Clinical Drug-drug Interactions Research Articles

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

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

A Comprehensive Review of the Clinical Pharmacokinetics, Pharmacodynamics, and Drug Interactions of Nirmatrelvir/Ritonavir.

Nirmatrelvir is a potent and selective inhibitor of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease that is used as an oral antiviral coronavirus disease 2019 (COVID-19) treatment. To sustain unbound systemic trough concentrations above the antiviral in vitro 90% effective concentration value (EC90), nirmatrelvir is coadministered with 100 mg of ritonavir, a pharmacokinetic enhancer. Ritonavir inhibits nirmatrelvir's cytochrome P450 (CYP) 3A4-mediated metabolism which results in renal elimination becoming the primary route of nirmatrelvir elimination when dosed concomitantly. Nirmatrelvir exhibits absorption-limited nonlinear pharmacokinetics. When coadministered with ritonavir in patients with mild-to-moderate COVID-19, nirmatrelvir reaches a maximum concentration of 3.43 µg/mL (11.7× EC90) in approximately 3 h on day 5 of dosing, with a geometric mean day 5 trough concentration of 1.57 µg/mL (5.4× EC90). Drug interactions with nirmatrelvir/ritonavir (PAXLOVIDTM) are primarily attributed to ritonavir-mediated CYP3A4 inhibition, and to a lesser extent CYP2D6 and P-glycoprotein inhibition. Population pharmacokinetics and quantitative systems pharmacology modeling support twice daily dosing of 300 mg/100 mg nirmatrelvir/ritonavir for 5 days, with a reduced 150 mg/100 mg dose for patients with moderate renal impairment. Rapid clinical development of nirmatrelvir/ritonavir in response to the emerging COVID-19 pandemic was enabled by innovations in clinical pharmacology research, including an adaptive phase 1 trial design allowing direct to pivotal phase 3 development, fluorine nuclear magnetic resonance spectroscopy to delineate absorption, distribution, metabolism, and excretion profiles, and innovative applications of model-informed drug development to accelerate development.

SELF-MEDICATION ASSOCIATED WITH TOOTHACHE: A SYSTEMATIC LITERATURE REVIEW

Introduction: Self-medication consists of selecting and using medication without a prescription or guidance from a healthcare professional. This practice has been widely reported worldwide, which has contributed to a series of adverse health outcomes, such as delayed diagnosis, worsening of clinical conditions, drug interactions, intoxication, and adverse reactions, which tend to compromise patient safety. Objective: To analyze the prevalence of self-medication associated with toothache, the main factors associated with self-medication in dental patients, as well as outline the profile of medications used by these individuals, the preferred route of administration, and the main sources of medication. Methodology: A systematic review was developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Relevant articles published in the last ten years, without limitations of language were searched using the following descriptors/MeSHterms and keywords: "self-medication" and (toothache or "dental pain") not Child. Results: The initial search returned 57 manuscripts. Fourteen papers, all cross-sectional studies, were eligible for inclusion in the systematic review. Conclusions: The prevalence of self-medication for toothache ranged from 6.5% to 100.0%. Cultural and economic factors, barriers to access, the high cost of dental treatments, lack of time and money, and the perception that dental problems are not a serious problem are among the main factors associated with the practice. Regarding the drugs used, the most used classes were paracetamol, especially anti-inflammatory drugs, particularly ibuprofen, and analgesics administered orally.

Physiologically Based Pharmacokinetic Modeling for Maribavir to Inform Dosing in Drug-Drug Interaction Scenarios with CYP3A4 Inducers and Inhibitors.

Maribavir, an orally available antiviral agent, has been approved in multiple countries for the treatment of patients with refractory post-transplant cytomegalovirus (CMV) infection and/or disease. Maribavir is primarily metabolized by CYP3A4; coadministration with CYP3A4 inducers and inhibitors may significantly alter maribavir exposure, thereby affecting its efficacy and safety. The effect of CYP3A4 inducers and inhibitors on maribavir exposure was evaluated based on a drug-drug interaction (DDI) study and physiologically-based pharmacokinetic (PBPK) modeling. The effect of rifampin (a strong inducer of CYP3A4 and moderate inducer of CYP1A2), administered at a 600mg dose once daily, on maribavir pharmacokinetics was assessed in a clinical phase1 DDI study in healthy participants. A full PBPK model for maribavir was developed and verified using invitro and clinical pharmacokinetic data from phase1 studies. The verified PBPK model was then used to simulate maribavir DDI interactions with various CYP3A4 inducers and inhibitors. The DDI study results showed that coadministration with rifampin decreased the maribavir maximum plasma concentration (Cmax), area under the plasma concentration-time curve (AUC), and trough concentration (Ctrough) by 39%, 60%, and 82%, respectively. Based on the results from the clinical DDI study, the coadministration of maribavir with rifampin is not recommended. The PBPK model did not predict a clinically significant effect of CYP3A4 inhibitors on maribavir exposure; however, it predicted that strong or moderate CYP3A4 inducers, including carbamazepine, efavirenz, phenobarbital, and phenytoin, may reduce maribavir exposure to a clinically significant extent, and may prompt the consideration of a maribavir dosing increase, in accordance with local approved labels and/or regulations.

Creation of Novel Sensitive Probe Substrate and Moderate Inhibitor Models for a Comprehensive Prediction of CYP2C8 Interactions for Tucatinib.

A physiologically-based pharmacokinetic (PBPK) model was developed to simulate plasma concentrations of tucatinib (TUKYSA®) after single-dose or multiple-dose administration of 300 mg b.i.d. orally. This PBPK model was subsequently applied to support evaluation of drug-drug interaction (DDI) risk as a perpetrator resulting from tucatinib inhibition of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was also applied to support evaluation of DDI risk as a victim resulting from co-administration with CYP3A4 or CYP2C8 inhibitors, or a CYP3A4 inducer. After refinement with clinical DDI data, the final PBPK model was able to recover the clinically observed single and multiple-dose plasma concentrations for tucatinib when tucatinib was administered as a single agent in healthy subjects. In addition, the final model was able to recover clinically observed plasma concentrations of tucatinib when administered in combination with itraconazole, rifampin, or gemfibrozil as well as clinically observed plasma concentrations of probe substrates of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was then applied to prospectively predict the potential perpetrator or victim DDIs with other substrates, inducers, or inhibitors. To simulate a potential interaction with a moderate CYP2C8 inhibitor, two novel PBPK models representing a moderate CYP2C8 inhibitor and a sensitive CYP2C8 substrate were developed based on the existing PBPK models for gemfibrozil and rosiglitazone, respectively. The simulated population geometric mean area under the curve ratio of tucatinib with a moderate CYP2C8 inhibitor ranged from 1.98- to 3.08-fold, and based on these results, no dose modifications were proposed for moderate CYP2C8 inhibitors for the tucatinib label.

Inhibitory Effects of Tricyclic Antidepressants on Human Liver Microsomal Morphine Glucuronidation: Application of IVIVE to Predict Potential Drug-Drug Interactions in Humans.

Tricyclic antidepressants (TCAs) are commonly co-administered with morphine as an adjuvant analgesic. Nevertheless, there remains a lack of information concerning metabolic drug-drug interactions (DDIs) resulting from TCA inhibition on morphine glucuronidation. This study aimed to (i) examine the inhibitory effects of TCAs (viz., amitriptyline, clomipramine, imipramine, and nortriptyline) on human liver microsomal morphine 3- and 6-glucuronidation and (ii) evaluate the potential of DDI in humans by employing in vitro-in vivo extrapolation (IVIVE) approaches. The inhibition parameters for TCA inhibition on morphine glucuronidation were derived from the in vitro system containing 2% BSA. The Ki values were employed to predict the DDI magnitude in vivo by using static and dynamic mechanistic PBPK approaches Results: TCAs moderately inhibited human liver microsomal morphine glucuronidation, with clomipramine exhibiting the most potent inhibition potency. Amitriptyline, clomipramine, imipramine, and nortriptyline competitively inhibited morphine 3- and 6-glucuronide formation with the respective Ki values of 91 ± 7.5 and 82 ± 11 μM, 23 ± 1.3 and 14 ± 0.7 μM, 103 ± 5 and 90 ± 7 μM, and 115 ± 5 and 110 ± 3 μM. Employing the static mechanistic IVIVE, a prediction showed an estimated 20% elevation in the morphine AUC when co-administered with either clomipramine or imipramine, whereas the predicted increase was <5% for amitriptyline or nortriptyline. PBPK modelling predicted an increase of less than 10% in the morphine AUC due to the inhibition of clomipramine and imipramine in both virtual healthy and cirrhotic populations. The results suggest that the likelihood of potential clinical DDIs arising from tricyclic antidepressant inhibition on morphine glucuronidation is low.

Quantitative prediction of CYP3A-mediated drug-drug interactions by correctly estimating fraction metabolized using human liver chimeric mice.

Fraction metabolized (fm ) and fraction transported (ft ) are important for understanding drug-drug interactions (DDIs) in drug discovery and development. However, current in vitro systems cannot accurately estimate in vivo fm due to inability to reflect the ft by efflux transporters (ft,efflux ). This study demonstrates how CYP3A-mediated DDI for CYP3A/P-gp substrates can be predicted using Hu-PXB mice as human liver chimeric mice. For estimating human in vitro fm by CYP3A enzyme (fm,CYP3A,in vitro ), six drugs, including CYP3A/P-gp substrates (alprazolam, cyclosporine, docetaxel, midazolam, prednisolone, and theophylline) and human hepatocytes were incubated with or without ketoconazole as a CYP3A inhibitor. We calculated fm,CYP3A,in vitro based on hepatic intrinsic clearance. To estimate human in vivo fm,CYP3A (fm,CYP3A,in vivo ), we collected information on clinical DDI caused by ketoconazole for these six drugs. We calculated fm,CYP3A,in vivo using the change of total clearance (CLtotal ). For evaluating the human DDI predictability, the six drugs were administered intravenously to Hu-PXB and SCID mice with or without ketoconazole. We calculated the change of CLtotal caused by ketoconazole. We compared the CLtotal change in humans with that in Hu-PXB and SCID mice. The fm,CYP3A,in vitro was overestimated compared to the fm,CYP3A,in vivo . Hu-PXB mice showed much better correlation in the change of CLtotal with humans (R2 = 0.95) compared to SCID mice (R2 = 0.0058). CYP3A-mediated DDI can be predicted by correctly estimating human fm,CYP3A,in vivo using Hu-PXB mice. These mice could be useful predicting hepatic fm and ft,efflux .

The Effect of BI 730357 (Retinoic Acid-Related Orphan Receptor Gamma t Antagonist, Bevurogant) on the Pharmacokinetics of a Transporter Probe Cocktail, Including Digoxin, Furosemide, Metformin, and Rosuvastatin: An Open-Label, Non-randomized, 2-Period Fixed-Sequence Trial in Healthy Subjects.

Evaluating Drug-Drug Interactions (DDIs) for new investigational compounds requires several trials evaluating different drugs with different transporter specificities. By using a cocktail of drugs with different transporter specificities, a single trial could evaluate the pharmacokinetics (PKs) of each cocktail drug simultaneously, reducing the number of clinical DDI trials required for clinical development. We aimed to investigate the effect of steady-state Boehringer Ingelheim (BI) 730357 (bevurogant) on the PKs of a validated and optimized 4-component transporter cocktail. This open-label, non-randomized, 2-period fixed-sequence phase I trial compared transporter cocktail (0.25mg digoxin/1mg furosemide/10mg metformin hydrochloride/10mg rosuvastatin) with and without BI 730357 in healthy subjects aged 18-55 years with body mass index 18.5-29.9kg/m2 . During reference treatment/period 1, transporter cocktail was administered 90 minutes after breakfast. After a washout period, during test treatment/period 2, BI 730357 was dosed twice daily for 13 days, with transporter cocktail administered on day 1. The primary endpoints were the area under the concentration-time curve of the analyte in plasma over the time interval from 0 extrapolated to infinity (AUC0-∞ ) and the maximum measured concentration of the analyte in plasma (Cmax ), and the secondary endpoint was the area under the concentration-time curve of the analyte in plasma over the time interval from 0 to the last quantifiable data point (AUC0-tz ). Steady-state BI 730357 increased digoxin (+48% to +94%), minimally affected metformin (-2% to -9%), furosemide (+12% to +18%), and rosuvastatin (+19% to +39%) exposure. Therefore, no clinically relevant inhibition of transporters OCT2/MATE-1/MATE-2K, OAT1/OAT3, OATP1B1/OATP1B3 was observed. Potential inhibition of breast cancer resistance protein noted as PK parameters of coproporphyrin I/III (OATP1B1/OATP1B3 biomarkers) remained within bioequivalence boundaries while rosuvastatin PK parameters (AUC0-∞ /Cmax /AUC0-tz ) exceeded the bioequivalence boundary. BI 730357 was safe and well tolerated. This trial confirms the usefulness and tolerability of the transporter cocktail consisting of digoxin, furosemide, metformin, and rosuvastatin in assessing drug-transporter interactions in vivo.

Poor Correlation of Rivaroxaban Concentration with the Routine Coagulation Screening Test in Chinese Patients with Atrial Fibrillation

Aims. The aim of this study is to assess the relationship between rivaroxaban plasma concentration quantified by the gold standard and anticoagulant activities measured by routine coagulation assays in Chinese atrial fibrillation (AF) patients. Whether the normal results of these tests were reliable to rule out clinically relevant rivaroxaban levels at various thresholds was also explored. The effect of clinical drug-drug interactions (DDIs) on the exposure and anticoagulant effect of rivaroxaban were further evaluated. Methods. 116 patients receiving rivaroxaban for the management of nonvalvular AF were recruited. Rivaroxaban concentrations and coagulation tests were measured by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and a blood coagulation analyzer, respectively. Results. The correlation of trough concentration (Ctrough) and prothrombin time (PT) or international normalized ratio (INR) was moderate with Spearman’s correlation coefficient of 0.495 and 0.506, respectively. A normal PT/INR was unable to rule out Ctrough levels of &gt;30 ng/mL and &gt;50 ng/mL, but the negative predictive value reached 100% to exclude Ctrough of &gt;100 ng/mL. Ctrough showed a small correlation with activated partial thromboplastin time (aPTT) (Spearman’s correlation coefficient: 0.241) and no correlation with thrombin time (TT) (Spearman’s correlation coefficient: 0.074). Neither aPTT nor TT accurately predicted Ctrough at any concentration. Peak concentration (Cpeak) did not correlate with any coagulation parameters. The presence of digoxin and febuxostat significantly increased rivaroxaban Ctrough by 2.18 fold and prolonged PT and INR by 44.16% and 43.60%, respectively. Conclusions. Normal routine coagulation assays were insufficient to monitor therapy with rivaroxaban. Poor correlations between rivaroxaban concentration and routine coagulation assays were observed in Chinese AF patients. The use of digoxin/febuxostat alone had no effect on rivaroxaban concentrations; however, combined strong breast cancer resistance protein inhibitor (febuxostat) and P-glycoprotein probe (digoxin) in patients with renal impairment is likely to cause clinically significant DDI with rivaroxaban. More studies are needed to establish routine therapeutic drug monitoring of rivaroxaban in clinical practice.

Physiologically Based Pharmacokinetic Modeling of the Drug-Drug Interaction Between CYP3A4 Substrate Glasdegib and Moderate CYP3A4 Inducers in Lieu of a Clinical Study.

Glasdegib (DAURISMO) is a hedgehog pathway inhibitor approved for the treatment of acute myeloid leukemia (AML). Cytochrome P450 3A4 (CYP3A4) has been identified as a major metabolism and clearance pathway for glasdegib. The role of CYP3A4 in the clearance of glasdegib has been confirmed with clinical drug-drug interaction (DDI) studies following the coadministration of glasdegib with the strong CYP3A4 inhibitor ketoconazole and the strong inducer rifampin. To evaluate potential drug interactions with CYP3A4 modulators, the coadministration of glasdegib with a moderate CYP3A4 inducer, efavirenz, was evaluated using physiologically based pharmacokinetic (PBPK) modeling using the Simcyp simulator. The glasdegib compound file was developed using measured physicochemical properties, data from human intravenous and oral pharmacokinetics, absorption, distribution, metabolism, and excretion studies, and invitro reaction phenotyping results. The modeling assumptions, model parameters, and assignments of fractional CYP3A4 metabolism were verified using results from clinical pharmacokinetics (PK) and DDI studies with ketoconazole and rifampin. The verified glasdegib and efavirenz compound files, the latter of which was available in the Simcyp simulator, were used to estimate the potential impact of efavirenz on the PK of glasdegib. PBPK modeling predicted a glasdegib area under the concentration-time curve ratio of 0.45 and maximum plasma concentration ratio of 0.75 following coadministration with efavirenz. The PBPK results, in lieu of a formal clinical study, informed the drug label, with the recommendation to double the clinical dose of glasdegib when administered in conjunction with a moderate CYP3A4 inducer, followed by a resumption of the original dose 7days post-discontinuation.

Applied physiologically-based pharmacokinetic modeling to assess uridine diphosphate-glucuronosyltransferase-mediated drug-drug interactions for Vericiguat.

Vericiguat (Verquvo; US: Merck, other countries: Bayer) is a novel drug for the treatment of chronic heart failure. Preclinical studies have demonstrated that the primary route of metabolism for vericiguat is glucuronidation, mainly catalyzed by uridine diphosphate-glucuronosyltransferase (UGT)1A9 and to a lesser extent UGT1A1. Whereas a drug-drug interaction (DDI) study of the UGT1A9 inhibitor mefenamic acid showed a 20% exposure increase, the effect of UGT1A1 inhibitors has not been assessed clinically. This modeling study describes a physiologically-based pharmacokinetic (PBPK) approach to complement the clinical DDI liability assessment and support prescription labeling. A PBPK model of vericiguat was developed based on invitro and clinical data, verified against data from the mefenamic acid DDI study, and applied to assess the UGT1A1 DDI liability by running an in silico DDI study with the UGT1A1 inhibitor atazanavir. A minor effect with an area under the plasma concentration-time curve (AUC) ratio of 1.12 and a peak plasma concentration ratio of 1.04 was predicted, which indicates that there is no clinically relevant DDI interaction anticipated. Additionally, the effect of potential genetic polymorphisms of UGT1A1 and UGT1A9 was evaluated, which showed that an average modest increase of up to 1.7-fold in AUC may be expected in the case of concomitantly reduced UGT1A1 and UGT1A9 activity for subpopulations expressing non-wild-type variants for both isoforms. This study is a first cornerstone to qualify the PK-Sim platform for use of UGT-mediated DDI predictions, including PBPK models of perpetrators, such as mefenamic acid and atazanavir, and sensitive UGT substrates, such as dapagliflozin and raltegravir.

Utilization of OATP1B Biomarker Coproporphyrin-I to Guide Drug-Drug Interaction Risk Assessment: Evaluation by the Pharmaceutical Industry.

Drug-drug interactions (DDIs) involving hepatic organic anion transporting polypeptides 1B1/1B3 (OATP1B) can be substantial, however, challenges remain for predicting interaction risk. Emerging evidence suggests that endogenous biomarkers, particularly coproporphyrin-I (CP-I), can be used to assess in vivo OATP1B activity. The present work under the International Consortium for Innovation and Quality in Pharmaceutical Development was aimed primarily at assessing CP-I as a biomarker for informing OATP1B DDI risk. Literature and unpublished CP-I data along with pertinent in vitro and clinical DDI information were collected to identify DDIs primarily involving OATP1B inhibition and assess the relationship between OATP1B substrate drug and CP-I exposure changes. Static models to predict changes in exposure of CP-I, as a selective OATP1B substrate, were also evaluated. Significant correlations were observed between CP-I area under the curve ratio (AUCR) or maximum concentration ratio (Cmax R) and AUCR of substrate drugs. In general, the CP-I Cmax R was equal to or greater than the CP-I AUCR. CP-I Cmax R < 1.25 was associated with absence of OATP1B-mediated DDIs (AUCR < 1.25) with no false negative predictions. CP-I Cmax R < 2 was associated with weak OATP1B-mediated DDIs (AUCR < 2). A correlation was identified between CP-I exposure changes and OATP1B1 static DDI predictions. Recommendations for collecting and interpreting CP-I data are discussed, including a decision tree for guiding DDI risk assessment. In conclusion, measurement of CP-I is recommended to inform OATP1B inhibition potential. The current analysis identified changes in CP-I exposure that may be used to prioritize, delay, or replace clinical DDI studies.

Quantitative prediction of transporter-mediated drug-drug interactions using the mechanistic static pharmacokinetic (MSPK) model

Guidance/guidelines on drug-drug interactions (DDIs) have been issued in Japan, the United States, and Europe. These guidance/guidelines provide decision trees for conducting metabolizing enzyme-mediated clinical DDI studies; however, the decision trees for transporter-mediated DDIs lack quantitative prediction methods. In this study, the accuracy of a net-effect mechanistic static pharmacokinetics (MSPK) model containing the fraction transported (ft) of transporters was examined to predict transporter-mediated DDIs. This study collected information on 25 oral drugs with new active reagents that were used in clinical DDI studies as perpetrators (42 cases) from drugs approved in Japan between April 2016 and June 2020. The AUCRs (AUC ratios with and without perpetrators) of victim drugs were predicted using the net-effect MSPK model. As a result, 83 and 95% of the predicted AUCRs were within 1.5- and 2-fold error in the observed AUCRs, respectively. In cases where the victims were statins in which pharmacokinetics several transporters are involved, 70 and 91% of the predicted AUCRs were within 1.5- and 2-fold errors, respectively. Therefore, the net-effect MSPK model was applicable for predicting the AUCRs of victims, which are substrates for multiple transporters.

Impact of redesign of a clinical decision allergy and drug interactions alerts in an electronic prescribing system on patient safety – a quantitative descriptive study: Erratum

Impact of redesign of a clinical decision allergy and drug interactions alerts in an electronic prescribing system on patient safety – a quantitative descriptive study: Erratum

Is use of a long-term proton pump inhibitor or histamine-2 receptor antagonist a risk factor for iron-deficiency anaemia in Taiwan? A neglected clinical drug-drug interaction.

Proton pump inhibitors (PPIs) and histamine-2 receptor (H2) antagonists change the gastric pH and reduce the intestinal absorption of nonheme iron. Case reports and case-control studies have demonstrated that absorption of iron is affected by gastric acidity, but the clinical importance of these drug-drug interactions has remained uncertain. The present case-control study employed 2 million longitudinal claims in 2011-2018 in the Taiwan National Health Insurance Research Database to investigate the impact of PPIs/H2 antagonists on the occurrence of iron-deficiency anaemia (IDA). The present study retrospectively compared exposure to PPIs/H2 antagonists for 1 year among 5,326 cases with IDA and 21,304 matched controls. The postdiagnosis prescribing pattern was also calculated to understand current practice. Long-term (≥2 month) use of PPIs/H2 antagonists resulted in a higher risk of developing IDA than noncontinuous use/nonuse of those drugs (adjusted odds ratio [aOR] = 2.36, 95% confidence interval [CI] = 1.94-2.86, P < 0.001). There were significant changes in the postdiagnosis prescribing patterns of PPIs/H2 antagonists. The risk of developing IDA remained significant in the female subgroup (aOR = 2.16, 95% CI = 1.73-2.70, P < 0.001) and was even more prominent in those aged ≥ 50 years (aOR = 2.68, 95% CI = 1.94-3.70, P < 0.05). This study found that long-term use of PPIs/H2 antagonists increased the risk of developing IDA, and there was strong evidence of prescription pattern adjustments postdiagnosis. Physicians and pharmacists should be aware of this risk when patients are expected to take or have been taking PPIs/H2 antagonists for the long term.

Imeglimin: A Clinical Pharmacology Review.

Imeglimin (PXL008, EMD-387008, Twymeeg®) is a first-in-class novel oral hypoglycemic agent, launched in Japan, for the treatment of type 2 diabetes mellitus. Its mechanism of action targets mitochondrial bioenergetics to ameliorate insulin resistance and to enhance β-cell function. This review summarizes the properties underlying the pharmacokinetic profile of imeglimin, a small cationic drug belonging to the tetrahydrotriazine chemical class, with a complex mechanism of absorption involving an active transport through organic cation transporters (OCTs). Imeglimin absorption decreases when dose increases due to the saturation of the active uptake transport. Post absorption, imeglimin is rapidly and primarily distributed to organs and tissues, and has a half-life ranging from 9.03 to 20.2h. Plasma protein binding of imeglimin is low, which explains the rapid distribution to the organs observed in all species. Imeglimin is excreted unchanged in urine, indicating a low extent of metabolism. Imeglimin is a substrate of multidrug and toxic compound extrusion (MATE)2-K and a substrate and inhibitor of OCT1, OCT2, and MATE1. Clinical drug-drug interaction studies confirmed the absence of relevant clinical interaction with substrates or inhibitors of these transporters. Overall, the drug-drug interaction potential of imeglimin is low. Its pharmacokinetics profile has also been characterized in special populations, showing no influence of mild and moderate hepatic impairment but an impact of renal function on imeglimin renal clearance. Dosage adjustment is thus required in moderately and severely renally impaired patients. Imeglimin pharmacokinetics was shown to be insensitive to ethnicity and food intake and to have no effect on QTcF interval.

TICBase: Integrated Resource for Data on Drug and Environmental Chemical Interactions with Mammalian Drug Transporters.

Environmental health science seeks to predict how environmental toxins, chemical toxicants, and prescription drugs accumulate and interact within the body. Xenobiotic transporters of the ATP-binding cassette (ABC) and solute carrier (SLC) superfamilies are major determinants of the uptake and disposition of xenobiotics across the kingdoms of life. The goal of this study was to integrate drug and environmental chemical interactions of mammalian ABC and SLC proteins in a centralized, integrative database. We built upon an existing publicly accessible platform-the "TransPortal"-which was updated with novel data and searchable features on transporter-interfering chemicals from manually curated literature data. The integrated resource TransPortal-TICBase (https://transportal.compbio.ucsf.edu) now contains information on 46 different mammalian xenobiotic transporters of the ABC- and SLC-type superfamilies, including 13 newly added rodent and 2 additional human drug transporters, 126 clinical drug-drug interactions, and a more than quadrupled expansion of the initial in vitro chemical interaction data from 1,402 to 6,296 total interactions. Based on our updated database, environmental interference with major human and rodent drug transporters occurs across the ABC- and SLC-type superfamilies, with kinetics indicating that some chemicals, such as the ionic liquid 1-hexylpyridinium chloride and the antiseptic chlorhexidine, can act as strong inhibitors with potencies similar or even higher than pharmacological model inhibitors. The new integrated web portal serves as a central repository of current and emerging data for interactions of prescription drugs and environmental chemicals with human drug transporters. This archive has important implications for predicting adverse drug-drug and drug-environmental chemical interactions and can serve as a reference website for the broader scientific community of clinicians and researchers.

Prediction of Drug-Drug Interactions with Ensartinib as a Time-Dependent CYP3A Inhibitor Using Physiologically Based Pharmacokinetic Model.

Ensartinib (X-396) is a second-generation anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitor (TKI) indicated for the treatment of ALK-positive patients with locally advanced or metastatic non-small cell lung cancer. Although in vitro experiments and molecular docking suggested its potential as a cytochrome P450 inhibitor, no further investigation or clinical trials have been conducted to assess its drug-drug interaction (DDI) risk. In this study, we conducted a series of in vitro experiments to elucidate the inhibition mechanism of ensartinib. Furthermore, a physiologically-based pharmacokinetic (PBPK) model was developed based on in vitro, in silico, and in vivo parameters, verified using clinical data, and applied to predict the clinical DDI mediated by ensartinib. The in vitro incubation experiments suggested that ensartinib exhibited strong time-dependent inhibition. Simulation results from the PBPK model indicated a significant increase in the exposure of CYP3A substrates in the presence of ensartinib, with the maximal plasma concentration and area under the plasma concentration-time curve increasing up to 12-fold and 29-fold for sensitive substrates. Based on these findings, it is evident that co-administration of ensartinib and CYP3A substrates requires careful regulatory consideration. SIGNIFICANCE STATEMENT: Ensartinib was found to be a strong time-dependent inhibitor of CYP3A for the first time based on in vitro experiments, but there was no research conducted to estimate the risk of drug-drug interaction (DDI) of ensartinib in clinic. Therefore, the first ensartinib physiologically based pharmacokinetic model was developed and applied to predict various untested scenarios. The simulation result indicated that the exposure of CYP3A substrate increased significantly and urged the further clinical DDI study.

Unraveling a Combined Inactivation Mechanism of Cytochrome P450s by Genipin, the Major Reactive Aglycone Derived from Gardeniae Fructus.

Genipin (GP) is the reactive aglycone of geniposide, the main component of traditional Chinese medicine Gardeniae Fructus (GF). The covalent binding of GP to cellular proteins is suspected to be responsible for GF-induced hepatotoxicity and inhibits drug-metabolizing enzyme activity, although the mechanisms remain to be clarified. In this study, the mechanisms of GP-induced human hepatic P450 inactivation were systemically investigated. Results showed that GP inhibited all tested P450 isoforms via distinct mechanisms. CYP2C19 was directly and irreversibly inactivated without time dependency. CYP1A2, CYP2C9, CYP2D6, and CYP3A4 T (testosterone as substrate) showed time-dependent and mixed-type inactivation, while CYP2B6, CYP2C8, and CYP3A4 M (midazolam as substrate) showed time-dependent and irreversible inactivation. For CYP3A4 inactivation, the kinact/KI values in the presence or absence of NADPH were 0.26 or 0.16 min-1 mM-1 for the M site and 0.62 or 0.27 min-1 mM-1 for the T site. Ketoconazole and glutathione (GSH) both attenuated CYP3A4 inactivation, suggesting an active site occupation- and reactive metabolite-mediated inactivation mechanism. Moreover, the in vitro and in vivo formation of a P450-dependent GP-S-GSH conjugate indicated the involvement of metabolic activation and thiol residues binding in GP-induced enzyme inactivation. Lastly, molecular docking analysis simulated potential binding sites and modes of GP association with CYP2C19 and CYP3A4. We propose that direct covalent binding and metabolic activation mediate GP-induced P450 inactivation and alert readers to potential risk factors for GP-related clinical drug-drug interactions.

Impact of clinical pharmacist-led intervention for drug-related problems in neonatal intensive care unit a randomized controlled trial.

Introduction: Drug-related problems (DRPs) incidence is higher in neonatal intensive care units (NICUs), compared to other pediatric wards due to aspects like off-label medications, pharmacokinetic/dynamic variability, or organ dysfunction/immaturity. This study aimed to determine whether and to what extent a clinical pharmacist intervention improves medication safety and prevents DRPs [medication errors (MEs), adverse drug reactions (ADRs), drug-drug interactions (DDIs)]. Methods: A prospective, randomized, double blind, controlled study in NICU-admitted neonates was conducted. NICU patients were randomly assigned to the intervention (clinical pharmacist-led) (IG) or control group (standard care such as clinical diagnosis, pharmacotherapy) (CG). The clinical pharmacist was involved in the IG to identify-prevent-intervene MEs, or identify and monitor ADRs and DDIs. The primary outcome was the number of neonates who developed at least one DRP compared with those seen across IG and CG. Secondary outcomes included length of hospital stay, total number of drugs or DRP type. Results: Neonates were randomly assigned to CG (n = 52) or IG (n = 48). In total, 45%, 42%, and 16% of patients had at least 1MEs, ADRs, and clinically significant DDIs, respectively. The number of patients with at least 1ME was 28 (53%) and 17 (35%) in the CG and IG (p>0.05). The median (range) number of ME was higher in CG [1 (0-7)] than in IG [0 (0-4)] (p = 0.003). Applying regression analysis, the CG had 2.849 times more MEs than the IG (p<0.001). Furthermore, the number of patients (CG to IG) with at least one detected ADR or clinical DDI was 19 (36%) to 23 (47%) (p>0.05) and 4 (7%) to 12 (25%), respectively (p = 0.028). Conclusion: Clinical pharmacist availability to systematically and standardized identify, prevent and resolve DRPs among NICU patients is effective. Daily detailed clinical pharmacist observations and interventions enables prevention and monitoring of DRPs. Clinical Trial Registration ClinicalTrials.gov, identifier NCT04899960.