Assessment Of Drug-drug Interactions Research Articles

Dose Optimization Informed by PBPK Modeling: State-of-the Art and Future.

Model-informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically-based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug-drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials.

Clinical assessment of momelotinib drug-drug interactions via CYP3A metabolism and transporters.

Momelotinib-approved for treatment of myelofibrosis in adults with anemia-and its major active metabolite, M21, were assessed as drug-drug interaction (DDI) victims with a strong cytochrome P450 (CYP) 3A4 inhibitor (multiple-dose ritonavir), an organic anion transporting polypeptide (OATP) 1B1/1B3 inhibitor (single-dose rifampin), and a strong CYP3A4 inducer (multiple-dose rifampin). Momelotinib DDI perpetrator potential (multiple-dose) was evaluated with CYP3A4 and breast cancer resistance protein (BCRP) substrates (midazolam and rosuvastatin, respectively). DDI was assessed from changes in maximum plasma concentration (Cmax), area under the concentration-time curve (AUC), time to reach Cmax, and half-life. The increase in momelotinib (23% Cmax, 14% AUC) or M21 (30% Cmax, 24% AUC) exposure with ritonavir coadministration was not clinically relevant. A moderate increase in momelotinib (40% Cmax, 57% AUC) and minimal change in M21 was observed with single-dose rifampin. A moderate decrease in momelotinib (29% Cmax, 46% AUC) and increase in M21 (31% Cmax, 15% AUC) were observed with multiple-dose rifampin compared with single-dose rifampin. Due to potentially counteracting effects of OATP1B1/1B3 inhibition and CYP3A4 induction, multiple-dose rifampin did not significantly change momelotinib pharmacokinetics compared with momelotinib alone (Cmax no change, 15% AUC decrease). Momelotinib did not alter the pharmacokinetics of midazolam (8% Cmax, 16% AUC decreases) or 1'-hydroxymidazolam (14% Cmax, 16% AUC decreases) but increased rosuvastatin Cmax by 220% and AUC by 170%. Safety findings were mild in this short-term study in healthy volunteers. This analysis suggests that momelotinib interactions with OATP1B1/1B3 inhibitors and BCRP substrates may warrant monitoring for adverse reactions or dose adjustments.

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<0.05). In the multiple binary logistic regression analysis, DDIs were significantly associated with comorbidities and the number of prescribed medications (p<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.

Assessing the relative contribution of CYP3A-and P-gp-mediated pathways to the overall disposition and drug-drug interaction of dabigatran etexilate using a comprehensive mechanistic physiological-based pharmacokinetic model.

Dabigatran etexilate (DABE) is a clinical probe substrate for studying drug-drug interaction (DDI) through an intestinal P-glycoprotein (P-gp). A recent in vitro study, however, has suggested a potentially significant involvement of CYP3A-mediated oxidative metabolism of DABE and its intermediate monoester BIBR0951 in DDI following microdose administration of DABE. In this study, the relative significance of CYP3A- and P-gp-mediated pathways to the overall disposition of DABE has been explored using mechanistic physiologically based pharmacokinetic (PBPK) modeling approach. The developed PBPK model linked DABE with its 2 intermediate (BIBR0951 and BIBR1087) and active (dabigatran, DAB) metabolites, and with all relevant drug-specific properties known to date included. The model was successfully qualified against several datasets of DABE single/multiple dose pharmacokinetics and DDIs with CYP3A/P-gp inhibitors. Simulations using the qualified model supported that the intestinal CYP3A-mediated oxidation of BIBR0951, and not the gut P-gp-mediated efflux of DABE, was a key contributing factor to an observed difference in the DDI magnitude following the micro-versus therapeutic doses of DABE with clarithromycin. Both the saturable CYP3A-mediated metabolism of BIBR0951 and the solubility-limited DABE absorption contributed to the relatively modest nonlinearity in DAB exposure observed with increasing doses of DABE. Furthermore, the results suggested a limited role of the gut P-gp, but an appreciable, albeit small, contribution of gut CYP3A in mediating the DDIs following the therapeutic dose of DABE with dual CYP3A/P-gp inhibitors. Thus, a possibility exists for a varying extent of CYP3A involvement when using DABE as a clinical probe in the DDI assessment, across DABE dose levels.

Assessment of potential drug-drug interactions in hospitalized cancer patients.

Drug-drug interactions (DDIs) pose a significant threat to patients with cancer, resulting in several adverse events in an oncology setting. Our study aims to identify potential DDIs in inpatient oncology wards, assess their severity, and provide recommendations to avoid these interactions. This prospective study was conducted in 79 hospitalized cancer patients over a period of 9 months (from August 2021 to May 2022) at the Amrita Institute of Medical Sciences, Kochi receiving at least two oncological or non-oncological drugs for 5 days. Significant differences were found in drug count (61.6% vs. 38.4%), hospitalization duration (63.1% vs. 36.9%), and medications for comorbidities (63% vs. 37%) between patients with and without DDIs (p < 0.001, <0.001, and 0.01, respectively). The study identified 321 DDIs, with 14 (4.4%) X interactions, 93 (30%) D interactions, 161 (50%) C interactions, and 53 (15.6%) B interactions. Severity-wise, 76 (23.7%) were major, 190 (59.1%) were moderate, and 55 (17.2%) were minor. Our study showed that drug count, medications for comorbidities, and hospitalization duration significantly increase the risk of DDIs in hospitalized oncology patients. Around 96.4% of recommendations for potential interactions were accepted and implemented, highlighting the huge opportunities and requirements for improvement, implementation, and management of drug interactions in oncology settings.

Use of a Double-Transfected System to Predict hOCT2/hMATE1-Mediated Renal Drug-Drug Interactions.

Accurate predictions of renal drug-drug interactions (DDIs) mediated by the human organic cation transporter 2 (hOCT2) and multidrug and toxin extrusion proteins (hMATEs) remain challenging. Current DDI evaluation using plasma maximal unbound inhibitor concentrations (Imax,u) and IC50 values determined in single transporter-transfected cells frequently leads to false or overprediction especially for hMATE1. Emerging evidence suggests intracellular unbound inhibitor concentration may be more relevant for hMATE1 inhibition in vivo. However, determination of intrarenal inhibitor concentrations is impractical. Here, we explored the use of hOCT2/hMATE1 double-transfected Madin-Darby canine kidney (MDCK) cells as a new in vitro tool for DDI risk assessment. Our results showed that potent in vitro hMATE1 inhibitors (hydroxychloroquine, brigatinib, and famotidine) failed to inhibit metformin B-to-A flux in the double-transfected system. On the other side, the classic hOCT2/hMATE1 inhibitors, pyrimethamine and cimetidine, dose-dependently inhibited metformin apparent B-to-A permeability (Papp). The different behaviors of these hMATE1 inhibitors in the double-transfected system can be explained by their different ability to gain intracellular access either via passive diffusion or transporter-mediated uptake. A new parameter (IC50,flux) was proposed reflecting the inhibitor's potency on overall hOCT2/hMATE1-mediated tubular secretion. The IC50,flux values significantly differ from the IC50 values determined in single transporter-transfected cells. Importantly, the IC50,flux accurately predicted in vivo DDIs (within 2-fold) when used in a static model. Our data demonstrated that the IC50,flux approach circumvents the need to measure intracellular inhibitor concentrations and more accurately predicted hOCT2/hMATE1-mediated renal DDIs. This system represents a new approach that could be used for improved DDI assessment during drug development. SIGNIFICANCE STATEMENT: This study demonstrated that flux studies in double-transfected MDCK cells and the IC50,flux represents a better approach to assess in vivo DDI potential for the renal organic cation secretion system. This study highlights the importance of inhibitor intracellular accessibility for accurate prediction of hMATE1-mediated renal DDIs. This approach has the potential to identify in vitro hMATE1 inhibitors that are unlikely to result in in vivo DDIs, thus reducing the burden of unnecessary and costly clinical DDI investigations.

Drug-drug interaction assessment based on a large-scale spontaneous reporting system for hepato- and renal-toxicity, and thrombocytopenia with concomitant low-dose methotrexate and analgesics use

BackgroundMethotrexate (MTX) is the cornerstone of rheumatoid arthritis (RA) treatment and is highly effective with low-dose intermittent administration. MTX is occasionally used in combination with non-steroidal anti-inflammatory drugs (NSAIDs) and acetaminophen (APAP)/paracetamol for pain or inflammation control. With MTX treatment, the side effects, such as hepatotoxicity, renal failure, and myelosuppression should be considered. These are also seen with analgesics treatment.MethodsWe used a large spontaneously reported adverse event database (FAERS [JAPIC AERS]) to analyze whether the reporting of adverse events increased upon MTX and analgesic therapy in patients with RA.ResultsAfter identifying RA cases, the crude reporting odds ratios (cRORs) for hepatotoxicity, renal failure, and thrombocytopenia associated with the use of MTX, APAP, or NSAIDs were calculated by disproportionality analysis, which revealed significantly higher cRORs for these events. No analgesics showed consistent positive signals for drug-drug interaction (DDI) with concomitant low-dose MTX analyzed using four algorithms for DDI interaction (the Ω shrinkage measure, additive or multiplicative, and combination risk ratio models). However, in renal failure and thrombocytopenia, loxoprofen (Ω025 = 0.08) and piroxicam (Ω025 = 0.46), and ibuprofen (Ω025 = 0.74) and ketorolac (Ω025 = 3.52), respectively, showed positive signals in the Ω shrinkage measure model, and no consistency was found among adverse events or NSAIDs.ConclusionsStudies using spontaneous reporting systems have limitations such as reporting bias or lack of patient background; however, the results of our comprehensive analysis support the results of previous clinical or epidemiological studies. This study also demonstrated the usefulness of FAERS for DDI assessment.

Physiologically-based pharmacokinetic modeling of prominent oral contraceptive agents and applications in drug-drug interactions.

Considerable interest remains across the pharmaceutical industry and regulatory landscape in capabilities to model oral contraceptives (OCs), whether combined (COCs) with ethinyl estradiol (EE) or progestin-only pill. Acceptance of COC drug-drug interaction (DDI) assessment using physiologically-based pharmacokinetic (PBPK) is often limited to the estrogen component (EE), requiring further verification, with extrapolation from EE to progestins discouraged. There is a paucity of published progestin component PBPK models to support the regulatory DDI guidance for industry to evaluate a new chemical entity's (NCE's) DDI potential with COCs. Guidance recommends a clinical interaction study to be considered if an investigational drug is a weak or moderate inducer, or a moderate/strong inhibitor, of CYP3A4. Therefore, availability of validated OC PBPK models within one software platform, will be useful in predicting the DDI potential with NCEs earlier in the clinical development. Thus, this work was focused on developing and validating PBPK models for progestins, DNG, DRSP, LNG, and NET, within Simcyp, and assessing the DDI potential with known CYP3A4 inhibitors (e.g., ketoconazole) and inducers (e.g., rifampicin) with published clinical data. In addition, this work demonstrated confidence in the Simcyp EE model for regulatory and clinical applications by extensive verification in 70+ clinical PK and CYP3A4 interaction studies. The results provide greater capability to prospectively model clinical CYP3A4 DDI with COCs using Simcyp PBPK to interrogate the regulatory decision-tree to contextualize the potential interaction by known perpetrators and NCEs, enabling model-informed decision making, clinical study designs, and delivering potential alternative COC options for women of childbearing potential.

A Review of CYP-Mediated Drug Interactions: Mechanisms and In Vitro Drug-Drug Interaction Assessment.

Drug metabolism is a major determinant of drug concentrations in the body. Drug-drug interactions (DDIs) caused by the co-administration of multiple drugs can lead to alteration in the exposure of the victim drug, raising safety or effectiveness concerns. Assessment of the DDI potential starts with in vitro experiments to determine kinetic parameters and identify risks associated with the use of comedication that can inform future clinical studies. The diverse range of experimental models and techniques has significantly contributed to the examination of potential DDIs. Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of many drugs on the market, making them frequently implicated in drug metabolism and DDIs. Consequently, there has been a growing focus on the assessment of DDI risk for CYPs. This review article provides mechanistic insights underlying CYP inhibition/induction and an overview of the in vitro assessment of CYP-mediated DDIs.

Building a Predictive PBPK Model for Human OATP Substrates: a Strategic Framework for Early Evaluation of Clinical Pharmacokinetic Variations Using Pitavastatin as an Example.

To select a drug candidate for clinical development, accurately and promptly predicting human pharmacokinetic (PK) profiles, assessing drug-drug interactions (DDIs), and anticipating potential PK variations in disease populations are crucial steps in drug discovery. The complexity of predicting human PK significantly increases when hepatic transporters are involved in drug clearance (CL) and volume of distribution (Vss). A strategic framework is developed here, utilizing pitavastatin as an example. The framework includes the construction of a monkey physiologically-based PK (PBPK) model, model calibration to obtain scaling factors (SF) of in vitro-in vivo extrapolation (IVIVE) for various clearance parameters, human model development and validation, and assessment of DDIs and PK variations in disease populations. Through incorporating in vitro human parameters and calibrated SFs from the monkey model of 3.45, 0.14, and 1.17 for CLint,active, CLint,passive, and CLint,bile, respectively, and together with the relative fraction transported by individual transporters obtained from in vitro studies and the optimized Ki values for OATP inhibition, the model reasonably captured observed pitavastatin PK profiles, DDIs and PK variations in human subjects carrying genetic polymorphisms, i.e., AUC within 20%. Lastly, when applying the functional reduction based on measured OATP1B biomarkers, the model adequately predicted PK changes in the hepatic impairment population. The present study presents a strategic framework for early-stage drug development, enabling the prediction of PK profiles and assessment of PK variations in scenarios like DDIs, genetic polymorphism, and hepatic impairment-related disease states, specifically focusing on OATP substrates.

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

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

Neuroimaging and the Investigation of Drug-Drug Interactions Involving Psychedelics.

Psychedelic therapies are an emerging class of treatments in psychiatry with great potential, however relatively little is known about their interactions with other commonly used psychiatric medications. As psychedelic therapies become more widespread and move closer to the clinic, they likely will need to be integrated into existing treatment models which may include one or more traditional pharmacological therapies, meaning an awareness of potential drug-drug interactions will become vital. This commentary outlines some of the issues surrounding the study of drug-drug interactions of this type, provides a summary of some of the relevant key results to date, and charts a way forward which relies crucially on multimodal neuroimaging investigations. Studies in humans which combine Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI), plus ancillary measures, are likely to provide the most comprehensive assessment of drug-drug interactions involving psychedelics and the relevant effects at multiple levels of the drug response (molecular, functional, and clinical).

Evaluating drug-drug interaction risk associated with peptide analogues using advanced in vitro systems.

Drug-drug interaction (DDI) assessment of therapeutic peptides is an evolving area. The industry generally follows DDI guidelines for small molecules, but the translation of data generated with commonly used in vitro systems to in vivo is sparse. In the current study, we investigated the ability of advanced human hepatocyte in vitro systems namely HepatoPac, spheroids, and Liver-on-a-chip to assess potential changes in regulation of CYP1A2, CYP2B6, CYP3A4, SLCO1B1 and ABCC2 in the presence of selected therapeutic peptides, proteins, and small molecules. The peptide NN1177, a glucagon and GLP-1 receptor co-agonist, did not suppress mRNA expression or activity of CYP1A2, CYP2B6, and CYP3A4 in HepatoPac, spheroids, or Liver-on-a-chip; these findings were in contrast to the data obtained in sandwich cultured hepatocytes. No effect of NN1177 on SLCO1B1 and ABCC2 mRNA was observed in any of the complex systems. The induction magnitude differed across the systems (e.g., rifampicin induction of CYP3A4 mRNA ranged from 2.8-fold in spheroids to 81.2-fold in Liver-on-a-chip). Small molecules, obeticholic acid and abemaciclib, showed varying responses in HepatoPac, spheroids and Liver-on-a-chip, indicating a need for EC50 determinations to fully assess translatability data. HepatoPac, the most extensively investigated in this study (3 donors), showed high potential to investigate DDIs associated with CYP regulation by therapeutic peptides. Spheroids and Liver-on-a-chip were only assessed in one hepatocyte donor and further evaluations are required to confirm their potential. This study establishes an excellent foundation towards the establishment of more clinically-relevant in vitro tools for evaluation of potential DDIs with therapeutic peptides. Significance Statement At present, there are no guidelines for drug-drug interaction (DDI) assessment of therapeutic peptides. Existing in vitro methods recommended for assessing small molecule DDIs do not appear to translate well for peptide drugs, complicating drug development for these moieties. Here, we establish evidence that complex cellular systems have potential to be used as more clinically-relevant tools for the in vitro DDI evaluation of therapeutic peptides.

SAT340 Matters Of The HAART - Ritonavir Induced CYP3A4 Inhibition of Intranasal Fluticasone Leading To Cushing’s Syndrome

Abstract Disclosure: A. Ramachandran: None. S. Ghaith: None. A. Ramachandran: None. Background: Ritonavir, a potent inhibitor of the CYP3A4 enzyme, can lead to high systemic concentrations of even intranasal steroids causing Cushing’s syndrome. Case: A fifty-seven-year-old man with history of HIV on HAART presented with a 3-month history of fatigue, weight gain and easy bruising. History was negative for heat/cold intolerance, hair loss, constipation, erectile dysfunction. Medications included emtricitabine-tenofovir-alafenamide and ritonavir at stable doses for several years. He denied taking any oral or topical steroids, but reported using over the counter (OTC) fluticasone propionate (FP) for the past 6 months for seasonal allergies. Physical examination was significant for moon facies and abdominal striae. Labs were remarkable for low serum morning cortisol of 0.6 µg/dl (0.4-22.6 µg/dl), and low serum ACTH of &amp;lt;5 pg/ml (7-69 pg/ml). A diagnosis of exogenous steroid induced Cushing’s syndrome, as a result of ritonavir induced increase in FP levels was made. FP was gradually tapered and stopped. Serum cortisol and ACTH levels normalized at 15 µg/dl and 13 pg/ml respectively and his symptoms resolved completely after three months. Discussion: Ritonavir, a protease inhibitor (PI), is one of the strongest known inhibitors of CYP3A4 and is generally used to boost the plasma levels of other PIs. FP, a potent glucocorticoid, is generally used as monotherapy or as a combination inhaler in the treatment of asthma. It is rapidly metabolized by CYP3A4 and hence produces minimal side effects. However, its concurrent use with ritonavir results in increased serum concentration of FP leading to systemic adverse effects of glucocorticoids. Due to emerging awareness about this drug-drug interaction among physicians, prescription of inhalational steroids in patients on ritonavir is avoided. However, FP is an OTC intranasal glucocorticoid that is easily accessible, and its self-use is often times not reported by patients which makes it difficult for physicians to track on their patient’s medication list. A thorough review of OTC medications/supplements needs to be done when Cushing’s syndrome from exogenous steroids is suspected. It is also imperative that patients on ritonavir be counseled about the risks of taking any form of steroid formulations by any route. Conclusion: Educating patients on ritonavir about steroids being a component of many OTC medications/supplements, and a careful medication history and drug-drug interaction assessment is important in preventing steroid related adverse effects. Presentation: Saturday, June 17, 2023

The Impact of Drug-Drug Interactions on the Toxicity Profile of Combined Treatment with BRAF and MEK Inhibitors in Patients with BRAF-Mutated Metastatic Melanoma.

BRAF and MEK inhibition is a successful strategy in managing BRAF-mutant melanoma, even if the treatment-related toxicity is substantial. We analyzed the role of drug-drug interactions (DDI) on the toxicity profile of anti-BRAF/anti-MEK therapy. In this multicenter, observational, and retrospective study, DDIs were assessed using Drug-PIN software (V 2/23). The association between the Drug-PIN continuous score or the Drug-PIN traffic light and the occurrence of treatment-related toxicities and oncological outcomes was evaluated. In total, 177 patients with advanced BRAF-mutated melanoma undergoing BRAF/MEK targeted therapy were included. All grade toxicity was registered in 79% of patients. Cardiovascular toxicities occurred in 31 patients (17.5%). Further, 94 (55.9%) patients had comorbidities requiring specific pharmacological treatments. The median Drug-PIN score significantly increased when the target combination was added to the patient's home therapy (p-value < 0.0001). Cardiovascular toxicity was significantly associated with the Drug-PIN score (p-value = 0.048). The Drug-PIN traffic light (p = 0.00821) and the Drug-PIN score (p = 0.0291) were seen to be significant predictors of cardiotoxicity. Patients with low-grade vs. high-grade interactions showed a better prognosis regarding overall survival (OS) (p = 0.0045) and progression-free survival (PFS) (p = 0.012). The survival analysis of the subgroup of patients with cardiological toxicity demonstrated that patients with low-grade vs. high-grade DDIs had better outcomes in terms of OS (p = 0.0012) and a trend toward significance in PFS (p = 0.068). DDIs emerged as a critical issue for the risk of treatment-related cardiovascular toxicity. Our findings support the utility of DDI assessment in melanoma patients treated with BRAF/MEK inhibitors.

“Assessment of potential drug-drug interactions and their associated risk factor in patients with rheumatoid arthritis: A cross-sectional study”

BackgroundRheumatoid arthritis patients poses high risk for the development of potential drug-drug interactions (PDDIs) due to polypharmacy. Data relating the assessment of PDDIs in rheumatoid arthritis patients is still limited. Therefore, we assessed the prevalence, severity and adverse events of PDDIs, and their risk factors in rheumatoid arthritis patients. MethodsA cross-sectional research was carried out for 36 months in a tertiary care teaching hospital. Patient who met study eligibility were enrolled and their drug therapies were reviewed thoroughly. Generic name of drug was entered into Micromedex® software to identify the PDDIs. Adverse events related to PDDIs were identified and subsequently managed. Logistic regression analysis was applied to identify the risk factors associated with PDDIs. ResultsOf 598 patients, 518 (86.6%) patients were presented with ≥1 PDDIs. A total of 1492 PDDIs were identified, and 43.1% were moderate in their severity. Corticosteroids (32.8%) was major class of drugs involved in PDDIs development. Aceclofenac plus prednisolone (7.9%) was most common drug pair involved in the development of PDDIs. About 2.7% adverse events related to PDDIs were found. Age and multiple comorbidities were the most common risk factors associated with PDDIs. ConclusionThe occurrence of PDDIs was high among rheumatoid arthritis patients, majority were moderate in their severity. Age and multiple comorbidities were the most common risk factors associated with development of PDDIs. Therefore, prescriber and pharmacists’ need to take urgent action in reviewing medications chart and subjected to identify PDDIs, and their associated risk factors to enhance drug safety.

Clinical Pharmacology Applications of Real-World Data and Real-World Evidence in Drug Development and Approval-An Industry Perspective.

Since the 21st Century Cures Act was signed into law in 2016, real-world data (RWD) and real-world evidence (RWE) have attracted great interest from the healthcare ecosystem globally. The potential and capability of RWD/RWE to inform regulatory decisions and clinical drug development have been extensively reviewed and discussed in the literature. However, a comprehensive review of current applications of RWD/RWE in clinical pharmacology, particularly from an industry perspective, is needed to inspire new insights and identify potential future opportunities for clinical pharmacologists to utilize RWD/RWE to address key drug development questions. In this paper, we review the RWD/RWE applications relevant to clinical pharmacology based on recent publications from member companies in the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) RWD Working Group, and discuss the future direction of RWE utilization from a clinical pharmacology perspective. A comprehensive review of RWD/RWE use cases is provided and discussed in the following categories of application: drug-drug interaction assessments, dose recommendation for patients with organ impairment, pediatric plan development and study design, model-informed drug development (e.g., disease progression modeling), prognostic and predictive biomarkers/factors identification, regulatory decisions support (e.g., label expansion), and synthetic/external control generation for rare diseases. Additionally, we describe and discuss common sources of RWD to help guide appropriate data selection to address questions pertaining to clinical pharmacology in drug development and regulatory decision making.

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.

Assessment of Potential Drug-drug Interactions (pDDIs) and Their Risk Factors Among Hospitalized Cardiac Patients in a Tertiary-care Center of Central India: A Retrospective Record-based Study.

Background: Patients with cardiovascular disorders (CVD) possess multiple comorbidities and are prone to be prescribed multiple drugs, thus predisposing them to various drug-drug interactions (DDIs). Objective: This study was carried out to assess the potential-DDIs (pDDIs) among the drugs prescribed to hospitalized patients with CVD and associated factors. Method: It was a retrospective study conducted with the help of the medical records department. Medical records of all the patients admitted to the cardiology department of our tertiary care center from January 1st, 2019, to December 31st, 2019, were included for analysis using Lexicomp, an up-to-date drug interaction screening tool. The pDDIs were divided into classes A, B, C, D, and X, and those belonging to classes D or X were considered clinically significant. Multiple logistic regression was used to analyze the association between the factors associated with and the occurrence of clinically significant pDDIs, with a P-value < .05 considered statistically significant. Results: Almost all the records reflected (335/338) at least 1 pDDI. A total of 4966 pDDIs were detected, of which the majority belonged to category C (75.3%), and 5.1% of pDDIs were clinically significant. The patients who were prescribed more than 10 drugs per day (OR = 2.46; 95% CI: 1.27-4.82; P = .008), prescribed parenteral formulation (OR = 1.84; 95% CI: 1.57-2.21; P < .0001), or had a diagnosis of acute coronary syndrome (OR = 2.33; 95% CI:1.1-5.12; P = .03) were associated with clinically significant pDDIs. Other factors, that is, female sex, use of fixed-dose combinations, and the triad of diabetes mellitus, hypertension, and dyslipidemia, were positively associated with clinically significant pDDIs. Conclusion: Even though every patient had at least 1 pDDI, the prevalence of clinically significant pDDIs was relatively less. Use of >10 drugs/day, parenteral formulation, patients with acute coronary syndrome were significantly associated with clinically significant pDDIs.

The Potentially Significant Role of CYP3A-Mediated Oxidative Metabolism of Dabigatran Etexilate and its Intermediate Metabolites in Drug-Drug Interaction Assessments Using Microdose Dabigatran Etexilate.

Dabigatran etexilate (DABE), a double ester prodrug of dabigatran (DAB), is a probe substrate of intestinal P-glycoprotein (P-gp) commonly used in clinical drug-drug interaction (DDI) studies. When compared to its therapeutic dose at 150 mg, microdose DABE (375 µg) showed approximately 2-fold higher in DDI magnitudes with CYP3A/P-gp inhibitors. In this study, we conducted several in vitro metabolism studies to demonstrate that DABE at a theoretical gut concentration after microdosing significantly underwent NADPH-dependent oxidation (~40-50%) in parallel to carboxylesterase-mediated hydrolysis in human intestinal microsomes. Furthermore, NADPH-dependent metabolism of its intermediate monoester BIBR0951 was also observed in both human intestinal and liver microsomes, accounting for 100% and 50% of total metabolism, respectively. Metabolite profiling using LC-MS/MS confirmed the presence of several novel oxidative metabolites of DABE and of BIBR0951 in the NADPH-fortified incubations. CYP3A was identified as the major enzyme catalyzing the oxidation of both compounds. The metabolism of DABE and BIBR0951 was well described by Michaelis-Menten kinetics, with Km ranging 1-3 µM, significantly below the expected concentrations following the therapeutic dose of DABE. Overall, the present results suggested that CYP3A played a significant role in the presystemic metabolism of DABE and BIBR0951 following microdose DABE administration, thus attributing partly to the apparent overestimation in the DDI magnitude observed with the CYP3A/P-gp inhibitors. Therefore, DABE at the microdose, unlike the therapeutic dose, would likely be a less predictive tool and should be considered as a clinical dual substrate for P-gp and CYP3A when assessing potential P-gp-mediated impacts by dual CYP3A/P-gp inhibitors. Significance Statement This is the first study demonstrating a potentially significant role of CYP-mediated metabolism of the prodrug DABE following a microdose, but not a therapeutic dose. This additional pathway coupled with its susceptibility to P-gp may make DABE a clinical dual substrate for both P-gp and CYP3A at a microdose. The study also highlights the need for better characterization of the pharmacokinetics and metabolism of a clinical DDI probe substrate over the intended study dose range for proper result interpretations.