Potential Drug Interactions Research Articles

In vitro mechanistic study on mycophenolate mofetil drug interactions: effect of prednisone, cyclosporine, and others.

The metabolism- and transporter-based drug-drug interactions (DDIs) between mycophenolate mofetil (MMF) and co-administered medications may be key factors for the high individual variability in MMF exposure. This study systematically assessed the influence of co-medications on the mycophenolic acid (MPA) pharmacokinetic (PK) process in vitro, particularly to provide mechanistic evidence of the metabolic interaction among steroids, cyclosporine (CsA), and MMF. Based on a previous study, we hypothesized that there are three main DDI pathways affecting MMF PK in vivo. A human hepatocyte induction study, transporter substrate/inhibition study using human embryonic kidney 293 cells, and multidrug resistance-associated protein 2 (MRP2) substrate/inhibition study using vesicle membrane were conducted to assess the mechanistic evidence of the metabolic interaction in triple therapies. The potential DDI risks associated with seven medications commonly co-administered with MMF in clinical practice were further evaluated. The in vitro results suggested that prednisolone, the active metabolite of prednisone, induces the enzymatic activity of uridine 5'-diphospho-glucuronosyltransferase (UGT), particularly the UGT1A9 and UGT2B7 isoforms, resulting in increased metabolism of MPA to MPA glucuronide (MPAG). This induction potential was not observed in CsA-treated human hepatocytes. CsA inhibits organic anion-transporting polypeptide (OATP) 1B1- and OATP1B3-mediated MPAG. Prednisolone and CsA showed no inhibitory effect on MRP2-mediated MPAG efflux. Salvia miltiorrhiza significantly inhibited organic anion-transporting polypeptide and OAT 3 activities, suggesting that it affects the hepatic uptake and renal excretion of MPAG, causing increased MPAG exposure in vivo. These identified factors may contribute to the high inter-individual variability in MMF exposure and facilitate further development of mechanistic MMF PK models and individualized therapies.

Cytochrome P450-mediated metabolic interactions between donepezil and tadalafil in human liver microsomes

Donepezil and tadalafil, commonly prescribed among older persons to treat dementia and erectile dysfunction, respectively, are primarily metabolized by cytochrome P450 (CYP) 3A4. However, the drug-drug interactions (DDIs) of these drugs are unknown. Therefore, this study evaluated the CYP-mediated metabolic interaction between donepezil and tadalafil using pooled human liver microsomes (HLMs) to predict their DDI potential. Donepezil metabolism was tadalafil-concentration dependently changed in HLMs incubated with 0.1 μM donepezil and showed the maximum 32.3% increase in the donepezil half-life at 1 μM tadalafil. The formation rates of donepezil metabolites, such as N-desbenzyl donepezil and 3-hydroxy donepezil, decreased by 28.3% and 30.3%, respectively, in HLMs incubated with 1 μM tadalafil and 0.1 μM donepezil. In contrast, neither the half-life of tadalafil nor the production rate of its metabolite, desmethylene tadalafil, was changed by >20% in the presence of donepezil (up to 1 μM). CYP3A4 activity was inhibited by tadalafil with an IC50 value of 22.6 μM but not by donepezil. After pre-incubating HLMs with tadalafil and NADPH, the tadalafil IC50 value against CYP3A4 was approximately 7.04-fold lower, suggesting time-dependent tadalafil inhibition. This study shows that the DDI between donepezil and tadalafil is primarily due to time-dependent inhibition against CYP3A4 by tadalafil.

Food Supplements and Their Use in Elderly Subjects-Challenges and Risks in Selected Health Issues: A Narrative Review.

The European population is ageing. Food Supplements (FSs) are foods with particular characteristics, consumed by elderly people for various purposes, including combating nutritional deficits. Their consumption in this age group, associated with a high prevalence of polypharmacy, can enhance interactions. Potential drug-food (or food supplements), drug-drug interactions and polypharmacy are common health issues among older adults. The prevalence of polypharmacy is high, and preliminary data also indicate that there is significant FS use, increasing the risk of the duplication of therapies and various adverse reactions as well as drug-FS and FS-FS interactions. Therefore, the intervention of health professionals in mitigating these risks is essential. This review highlights and discusses the association between FSs, polypharmacy, and adverse reactions due to the risk of potential interactions between these products. Moreover, it also provides current scientific evidence regarding the use of FSs by the elderly. A review of the challenges, advantages, and risks of using FSs in elderly people who are malnourished and/or polymedicated, focusing on the good practises needed to support healthy ageing, is presented. In this regard, this paper aims to help health professionals better deal with the issue of the use of multiple FSs and polypharmacy, overcome the malnutrition problem, and improve the health and well-being of older adults.

Pharmacokinetics and Bioavailability Study of a Novel Smoothened Inhibitor TPB15 for Treatment of Triple-Negative Breast Cancer in Rats by High Performance Liquid Chromatography-Mass Spectrometry.

Smoothened (SMO), a key component of the hedgehog signaling pathway, represents a therapeutic target for triple negative breast cancer(TNBC), yet the chemotherapy response rate in TNBC patients is only 40-50%, underscoring the urgent need for the development of novel drugs to effectively treat this condition. The novel compound TPB15, an SMO inhibitor derived from [1,2,4] triazolo [4,3-α] pyridines, demonstrated superior anti-TNBC activity and lower toxicity compared to the first SMO inhibitor vismodegib in both in vitro and in vivo. However, the compound's pharmacokinetic properties remain unclear. The present work aims to develop a simple HPLC-MS/MS method to profile the pharmacokinetics and bioavailability of TPB15 in rats as a ground work for further clinical research. Separation was performed on an Agilent ZORBAX StableBond C18 column by gradient elution using acetonitrile and 0.1% formic acid as mobile phase at a flow rate of 0.3mL/min. Multiple reaction monitoring(MRM) in positive mode with the transitions of m/z 454.2 → 100.0, 248.1 → 121.1 was employed to determine TPB15 and internal standard tinidazole, respectively. The specificity, intra- and inter- day precision and accuracy, extraction recovery, stability, matrix effect, dilution integrity and carryover of the method was validated. The pharmacokinetics and bioavailability studyof TPB15 were carried out on rats through intravenous injection at the dose of 5 mg/kg and oral gavage at the dose of 25 mg/kg, and the pharmacokinetics parameters were calculated by the non-compartment analysis using the pharmacokinetics software DAS 2.1.1. The values of specificity, intra- and inter- day precision and accuracy, extraction recovery, stability, matrix effect, dilution integrity and carryover satisfied the acceptable limits. The lower limit of quantification of this method was 10 ng/mL with a linear range of 10-2000ng/mL. The validated method was then applied to pharmacokinetics and bioavailability studies in rat by dosing with gavage (25mg/kg) and intravenous injection(5mg/kg), and the oral bioavailability of TBP15 in rat was calculated as 16.4 ± 3.5%. The pharmacokinetic parameters were calculated as following: maximum of plasma concentration (Cmax) (PO: 2787.17 ± 279.45µg/L), Time to maximum plasma concentration (Tmax) (PO: 4.20 ± 0.90 h), the area under the concentration-time curve 0 to time (AUC0-t) (PO: 17,373.03 ± 2585.18 ng/mL·h, IV: 21,129.79 ± 3360.84ng/mL·h), the area under the concentration-time curve 0 to infinity (AUC0-∞) (PO: 17,443.85 ± 2597.63 ng/mL·h, IV: 17,443.85 ± 2597.63ng/mL·h), terminal elimination half-life (t1/2) (PO: 7.26 ± 2.16h, IV: 4.78 ± 1.09h). TPB15, a promising candidate for treating TNBC, hasdemonstrated outstanding efficacy and safety in vitro and in vivo. This study established a simple, sensitive, and rapid HPLC-MS/MS bioanalytical method, developed and validated in accordance with FDA and EMA guidelines, for conducting pharmacokinetic and bioavailability studies of TPB15. The results revealed a favorable pharmacokinetic profile owing to its long t1/2. Nevertheless, the next phase of research should include formulation screening to enhance bioavailability, as well as clinical trials, metabolism pathway analysis, and assessment of potential drug-drug interactions.

Unlocking the potential of advanced large language models in medication review and reconciliation: A proof-of-concept investigation

BackgroundMedication review and reconciliation is essential for optimizing drug therapy and minimizing medication errors. Large language models (LLMs) have been recently shown to possess a lot of potential applications in healthcare field due to their abilities of deductive, abductive, and logical reasoning. The present study assessed the abilities of LLMs in medication review and medication reconciliation processes. MethodsFour LLMs were prompted with appropriate queries related to dosing regimen errors, drug-drug interactions, therapeutic drug monitoring, and genomics-based decision-making process. The veracity of the LLM outputs were verified from validated sources using pre-validated criteria (accuracy, relevancy, risk management, hallucination mitigation, and citations and guidelines). The impacts of the erroneous responses on the patients' safety were categorized either as major or minor. ResultsIn the assessment of four LLMs regarding dosing regimen errors, drug-drug interactions, and suggestions for dosing regimen adjustments based on therapeutic drug monitoring and genomics-based individualization of drug therapy, responses were generally consistent across prompts with no clear pattern in response quality among the LLMs. For identification of dosage regimen errors, ChatGPT performed well overall, except for the query related to simvastatin. In terms of potential drug-drug interactions, all LLMs recognized interactions with warfarin but missed the interaction between metoprolol and verapamil. Regarding dosage modifications based on therapeutic drug monitoring, Claude-Instant provided appropriate suggestions for two scenarios and nearly appropriate suggestions for the other two. Similarly, for genomics-based decision-making, Claude-Instant offered satisfactory responses for four scenarios, followed by Gemini for three. Notably, Gemini stood out by providing references to guidelines or citations even without prompting, demonstrating a commitment to accuracy and reliability in its responses. Minor impacts were noted in identifying appropriate dosing regimens and therapeutic drug monitoring, while major impacts were found in identifying drug interactions and making pharmacogenomic-based therapeutic decisions. ConclusionAdvanced LLMs hold significant promise in revolutionizing the medication review and reconciliation process in healthcare. Diverse impacts on patient safety were observed. Integrating and validating LLMs within electronic health records and prescription systems is essential to harness their full potential and enhance patient safety and care quality.

Simethicone Medication Should Be Avoided in Infants Receiving Oral Lactase Treatment.

In this retrospective study, we assessed the efficacy of oral lactase in infants with lactose intolerance in terms of sex, birth weight, and interference by other medications. The study was conducted on patients aged 0-6 months who had been diagnosed with lactose intolerance on admission to the Department of Social Pediatrics at Dokuz Eylul University. Demographic data, the onset of symptoms, and medications used were recorded. We found that 86.7% of the infants responded to lactase, with no significant differences based on sex, birth weight, or age at symptom presentation. We observed, however, that the efficacy of treatment did improve over time, thereby deriving benefits from intestinal development and adaptation. Interestingly, the response to lactase was reduced in infants receiving concomitant simethicone for colic symptoms, suggesting a potential drug interaction, while probiotics had no impact on treatment outcomes. We advise against using additional medications with oral lactase, pointing out a possible interaction with simethicone that might decrease the effectiveness of treatment.

Obesity management in the pediatric patient.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. The purpose of this review is to discuss treatment modalities for obesity in children and adolescents, including nonpharmacological, pharmacological, and surgical interventions. The prevalence of pediatric obesity has dramatically risen, with rates of 20.7% and 22.2% among children and adolescents, respectively. Obesity is a complex medical condition with multifactorial risk factors, including diet and exercise, social determinants of health, and environmental and genetic factors. The management approach among children and adolescents with obesity includes nutrition counseling, increased physical activity, and readiness for behavioral change. Pharmacotherapy may be recommended, yet the literature has not elucidated the most appropriate first-line treatment. Metformin and orlistat have been studied and may be considered in pediatric patients with comorbid complications, including type 2 diabetes and nonalcoholic fatty liver disease. Phentermine and topiramate in combination, as well as glucagon-like peptide-1 receptor agonists, have provided modest benefits in weight reduction among youth. Setmelanotide has a unique mechanism of action and may be considered for those with obesity due to genetic disorders. Bariatric surgery should be reserved for adolescents meeting criteria for severe obesity. Treatment for obesity in children and adolescents includes a comprehensive approach with structured lifestyle programs, mental health support, and mitigation of social determinants of health. Pharmacotherapy may also be considered, yet no medication is recommended over another, giving flexibility for shared decision-making with the patient and family regarding comorbidities and potential drug interactions. Adolescents with severe obesity who meet specified criteria may also be referred for surgical evaluation.

Polypharmacy and potential drug-drug interactions in older cardiovascular patients according to medical information system

Polypharmacy and potential drug-drug interactions in older cardiovascular patients according to medical information system

Avapritinib Carries the Risk of Drug Interaction via Inhibition of UDP-Glucuronyltransferase (UGT) 1A1.

Avapritinib is the only drug for adult patients with PDGFRA exon 18 mutated unresectable or metastatic gastrointestinal stromal tumor (GIST). Although avapritinib has been approved by the FDA for four years, little is known about the risk of drug-drug interactions (DDIs) via UDP-glucuronyltransferases (UGTs) inhibition. The aim of the present study was to systematically evaluate the inhibitory effects of avapritinib against UGTs and to quantitatively estimate its potential DDIs risk in vivo. Recombinant human UGTs were employed to catalyze the glucuronidation of substrates in a range of concentrations of avapritinib. The kinetics analysis was performed to evaluate the inhibition types of avapritinib against UGTs. The quantitative prediction of DDIs was done using in vitro-in vivo extrapolation (IVIVE). Avapritinib had a potent competitive inhibitory effect on UGT1A1. Quantitative prediction results showed that avapritinib administered at clinical doses might result in a 14.85% increase in area under the curve (AUC) of drugs primarily cleared by UGT1A1. Moreover, the Rgut value was calculated to be 18.44. Avapritinib has the potential to cause intestinal DDIs via the inhibition of UGT1A1. Additional attention should be paid when avapritinib is coadministered with UGT1A1 substrates.

Transformer-based medication recommendation with a multiple graph augmentation strategy

Medication recommendation (MR) is a promising task that benefits both patients and medical practitioners. However, the individual differences in patients and drug–drug interactions (DDIs) in medication combinations are two key factors that severely limit the personalization and safety of the present MR models. To alleviate the challenges mentioned above, this paper proposes a novel MR model named Trans-GAHNet, which innovatively leverages transformer-based representation learning and constructs multiple graphs for drug information augmentation. More specifically, the transformer network architecture is deployed to fully encode the sequential EHR data for effective patient representations, which addresses the cold start issue and enhances the interpretability of representation learning. Next, multiple graphs are employed to capture the co-occurrence and exclusiveness in drug pairs and to mitigate potential DDIs in drug combinations, thereby enhancing the personalization and safety of the predicted medication combinations. Finally, extensive experiments on real-world datasets are conducted to evaluate the proposed model, and the experimental results demonstrate that Trans-GAHNet outperforms the state-of-the-art baseline models on multiple metrics, with Jaccard, F1 and PRAUC scores of 0.5238, 0.6786 and 0.7795, respectively.

Assessment of co-ingestion effects on poisoning patterns, drug-drug interactions, and adverse outcomes in acute toxic exposure

Multiple toxic exposures are increasing nowadays. In cases of acute poisoning involving multiple agents, there is a potential for additional toxicity that goes beyond the effects and toxicity of each drug. Very scarce studies have investigated the problem of multiple toxic exposures where the information on drug-drug interactions (DDIs) originates from clinical experience, which is inconclusive and cannot be generalized to patients. Therefore, the current study aimed to explore the influence of co-ingestion on the clinical presentation of exposed patients and to identify the common associated DDIs and their effect on poisoning outcomes, including the need for mechanical ventilation (MV), intensive care unit (ICU) utilization, and prolonged hospital stay. The current study is a retrospective cross-sectional study that was conducted using medical records of 169 adult patients admitted to a poison control center and diagnosed with acute drug poisoning. Of them, 40.8 % were exposed to multiple drugs. The total number of drugs reported in the current study was 320 preparations, with an average of 1.9 drugs per patient. There were about 726 potential DDIs; more than half of these interactions were significant (n = 486). Antidepressants and psychotropics showed the highest total number of DDIs. Patients with multiple ingestion were significantly older and this pattern of exposure was more frequent among suicidal attempters, substance abusers, cardiac patients, and patients diagnosed with neurological and psychological problems. Moreover, patients with multiple ingestions showed severe presentations indicated by higher grades of Poison Severity Score and lower Glasgow Coma Scale. Multiple ingestion was associated with higher liability for MV, ICU admission, and prolonged length of hospital stay (p < 0.001). There was a significant moderate direct correlation between the number of drugs consumed and the number of resulting DDIs (r = 0.542, p < 0.001). There was a significant direct correlation between the occurrence of significant chronic/chronic drug interactions from one side and the history of substance abuse (r = 0.596, p = 0.041) and psychological illness (r = 0.662, p = 0.019) from the other side. Moreover, significant acute/acute drug interactions were correlated with being male (r = 0.969, p < 0.001) of older age (r = 0.672, p = 0.024). Similarly, significant acute/chronic drug interactions were moderately correlated with being a male (r = 0.692, p = 0.013). The presence of epilepsy and psychological problems were the main significant predictors of multiple acute toxic exposures. Among the patients exposed acutely to more than one agent who were on long-term treatment, exposure to three drugs or more could significantly predict the need for MV with excellent area under the curve (AUC) of 0.896 and 77.0 % accuracy. Moreover, and it was a fair predictor of ICU admission (AUC = 0.625), with an 88.9 % ability to exclude patients unlikely to need ICU admission. Particular attention should be paid to the patients at risk of potential DDIs. When prescribing drugs, the minimum number of drugs with the lowest effective doses, and minimal potential DDIs should be prioritized.

Medicine Prescribing Practices and Prescription Errors Evaluations at Outpatient Department in Debre Berhan Comprehensive Specialized Hospital, Amhara Regional State, Ethiopia.

Background: Currently, irrational uses of medicines becoming global problem largely in developing countries like Ethiopia. Inappropriate prescribing is a major cause for poor treatment outcome and higher costs. Hence, this study was aimed to investigate medicine prescribing practice and prescription errors using WHO medicine-utilization core indicators. Methods: A hospital based retrospective cross sectional study design was used to evaluate prescribing practices and prescription errors from September to October, 2024 at the OPD pharmacy using systematic random sampling technique while a prospective approach was employed for facility indicators. Presence of potential drug-drug interactions (DDIs) were evaluated using Medscape Online Drug Interaction Checker. Data were analyzed using SPSS version 25 and interpreted as tables and figures. Results: A total of 1019 medicines were prescribed in 524 prescriptions and 81.6% (n = 832) were actually dispensed. The percentage of antibiotic, injections and medicine prescribed from Essential Drug List was 33.9% (n = 345),3.5% (n = 36) and 92.3% (n = 941) respectively. The most frequently prescribed class of medicine were antibiotics 33.9% (n = 345). 65.1% (n = 341) were ≥2 medicines and 8.3% (n = 85) had at least one potential DDIs. Among overall DDIs, the monitor closely and serious level was 60% (n = 51) and 11.8% (n = 10) respectively. The average prescription error was 4.3. Prescription errors due to failure to mention diagnosis was 40.6% (n = 213). Conclusion: Based on findings, the prescribing practices had defects to the optimum value recommended by WHO and showed high prescription errors. Antibiotics prescribing was the major problem in practice. Remarkable DDIs were observed in prescribed medicines. Therefore, designing and implementing policy to improve medicine use practice is highly indispensable.

Assessment of potential drug-drug interactions in hospitalized patients with infectious diseases: an experience from a secondary care hospital

Background Polypharmacy is common among hospitalized patients with infectious infections owing to comorbidities or concomitant illnesses. This raises the likelihood of drug-drug interactions and creates uncertainty for healthcare providers. This study aimed to assess the potential drug-drug interactions (pDDIs) among hospitalized patients with infectious diseases in a secondary care hospital. Methods A prospective observational study was conducted in the internal medicine ward for six months after the ethics committee’s approval. Data were collected from patient case records, and prescriptions were screened for pDDIs from a portable electronic physician information database (PEPID) resource analyzed using SPSS, version 27.0. Results In total, 148 patient case records were analyzed, and 549 pDDIs were identified, with 66.8% having at least one or more DDIs. The mean number of drug interactions was 3.70 ± 4.58 per prescription. The most frequently encountered drug interactions were drug combinations such as bisoprolol with atorvastatin and aspirin with tazobactam/piperacillin. Bivariate analysis showed that age, comorbidities, length of hospital stay, and the number of drugs prescribed were risk factors associated with DDIs (p&lt;0.05). In the multiple binary logistic regression analysis, DDIs were significantly associated with comorbidities and the number of prescribed medications (p&lt;0.0001). Conclusions This study observed the prevalence of DDIs in hospitalized patients with infectious diseases of ‘moderate’ severity. Prescription screening using a drug information database assists in early identification and prevention of DDIs, enhancing drug safety and quality of patient-centered care.

Advancements in physiologically based pharmacokinetic modeling for fedratinib: updating dose guidance in the presence of a dual inhibitor of CYP3A4 and CYP2C19.

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. 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). 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 400mg once daily along with fluconazole 200mg daily, the model predicted an approximate 50% increase in fedratinib exposure at steady state. 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.

Sulfotransferase-mediated phase II drug metabolism prediction of substrates and sites using accessibility and reactivity-based algorithms.

Sulphotransferases (SULTs) are a major phase II metabolic enzyme class contributing ~20 % to the Phase II metabolism of FDA-approved drugs. Ignoring the potential for SULT-mediated metabolism leaves a strong potential for drug-drug interactions, often causing late-stage drug discovery failures or black-boxed warnings on FDA labels. The existing models use only accessibility descriptors and machine learning (ML) methods for class and site of sulfonation (SOS) predictions for SULT. In this study, a variety of accessibility, reactivity, and hybrid models and algorithms have been developed to make accurate substrate and SOS predictions. Unlike the literature models, reactivity parameters for the aliphatic or aromatic hydroxyl groups (R/Ar-O-H), the Bond Dissociation Energy (BDE) gave accurate models with a True Positive Rate (TPR)=0.84 for SOS predictions. We offer mechanistic insights to explain these novel findings that are not recognized in the literature. The accessibility parameters like the ratio of Chemgauss4 Score (CGS) and Molecular Weight (MW) CGS/MW and distance from cofactor (Dis) were essential for class predictions and showed TPR=0.72. Substrates consistently had lower BDE, Dis, and CGS/MW than non-substrates. Hybrid models also performed acceptablely for SOS predictions. Using the best models, Algorithms gave an acceptable performance in class prediction: TPR=0.62, False Positive Rate (FPR)=0.24, Balanced accuracy (BA)=0.69, and SOS prediction: TPR=0.98, FPR=0.60, and BA=0.69. A rule-based method was added to improve the predictive performance, which improved the algorithm TPR, FPR, and BA. Validation using an external dataset of drug-like compounds gave class prediction: TPR=0.67, FPR=0.00, and SOS prediction: TPR=0.80 and FPR=0.44 for the best Algorithm. Comparisons with standard ML models also show that our algorithm shows higher predictive performance for classification on external datasets. Overall, these models and algorithms (SOS predictor) give accurate substrate class and site (SOS) predictions for SULT-mediated Phase II metabolism and will be valuable to the drug discovery community in academia and industry. The SOS predictor is freely available for academic/non-profit research via the GitHub link.

Effect of midostaurin on the pharmacokinetics of P-gp, BCRP, and CYP2D6 substrates: assessing potential drug-drug interactions in healthy participants : Brief title: Drug-drug interaction of midostaurin.

Midostaurin, approved for FLT3-mutated acute myeloid leukemia and advanced systemic mastocytosis, is mainly metabolized by cytochrome P450 (CYP) 3A4. Midostaurin exhibited potential inhibitory effects on P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion-transporting polyprotein 1B1, and CYP2D6 in in vitro studies. This study investigated the pharmacokinetic (PK) effects of midostaurin on P-gp (digoxin), BCRP (rosuvastatin) and CYP2D6 (dextromethorphan) substrates in healthy adults. This was an open-label, single-sequence, phase I clinical study evaluating the effect of single-dose midostaurin (100mg) on the PK of digoxin and rosuvastatin (Arm 1), and dextromethorphan (Arm 2). Participants were followed up for safety 30 days after last dose. In addition, the effect of midostaurin on the PK of dextromethorphan metabolite (dextrorphan) was assessed in participants with functional CYP2D6 genes in Arm 2. The effect of midostaurin on digoxin was minor and resulted in total exposure (AUC) and peak plasma concentration (Cmax) that were only 20% higher. The effect on rosuvastatin was mild and led to an increase in AUCs of approximately 37-48% and of 100% in Cmax. There was no increase in the primary PK parameters (AUCs and Cmax) of dextromethorphan in the presence of midostaurin. The study treatments were very well tolerated with no occurance of severe adverse events (AEs), AEs of grade ≥ 2, or deaths. Midostaurin showed only a minor inhibitory effect on P-gp, a mild inhibitory effect on BCRP, and no inhibitory effect on CYP2D6. Study treatments were well tolerated in healthy adults.

A Study of Polypharmacy and its Consequences in Geriatric Patients

The term polypharmacy is the concurrent use of five or more drug by a patient. In older persons, the cutoff threshold of five medicines is linked to the unfavourable outcomes such falls, disability, and mortality one of the crucial components. The main components of polypharmacy therapy in the clinical setting are reviewed in this study. Potential Drug-Drug Interactions (pDDIs) and Potentially Inappropriate Medications (PIMs) are threatening and contribute to increased rate of morbidity and mortality rate. The present study was performed on the prevalence of pDDIs and PIMs among the geriatric patients at a tertiary care hospital. Methodology: The study was Prospective, Cross-sectional study carried out for a period of six months in General Medical Ward at Akash hospital, Bangalore PIMs were analyzed using Beer’s criteria and pDDIs were analyzed using online data base system (Micromedex 2.2) Results: In this study, a total of 110 patients were enrolled, out of which 69 (62.72%) were males and 41 (37.28%) were females. Out of which 21 (19.10%) prescription showed PIMs and 66 (56%) prescription showed pDDIs. A total of 180 pDDIs were observed, 3 interactions (1.7%) come under the classification of contraindication, 87 (48.3%) fall under major severity, 85 (47.29%) were of moderate severity and 5 (2.8%) were of minor severity. Among 180 pDDIs, 13 (7.2%) were of rapid, 21 (11.6%) were delayed and 146 (81.6%) were not specified. 97 (57.30%) were of synergism, 49 (27.40%) were antagonism and 34 (18.80%) were unknown. 13 (7.2%) were of excellent, 29 (16.20%) were good and 138 (76.60%) were fair. Conclusion: This study concluded that awareness on the most prevalent pDDIs can help the practitioners to prescribe drugs with a low risk for pDDIs and prevent the concomitant use of various drug combinations.

Characteristics of CYP3A4-related potential drug-drug interactions in outpatients receiving prescriptions from multiple clinical departments

BackgroundDrug-drug interactions (DDIs) increase the incidence of adverse drug reactions (ADRs). In a previous report, we revealed that the incidence of potential DDIs due to the same CYP molecular species in one prescription exceeds 90% among patients taking six or more drugs and that CYP3A4 markedly influences the increase in the number of potential DDIs in clinical practice. However, the factors contributing to an increased number of potential DDIs in prescriptions from multiple clinical departments remain poorly clarified.MethodsThis observational study was performed at five pharmacies in Okayama Prefecture, Japan. Patients who visited these pharmacies from 11 April 2022 to 24 April 2022 were included, except those who had prescriptions only from a single clinical department. A stratified analysis was performed to determine the incidence of CYP3A4-related potential DDIs according to the number of drugs taken. Additionally, factors associated with an increase in the number of drugs involved in CYP3A4-related potential DDIs were identified using multiple linear regression analysis. In this study, potential DDIs for the prescription data subdivided by clinical department, containing two or more drugs, were used as control data.ResultsOverall, 372 outpatients who received prescriptions from multiple clinical departments were included in the current study. The number of drugs contributing to CYP3A4-related potential DDIs increased with an increase in the number of clinical departments. Notably, in cases taking fewer than six drugs, prescriptions from multiple clinical departments had a higher frequency of CYP3A4-related potential DDIs than those in prescriptions subdivided by clinical department. Multiple regression analysis identified "Cardiovascular agents", "Agents affecting central nervous system", and "Urogenital and anal organ agents" as the top three drug classes that increase CYP3A4-related potential DDIs.ConclusionCollectively, these results highlight the importance of a unified management strategy for prescribed drugs and continuous monitoring of ADRs in outpatients receiving prescriptions from multiple clinical departments even if the number of drugs taken is less than six.

Severity and Risk Rating of Drug-Drug Interaction Potency in Chronic Kidney Disease in Public Health Hospital

Background: Chronic kidney disease has emerged as a prominent cause of mortality worldwide in the last two decades. Drug interactions are a significant problem in individuals with chronic kidney disease, as they often receive numerous concurrent treatments. The aim is to examine the frequency of drug-drug interactions in outpatient treatment for chronic renal disease, classified according to their severity and risk level. Furthermore, the study aims to demonstrate the combined effect of the most common drug-drug interactions potency and associated risk factors. Methods: This study is a retrospective cross-sectional analysis of outpatients diagnosed with chronic kidney disease at Ansari Saleh Public Hospital in Banjarmasin, Indonesia. Medical records from 2022 were obtained retrospectively from computerised sources. The evaluation of potential interactions between drugs was conducted using Lexicomp®. The categorical data were displayed as percentages, and the continuous variables were depicted as means. Results: The study found that most drug interactions fell into the moderate severity (77.1%) and category C (75.5%) for the risk assessment. The prevalence of drug-drug interactions was 83.6% and the average number of potential drug interactions per patient was 3.34 ± 3.481. The concurrent use of candesartan and furosemide was the most prevalent drug-drug interaction (5.1%). The number of prescribed medications was a notable determinant for probable drug-drug interactions (p &lt; 0.05). Conclusion: Identifying and averting potential drug-drug interactions is crucial to guarantee patient safety.

A practical guide for the use of apalutamide for non-metastatic castration-resistant prostate cancer in Australia.

Studies of patients with castrate-resistant prostate cancer at high risk of developing overt metastases but with no current evidence of evaluable disease on computed tomography or bone scan non-metastatic castrate-resistant prostrate cancer have demonstrated increased metastasis-free survival and overall survival following treatment with the next-generation oral anti-androgen apalutamide (in addition to therapies that aim to lower testosterone to castrate levels) or luteinizing hormone-releasing hormone antagonist or surgical castration. Patients receiving apalutamide can be managed by medical oncologists, radiation oncologists, or urologists, preferably as part of a multidisciplinary team. However, the importance of additional safety monitoring for significant adverse effects and drug interactions should not be underestimated. The toxicities of apalutamide are manageable with experience and should be managed proactively to minimize their impact on patients. Monitoring of patients for apalutamide-specific toxicities, including skin rash, hypothyroidism, and QT prolongation should be carried out regularly, particularly in the first few months following initiation. Monitoring should continue alongside monitoring for toxicities of androgen deprivation, including cardiovascular risk, hot flashes, weight gain, bone health, muscle wasting, and diabetic risk. This review is a practical guide to the use of apalutamide describing the management of patients including dosing and administration, toxicities, potential drug interactions, and safety monitoring requirements.