs) are a significant cause of emergency department (ED) visits and consequent hospitalization. Preventing ADEs and their related ED visits in outpatients remains a public health safety challenge. In this context, the aims of the present study were to describe the frequency, seriousness and preventability of outpatients’ ADE-related ED visits and hospitalizations in the Italian general population, and to identify the presence of potential predictors of ADE-related hospitalization.MethodsWe performed a nationwide, multicentre, observational, retrospective study based on reports of suspected ADEs collected between January 1, 2007 and December 31, 2018 in 94 EDs involved in the MEREAFaPS project. Patients’ demographic characteristics, their clinical status, suspected and concomitant drugs, ADE description, and its degree of seriousness, were collected. Causality and preventability were assessed using validated algorithms, and logistic regression analyses were used to estimate the reporting odds ratios (RORs) with 95% confidence intervals (CIs) of ADE-related hospitalization, considering the following covariates: age, sex, ethnicity, number of implicated medications, parenteral administration, presence of interaction, therapeutic error, and/or complementary and alternative medicines (CAM).ResultsWithin 12 years, 61,855 reports of suspected ADE were collected, of which 18,918 (30.6%) resulted in hospitalization (ADE defined as serious). Patients were mostly female (56.6%) and Caucasians (87.7%), with a mean age of 57.5 ± 25.0 years. 58% of patients were treated with more than two drugs, and 47% of ADEs leading to hospitalization were preventable. Anticoagulants, antibiotics, and nonsteroidal anti-inflammatory drugs (NSAIDs) were the most frequently implicated agents for ED visits and/or hospitalization, which included clinically significant ADEs, such as haemorrhage for anticoagulants, moderate to severe allergic reactions for antibiotics, and dermatologic reactions and gastrointestinal disturbances for NSAIDs. Older age (1.54 [1.48–1.60]), higher number of concomitantly taken drugs (2.22 [2.14–2.31]), the presence of drug-drug interactions (1.52 [1.28–1.81]), and therapeutic error (1.54 [1.34–1.78]), were significantly associated with an increased risk of hospitalization.ConclusionOur long-term active pharmacovigilance study in ED provided a valid estimation of ADE-related hospitalization in a representative sample of the Italian general population and can suggest further focus on medication safety in outpatients, in order to early recognise and prevent ADEs.

Assessment of drug–drug interactions between chemotherapeutic and chronically used medications at Khartoum Oncology Hospital

Background: Drug–drug interactions (DDIs) in oncology are significantly crucial because chemotherapeutic drugs usually have a narrow therapeutic index. Many DDIs are expected to be present between chemotherapeutic agents and chronically used medications as the number of DDIs increases in parallel with the number of drugs taken. Because of the limited literature about this area in Sudan. Thus, this study was conducted to assess the DDIs between chemotherapeutic and chronically used medications in Sudanese patients.Methods: This study was carried out in Khartoum Oncology Hospital from March to May 2019. The data were collected using data collection sheets that were filled from patient records and direct interviews with the patients. The presence of DDIs was detected by Lexicomp® drug interaction software. Results: A total of 117 patients have been involved in this study. The main DDIs between chemotherapeutic and chronically used medications were identified in 20.5% of patients, which represented 8% of the total DDIs between all drugs. Of these, 76% of the DDIs were pharmacodynamic (PD), 20% were pharmacokinetic (PK), and 4% were both PD and PK. The majority (92%) of these DDIs have been moderate in severity and had the risk rate of C (84%). 12.5% of these patients experienced clinical consequences for which they were admitted to the emergency department. DDIs between antihypertensive medications and paclitaxel were the most common (68%). There was a significant association between the age and the presence of DDIs (P = 0.017). Conclusion: DDIs between chemotherapeutic and chronically used medications represented 8% of the total identified DDIs in the study patients.

Quantifying Hepatic Enzyme Kinetics of (-)-∆9-Tetrahydrocannabinol (THC) and Its Psychoactive Metabolite, 11-OH-THC, through In Vitro Modeling.

The prevalence of cannabis use and the concentrations of the psychoactive cannabinoid in cannabis, (-)-∆9-tetrahydrocannabinol (THC), are rising. Physiologically based pharmacokinetic modeling and simulations (PBPK M&S) can mechanistically predict exposure of THC and its major and active metabolite, 11-hydroxy-THC (11-OH-THC). To build a THC/11-OH-THC PBPK model, mechanistic information about the disposition of these compounds is necessary, including the drug-metabolizing enzymes (DMEs) involved and the fraction metabolized (fm) and metabolic kinetic parameters (intrinsic clearance, maximal formation rate, and Km) via the identified enzymes. We previously identified and quantified the fm of DMEs involved in hepatic depletion of THC and 11-OH-THC. In this study, we extend this work to characterize the enzyme kinetics of THC and 11-OH-THC by monitoring their depletion and formation of some of their metabolites in pooled human liver microsomes. A P450 and UDP-glucuronosyltransferase (UGT) kinetic model was fitted to the concentration-time depletion/formation profiles to establish the contribution and kinetics of the individual DME pathways. CYP2C9 pathway was the major pathway for depletion of THC (fm = 0.91, Km,u = 3 nM) and formation of 11-OH-THC. The remaining THC depletion pathway was attributed to CYP2D6. 11-OH-THC was depleted by UGTs (fm = 0.67 and Km,u = 39 nM), CYP3A4 (fm = 0.18, Km,u = 824 nM), and CYP2C9 (fm = 0.15, Km,u = 33 nM). These mechanistic in vitro data can be used to predict the exposure of THC and 11-OH-THC in healthy and special populations, including in the presence of drug-drug interactions, via PBPK M&S.

SignalDetDDI: An SAS macro for detecting adverse drug-drug interactions in spontaneous reporting systems.

Statistical methods for detecting adverse drug reactions (ADRs) resulting from drug-drug interactions (DDIs) have been used in recent years to analyze the datasets in spontaneous reporting systems. We provide the SignalDetDDI macro in SAS to calculate the criteria for detecting ADRs resulting from the concomitant use of two drugs. We outline two criteria for detecting DDIs with the combination of two drugs and illustrate the implementation of the macro by way of an example. To implement the macro, a user specifies the target ADR and the two drugs to be evaluated. The SignalDetDDI macro outputs a table showing the number of reports on ADRs, the values of the two criteria for detecting ADRs, and the presence of DDIs. This macro enables users to easily and automatically assess the clinical DDIs that result from ADRs. The SignalDetDDI macro is freely available in the Supporting Information.

Interacciones medicamentosas en pacientes pluripatológicos

Objective To determine the prevalence of relevant drug-drug interactions (DDIs) and associated predictor factors in a sample of patients with multiple complex chronic diseases (polypathological patients) receiving multiple drug therapy. Our secondary objective was to determine the acceptance of a drug interaction reporting program with recommendations addressed to the prescribing physicians. Subjects and methods A cross-sectional study performed in three primary care centres assigned to a teaching hospital. All patients with 2 or more chronic diseases and treated simultaneously with 5 or more drugs were recruited in the study. DDIs were detected by using Drug-Reax System ® (Micromedex) program, the Drug Data Base (Bot) Spanish General Council of Official Colleges of Pharmacists or literature search when needed. Those DDIs which, according to the opinion of the pharmacist investigators, required any intervention were considered relevant. Acceptance of the reported DDI recommendations was evaluated by means of a survey addressed by primary care physicians ("acceptable," pertinent recommendation to modify treatment). Results A total of 283 polypathological polymedicated patients were included. Mean age was 74.5 years (range 43–100 years). Mean number of diseases per patient was 2.5 and prescriptions 9.7). Out of a total of 2748 drug prescriptions, 1053 DDIs in 250 patients (96.5%) were identified. Of these, 45% were filtered as relevant DDIs. The presence of ischemic heart disease, two or more hospital admissions and having received 7 or more prescriptions were associated with the presence of DDIs. 177 informs containing 473 recommendations about DDIs were sent to primary care physicians from our Pharmacy Department. 339 recommendations were answered by primary care physicians, and 84% were favourably accepted. Conclusions Almost every polypathological polymedicated patient is exposed to at least one DDI and about a 60% would require any intervention. Appropriate filtering and personalising recommendations in a collaborative way may represent an adequate manner to improve the risk-benefit ratio of the drug prescriptions.

Arzneimittelwechselwirkungen in den Verordnungen von Patienten vor und nach dem Herzinfarkt: Resultate, des MONICA Augsburg Herzinfarktregisters

The prescriptions of 603 patients who had survived acute myocardial infarction (AMI) for at least one year and were registered from 1 Oct 84 to 31 Dec 86 in the Coronary Event Register of the MONICA project Augsburg were analyzed for the presence of drug-drug interactions with the aid of a computerized drug information system (SMA). Prior to AMI, 59% of patients were treated (average of 2 active substance per patient), 100% were treated on release from hospital (4.5 active substances), and 96% one year after AMI (5.8 active substances). Potential drug-drug interactions were found in 18% of patients before AMI, 65% on discharge from hospital, and 66% one year after AMI. While the potential frequency and severity of interactions are minor on average, prescriptions frequently contain several interactions. Calculations show that at least 5-6% of all prescriptions after AMI will produce interactions, so that drug safety for this high-risk patient group can be enhanced by a drug information system. Beta-blockers are the substance group most frequently involved in potential interactions in AMI patients.

Physiologically based pharmacokinetics of drug-drug interaction: a study of tolbutamide-sulfonamide interaction in rats.

A blood flow rate-limited pharmacokinetic model was developed to study the effect of sulfonamide on the plasma elimination and tissue distribution of 14C-tolbutamide (TB) in rats. The sulfonamides (SA) used were sulfaphenazole (SP), sulfadimethoxine (SDM), and sulfamethoxazole (SMZ). The tissue-to-plasma partition coefficients (Kp) of all tissues studied, i.e., lung, liver, heart, kidney, spleen, G.I. tract, pancreas, brain, muscle, adipose tissue, and skin, increased in the presence of SA, but except for brain, liver, and spleen, the tissue-to-plasma unbound concentration ratio (Kp,f) of other tissues did not show a significant alteration. This suggested that the tissue binding of TB is not affected by SA and that the increase of Kp is due mainly to the displacement of plasma protein-bound TB by SA. The concentrations of TB in several tissues and plasma were predicted by a physiologically based pharmacokinetic model using in vitro plasma binding and metabolic parameters, the plasma-to-blood concentration ratio and the tissue-to-plasma unbound concentration ratios having been determined from both the tissue and plasma concentrations of TB at the beta-phase after intravenous administration of TB and the plasma free fraction. The predicted concentration curves of TB in each tissue and in plasma showed good agreement with the observed values except for the brain, for which the predicted concentrations were lower than the observed values in the early time period. In the SP- and SDM-treated rats, the predicted free concentration of TB in the target organ, the pancreas, at 6 h was six times higher than that of the control rats. From these findings, it is suggested that physiologically based pharmacokinetic analysis could be generally useful to predict approximate plasma and tissue concentrations of a drug in the presence of drug-drug interaction.