RESUMEN

Of the 450 cell membrane transporters responsible for shuttling substrates, nutrients, hormones, neurotransmitters, antioxidants, and signaling molecules, approximately nine are associated with clinically relevant drug-drug interactions (DDIs) due to their role in drug and metabolite transport. Therefore, a clinical study evaluating potential transporter DDIs is recommended if an investigational product is intestinally absorbed, undergoes renal or hepatic elimination, or is suspected to either be a transporter substrate or perpetrator. However, many of the transporter substrates and inhibitors administered during a DDI study also affect cytochrome P450 (CYP) activity, which can complicate data interpretation. To overcome these challenges, the assessment of endogenous biomarkers can help elucidate the mechanism of complex DDIs when multiple transporters or CYPs may be involved. This perspective article will highlight how creative study designs are currently being utilized to address complex transporter DDIs and the role of physiology-based -pharmacokinetic (PBPK) models can play.

RESUMEN

Venetoclax (VEN) is used in patients with acute myeloid leukemia (AML) and is primarily metabolized by CYP3A4, a major drug-metabolizing enzyme. Patients with AML simultaneously administered VEN and CYP3A4 inhibitors require a more appropriate management of drug-drug interactions (DDIs). Here, we report two cases of patients with AML (54-year-old man and 22-year-old woman) administrated VEN and CYP3A4 inhibitors, such as posaconazole, cyclosporine, or danazol. In the first case, we evaluated the appropriateness of timing for adjusting VEN dosage subsequent to the cessation of posaconazole. Consequently, modifying the VEN dosage in conjunction with the cessation of Posaconazole simultaneously may result in elevated plasma VEN levels. In the second case, plasma VEN concentrations were markedly elevated when co-administered with several CYP3A4 inhibitors. Additionally, in vitro assays were conducted for reverse translational studies to analyze CYP3A4 inhibition. CYP3A4 inhibition by combinatorial administration of cyclosporine A and danazol was demonstrated in vitro, which potentially explains the increasing plasma VEN concentrations observed in clinical settings. Although the acquisition of therapeutic effects is a major priority for patients, frequent therapeutic drug monitoring and dosage adjustments considering DDIs would be important factors in chemotherapy.

Asunto(s)

Compuestos Bicíclicos Heterocíclicos con Puentes , Inhibidores del Citocromo P-450 CYP3A , Citocromo P-450 CYP3A , Interacciones Farmacológicas , Monitoreo de Drogas , Leucemia Mieloide Aguda , Sulfonamidas , Humanos , Sulfonamidas/administración & dosificación , Leucemia Mieloide Aguda/tratamiento farmacológico , Inhibidores del Citocromo P-450 CYP3A/administración & dosificación , Masculino , Adulto Joven , Persona de Mediana Edad , Compuestos Bicíclicos Heterocíclicos con Puentes/administración & dosificación , Compuestos Bicíclicos Heterocíclicos con Puentes/farmacocinética , Compuestos Bicíclicos Heterocíclicos con Puentes/sangre , Femenino , Citocromo P-450 CYP3A/metabolismo , Ciclosporina/administración & dosificación , Triazoles/administración & dosificación , Antineoplásicos/administración & dosificación

RESUMEN

Icaritin is a prenylflavonoid derivative of the genus Epimedium (Berberidaceae) and has a variety of pharmacological actions. Icaritin is approved by the National Medical Products Administration as an anticancer drug that exhibits efficacy and safety advantages in patients with hepatocellular carcinoma cells. This study aimed to evaluate the inhibitory effects of icaritin on UDP-glucuronosyltransferase (UGT) isoforms. 4-Methylumbelliferone (4-MU) was employed as a probe drug for all the tested UGT isoforms using in vitro human liver microsomes (HLM). The inhibition potentials of UGT1A1 and 1A9 in HLM were further tested by employing 17ß-estradiol (E2) and propofol (PRO) as probe substrates, respectively. The results showed that icaritin inhibits UGT1A1, 1A3, 1A4, 1A7, 1A8, 1A10, 2B7, and 2B15. Furthermore, icaritin exhibited a mixed inhibition of UGT1A1, 1A3, and 1A9, and the inhibition kinetic parameters (Ki) were calculated to be 3.538, 2.117, and 0.306 (µM), respectively. The inhibition of human liver microsomal UGT1A1 and 1A9 both followed mixed mechanism, with Ki values of 2.694 and 1.431 (µM). This study provides supporting information for understanding the drug-drug interaction (DDI) potential of the flavonoid icaritin and other UGT-metabolized drugs in clinical settings. In addition, the findings provide safety evidence for DDI when liver cancer patients receive a combination therapy including icaritin.

Asunto(s)

Interacciones Farmacológicas , Flavonoides , Glucuronosiltransferasa , Microsomas Hepáticos , Glucuronosiltransferasa/antagonistas & inhibidores , Glucuronosiltransferasa/metabolismo , Humanos , Flavonoides/farmacología , Microsomas Hepáticos/metabolismo , Estradiol/farmacología , Himecromona/farmacología , Propofol/farmacología , Inhibidores Enzimáticos/farmacología

RESUMEN

Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the root causes have not been fully studied. This study aims to investigate the mechanisms behind CBZ's nonlinear PK and its induction potential on CYP3A4 and CYP2C9 enzymes. To achieve this, we developed and validated a physiologically based pharmacokinetic (PBPK) parent-metabolite model of CBZ and its active metabolite Carbamazepine-10,11-epoxide in GastroPlus®. The model was utilized for Drug-Drug Interaction (DDI) prediction with CYP3A4 and CYP2C9 victim drugs and to further explore the underlying mechanisms behind CBZ's nonlinear PK. The model accurately recapitulated CBZ plasma PK. Good DDI performance was demonstrated by the prediction of CBZ DDIs with quinidine, dolutegravir, phenytoin, and tolbutamide; however, with midazolam, the predicted/observed DDI AUClast ratio was 0.49 (slightly outside of the two-fold range). CBZ's nonlinear PK can be attributed to its nonlinear metabolism caused by autoinduction, as well as nonlinear absorption due to poor solubility. In further applications, the model can help understand DDI potential when CBZ serves as a CYP3A4 and CYP2C9 inducer.

RESUMEN

The new adjuvant chemotherapy of docetaxel, epirubicin, and cyclophosphamide has been recommended for treating breast cancer. It is necessary to investigate the potential drug-drug Interactions (DDIs) since they have a narrow therapeutic window in which slight differences in exposure might result in significant differences in treatment efficacy and tolerability. To guide clinical rational drug use, this study aimed to evaluate the DDI potentials of docetaxel, cyclophosphamide, and epirubicin in cancer patients using physiologically based pharmacokinetic (PBPK) models. The GastroPlus™ was used to develop the PBPK models, which were refined and validated with observed data. The established PBPK models accurately described the pharmacokinetics (PKs) of three drugs in cancer patients, and the predicted-to-observed ratios of all the PK parameters met the acceptance criterion. The PBPK model predicted no significant changes in plasma concentrations of these drugs during co-administration, which was consistent with the observed clinical phenomenon. Besides, the verified PBPK models were then used to predict the effect of other Cytochrome P450 3A4 (CYP3A4) inhibitors/inducers on these drug exposures. In the DDI simulation, strong CYP3A4 modulators changed the exposure of three drugs by 0.71-1.61 fold. Therefore, patients receiving these drugs in combination with strong CYP3A4 inhibitors should be monitored regularly to prevent adverse reactions. Furthermore, co-administration of docetaxel, cyclophosphamide, or epirubicin with strong CYP3A4 inducers should be avoided. In conclusion, the PBPK models can be used to further investigate the DDI potential of each drug and to develop dosage recommendations for concurrent usage by additional perpetrators or victims.

Asunto(s)

Ciclofosfamida , Citocromo P-450 CYP3A , Docetaxel , Interacciones Farmacológicas , Epirrubicina , Modelos Biológicos , Humanos , Epirrubicina/farmacocinética , Epirrubicina/administración & dosificación , Docetaxel/farmacocinética , Docetaxel/administración & dosificación , Ciclofosfamida/farmacocinética , Ciclofosfamida/administración & dosificación , Femenino , Citocromo P-450 CYP3A/metabolismo , Persona de Mediana Edad , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/metabolismo , Adulto , Inhibidores del Citocromo P-450 CYP3A/farmacocinética , Inhibidores del Citocromo P-450 CYP3A/administración & dosificación , Taxoides/farmacocinética , Taxoides/administración & dosificación , Simulación por Computador , Antineoplásicos/farmacocinética , Antineoplásicos/administración & dosificación , Inductores del Citocromo P-450 CYP3A/farmacología , Inductores del Citocromo P-450 CYP3A/farmacocinética , Anciano , Protocolos de Quimioterapia Combinada Antineoplásica/farmacocinética , Protocolos de Quimioterapia Combinada Antineoplásica/administración & dosificación

RESUMEN

PURPOSE: Entrectinib (ENT) is a potent c-ros oncogene 1(ROS1) and neurotrophic tyrosine receptor kinase (NTRKA/B/C) inhibitor. To determine the optimum dosage of ENT using ROS1 and NTRKA/B/C occupancy in plasma and cerebrospinal fluid (CSF) in drug-drug interactions (DDIs), physiologically-based pharmacokinetic (PBPK) models for healthy subjects and cancer population were developed for ENT and M5 (active metabolite). METHODS: The PBPK models were built using the modeling parameters of ENT and M5 that were mainly derived from the published paper on the ENT PBPK model, and then validated by the observed pharmacokinetics (PK) in plasma and CSF from healthy subjects and patients. RESULTS: The PBPK model showed that AUC, Cmax, and Ctrough ratios between predictions and observations are within the range of 0.5-2.0, except that the M5 AUC ratio is slightly above 2.0 (2.34). Based on the efficacy (> 75% occupancy for ROS1 and NTRKA/B/C) and safety (AUC < 160 µM·h and Cmax < 8.9 µM), the appropriate dosing regimens were identified. The appropriate dosage is 600 mg once daily (OD) when administered alone, reduced to 200 mg and 400 mg OD with itraconazole and fluconazole, respectively. ENT is not recommended for co-administration with rifampicin or efavirenz, but is permitted with fluvoxamine or dexamethasone. CONCLUSION: The PBPK models can serve as a powerful approach to predict ENT concentration as well as ROS1 and NTRKA/B/C occupancy in plasma and CSF.

Asunto(s)

Benzamidas , Indazoles , Proteínas Tirosina Quinasas , Proteínas Proto-Oncogénicas , Humanos , Interacciones Farmacológicas , Itraconazol/farmacocinética , Modelos Biológicos

RESUMEN

The concomitant use of elexacaftor/tezacaftor/ivacaftor (ETI) and strong CYP3A inducers including rifampin and rifabutin is not recommended due to the risk of drug-drug interactions (DDI). This presents a significant challenge to the treatment of non-tuberculous mycobacteria precluding the first line treatment. While rifabutin induces CYP3A activity, its effect appears to be moderate compared to rifampin. In this study, we investigated three cases in which concomitant use of rifabutin and CFTR modulators (ETI or ivacaftor monotherapy) was used, and these cases suggest that addition of rifabutin did not compromise the efficacy of ETI or ivacaftor as evidenced by pulmonary function and sweat chloride testing. A full physiologically based pharmacokinetic model predicted lung concentrations of ETI upon rifabutin coadministration to exceed the half-maximal effective concentrations (EC50) determined from chloride transport in phe508del human bronchial epithelial cells. This study provides preliminary evidence in support of the use of rifabutin in patients receiving ETI.

RESUMEN

Because of the high research and development cost of new drugs, the long development process of new drugs, and the high failure rate at later stages, combining past drugs has gradually become a more economical and attractive alternative. However, the ensuing problem of drug-drug interactions (DDIs) urgently need to be solved, and combination has attracted a lot of attention from pharmaceutical researchers. At present, DDI is often evaluated and investigated from two perspectives: pharmacodynamics and pharmacokinetics. However, in some special cases, DDI cannot be accurately evaluated from a single perspective. Therefore, this review describes and compares the current DDI evaluation methods based on two aspects: pharmacokinetic interaction and pharmacodynamic interaction. The methods summarized in this paper mainly include probe drug cocktail methods, liver microsome and hepatocyte models, static models, physiologically based pharmacokinetic models, machine learning models, in vivo comparative efficacy studies, and in vitro static and dynamic tests. This review aims to serve as a useful guide for interested researchers to promote more scientific accuracy and clinical practical use of DDI studies.

RESUMEN

The COVID-19 pandemic sparked the development of novel anti-viral drugs that have shown to be effective in reducing both fatality and hospitalization rates in patients with elevated risk for COVID-19 related morbidity or mortality. Currently, nirmatrelvir/ritonavir (Paxlovid™) fixed-dose combination is recommended by the World Health Organization for treatment of COVID-19. The ritonavir component is an inhibitor of cytochrome P450 (CYP) 3A, which is used in this combination to achieve needed therapeutic concentrations of nirmatrelvir. Because of the critical pharmacokinetic effect of this mechanism of action for Paxlovid™, co-administration with needed medications that inhibit or induce CYP3A is contraindicated, reflecting concern for interactions with the potential to alter the efficacy or safety of co-administered drugs that are also metabolized by CYP3A. Some herbal medicines are known to interact with drug metabolizing enzymes and transporters, including but not limited to inhibition or induction of CYP3A and P-glycoprotein. As access to these COVID-19 medications has increased in low- and middle-income countries (LMICs), understanding the potential for herb-drug interactions within these regions is important. Many studies have evaluated the utility of herbal medicines for COVID-19 treatments, yet information on potential herb-drug interactions involving Paxlovid™, specifically with herbal medicines commonly used in LMICs, is lacking. This review presents data on regionally-relevant herbal medicine use (particularly those promoted as treatments for COVID-19) and mechanism of action data on herbal medicines to highlight the potential for herbal medicine interaction Herb-drug interaction mediated by ritonavir-boosted antiviral protease inhibitors This work highlights potential areas for future experimental studies and data collection, identifies herbal medicines for inclusion in future listings of regionally diverse potential HDIs and underscores areas for LMIC-focused provider-patient communication. This overview is presented to support governments and health protection entities as they prepare for an increase of availability and use of Paxlovid™.

RESUMEN

Background: Acute kidney injury (AKI), with an increase in serum creatinine, is a common adverse drug event. Although various clinical studies have investigated whether a combination of two nephrotoxic drugs has an increased risk of AKI using traditional statistical models such as multivariable logistic regression (MLR), the evaluation metrics have not been evaluated despite the fact that traditional statistical models may over-fit the data. The aim of the present study was to detect drug-drug interactions with an increased risk of AKI by interpreting machine-learning models to avoid overfitting. Methods: We developed six machine-learning models trained using electronic medical records: MLR, logistic least absolute shrinkage and selection operator regression (LLR), random forest, extreme gradient boosting (XGB) tree, and two support vector machine models (kernel = linear function and radial basis function). In order to detect drug-drug interactions, the XGB and LLR models that showed good predictive performance were interpreted by SHapley Additive exPlanations (SHAP) and relative excess risk due to interaction (RERI), respectively. Results: Among approximately 2.5 million patients, 65,667 patients were extracted from the electronic medical records, and assigned to case (N = 5,319) and control (N = 60,348) groups. In the XGB model, a combination of loop diuretic and histamine H2 blocker [mean (|SHAP|) = 0.011] was identified as a relatively important risk factor for AKI. The combination of loop diuretic and H2 blocker showed a significant synergistic interaction on an additive scale (RERI 1.289, 95% confidence interval 0.226-5.591) also in the LLR model. Conclusion: The present population-based case-control study using interpretable machine-learning models suggested that although the relative importance of the individual and combined effects of loop diuretics and H2 blockers is lower than that of well-known risk factors such as older age and sex, concomitant use of a loop diuretic and histamine H2 blocker is associated with increased risk of AKI.

RESUMEN

Enzalutamide is known to strongly induce cytochrome P450 3A4 (CYP3A4). Furthermore, enzalutamide showed induction and inhibition of P-glycoprotein (P-gp) in in vitro studies. A clinical drug-drug interaction (DDI) study between enzalutamide and digoxin, a typical P-gp substrate, suggested enzalutamide has weak inhibitory effect on P-gp substrates. Direct oral anticoagulants (DOACs), such as apixaban and rivaroxaban, are dual substrates of CYP3A4 and P-gp, and hence it is recommended to avoid co-administration of these DOACs with combined P-gp and strong CYP3A inducers. Enzalutamide's net effect on P-gp and CYP3A for apixaban and rivaroxaban plasma exposures is of interest to physicians who treat patients for venous thromboembolism with prostate cancer. Accordingly, a physiologically-based pharmacokinetic (PBPK) analysis was performed to predict the magnitude of DDI on apixaban and rivaroxaban exposures in the presence of 160 mg once-daily dosing of enzalutamide. The PBPK models of enzalutamide and M2, a major metabolite of enzalutamide which also has potential to induce CYP3A and P-gp and inhibit P-gp, were developed and verified as perpetrators of CYP3A-and P-gp-mediated interaction. Simulation results predicted a 31% decrease in AUC and no change in Cmax for apixaban and a 45% decrease in AUC and a 25% decrease in Cmax for rivaroxaban when 160 mg multiple doses of enzalutamide were co-administered. In summary, enzalutamide is considered to decrease apixaban and rivaroxaban exposure through the combined effects of CYP3A induction and net P-gp inhibition. Concurrent use of these drugs warrants careful monitoring for efficacy and safety.

Asunto(s)

Citocromo P-450 CYP3A , Rivaroxabán , Masculino , Humanos , Citocromo P-450 CYP3A/metabolismo , Interacciones Farmacológicas , Preparaciones Farmacéuticas/metabolismo , Modelos Biológicos

RESUMEN

Elexacaftor/tezacaftor/ivacaftor (ETI) treatment has potential benefits in lung transplant recipients, including improvements in extrapulmonary manifestations, such as gastrointestinal and sinus disease; however, ivacaftor is an inhibitor of cytochrome P450 3A (CYP3A) and may, therefore, pose a risk for elevated systemic exposure to tacrolimus. The aim of this investigation is to determine the impact of ETI on tacrolimus exposure and devise an appropriate dosing regimen to manage the risk of this drug-drug interaction (DDI). The CYP3A-mediated DDI of ivacaftor-tacrolimus was evaluated using a physiologically based pharmacokinetic (PBPK) modeling approach, incorporating CYP3A4 inhibition parameters of ivacaftor and in vitro enzyme kinetic parameters of tacrolimus. To further support the findings in PBPK modeling, we present a case series of lung transplant patients who received both ETI and tacrolimus. We predicted a 2.36-fold increase in tacrolimus exposure when co-administered with ivacaftor, which would require a 50% dose reduction of tacrolimus upon initiation of ETI treatment to avoid the risk of elevated systemic exposure. Clinical cases (N = 13) indicate a median 32% (IQR: -14.30, 63.80) increase in the dose-normalized tacrolimus trough level (trough concentration/weight-normalized daily dose) after starting ETI. These results indicate that the concomitant administration of tacrolimus and ETI may lead to a clinically significant DDI, requiring the dose adjustment of tacrolimus.

RESUMEN

Introduction: Bulevirtide is a first-in-class antiviral drug to treat chronic hepatitis B/D. We investigated the drug-drug interaction potential and pharmacokinetics of high-dose subcutaneous bulevirtide (5 mg twice daily) with organic anion transporting polypeptide 1B1 (OATP1B1) and cytochrome P450 (CYP) 3A4. Methods: This was a single-center, open-label, fixed-sequence drug-drug interaction trial in 19 healthy volunteers. Before and at bulevirtide steady state, participants ingested a single 40 mg dose of pravastatin. A midazolam microdose was applied to quantify CYP3A4 activity. Results: At bulevirtide steady state, pravastatin area under the concentration-time curve (AUC0-∞) increased 1.32-fold (90% CI 1.08-1.61). The 5 mg bulevirtide twice-daily treatment resulted in a mean AUC0-12 of 1210 h*ng/ml (95% CI 1040-1408) and remained essentially unchanged under the influence of pravastatin. CYP3A4 activity did not change to a clinically relevant extent. As expected, total bile acids increased substantially (35-fold) compared to baseline during bulevirtide treatment. All study medication was well tolerated. Discussion: The study demonstrated that high-dose bulevirtide inhibited OATP1B-mediated hepatic uptake of the marker substrate pravastatin but the extent is considered clinically not relevant. Changes in CYP3A4 activity were also not clinically relevant. In conclusion, this study suggests that OATP1B substrate drugs as well as CYP3A4 substrates may safely be used without dose adjustment in patients treated with bulevirtide. However, in patients using high statin doses and where concomitant factors potentially further increase statin exposure, caution may be required when using bulevirtide.

RESUMEN

Uricosuric agents lower serum uric acid levels by increasing urinary excretion via inhibition of urate transporter 1 (URAT1), urate reabsorption transporter in the renal proximal tubules. Probenecid and benzbromarone have been used as uricosurics, but these drugs inhibit organic anion transporters (OATs) in addition to URAT1. In this study, we investigated whether uricosuric agents interacted with adefovir, known as a substrate for OAT1, using Sprague-Dawley (SD) rats. Furthermore, involvement of other transporters, multi-drug resistance protein 2 (MRP2) in this interaction was examined using Mrp2-deficient rats. Probenecid and lesinurad increased plasma adefovir concentrations and decreased kidney-to-plasma partition coefficient (Kp) in these rats, presumably by inhibiting Oat1. Although benzbromarone had no effect on plasma adefovir concentration, it increased the Kp to 141% in SD rats. Since this effect was abolished in Mrp2-deficient rats, together with the MRP2 inhibition study, it is suggested that benzbromarone inhibits Mrp2-mediated adefovir excretion from the kidney. In contrast, dotinurad, a novel uricosuric agent that selectively inhibits URAT1, had no effect on the plasma and kidney concentrations of adefovir. Therefore, due to the lack of interaction with adefovir, dotinurad is expected to have low drug-drug interaction risk mediated by OAT1, and also by MRP2.

Asunto(s)

Transportadores de Anión Orgánico , Uricosúricos , Ratas , Animales , Uricosúricos/farmacología , Benzbromarona , Probenecid/farmacología , Probenecid/metabolismo , Ácido Úrico , Ratas Sprague-Dawley , Riñón/metabolismo , Transportadores de Anión Orgánico/metabolismo

RESUMEN

Ripretinib, as an oral kinase inhibitor, has been approved to treat advanced gastrointestinal stromal tumors (GIST) and is often used in combination with other drugs to slow disease progression, thus potential drug-drug Interactions (DDIs) and drug-disease interactions (DDZIs) have received much attention. To guide clinical rational drug use, this study assessed the effect of co-administered drugs and diseases on ripretinib exposure. Simcyp® Simulator was used to develop the physiologically-based pharmacokinetic (PBPK) model of ripretinib, which was validated and refined with clinical data. We then examined the impact of several CYP3A4 inhibitors and inducers as well as different diseases on ripretinib exposure using the validated model. In the DDI simulation, moderate CYP3A4 inhibitors and inducers changed the exposure of ripretinib by 1.25-2 fold. In hepatic impairment (HI), the simulation showed that ripretinib's AUC increased by 32%, 100%, and 152% for Child-Pugh A, B, and C classification while Cmax increased by 2%, 10%, and 15%, respectively. In renal impairment (RI), the model-simulated AUC in moderate and severe RIs increased by 27% and 20%. In conclusion, PBPK models demonstrated quantitative prediction of ripretinib's pharmacokinetic changes under varying conditions that might be useful for its rational use.

Asunto(s)

Inhibidores del Citocromo P-450 CYP3A , Hepatopatías , Humanos , Naftiridinas , Interacciones Farmacológicas , Modelos Biológicos , Citocromo P-450 CYP3A , Simulación por Computador

Asunto(s)

Transportadores de Anión Orgánico Sodio-Independiente , Insuficiencia Renal Crónica , Humanos , Meropenem , Interacciones Farmacológicas , Riñón , Células HEK293

RESUMEN

Background: Combination of Polygonum capitatum Buch.-Ham. ex D. Don extract (PCE) and ciprofloxacin (CIP) was commonly prescribed in the treatment of urinary tract infections. Their pharmacokinetic herb-drug interactions (HDIs) were focused in this study to assess potential impact on the safety and effectiveness. Methods: A randomized, three-period, crossover trial was designed to study the pharmacokinetic HDI between PCE and CIP in healthy humans. Their pharmacokinetic- and tissue distribution-based HDIs were also evaluated in rats. Gallic acid (GA) and protocatechuic acid (PCA) were chosen as PK-markers of PCE in humans and rats. Potential drug interaction mechanisms were revealed by assessing the effects of PCE on the activity and expression of multiple transporters, including OAT1/3, OCT2, MDR1, and BCRP. Results: Concurrent use of PCE substantially reduced circulating CIP (approximately 40%-50%) in humans and rats, while CIP hardly changed circulating GA and PCA. PCE significantly increased the tissue distribution of CIP in the prostate and testis of rats, but decreased in liver and lungs. Meanwhile, CIP significantly increased the tissue distribution of GA or PCA in the prostate and testis of rats, but decreased in kidney and heart. In the transporter-mediated in vitro HDI, GA and PCA presented inhibitory effects on OAT1/3 and inductive effects on MDR1 and BCRP. Conclusion: Multiple transporter-mediated HDI contributes to effects of PCE on the reduced systemic exposure and altered tissue distribution of CIP. More attention should be paid on the potential for PCE-perpetrated interactions.

RESUMEN

Background: Selecting a medicine has a significant impact on the quality of therapy including efficacy and safety. P-glycoprotein and CYP3A4 share several common substrates known as bi-substrates. Both play major role in the pharmacokinetics and pharmacodynamics when over or under expressed. Objective: The study aimed to assess the Drug-Drug Interaction (DDI) related to P-glycoprotein (P-gp) and Cytochrome P450-3A4 (CYP3A4), to predict their clinical outcomes and also to discover prospective predictors of pDDIs. Methods: The subjects in this retrospective study ranged in age from 18 to 95 years with polypharmacy prescriptions. Information was gathered through patient medical records. Based on Micromedex and previous literature studies, medications prescribed to the patients were observed for pDDIs according to risk rating scale for drug interactions. Results: A total of 504 patients (160 males and 344 females) were included in the study. The mean of pDDI seen in the patients was 1.66 ± 1.48 and total 825 pDDIs were discovered. The factors significantly associated with having ≥1 pDDIs included: taking ≥5 medicines (OR 1.747), increased age (OR 1.026) increased comorbidities (OR 1.73). Conclusion: In prescriptions, a considerable number of probable DDI were discovered. Therefore, careful selection of drugs and identification of mechanisms for DDI is needed to lower the frequency of pDDI.

RESUMEN

Antimicrobial therapy is often a life-saving medical intervention for inpatients and outpatients. Almost all medical disciplines are involved in this therapeutic procedure. Knowledge of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) is important to avoid drug-related harm. Within the broad spectrum of antibiotic and antifungal therapy, most typical ADRs are known to physicians. The aim of this study was to evaluate relevant pharmacological aspects with which we are not so familiar and to provide further practical guidance. Individual pharmacotherapy management (IPM) as a synopsis of internal medicine and clinical pharmacology based on the entirety of the digital patient information with reference to drug information, guidelines, and literature research has been continuously performed for over 8 years in interdisciplinary intensive care and trauma and transplant patients. Findings from over 52,000 detailed medication analyses highlight critical ADRs and DDIs, especially in these vulnerable patients with polypharmacy. We present the most relevant ADRs and DDIs in antibiotic and antifungal pharmacology, which are less frequently considered in relation to neurologic, hemostaseologic, hematologic, endocrinologic, and cardiac complexities. Constant awareness and preventive strategies help avoid life-threatening manifestations of these inherent risks and ensure patient and drug safety in antimicrobial therapy.

RESUMEN

Aim: It has been found that the co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. But, whether this pharmacokinetic drug-drug interaction (DDI) between nifedipine and apatinib could enhance the antihypertensive effect of nifedipine, causing sever changes of blood pressure was unknown. Therefore, the aim of the present study was to conduct the pharmacokinetic/pharmacodynamic (PK/PD) modelling to evaluate the effect of pharmacokinetic changes on the antihypertensive effect of nifedipine. Thus, the results could guide the co-administration of these two drugs in clinic. Methods: A physiologically-based pharmacokinetic (PBPK) model was first developed for nifedipine. The pharmacokinetic DDI between nifedipine and apatinib was evaluated. Then the verified PBPK models were linked to a PD model for investigating whether the exposure changes of nifedipine could cause severe changes in blood pressure. Furthermore, the changes in blood pressure caused by combination with apatinib were also assessed in patients with hepatic impairment via the PBPK/PD models. Results: The predicted area under plasma concentration-time profile (AUC), maximum concentration (Cmax), area under effect-time profile (AUE), and maximum reduction in systolic blood pressure (Rmax) are all within 0.5-2.0-fold of the observed data, indicating that the PBPK/PD models for nifedipine are successfully established. The increases of predicted AUC and Cmax of nifedipine in the presence of apatinib are 1.73 and 1.41-fold, respectively. Co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. However, the predicted AUE and Rmax changes of nifedipine in the presence to the absence of apatinib in cancer patients as well as in patients with hepatic impairment are all within 1.25-fold. The results indicate that the exposure changes of nifedipine caused by combination of apatinib has little effect on the changes of systolic blood pressure both in cancer patients and patients with hepatic impairment. Conclusion: The pharmacokinetic changes of nifedipine caused by co-administration with apatinib has little impact on the antihypertensive effect of nifedipine. Apatinib is unlikely to cause severe pharmacodynamic DDI via inhibition of CYP3A4. It is suggested that nifedipine could be used in combination with apatinib without dose adjustment in clinic.