Drug-drug Interactions In Patients Research Articles

Impact of Comorbidities and Drug Interactions in Patients With Metastatic Castration-Resistant Prostate Cancer Receiving Androgen Receptor Pathway Inhibitors.

Androgen receptor pathway inhibitors (ARPIs) are widely prescribed in metastatic castration-resistant prostate cancer (mCRPC). Real-world frequencies and potential impacts of comorbidities and concomitant medication (conmed) interactions with ARPIs are not well described. Patients receiving ARPIs for mCRPC were identified from the electronic Prostate Cancer Australian Database (ePAD). Demographics, clinicopathologic characteristics, and outcome data were extracted. Conmeds and comorbidities were collected from medical records. Potential interacting comorbidities were defined from trial and post-trial data. Clinically significant drug-drug interactions (DDIs) were identified using UpToDate Lexicomp and Stockley's databases. Patient characteristics, comorbidity interactions, DDIs, and outcomes were analyzed. Two hundred thirty-five patients received first- or second-line ARPIs for mCRPC from 2012 to 2021, with a median follow-up of 27 months. One hundred sixteen received abiraterone acetate (AAP) and 135 received enzalutamide (ENZ). The median age was 74 years, and the median number of conmeds was 4. Clinically significant DDIs occurred in 55 (47%) AAP patients and 90 (67%) ENZ patients. Only 5% of DDIs were predicted to affect ARPI pharmacokinetics (PK) or pharmacodynamics, whereas 95% were predicted to impact conmed PK or increase toxicity risk. In patients receiving ENZ, DDIs were associated with lower PSA50 (50% v 74%, P = .04) and poorer overall survival (28 v 45 months, P = .04), although statistical significance was not maintained on multivariate analysis. No significant survival differences were seen with DDIs in patients receiving AAP. Potential interactions between comorbidities and ARPI were present in 72% on AAP and 14% on ENZ with no significant associated survival differences. DDIs and drug-comorbidity interactions in real-world patients receiving ARPIs for mCRPC are common and may affect outcomes. Ongoing clinician education regarding DDIs is necessary to optimize patient outcomes.

Review of drug-drug interactions in patients with prostate cancer.

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. 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. 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. 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.

An Assessment of Different Decision Support Software from the Perspective of Potential Drug-Drug Interactions in Patients with Chronic Kidney Diseases.

Chronic kidney disease (CKD) is a multifaceted disorder influenced by various factors. Drug-drug interactions (DDIs) present a notable risk factor for hospitalization among patients with CKD. This study aimed to assess the frequency and attributes of potential DDIs (pDDIs) in patients with CKD and to ascertain the concordance among different Clinical Decision Support Software (CDSS). A cross-sectional study was conducted in a nephrology outpatient clinic at a university hospital. The pDDIs were identified and evaluated using Lexicomp® and Medscape®. The patients' characteristics, comorbidities, and medicines used were recorded. The concordance of different CDSS were evaluated using the Kendall W coefficient. An evaluation of 1121 prescribed medications for 137 patients was carried out. The mean age of the patients was 64.80 ± 14.59 years, and 41.60% of them were male. The average year with CKD was 6.48 ± 5.66. The mean number of comorbidities was 2.28 ± 1.14. The most common comorbidities were hypertension, diabetes, and coronary artery disease. According to Medscape, 679 pDDIs were identified; 1 of them was contraindicated (0.14%), 28 (4.12%) were serious-use alternative, and 650 (9.72%) were interventions that required closely monitoring. According to Lexicomp, there were 604 drug-drug interactions. Of these interactions, 9 (1.49%) were in the X category, 60 (9.93%) were in the D category, and 535 (88.57%) were in the C category. Two different CDSS systems exhibited statistically significant concordance with poor agreement (W = 0.073, p < 0.001). Different CDSS systems are commonly used in clinical practice to detect pDDIs. However, various factors such as the operating principles of these programs and patient characteristics can lead to incorrect guidance in clinical decision making. Therefore, instead of solely relying on programs with lower reliability and consistency scores, multidisciplinary healthcare teams, including clinical pharmacists, should take an active role in identifying and preventing pDDIs.

Investigation of polypharmacy, antimicrobial-related potential drug-drug interactions in patients with hematological malignancies.

Drug-drug interactions (DDIs) occur when one drug interferes with the pharmacological activity of another and can lead to increased side effects. The purpose of this study was to examine potential interactions between antimicrobials and other drugs in patients with hematological malignancies (HMs). The medications used by 233 patients with HMs before and during hospitalization in Ankara City Hospital Hematology Clinic services between January 2021 and July 2021 were examined. Potential DDIs (pDDIs) were identified through UptoDate, Drugs.com, and MedScape databases. The effects of major antimicrobial-related pDDIs on patients were examined. Agreement between the two interaction systems was judged based on the kappa test. SPSS R Version 4.0.2 was used in the statistical analysis of the data, p<.05 was considered significant. The prevalence of polypharmacy before hospitalization was determined as 22.7%. Diagnosed with acute leukemia and multiple myeloma, more antimicrobial-related pDDIs were detected during hospitalization (p<.001). A total of 758 antimicrobial-related pDDIs, which were in the major category in at least one of the three databases, were detected in 72.5% (169/233) of the participants. It was determined that the total hospitalization period of patients with major antimicrobial-related pDDIs was longer (p<.001). There was negligible agreement between UptoDate and Dugs.com and between Drugs.com and MedScape (kappa: 0.008 for both). There was no compatibility between UptoDate and MedScape (kappa<0). Interactions between antimicrobials and other drugs are undesirable problems. Further studies are required to evaluate the clinical and economic effects of the interactions on patients with HMs.

Risk Factors for Potential Drug-Drug Interactions in Patients on Chronic Peritoneal Dialysis

Plain Language SummaryIntroductionWhen people take many medications at the same time, it can be tricky. One medication might change how another one works if they are taken together, which can lead to harmful effects. This is known as potential drug-drug interactions (pDDIs), which means that two drugs might interact with each other in a way that could be harmful. This risk is even higher in patients with chronic kidney disease. Our study looked at how common pDDIs are and what factors are associated with them in patients undergoing a long-term kidney treatment called peritoneal dialysis.MethodsWe studied 140 patients who were on peritoneal dialysis and were being treated at four major hospitals in Serbia. We used a software called Lexicomp to identify pDDIs. We also used a statistical method called multiple linear regression to find out what factors might predict pDDIs.ResultsWe found that pDDIs are common, especially in patients who had just started peritoneal dialysis, had diabetes, or were taking many medications. This was particularly true for medications used to control irregular heart rhythms, known as antiarrhythmics. We also found that women had a higher risk of serious pDDIs, especially if they were taking many medications. This is important because women are more likely to experience unwanted side effects from medications.ConclusionOur study highlights the importance of checking for pDDIs, especially in patients who are at high risk. This can help avoid serious medical consequences.

Drug-Drug Interactions in Patients with Acute Respiratory Distress Syndrome.

Acute respiratory distress syndrome (ARDS) is a potential life-threatening, heterogenous, inflammatory lung disease. There are no data available on potential drug-drug interactions (pDDIs) in critically ill patients with ARDS. This study analyzed pDDIs in this specific cohort and aimed to investigate possible associations of coronavirus disease 2019 (COVID-19) as an underlying cause of ARDS and treatment with extracorporeal membrane oxygenation (ECMO) with the occurrence of pDDIs. This retrospective study included patients ≥18 years of age diagnosed with ARDS between January 2010 and September 2021. The Janusmed database was used for the identification of pDDIs. A total of 2694 pDDIs were identified in 189 patients with a median treatment duration of 22 days. These included 323 (12%) clinically relevant drug combinations that are best avoided, corresponding to a median rate of 0.05 per day. There was no difference in the number of pDDIs between COVID-19- and non-COVID-19-associated ARDS. In patients treated with ECMO, the rate of the most severely graded pDDIs per day was significantly higher compared with those who did not require ECMO. PDDIs occur frequently in patients with ARDS. On average, each patient may encounter at least one clinically relevant drug combination that should be avoided during their intensive care unit stay.

Assessment of drug-drug interactions in patients with chronic kidney disease

Assessment of drug-drug interactions in patients with chronic kidney disease

The association between warfarin usage and international normalized ratio increase: systematic analysis of FDA Adverse Event Reporting System (FAERS).

Elevated international normalized ratio (INR) has been commonly reported as an adverse drug event (ADE) for patients taking warfarin for anticoagulant therapy. The purpose of this study was to determine the association between increased INR and the usage of warfarin by using the pharmacovigilance data from the FDA Adverse Event Reporting System (FAERS). The ADEs in patients who took warfarin (N = 77,010) were analyzed using FAERS data. Association rule mining was applied to identify warfarin-related ADEs that were most associated with elevated INR (n = 15,091) as well as possible drug-drug interactions (DDIs) associated with increased INR. Lift values were used to identify ADEs that were most commonly reported alongside elevated INR based on the correlation between both item sets. In addition, this study sought to determine if the increased INR risk was influenced by sex, age, temporal distribution, and geographic distribution and were reported as reporting odds ratios (RORs). The top 5 ADEs most associated with increased INR in patients taking warfarin were decreased hemoglobin (lift = 2.31), drug interactions (lift = 1.88), hematuria (lift = 1.58), asthenia (lift = 1.44), and fall (lift = 1.32). INR risk increased as age increased, with individuals older than 80 having a 63% greater likelihood of elevated INR compared to those younger than 50. Males were 9% more likely to report increased INR as an ADE compared to females. Individuals taking warfarin concomitantly with at least one other drug were 43% more likely to report increased INR. The top 5 most frequently identified DDIs in patients taking warfarin and presenting with elevated INR were acetaminophen (lift = 1.81), ramipril (lift = 1.71), furosemide (lift = 1.64), bisoprolol (lift = 1.58), and simvastatin (lift = 1.58). The risk of elevated INR increased as patient age increased, particularly among those older than 80. Elevated INR frequently co-presented with decreased hemoglobin, drug interactions, hematuria, asthenia, and fall in patients taking warfarin. This effect may be less pronounced in women due to the procoagulatory effects of estrogen signaling. Multiple possible DDIs were identified, including acetaminophen, ramipril, and furosemide.

The prevalence of relevant drug-drug interactions and associated clinical outcomes in patients with cancer-associated thrombosis on concurrent anticoagulation and anticancer or supportive care therapies

BackgroundA main concern in the management of patients with cancer-associated thrombosis (CAT) is drug-drug interactions (DDIs) between anticoagulants and anticancer therapies. Their clinical implications remain unclear. MethodsTo quantify the prevalence of DDIs and risks of recurrent venous thromboembolism (VTE) and bleeding events in patients with CAT on anticoagulation, we conducted a retrospective cohort study in patients with CAT on concurrent anticoagulants and anticancer and/or supportive care therapies. All patients were followed for 6 months from CAT diagnosis or until death (whichever occurred first). The primary outcome was the percentage of patients with anticoagulant DDIs classified as risk C, D, or X in Lexicomp® at any time during the 6 months. Secondary outcomes included recurrent VTE and clinically relevant bleeding events. We calculated the 6-month cumulative incidence of outcomes with 95 % confidence interval (CI) and compared those with and without DDIs, considering death as a competing risk. ResultsAmong 267 patients included, 111 (41.6 %) had DDIs with anticoagulants at any time during the study. Those on DOACs at any time had more DDIs compared to LMWH (50.9 % vs 19.3 %, p < 0.0001). The 6-month incidence was 8.2 % (95 % CI 5.3–11.9) for recurrent VTE and 6.7 % (95 % CI 4.2–10.2) for clinically relevant bleeding, with no significant differences between groups with or without DDIs. ConclusionsThere are high incidences of DDIs in patients with CAT on anticoagulants, more with DOACs. DDIs classified as risk C, D, or X by Lexicomp® were not associated with recurrent VTE or bleeding events in our cohort.

B-337 Case Report: Fatal Opioid Overdose Induced by Over-the-Counter Cold Medication Diphenhydramine

Abstract Background Accidental drug-related deaths frequently arise following ingestion of multiple co-intoxicants, including opioid analgesics. Hydrocodone, the most prescribed opioid for pain management, is metabolized by hepatic enzymes CYP2D6 and CYP3A4 to the pharmacologically active metabolite hydromorphone and the inactive metabolite norhydrocodone, respectively. As a result, inhibition of CYP2D6 by other pharmacologic agents can impair the analgesic properties of hydrocodone and prolong its half-life in circulation. One such example is diphenhydramine, which is a potent inhibitor of CYP2D6 activity. This case highlights a drug-drug interaction likely resulting in an accidental fatal opioid overdose. Case Presentation A 58-year-old female had longstanding prescriptions for hydrocodone/acetaminophen (Norco® 10/325), alprazolam, carisoprodol, and diltiazem. The decedent had recently taken an over-the-counter cold medication, diphenhydramine (Benadryl), shortly preceding death. A toxicology report (NMS labs, Horsham, PA) from a post-mortem femoral blood sample detected the presence of the following therapeutic compounds by High Performance Liquid Chromatography/Time of Flight-Mass Spectrometry (LC/TOF-MS) analysis: acetaminophen (14 μg/mL), hydrocodone (410 ng/mL), dihydrocodeine (hydrocodol, 24 ng/mL), alprazolam (42 ng/mL), carisoprodol (88 ng/mL), diltiazem (110 ng/mL), and diphenhydramine (150 ng/mL). Hydromorphone, the active metabolite of hydrocodone, was not detected (&amp;lt;2 ng/mL). With the exception of hydrocodone, which was present at fatal concentrations, all other compounds were within therapeutic range. Together, these observations are strongly suggestive of a drug-drug interaction leading to impaired hydrocodone metabolism. Conclusions This case report highlights a fatal opioid overdose as a result of CYP2D6 inhibition by diphenhydramine, a readily available over-the-counter medication. Post-mortem toxicological analysis revealed hydrocodone was present in lethal concentrations, whereas its pharmacologically active metabolite, hydromorphone, was undetectable at time of autopsy. Further, the patient was prescribed a formulation of hydrocodone in combination with acetaminophen, which was present at therapeutic concentrations despite the two drugs having similar elimination half-lives. These toxicological findings suggest administration of diphenhydramine precipitated a deadly accumulation of hydrocodone in the deceased. Overall, this case report underscores the importance of understanding and preventing harmful drug-drug interactions in patients taking opioid medications for pain management.

Altered Gene Expression of Cytochrome P450 and ABC Transporter in Human Hepatocellular Carcinoma HepG2 Cells Exposed to Bardoxolone Methyl.

Bardoxolone methyl (BX) is expected to be an innovate therapeutic agent for chronic kidney disease (CKD). The aim of the present study was to examine whether the expression of subtypes of cytochrome P450 (CYP) and ABC transporters was altered in human hepatocellular carcinoma HepG2 cells by exposure to BX. The expression of mRNAs for CYP1A2, CYP2E1, P-glycoprotein, multidrug resistance-associated protein 1-3, and breast cancer resistance protein was significantly increased by exposure of HepG2 cells to BX, while the expression of CYP3A4 mRNA was significantly decreased under the same conditions. BX had no significant effect on the expression of mRNAs for CYP2C9 and CYP2C19 in HepG2 cells. In conclusion, this study demonstrated that the gene expression of several CYPs and ABC transporters in HepG2 cells was altered when exposed to BX, suggesting the need to pay careful attention to drug-drug interactions in patients receiving BX for CKD treatment.

Evaluation and clinical management of drug-drug interactions in hypertensive patients associated co-morbidities: A study in general medicine and ICU ward

This comparative study aims to evaluate and compare the clinical management of drug-drug interactions (DDIs) in hypertensive patients with associated co-morbidities, specifically focusing on the practices in general medicine and ICU ward settings. Hypertensive patients commonly experience co-morbidities that require multiple medications, increasing the risk of DDIs and subsequent adverse events. Understanding the current evaluation and management strategies for DDIs in these patient populations is essential for optimizing patient outcomes. This research investigates the approaches employed in general medicine and ICU wards, including DDI identification, assessment, and intervention methods. By comparing these practices, the study aims to identify potential variations, challenges, and areas for improvement in DDI management across these clinical settings. The findings of this study will contribute to the development of evidence-based guidelines and recommendations for enhancing the clinical management of DDIs in hypertensive patients with co-morbidities, ultimately improving patient safety and therapeutic outcomes.

Management of Polypharmacy and Potential Drug-Drug Interactions in Patients with Mycobacterial Infection: A 1-Year Experience of a Multidisciplinary Outpatient Clinic.

In 2022, we opened an outpatient clinic for the management of polypharmacy and potential drug-drug interactions (pDDIs) in patients with mycobacterial infection (called GAP-MyTB). All patients who underwent a GAP-MyTB visit from March 2022 to March 2023 were included in this retrospective analysis. Fifty-two patients were included in the GAP-MyTB database. They were given 10.4 ± 3.7 drugs (2.8 ± 1.0 and 7.8 ± 3.9 were, respectively, antimycobacterial agents and co-medications). Overall, 262 pDDIs were identified and classified as red-flag (2%), orange-flag (72%), or yellow-flag (26%) types. The most frequent actions suggested after the GAP-MyTB assessment were to perform ECG (52%), therapeutic drug monitoring (TDM, 40%), and electrolyte monitoring (33%) among the diagnostic interventions and to reduce/stop proton pump inhibitors (37%), reduce/change statins (14%), and reduce anticholinergic burden (8%) among the pharmacologic interventions. The TDM of rifampicin revealed suboptimal exposure in 39% of patients that resulted in a TDM-guided dose increment (from 645 ± 101 to 793 ± 189 mg/day, p < 0.001). The high prevalence of polypharmacy and risk of pDDIs in patients with mycobacterial infection highlights the need for ongoing education on prescribing principles and the optimal management of individual patients. A multidisciplinary approach involving physicians and clinical pharmacologists could help achieve this goal.

EPH239 Treatment Pattern and Drug-Drug Interactions in Patients with Metastatic Castration Resistant Prostate Cancer

EPH239 Treatment Pattern and Drug-Drug Interactions in Patients with Metastatic Castration Resistant Prostate Cancer

Current status and research progress of nanoparticle application in superficial fungal infection.

Superficial fungal infections (SFIs) are characterized by diverse etiologies, complex pathogenesis, and marked geographical differences in patient symptoms. Conventional management of SFIs is associated with complications such as hepatotoxicity, skin problems, severe headaches, and clinical difficulties including intractable relapses and drug-drug interactions in patients with chronic diseases remain to be addressed. Moreover, in topical treatment, low penetration of antifungal drugs in hard tissues such as finger (toe) nails and drug-resistant fungi are emerging concerns in current antifungal therapy. Nanotechnology has been a leading research topic in recent years for new dosing forms of antifungal drugs, chemical modification of traditional drugs, and pharmacokinetic improvement, providing potential opportunities for the effective treatment of SFIs. The present study reviewed the direct use of nanoparticles in SFIs and the use of nanoparticles as carriers in SFIs and discussed their future medicinal applications.https://www.europeanreview.org/wp/wp-content/uploads/01-12915-PM-29863.jpg.

Potential drug-drug interactions in patients presenting with osteoarthritis to community orthopaedic clinics of Abbottabad, Khyber Pakhtunkhwa: A cross-sectional study

Osteoarthritis (OA) causes long-term pain and disorders of lower extremities. Paracetamol is the drug of choice, however, NSAIDs, opioids and steroids are frequently employed in the symptomatic relief of OA. The prescribing of multiple analgesics leads to potential drug-drug interactions (pDDIs). The primary objective of this study was to identify the prevalence and predictors of pDDIs in OA. A total of three hundred and eighty-six patients, either newly diagnosed or with a history of OA were enrolled for this cross-sectional study. Data regarding patients' demographics, clinical characteristics and prescribed medications were recorded from the prescriptions and examined for the pDDIs using Medscape multi-drug interaction checker. Among 386, most patients were females (53.4%). The most prevalent diagnoses were knee OA (39.7%) and unspecified OA (31.3%). Paracetamol and topical NSAIDs were under-prescribed whereas an oral NSAID, Diclofenac, was the most frequently used drug in OA. Total of 109 pDDIs were found in 386 prescriptions, of which, 63.3% DDIs were categorised as moderate, followed by minor (34.9%) and major (1.8%). This study finds a prevalence of DDIs and polypharmacy among the OA patients. Collaborative efforts among healthcare providers, pharmacists, and patients themselves are essential to optimize medication regimens and minimize the polypharmacy including the associated risks as well as DDIs.

Potential drug-drug interactions in patients with non-small cell lung cancer at a university hospital in Turkey.

The aim of this study was to determine the drug profile of patients with non-small cell lung cancer (NSCLC) and to identify potential drug-drug interactions (PDDIs) during hospitalization. In particular, PDDIs in categories X and D were determined. This retrospective cross-sectional study was conducted in the oncology services of a university hospital between 2018 and 2021. PDDIs were evaluated using Lexicomp Drug Interactions® software included in UpToDate®. A total of 199 patients were included in the study. Polypharmacy was present in 92.5% of the patients and the median (min-max) number of drugs used was 8 (2-16). 32% of the patients had D and X PDDIs. A total of 16 PDDIs at risk grade X were found in 15 (7.5%) patients. A total of 81 PDDIs of risk grade D were found in 54 (27.1%) patients and a total of 276 PDDIs of risk grade C were identified in 97 (48.7%) patients. Anticancer drugs (p = 0.008), opioids (p = 0.046), steroids (p = 0.003), 5-HT3 receptor antagonists (p = 0.012), aprepitant (p = 0.025) and antihistamines (p < 0.001) were statistically more frequent among patients with PDDIs than among those without. The results of our study indicated that polypharmacy and PDDIs are common in hospitalized patients with NSCLC cancer. The monitoring of medications is critical for maximizing therapeutic effects and minimizing side effects related to PDDIs. As a part of multidisciplinary team, clinical pharmacists can contribute significantly to preventing, detecting and managing PDDIs.

Effects of Genetic Polymorphisms of Drug Metabolizing Enzymes and co-Medications on Tamoxifen Metabolism in Black South African Women with Breast Cancer.

Clinical outcomes of tamoxifen (TAM) treatment show wide interindividual variability. Comedications and genetic polymorphisms of enzymes involved in TAM metabolism contributes to this variability. Drug-drug and drug-gene interactions have seldom been studied in African Black populations. We evaluated the effects of commonly co-administered medicines on TAM pharmacokinetics in a cohort of 229 South African Black female patients with hormone-receptor positive breast cancer. We also investigated the pharmacokinetic effects of genetic polymorphism in enzymes involved in TAM metabolism, including the variants CYP2D6*17 and *29, which have been mainly reported in people of African descent. TAM and its major metabolites, N-desmethyltamoxifen (NDM), 4-OH-tamoxifen, and endoxifen (ENDO), were quantified in plasma using the liquid chromatography-mass spectrometry. The GenoPharm open array was used to genotype CYP2D6, CYP3A5, CYP3A4, CYP2B6, CYP2C9, and CYP2C19. Results showed that CYP2D6 diplotype and CYP2D6 phenotype significantly affected endoxifen concentration (P < 0.001 and P < 0.001). CYP2D6*17 and CYP2D6*29 significantly reduced the metabolism of NDM to ENDO. Antiretroviral therapy had a significant effect on NDM levels and the TAM/NDM and NDM/ENDO metabolic ratios but did not result in significant effects on ENDO levels. In conclusion, CYP2D6 polymorphisms affected endoxifen concentration and the variants CYP2D6*17 and CYP2D6*29 significantly contributed to low exposure levels of ENDO. This study also suggests a low risk of drug-drug interaction in patients with breast cancer on TAM.

Interaction of buspirone and its major metabolites with human organic cation transporters.

Buspirone, a cationic drug, is an anxiolytic and antidepressant drug. However, whether buspirone and its metabolites are interacted with organic cationic transporter remains uncertain. In this study, we examined the interaction of buspirone and its major metabolites 1-(2-pyrimidinyl)piperazine (1-PP) and 6-hydroxybuspirone (6'-OH-Bu) with hOCTs using human hepatocellular carcinoma (HepG2), human colorectal adenocarcinoma (Caco-2) cells, and S2 cells expressing OCT1 (S2hOCT1), 2 (S2hOCT2), or 3 (S2hOCT3). Coadministration of buspirone and fluorescent 4-(4-(dimethylamino)styryl)-N-methylpyridinium (ASP+ ) was examined using HepG2 cells, and [3 H]-1-methyl-4-phenylpyridinium (MPP+ ) transport was assessed in S2 cell overexpressing hOCTs. The results showed that ASP+ transport was suppressed by buspirone with an IC50 of 26.3 ± 2.9μM without any cytotoxic effects in HepG2 expressing hOCTs cells. Consistently, buspirone strongly inhibited [3 H]-MPP+ uptake by S2hOCT1, S2hOCT2, and S2hOCT3 cells with an IC50s of 89.0 ± 1.3μM, 43.7 ± 7.5μM, and 20.4 ± 1.0μM, respectively. Nonetheless, 6'-OH-Bu and 1-PP caused weak or no inhibition on ASP+ and [3 H]-MPP+ transport. These findings suggest the potential interaction of buspirone with organic cation drugs that are handled by hOCT3. However, further clinical relevance is needed to support these findings for preventing drug-drug interaction in patients who take prescribed drugs together with buspirone.

The prevalence of drug–drug interactions in cancer therapy and the clinical outcomes

BackgroundWhen a patient concomitantly uses two or more drugs, a drug–drug interaction (DDI) may occur, and patients with cancer are at high risk of DDIs because they commonly receive multiple medications. However, data on the prevalence of DDIs are scarce, especially in Saudi Arabia. ObjectiveOur aim was to evaluate the occurrence of DDIs in patients with cancer and identify risk factors for these DDIs and the clinical outcomes. MethodA retrospective cross-sectional study was conducted in KFMC. Data were collected from the medical records and phone calls, and the patient's drugs were screened for interactions using Micromedex and Lexi-Comp. The data were statistically analysed using IBM SPSS version 24 statistical program. ResultsIn 72 patients (mean age of 47 years; 11 medications), the prevalence of DDIs was 60 %, and 2 potential DDIs were identified. According to Lexi-Comp, 137 (51.8 %) were categorized as pharmacodynamics interactions. In Micromedex, 94 potential DDIs were identified, 68.1 % were categorized as pharmacokinetic interactions, the comparison between the interaction of Lexi-Comp and Micromedex for 9 drugs. Eight drug pairs showed statistically significant difference in category of interaction (P < 0.05). Six pair of drugs showed statistically significant difference in mechanism of action (p < 0.05). Number of drugs was reported as significant risk factor (p = 0.007), type of treatment such as chemotherapy (p = 0.0000) and inpatient admission in terms of length of stay in hospital was also found significant risk factor (p = 0.031). ConclusionTo prevent DDIs, Physicians and pharmacists should be more aware of these potential interactions to prevent DDIs.