Expert opinion on drug metabolism & toxicology最新文献

Introduction: Drug-induced liver injury (DILI) poses a significant challenge to drug development and human healthcare. The complex mechanisms underlying DILI make it challenging to accurately predict its occurrence, often leading to substantial financial losses from failed drug development projects and drug withdrawals. Growing evidence suggests that drug-metabolizing enzymes and transporters (DMETs) play a critical role in the development of DILI.

Areas covered: In this review, we explore findings about the contributions of DMETs to DILI, with a focus on the studies examining genetic polymorphisms and their interactions with drugs. Additionally, we highlight the roles of DMETs in the development of predictive models for assessing DILI potential and in uncovering the mechanisms involved in DILI.

Expert opinion: As new approach methods (NAMs) for assessing and predicting drug toxicity gain more prominence, it is imperative to better understand the adverse outcome pathways (AOPs) that underpin these methods. DMETs largely play a pivotal role in the molecular initiating events of DILI-related AOPs. Further research is needed to characterize DILI-related AOP networks and enhance the predictive performance of NAMs for assessing DILI risk.

Background: The aim of this study was to evaluate the bioequivalence of the test and reference products of ibrutinib capsule (140 mg).

Research design and methods: This was a fully replicated crossover study that included 100 healthy Chinese volunteers (50 in the fasting BE study and 50 in the fed BE study). Subjects were assigned to receive a single dose of test or reference product in each treatment period. The bioequivalence of main PK parameters (C_max, AUC_0-t, and AUC_0-∞) was evaluated using either the average bioequivalence (ABE) approach or the reference-scaled average bioequivalence (RSABE) approach, depending on the within-subject standard deviation of the reference product (S_WR) estimated in the study.

Results: RSABE approach was applied to C_max as the corresponding S_WR value exceeded the cutoff value of 0.294, while ABE approach was applied to AUC_0-t and AUC_0-∞ as the corresponding S_WR values were less than 0.294. All three PK parameters (C_max, AUC_0-t, and AUC_0-∞) met the bioequivalence acceptance criteria in both fasting and fed studies.

Conclusions: The test and reference products of ibrutinib capsule are bioequivalent under both fasting and fed conditions. This study also confirmed high intra-subject variability for the C_max of ibrutinib.

Clinical trial registration: http://www.chinadrugtrials.org.cn/index.html identifier is CTR20202168.

Introduction: Cyclophosphamide (CPA) is a widely used broad-spectrum antitumor drug with severe hepatotoxicity. Finding an effective way to mitigate the hepatotoxicity caused by CPA is a challenge in its clinical application.

Methods: In Rev-erbα knockout and wild-type mice, hepatotoxicity was evaluated by ALT, AST, and histopathological scores 4-h post dose of CPA (i.p. 300 mg/kg). CYP2B10 expression and pharmacokinetic behavior of CPA were also detected. SR9009 (i.p. 10 mg/kg) and Berberine (BBR, i.p. 50 mg/kg) were pre-administered to mice. Then, the measurements were carried out following the same procedures as previous. The regulation effects of SR9009 and BBR on CYP2B10 were validated using Hepa-1c1c7 cells.

Results: Firstly, REV-ERBα negatively regulated CPA-induced hepatotoxicity by altering the expression of CYP2B10 and CPA pharmacokinetics. Secondly, REV-ERBα agonists, SR9009 and BBR, increased REV-ERBα expression and alleviated hepatic toxicity of CPA. Furthermore, both SR9009 and BBR reduced expression of CYP2B10 and REV-ERBα target gene Bmal1 both in vivo and in vitro.

Conclusions: REV-ERBα agonists can significantly attenuate the hepatotoxicity of CPA by regulating CYP2B10. The discovery of REV-ERBα as novel regulator for CYP2B10 will help to establish new targets to improve drug efficacy or reduce toxicity.

Introduction: Healthcare professionals face increasing challenges when managing older patients, a group characterized by significant interindividual variability in comorbidity patterns, homeostatic capacity, frailty status, cognitive function, and life expectancy. Complex therapeutic decisions may increase the risk of inappropriate polypharmacy, drug-drug, and drug-disease interactions in the context of age-associated pharmacokinetic and pharmacodynamic alterations, with consequent drug accumulation and toxicity.

Areas covered: This state-of-the-art narrative review article summarizes and critically appraises the results of original research studies and reviews published in PubMed, Scopus, and Web of Science, from inception to 9 April 2025, on age-associated changes in critical organs and systems and relevant pharmacokinetic and pharmacodynamic alterations. It also discusses the emerging role of frailty and the gut microbiota in influencing such alterations and the potential utility of machine learning techniques in identifying new signals of drug efficacy and toxicity in older patients.

Expert opinion: The available knowledge regarding specific age-associated pharmacokinetic and pharmacodynamic alterations applies to a limited number of drugs, some of which are not frequently prescribed in contemporary practice. Future studies investigating a wider range of drugs and their patterns of use will likely enhance therapeutic efficacy and minimize toxicity in the older patient population.

Background: In intensive care units (ICU), the issue of drug-drug interactions (DDIs) is becoming increasingly prominent, and these interactions can lead to adverse drug reactions, therapeutic failure, or altered drug efficacy. This study aimed to assess the frequency and attributes of potential drug-drug interactions (pDDIs) and the consistency of different decision support software in ICU patients.

Research design and methods: A cross-sectional study was conducted in a tertiary hospital. The consistency of different decision support software was assessed using the Kendall W coefficient, Cohen's kappa, Cronbach's Alpha, Fleiss Kappa, Intraclass correlation coefficient and Gwet's AC1.

Results: A total of 897 prescriptions from 290 patients were evaluated. The total number of pDDIs identified varied significantly across platforms, ranging from 134 to 213. Inter-platform agreement on severity classification was poor (Gwet's AC1 = 0.32, ICC = 0.41).

Conclusions: This observational investigation revealed marked variability across clinical decision platforms regarding both quantitative and qualitative aspects of pDDIs identification in critical care populations, underscoring the imperative to establish unified protocols for pDDIs classification and implement dynamic DDI database maintenance.

Introduction: Non-small cell lung cancer (NSCLC) is the most prevalent form of lung cancer, accounting for 85% of cases worldwide. Despite advancements in treatment, many patients are diagnosed at advanced stages, and resistance to therapy, such as EGFR inhibitors, remains a significant challenge. Lazertinib, a third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR TKI) developed by Yuhan Corporation and Janssen Biotech, targets EGFR mutations, including T790M, which confer resistance to earlier-generation TKIs.

Areas covered: This review explores lazertinib's development, mechanism of action, clinical efficacy, and safety profile. Preclinical studies demonstrated its superior selectivity for mutant EGFR and blood-brain barrier penetration compared to osimertinib. Clinical trials highlight its efficacy as monotherapy and in combination with amivantamab, showing improved progression-free survival and response duration in patients with advanced NSCLC.

Expert opinion: Lazertinib represents a promising advance in the treatment of EGFR-mutated NSCLC, particularly for patients with brain metastases or resistance to previous EGFR TKIs. However, emerging resistance mutations, such as C797S, underscore the need for continued innovation, including combination therapies and fourth-generation TKIs. Future research must address these challenges to optimize treatment outcomes for NSCLC patients.

Introduction: Modelinformed precision dosing (MIPD) allows determining the optimal dosage regimen and its correction based on the target plasma/serum concentrations of the drug. MIPD software must go through a validation and clinical study of its effectiveness and safety before being used in clinical practice.

Areas covered: This narrative literature review provides insight into what is known to date about efficacy and safety trials of MIPD concept. Relevant publications were searched for in the PubMed database, without time or language constraints.

Expert opinion: The application of MIPD in clinical practice logically and theoretically has great potential to improve the treatment of patients by leading to optimal exposure of target tissues to drugs, while achieving full effect and minimizing toxicity. Greater implementation of MIPD in clinical practice is hindered by the fact that the beneficial effects of MIPD on treatment outcomes and reduction of drug toxicity have been proven through clinical studies only for a small number of drugs. It is necessary to conduct well-designed clinical studies of the effects of MIPD, with sufficient statistical power, to prove the benefits of MIPD administration and to justify the costs of implementation in clinical practice.

Introduction: Dravet syndrome (DS) and Lennox-Gastaut syndrome (LGS) are rare, severe epileptic encephalopathies requiring complex, individualized treatment due to drug-resistant seizures, non-seizure outcomes, and comorbidities. Polytherapy is an inevitable aspect of managing these conditions, making the management of drug-drug interactions (DDIs) crucial for optimizing efficacy, minimizing toxicity, and addressing broader patient needs.

Areas covered: This review discusses current and emerging pharmacological therapies for seizures in DS and LGS. We explore documented and theoretical DDIs between these drugs and other antiseizure medications (ASMs), focusing on pharmacokinetic and pharmacodynamic characteristics. The clinical significance of these DDIs is emphasized, with practical recommendations for their management.

Expert opinion: Advances in understanding DDIs are key to optimizing treatment, particularly through the combination of ASMs with distinct mechanisms of action. A rational therapeutic approach should consider not only seizure control but also comorbidities. Understanding metabolic pathways involved in pharmacokinetic interactions is essential for predicting and avoiding adverse effects. Digital tools and decision-support apps can assist clinicians in quickly assessing DDIs and selecting the most effective drug combinations. Ongoing research in pharmacogenetics and personalized medicine holds promise for improving the management of complex conditions like DS and LGS, offering potential for better, individualized therapeutic strategies.

Introduction: Idiosyncratic drug-induced liver injury (iDILI) remains unpredictable. As adverse responses arise in a small fraction of patients, drugs often fail in later drug development stages or post-approval, thereby tremendously increasing costs and putting patients at risk, highlighting the need for accurate early identification of iDILI liabilities.

Covered areas: Using articles from the last 5 years (PubMed), iDILI risk factors are described, in vitro liver models and mechanism-based readout strategies are evaluated on their potential to enable iDILI liability assessment.

Expert opinion: Various in vitro liver models are established for disease modeling and DILI prediction. Drawbacks for each of these seem inevitable, making the evaluation of their application domain and iDILI liability assessment potential crucial. A tiered approach could be considered, whereby compounds are initially screened and flagged using simple fit-for-purpose models for DILI prediction, followed by multicellular liver models that integrate the current knowledge of iDILI onset in combination with mechanistic readouts. Multiplexing models within an integrated mechanism-based testing strategy could improve the safety assessment accuracy. Defined in vitro models should integrate critical hepatocyte intrinsic risk factors as well as adaptive immune system components to refine iDILI liability assessment.