The Journal of Clinical Pharmacology最新文献

{"title":"Reply to Letter to the Editor From Asma Akhtar and Ume Hafsa Roman","authors":"Janneke M. Brussee PhD, Jasper Dingemanse PhD, FCP, Aline Frey PharmD, Andreas Krause PhD","doi":"10.1002/jcph.70279","DOIUrl":"10.1002/jcph.70279","url":null,"abstract":"<p>Dear Editor,</p><p>We thank Drs Akhtar and Roman for their interest in our article, “Population Pharmacokinetic Modeling for the Iminosugar Lucerastat Supports Dose Adaptation in Patients with Fabry Disease and Moderate to Severe Renal Function Impairment.”<span><sup>1</sup></span> Their letter raises three main points: external validation, exposure–response analyses, and heterogeneity between studies.</p><p>External validation with an independent dataset can provide additional reassurance regarding model predictability and generalizability. However, in rare diseases such as Fabry disease, independent datasets with adequate pharmacokinetic (PK) sampling, sufficient representation across renal function strata, and comparable dosing conditions are limited. For this reason, the model was developed using the totality of available lucerastat PK data from clinical studies, including healthy participants and patients with Fabry disease across a broad range of doses and renal function categories.</p><p>Keeping data aside for external validation and not using it for model building appears suboptimal, particularly in rare diseases with limited data available. The population PK methodology considers differences in the data at various levels. It comprises fixed effects (variability attributed to known subject characteristics), random effects (variability between subjects for unknown reasons), and residual variability (other unknown sources of variability).</p><p>Additional data from future studies will contribute further insight into differences between studies and the validity of this model applied to other populations, and clinical contexts.</p><p>The primary purpose of the population PK model was to support dose adaptation in participants with renal impairment by identifying doses expected to provide lucerastat exposure comparable to exposures observed in participants with preserved renal function. This is particularly relevant because lucerastat is mainly excreted unchanged in urine, and renal impairment is a major organ complication of Fabry disease. This analysis was not designed to establish a definitive exposure–response relationship for efficacy or safety.</p><p>Using population PK models as scientific rationale for dose selection underlies the common assumption that similar exposure leads to similar clinical response. Further analyses integrating exposure, biomarkers, clinical efficacy, and safety data may characterize the exposure–response relationship of lucerastat.<span><sup>2</sup></span></p><p>Between-study differences are well known, including study participant populations (age and demographics), clinical site standards and procedures, or ethnic differences (particularly in patient-reported outcomes such as neuropathic pain). The model incorporates such differences at multiple levels (see above). Pooling data from an entire clinical program provides strength to the model; the PK (absorption, distribution, and elimination) could not be esti","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70279","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149031475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on “Population Pharmacokinetic Modeling for the Iminosugar Lucerastat Supports Dose Adaptation in Patients with Fabry Disease and Moderate to Severe Renal Function Impairment”","authors":"Asma Akhtar MBBS, Ume Hafsa Roman MBBS","doi":"10.1002/jcph.70277","DOIUrl":"10.1002/jcph.70277","url":null,"abstract":"<p>To the Editor:</p><p>We read with interest the article by Brussee et al who reported the development of a population pharmacokinetic (PopPK) model for lucerastat based on pooled Phase I and Phase III clinical trial data to guide dose optimization in Fabry disease patients with varying degrees of renal impairment. This study is an important contribution to model-informed precision dosing and highlights the important role of renal function on lucerastat pharmacokinetics. Despite the comprehensive pharmacometric approach utilized by the authors, we believe that some methodological issues deserve further discussion as they may affect the interpretation of the outcomes and their application in clinical practice.<span><sup>1</sup></span></p><p>The primary issue is the lack of external validation of the proposed PopPK model. The model performance was assessed using internal evaluation techniques including goodness-of-fit diagnostics, visual predictive checks, and estimates of parameter precision. While these techniques indicate that the model fits the development data well, they do not offer evidence of its predictive performance in an independent patient population. As the model was developed to support customized dose decisions, external validation in a separate cohort or with prospective clinical data would provide a more reliable validation of its reliability, reproducibility, and usefulness in a broader spectrum of clinical settings.<span><sup>2</sup></span></p><p>A second consideration is that the proposed dose-adjustment strategy is supported predominantly by model-based pharmacokinetic simulations rather than exposure–response evidence. The authors conclude that adjusting the dose according to estimated glomerular filtration rate results in comparable drug exposure among patients with varying degrees of renal impairment. Moreover, the study does not include pharmacodynamic or clinical outcome assessments to determine whether comparable plasma drug concentrations result in similar therapeutic efficacy or safety. That is why it remains unclear whether the comparable pharmacokinetic profiles predicted by the model ultimately lead to equivalent clinical outcomes. Demonstrating a clear relationship between drug exposure and therapeutic efficacy or safety through dedicated exposure–response analyses would provide stronger support for the proposed renal dose-adjustment recommendations and increase confidence in their application in clinical practice.<span><sup>3</sup></span></p><p>The PopPK model was constructed on the pooled pharmacokinetic data from several Phase I and Phase III clinical trials with different study designs, patient populations, dosing regimens, and pharmacokinetic sampling strategies. Pooling data across studies can be advantageous for model development, but such differences can also lead to study-related variability that may influence parameter estimates and model predictions.<span><sup>2, 4</sup></span></p><p>In summary, Brussee","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70277","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149031521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to Letter to the Editor on the Review Article “Innovative Clinical Pharmacology, Modeling & Simulation Strategies for Accelerating Rare Disease Drug Development”","authors":"Rajneet K. Oberoi PhD, Cody J. Peer PhD, FCP, Ashutosh Tripathi PhD, Afroz S. Mohammad PhD, Yajing Sun PhD, Kenneth Der BS, Yang Song PhD, Jiayin Huang PhD, Vijay V. Upreti PhD, FCP","doi":"10.1002/jcph.70304","DOIUrl":"10.1002/jcph.70304","url":null,"abstract":"<p>Dear Editor,</p><p>We thank Sameed Hyder and Muhammad Amir Saeed for their thoughtful assessment of our work, highlighting important considerations regarding the real-world application and immunogenicity dynamics for inebilizumab and pegloticase case examples, respectively. We appreciate the opportunity to clarify these aspects.</p><p>We acknowledge the importance of understanding the challenges of small patient population and disease heterogeneity on its potential impact on pharmacokinetics (PK) and pharmacodynamics variability during drug development. Model-informed drug development (MIDD) approaches can help characterize this variability and assess its clinical impact. We agree that use of MIDD analyses using limited datasets during clinical development may limit the understanding of the impact of <i>extremes</i> of patient clinical characteristics and, therefore, should not be interpreted as eliminating this uncertainty. In this context, the use of real-world evidence can strengthen confidence in the totality of evidence. The objective of the review was to highlight case studies where MIDD approaches have been used successfully to accelerate drug development to approval. As noted in the review, availability of natural-history data or real-world data can help understand the challenges associated with rare diseases. However, these data are usually acquired post-marketing. For both inebilizumab and pegloticase, real-world evidence data has provided supportive evidence on the dosing regimen.</p><p>First, we would like to clarify that inebilizumab doses higher than 1 mg/kg demonstrated linear clearance in Phase 1 studies,<span><sup>1, 2</sup></span> and the approved 300 mg every 6-month regimen<span><sup>3</sup></span> exceeded the observed threshold for TMDD. In addition, observed Phase 3 data<span><sup>4</sup></span> along with a robust MIDD approach including population PK and exposure–response analysis<span><sup>5</sup></span> of variability in PK, and depth and durability of B-cell depletion,<span><sup>6</sup></span> further supported the dosing regimen.<span><sup>1, 7</sup></span> Inebilizumab dosing does not require any specialized biomarker and/or therapeutic drug monitoring. Therefore, no such assessments were part of the NMOSD pivotal trial<span><sup>4</sup></span> and use of the MIDD approach would not preclude any low-resource clinical setting. Furthermore, the registrational study showed that differential B-cell patterns may affect early clinical response, but not with long-term treatment.<span><sup>8</sup></span> Several ongoing studies on the long-term and real-world use of inebilizumab in NMOSD (NCT06180278, NCT05909761, and NCT04886492) are ongoing to evaluate if disease extremes or heterogeneity affect clinical response.</p><p>Second, the pegloticase example illustrated how a MIDD framework supported the characterization and mitigation plan to understand the clinical relevance of an observed immunogenicity signal, rather than ","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70304","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149026450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immunogenicity of locally acting large molecule products: An overview","authors":"Lei He PhD,&nbsp;Ping Ji PhD,&nbsp;Amit Golding MD,&nbsp;Yunzhao Ren MD, PhD,&nbsp;Chinmay Shukla PhD,&nbsp;William Boyd MD,&nbsp;Rhea Lloyd MD,&nbsp;Chandrahas Sahajwalla PhD","doi":"10.1002/jcph.70298","DOIUrl":"10.1002/jcph.70298","url":null,"abstract":"<p>Locally acting large molecule drug products, including biologics, are designed for site-specific pharmacological action with minimal systemic exposure. Immunogenicity is generally assessed to the same extent in the clinical development programs for these locally acting large molecule drug products as for biological products given systemically. However, it is uncertain whether the local route of administration bears the same clinical immunogenicity concerns relative to systemic administration. This overview examines the immunogenic potential of locally acting large molecules, summarizing the anti-drug antibody incidence and its impact on pharmacokinetics, safety, and efficacy, and highlighting the specific immunogenicity risk profiles for these locally acting drugs and biologics.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149026442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the Editor: Innovative Clinical Pharmacology, Modeling, and Simulation Strategies for Accelerating Rare Disease Drug Development","authors":"Sameed Hyder MBBS,&nbsp;Muhammad Amir Saeed MBBS","doi":"10.1002/jcph.70303","DOIUrl":"10.1002/jcph.70303","url":null,"abstract":"&lt;p&gt;To the Editor,&lt;/p&gt;&lt;p&gt;We read with great interest the comprehensive review by Oberoi et al detailing how quantitative clinical pharmacology and model-informed drug development (MIDD) streamline regulatory approval pathways in rare diseases.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; The authors convincingly demonstrate the utility of exposure–response relationships, mechanistic physiologically based pharmacokinetics (M-PBPK), and population PK (PopPK) modeling across diverse modalities.&lt;span&gt;&lt;sup&gt;1, 2&lt;/sup&gt;&lt;/span&gt; While we commend the authors for consolidating these framework benchmarks, we wish to highlight two crucial clinical considerations regarding real-world application and immunogenicity dynamics.&lt;/p&gt;&lt;p&gt;First, while direct-to-Phase 3 transitions guided by PopPK/PD modeling—such as the 300 mg fixed dosing of inebilizumab in neuromyelitis optica spectrum disorder—significantly accelerate development timelines,&lt;span&gt;&lt;sup&gt;1, 3&lt;/sup&gt;&lt;/span&gt; translating these static regimens to clinical settings with extreme disease or patient heterogeneity remains complex. Inebilizumab exhibits non-linear target-mediated clearance at lower concentrations before shifting to linear elimination.&lt;span&gt;&lt;sup&gt;3&lt;/sup&gt;&lt;/span&gt; In patients with high baseline disease activity or abnormal body mass profiles, rapid target-mediated clearance may compromise the durability of peripheral B-cell depletion before the 6-month maintenance dose. Without widespread access to specialized biomarker monitoring or therapeutic drug monitoring in low-resource clinical settings, reliance on model-simulated fixed-dose regimens risks undetected early B-cell repletion and subsequent clinical relapse.&lt;/p&gt;&lt;p&gt;Second, while the integration of immunomodulatory co-therapy (e.g., methotrexate with pegloticase) demonstrates how anti-drug antibody (ADA) formation can be mitigated,&lt;span&gt;&lt;sup&gt;1, 4&lt;/sup&gt;&lt;/span&gt; model-driven risk assessments may inadvertently oversimplify ADA kinetics in small patient cohorts.&lt;span&gt;&lt;sup&gt;2, 4&lt;/sup&gt;&lt;/span&gt; In rare diseases, patient populations often present uncharacterized immunological background noise.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; Small sample sizes in initial MIDD frameworks may mask low-frequency, high-titer ADA responses that drastically alter systemic clearance beyond the predictive boundaries of calibrated PopPK models.&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;In conclusion, quantitative modeling tools are indispensable for bridging evidence gaps in orphan drug development. However, future frameworks should explicitly integrate real-world monitoring paradigms and robust sensitivity analyses to account for post-marketing pharmacokinetic variability and variable immune responses in broader patient populations.&lt;/p&gt;&lt;p&gt;All the authors have made significant and equal contributions to this manuscript. All authors approved the final version and agree to be accountable for all aspects of the work, ensuring the accuracy and integrity of the data and interpretation&lt;/p&gt;&lt;p&gt;The authors declare no competing inter","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70303","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149026398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reviews and Perspectives in Clinical Pharmacology: Past, Present, and Future","authors":"John van den Anker","doi":"10.1002/jcph.70292","DOIUrl":"10.1002/jcph.70292","url":null,"abstract":"&lt;p&gt;It is with great pleasure that I share with you that two of the three special issues celebrating the 65th anniversary of the &lt;i&gt;Journal of Clinical Pharmacology&lt;/i&gt; (JCP) have been successfully published this year. The first special issue was dedicated to the papers that have received the McKeen Cattell Award over the years. Our second special issue highlighted the top-cited papers published in JCP during the past 15 years.&lt;/p&gt;&lt;p&gt;I would like to use this editorial to introduce the third and final special issue commemorating JCP's 65th anniversary. This issue will be published in the days preceding the 2026 annual meeting of the American College of Clinical Pharmacology (ACCP). This year's meeting will take place from September 27 to 29, with pre-meeting workshops and the American Board of Clinical Pharmacology (ABCP) Curriculum Review Course on September 26. The meeting will be held at the Bethesda North Marriott Hotel &amp; Conference Center in North Bethesda, Maryland.&lt;/p&gt;&lt;p&gt;This final special issue celebrating JCP's 65th anniversary features reviews and original research articles authored by ACCP members and non-members from across the globe. Contributors represent the United States; Canada; Europe including France, Italy, and the Netherlands; Asia, including China and Singapore; and Oceania, represented by New Zealand. This broad geographic representation underscores the global interest in publishing in JCP, the flagship journal of ACCP and reflects the Journal's global impact as a primary source for advances in clinical pharmacology.&lt;/p&gt;&lt;p&gt;The authors contributing to this special issue include clinicians, academicians, scientists from the pharmaceutical industry, and regulatory scientists from the US Food and Drug Administration (FDA). The breadth of topics represented is equally impressive, reflecting the remarkable scope and evolution of contemporary clinical pharmacology and pharmacometrics.&lt;/p&gt;&lt;p&gt;Topics including the history of JCP; the evolution of clinical pharmacology in China; mitochondrial medicine; street pharmacology; use of ketamine across clinical indications; the use of concentration-QTc modeling; factor XI inhibition for secondary prevention of ischemic stroke; genome sequencing; approaches to accelerating pediatric oncology drug development; simulation-based evaluation of busulfan sampling strategies in adults and adolescents; oligonucleotide therapeutics; clinical pharmacology of eplontersen; strategies for rare disease drug development; the role of clinical pharmacology in shaping rare disease drug development; the pharmacokinetics of therapeutic monoclonal antibodies in Japanese and non-Japanese individuals; long-acting injectable therapies for HIV treatment and prevention; semi-mechanistic HbA1c models in type 2 diabetes; endogenous biomarkers to evaluate transporter-mediated drug–drug interactions; physiologically based pharmacokinetics models for fetal drug exposure; model-informed dose selection of intranasal epinep","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70292","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149013156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Suzetrigine Is Not Expected to Have Clinically Relevant DDIs with Apixaban and Rivaroxaban Based on PBPK Modeling","authors":"Guanyu Wang PhD,&nbsp;Elizabeth Lakota PharmD,&nbsp;Bo Feng PhD,&nbsp;Licong Jiang PhD,&nbsp;Guiqing Liang PhD,&nbsp;Brian Hare PhD","doi":"10.1002/jcph.70288","DOIUrl":"https://doi.org/10.1002/jcph.70288","url":null,"abstract":"<p>Suzetrigine (VX-548) is a first-in-class, oral, non-opioid, FDA-approved analgesic for the treatment of moderate to severe acute pain. Based on Phase 1 clinical drug–drug interaction (DDI) studies, suzetrigine is a weak-to-moderate cytochrome P450 3A (CYP3A) inducer and thus has the potential to decrease exposure and impact efficacy of CYP3A substrates, such as apixaban and rivaroxaban, which are commonly used as anticoagulants peri- and post-operatively. Given this, it is important to assess the DDIs of apixaban and rivaroxaban with suzetrigine. Physiologically based pharmacokinetic (PBPK) models are commonly used to assess DDIs mediated through modulation of CYP3A and were used here to quantify the potential effect of co-administration of suzetrigine on apixaban and rivaroxaban PK. The PBPK models were validated using observed data from suzetrigine, apixaban, and rivaroxaban clinical DDI studies. The validated models predict that suzetrigine decreases apixaban AUCinf by 6.1% (90% confidence interval [CI]: 5.7% to 6.4%) and Cmax by 1.8% (90% CI: 1.7% to 1.9%), and rivaroxaban AUCinf by 8.4% (90% CI: 7.2% to 9.6%) and Cmax by 3.5% (90% CI: 3.3% to 3.7%). The predicted small reductions in apixaban and rivaroxaban exposures (AUCinf &lt;10%) are not expected to be clinically relevant since a 20% no-effect boundary is typically used to determine the clinical impact of a DDI. The PBPK model predictions are consistent with the apixaban and rivaroxaban labels, which do not warn against co-administration with weak or moderate CYP3A inducers, such as suzetrigine.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70288","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective Evaluation of Thiotepa Pharmacokinetics in Children and Young Adults Undergoing Allogeneic or Autologous Hematopoietic Cell Transplantation","authors":"Jordan Brooks PharmD,&nbsp;Shams Ismaeil PharmD,&nbsp;Maria-Stephanie Hughes PharmD,&nbsp;Beth Apsel-Winger MD, PhD,&nbsp;Ying Lu PhD,&nbsp;Liusheng Huang PhD,&nbsp;Christine Higham MD,&nbsp;Kristina Nelson PharmD,&nbsp;Susie Long PharmD,&nbsp;Ashish Gupta MD,&nbsp;Nahal Rose Lalefar MD,&nbsp;Eric Anderson MD,&nbsp;Michael A. Pulsipher MD,&nbsp;Sung-Yun Pai MD,&nbsp;Ron J. Keizer PharmD, PhD,&nbsp;Christopher C. Dvorak MD,&nbsp;Janel Long-Boyle PharmD, PhD","doi":"10.1002/jcph.70296","DOIUrl":"https://doi.org/10.1002/jcph.70296","url":null,"abstract":"<p>Thiotepa (TT) is often included in high-dose chemotherapy prior to hematopoietic cell transplantation (HCT); however, exposure–response relationships of TT and its primary metabolite, N,N',N''-triethylenethiophosphoramide (TEPA), remain undefined. This was a prospective study enrolling children and young adults undergoing autologous and allogeneic HCT from multiple centers. Time–concentration data were modeled using nonlinear mixed effects modeling along with clinical covariates potentially impacting pharmacokinetics. Cumulative area-under-the-curve (cAUC) for TT and TEPA were derived using post hoc individual estimates for clearance. The combined cAUC_TT and cAUC_TEPA were also evaluated, reflecting total alkylating exposure (cAUC_total). The ratio of cAUC_TT/cAUC_TEPA was used to evaluate the efficiency of metabolic conversion of TT to TEPA. A total of 91 subjects were included with a median (range) actual body weight and age of 16.7 kg (4.6–110) and 4.5 years (0.23–22.5), respectively. The best fit model was a two-compartment structure for TT, and a one-compartment structure for TEPA. The conversion of TT to TEPA was found to be saturable at higher doses and may have important implications for optimizing exposure. Model-based dosing, which accounts for age and body size, results in more predictive exposure as compared to conventional mg/kg dosing, particularly in the very young and obese. Next steps include evaluation of pharmacogenomics and exposure–response relationships to optimize dosing of TT in children.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70296","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ketamine Dose and Duration Effects in Internalizing Disorders","authors":"Neil McNaughton PhD,&nbsp;Ben Beaglehole FRANZCP,&nbsp;Paul Glue FRCPsych","doi":"10.1002/jcph.70299","DOIUrl":"10.1002/jcph.70299","url":null,"abstract":"<p>The dose-response profile of racemic ketamine in internalizing disorders is poorly characterized. This was a secondary analysis of outcome responses in patients with treatment-resistant depression, post-traumatic stress disorder, generalized and/or social anxiety, or obsessive-compulsive disorder. For each disorder, they received single intramuscular doses of racemic ketamine (0.5 and 1.0 mg/kg) and a psychoactive control, using a three-way within-subject double-blind active-controlled cross-over design. Intramuscular racemic ketamine doses of 0.5 and 1.0 mg/kg produced robust effects on diagnosis-appropriate outcome scales for all these internalizing disorders, compared with psychoactive controls. These effects were most obvious at 24 h after dosing and noticeably smaller at 168 h. The magnitude of change after 1 mg/kg did not differ significantly from 0.5 mg/kg at either time point, and did not differ significantly between the internalizing disorders at 24 h. When combined with other ketamine dose-response data, we propose that ketamine may have a narrow inverted-U dose-response profile (peaking in the regions of 0.5-1.0 mg/kg) in patients with internalizing disorders.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13579490/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148978365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Endogenous Biomarkers to Evaluate Transporter-Mediated Drug–Drug Interactions: Current Evidence, Impact on Clinical Pharmacology Strategy, Remaining Gaps, and Future Directions","authors":"Laura E. Russell PhD,&nbsp;Fenglei Huang PhD,FCP,&nbsp;Kit Wun Kathy Cheung PharmD,&nbsp;Manthena V. S. Varma PhD,&nbsp;Vijender Panduga PhD","doi":"10.1002/jcph.70280","DOIUrl":"10.1002/jcph.70280","url":null,"abstract":"<p>Endogenous biomarkers have gained considerable attention as tools for assessing transporter-mediated drug–drug interactions (tDDIs). While plasma coproporphyrin I is considered a validated biomarker for assessing hepatic organic anion transporting polypeptide (OATP) 1B-mediated DDI risk, data supporting biomarkers for other major drug transporters, particularly renal transporters, remains limited. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) included endogenous biomarker-based assessments in its recent guidance, ICH M12, as an alternative approach for evaluating tDDIs, which is anticipated to broaden the use of this strategy in early clinical development. However, methodological gaps remain in biomarker measurement, including study design, biological matrix selection, and data analysis. Importantly, consensus is still needed on the most appropriate biomarkers for renal organic cation transporter (OCT) 2 and multidrug and toxin extrusion (MATE) transporters 1 and 2-K, such as creatinine, N¹-methylnicotinamide, and N¹-methyladenosine, given the influence of various extrinsic and intrinsic factors on their performance. This review aims to summarize the current state of clinical evidence for endogenous biomarkers of major hepatic and renal transporters, including study design considerations relevant to meaningful data interpretation. It also briefly summarizes reported Physiologically based pharmacokinetic (PBPK) models of these biomarkers, highlights key gaps in current understanding, and identifies future work needed to expand the application of a biomarker-based tDDI strategy.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148978376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}