Expert opinion on drug metabolism & toxicology最新文献

Introduction: Asthma and type 2 diabetes mellitus (T2DM) frequently coexist and share overlapping immunometabolic pathways. Pharmacotherapies used to treat either condition may influence the course of the other, leading to clinically relevant cross-effects.

Areas covered: This narrative review synthesizes evidence on the bidirectional pharmacologic interactions between asthma and T2DM therapies, focusing on the metabolic consequences of asthma medications and the pulmonary effects of glucose-lowering agents. We highlight mechanistic links, comparative clinical impacts, and phenotype-specific considerations.

Expert opinion: Systemic corticosteroids and, to a lesser extent, high-dose inhaled corticosteroids, increase the risk of insulin resistance and hyperglycemia. β₂-agonists may acutely raise glucose levels, whereas leukotriene antagonists and LAMAs have minimal metabolic impact. Biologics indirectly benefit metabolic control by allowing steroid reduction, with dupilumab showing the most favorable profile. Among antidiabetic agents, metformin and GLP-1 receptor agonists robustly improve asthma outcomes, and SGLT2 inhibitors show promising signals. Insulin may worsen airway hyperresponsiveness through proliferative and immunologic pathways. Clinicians must navigate these interactions thoughtfully, especially in type 2-low and obesity-associated asthma, where metabolic dysfunction dominates disease expression. Evidence-based guidance remains lacking, underscoring the need for integrated, phenotype-driven approaches.

Introduction: In psychopharmacology, there is a growing interest in potential sex differences regarding psychotropic drugs, currently used or under development. Preclinical research repeatedly identifies sex differences in pharmacokinetics and pharmacodynamics of psychotropic drugs. However, clinical research either does not consistently corroborate such findings or does not necessarily support their clinical significance.

Areas covered: This review succinctly presents the main sex differences in mental disorders (epidemiology, symptomatology), pharmacokinetics (absorption, distribution, metabolism, excretion) and pharmacodynamics (therapeutic effects and adverse drug reactions). The review is based on a curated collection of articles, mainly from the 2000 onwards, listed in the U.S. NLM of Congress, and offers insights on why clinical findings about sex differences in psychopharmacology are inconsistent or of varied clinical importance.

Expert opinion: In psychopharmacology, sex differences in pharmacokinetics and pharmacodynamics are progressively discovered. Nevertheless, a significant knowledge gap still exists, resulting in an unclear clinical value of sex differences and perhaps suboptimal use of psychotropic drugs in the context of precision medicine. This review puts into context this knowledge gap and proposes how it can be addressed. Optimization of existing treatments and drug development can benefit by a better appreciation of potential sex differences in psychopharmacology.

Introduction: Sex and gender differences may significantly impact health outcomes, yet their role in antibiotic therapy remains underexplored. Despite the urgent threat of antimicrobial resistance, limited evidence exists on how biological, pharmacokinetic, and sociocultural differences affect antibiotic efficacy, safety, and usage. This gap is critical, as women are often underrepresented in clinical trials, leading to suboptimal treatment strategies and a higher incidence of adverse drug reactions.

Areas covered: This narrative review synthesizes current evidence on these disparities. We explore the biological basis for differential immune responses and drug pharmacokinetics, sociocultural drivers of prescribing patterns, gender-specific infections, and the intersection of gender with antimicrobial resistance. The review also addresses antibiotic use in pregnancy and highlights the profound lack of data for both cisgender and transgender women due to their exclusion from research.

Expert opinion: Sex-aware prescribing is a practical and necessary step toward equitable care. Key obstacles include historical underrepresentation of women in trials and insufficient sex-disaggregated data. We advocate for powering future trials for sex-specific analyses, updating clinical guidelines, and using decision support tools for dose adjustments. Integrating a gender lens into all levels of antimicrobial stewardship is essential to move from simply describing disparities to actively closing them.

Introduction: Short bowel syndrome (SBS) substantially alters nutrient and drug absorption and frequently necessitates long-term parenteral nutrition, increasing thrombotic risk. Indications for long-term anticoagulation such as atrial fibrillation or venous thromboembolism are common in this population. Because gastrointestinal anatomy and physiology are markedly distorted, the pharmacokinetics of direct oral anticoagulants (DOACs) may become unpredictable, creating uncertainty in drug selection and dosing.

Areas covered: This review compares pharmacokinetic and clinical evidence for rivaroxaban and apixaban, the two DOACs most often used in SBS. Literature from pharmacology studies, case reports, prospective cohorts, and emerging population pharmacokinetic analyses was examined. Relevant literature was identified through searches of PubMed and Embase up to 1 November 2025.

Expert opinion: Rivaroxaban exhibits food-dependent, dissolution-limited absorption in the stomach and proximal small intestine, and systemic exposure appears more sensitive to residual bowel length. Apixaban demonstrates linear, food-independent pharmacokinetics and generally preserved absorption in stable SBS, enabling concentration-guided dose adjustment when needed. Both agents can be effective in selected patients, but apixaban offers greater pharmacokinetic robustness in the context of altered intestinal anatomy or inconsistent oral intake. Early anti-Xa - based monitoring is advisable for either drug to confirm adequate absorption.

Introduction: Interindividual variability in drug response remains a significant clinical challenge, leading to therapeutic failure and toxicity. Much of this variability is unexplained by classical host-centric pharmacokinetic (PK) models, highlighting a critical gap in understanding of drug disposition. This review addresses this gap by establishing the gut microbiome as an important determinant of drug fate.

Areas covered: This narrative review with scoping approach examines how microbial enzymes affect therapeutics through comprehensive analysis of mechanistic and clinical studies. Key examples discussed include irinotecan, digoxin, and sulfasalazine. We highlight specific situations where the influence of gut bacteria is particularly significant, such as with low-bioavailability drugs and in patients with an ileocolonic anastomosis, where gut bacteria directly impact drug absorption and metabolism. Additionally, we address the limitations of current PK models and explore the potential of new integrated approaches.

Expert opinion: We propose that the gut microbiome should be recognized as a 'fifth pillar' of PKs. This shift in perspective is crucial for advancing personalized medicine. In this new model, a 'PK profile card' integrating microbial, genomic, and clinical data will help guide dosing. We anticipate microbiome analysis to become a standard clinical tool to optimize drug efficacy and safety.

Introduction: Dextromethorphan/Buproprion (DXM/BUP) has received breakthrough FDA approval in August 2022 as a rapid-acting antidepressant. DXM/BUP is a noncompetitive N-methyl-D-aspartate (NMDA) receptor antagonist and sigma-1 receptor agonist, with bupropion (BUP), a norepinephrine/dopamine reuptake inhibitor and cytochrome P450 2D6 (CYP2D6) inhibitor. As DXM/BUP moves closer to widespread clinical use for MDD, examining whether the combination does or does not carry meaningful abuse liability is essential given that DXM alone has long been misused, likely attributed to its metabolism into the psychoactive metabolite DXO.

Areas covered: We discuss the pharmacodynamics and pharmacokinetics of DXM and its primary active metabolite, dextrorphan (DXO). We then highlight the abuse potential of DXM when administered alone. Additionally, we present preclinical, clinical, and pharmacovigilance findings that support the reduced abuse liability of DXM/BUP.

Expert opinion: The formulation demonstrates clinically meaningful improvement within one week of its initiation. Given its safety and efficacy, alongside its novelty, this glutamatergic modulator represents a promising candidate for approval across global jurisdictions and regions. Future research should examine DXM/BUP's potential efficacy in bipolar depression and trauma-associated MDD, populations exhibiting refractory responses to conventional antidepressants and in need of an alternative, mechanistically distinct therapeutic.

Introduction: Pharmacological treatment is the mainstay in the acute and long-term management of severe mental disorders such as major depressive disorder, schizophrenia, and bipolar disorder. However, there is large interindividual variability in clinical response, with around one-third of patients presenting treatment-resistance.

Areas covered: This review provides a comprehensive overview of genes that modulate the efficacy or safety of antidepressants, antipsychotics, or mood stabilizers based on a high or moderate level of evidence and for which clinical recommendations are available. Next, we highlight novel methodological and analytical approaches such as polygenic scores, pleiotropic analysis and the analysis of multiomic data with machine learning methods that might allow to explain a larger proportion of genetically driven interindividual variability in clinical response to psychotropic medications.

Expert opinion: To date, a high level of evidence is only available for metabolizer phenotypes of a limited number of pharmacokinetic genes for antidepressants and antipsychotics (CYP2D6, CYP2C19, and CYP2B6), and selected HLA alleles for the mood stabilizer carbamazepine. However, transdiagnostic polygenic scores as well as machine learning models based on the integration of clinical determinants with multiomic data represent a promising strategy to move us closer to precision psychiatry.

Introduction: Predicting drug - drug interactions (DDIs) is essential for safe, effective medication therapy, yet conventional in vitro assays and in silico models are not completely reliable in their assessments. Multi-organ-on-a-chip (MOC) platforms provide a more physiologically relevant approach that may improve in vitro DDI predictions, particularly for complex DDIs.

Areas covered: We outline current DDI workflows, their strengths and limitations, and how single-organ chips can produce quantitative absorption, distribution, metabolism, and excretion (ADME) and toxicity parameters relevant for DDI analysis. We then discuss the need for emerging MOC platforms and the unique advantages that they offer, highlighting case studies that capture more complex DDI scenarios, as well as body-on-a-chip prototypes integrated with mechanistic modeling.

Expert opinion: MOC systems are currently poised to complement, not replace, established in vitro and modeling approaches for DDI predictions. Near-term value lies in fit-for-purpose contexts of use, supplying physiologically grounded parameters and mechanistic insight to physiologically based pharmacokinetic (PBPK) modeling. With continued progress in addressing key challenges (e.g. physiological scaling, sorptive materials, microscale analytics, variability, throughput, and standardization), MOCs should mature into reliable tools to assist in DDI prediction, and potentially even qualified assays as part of regulatory DDI risk assessment frameworks.

Introduction: Drug-drug interactions (DDIs) critically influence drug efficacy and safety, posing risks, but also offering therapeutic opportunities in some circumstances. Their dual nature necessitates balanced strategies in drug development, especially for high-unmet-need areas like oncology.

Areas covered: This review explores DDI risk assessment methods, challenges in correlating preclinical data with clinical outcomes, and advancements in predictive tools like physiologically based pharmacokinetic (PBPK) modeling. In particular, recent new publications highlight innovation such as artificial intelligence (AI) on DDI risk prediction and endogenous biomarkers for noninvasive monitoring. A comprehensive literature search was conducted in PubMed for relevant publications up to Oct 25, 2025.

Expert opinion: Moving beyond a purely defensive stance, we must strategically manage the dual nature of drug-drug interactions across the entire drug lifecycle. This capability is built on a proactive framework that seamlessly integrates multi-faceted data (computational, in vitro, and clinical) to continuously forecast DDI risks and opportunities. The ultimate endpoint of DDI assessment is its clinical impact, quantified through PBPK-DDI-pharmacodynamics (PD) and PBPK-DDI-Toxicity (Tox) models. Rigorous benchmarking of all these predictive methods remains essential to close the translational gap, enhance R&D efficiency, and advance more viable drug candidates.