CPT: Pharmacometrics & Systems Pharmacology最新文献

{"title":"A Pragmatic Approach to Handling Censored Data Below the Lower Limit of Quantification in Pharmacokinetic Modeling.","authors":"Marie Wijk, Roeland E Wasmann, Karen R Jacobson, Elin M Svensson, Paolo Denti","doi":"10.1002/psp4.70015","DOIUrl":"https://doi.org/10.1002/psp4.70015","url":null,"abstract":"<p><p>Proper handling of data below the lower limit of quantification (BLQ) is crucial for accurate pharmacokinetic parameter estimation. The M3 method proposed by Beal uses a likelihood-based approach that is precise but has been reported to suffer from numerical issues in converging. Common alternatives include ignoring the BLQs (M1), imputing half of the lower limit of quantification and ignoring trailing BLQs (M6) or imputing zero (M7). The imputation methods fail to account for the additional uncertainty affecting imputed observations. We used NONMEM with FOCE-I/Laplace to compare the stability, bias, and precision of methods M1, M3, M6, M7, and modified versions M6+ and M7+ that inflate the additive residual error for BLQs. Real and simulated datasets with a two-compartment model were used to assess stability through parallel retries with perturbed initial estimates. The resulting differences in objective function values (OFV) were compared. Bias and precision were evaluated on simulated data using stochastic simulations and estimations. M3 yielded different OFV across retries (±14.7), though the parameter estimates were similar. All other methods, except M7 (±130), were stable. M3 demonstrated the best bias and precision (average rRMSE 18.7%), but M6+ and M7+ performed comparably (26.0% and 23.3%, respectively). The unstable OFV produced by M3 represents a challenge when used to guide model development. Imputation methods showed superior stability, and including inflated additive error improved bias and precision to levels comparable with M3. For these reasons, M7+ (of simpler implementation than M6+) is an attractive alternative to M3, especially during model development.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genotype, Ethnicity, and Drug-Drug Interaction Modeling as Means of Verifying Transporter Biomarker PBPK Model: The Coproporphyrin-I Story.","authors":"Yuki Ujihira, Shawn Pei Feng Tan, Daniel Scotcher, Aleksandra Galetin","doi":"10.1002/psp4.70008","DOIUrl":"https://doi.org/10.1002/psp4.70008","url":null,"abstract":"<p><p>Coproporphyrin-I (CP-I) is a selective endogenous biomarker of organic anion-transporting polypeptide (OATP)1B. Multiple CP-I PBPK models with differing input parameters have been reported so far. This study proposed a harmonized CP-I PBPK model and evaluated its ability to predict the effect of ethnicity, SLCO1B1 genotype c.521T>C, and sex on CP-I baseline and CP-I-drug interactions using the largest clinical dataset to date. The CP-I PBPK model successfully predicted CP-I plasma baseline from 731 subjects, with 97% of predictions within 1.5-fold of the observed data. Prediction of weak, moderate, and strong OATP1B-mediated interactions with probenecid, low-dose cyclosporine, and rifampicin, respectively, was evaluated with 21 datasets. Overall, > 76% of CP-I C_maxR and AUCR were predicted within the Guest criterion. In vivo OATP1B K_i estimated by the biomarker model was up to ninefold lower compared to in vitro values. Sensitivity analyses showed differences in estimated in vivo K_i depending on the assumed contribution of non-inhibited/parallel pathway (renal) for CP-I (0%-15%), highlighting the need to consider this factor when using biomarker PBPK models for such purposes. Finally, the appropriate metric for monitoring CP-I was evaluated for inhibitors with different potency and PK relative to CP-I. In the case of strong/moderate OATP1B inhibitors with short t_1/2, C_maxR was the most sensitive metric for monitoring CP-I OATP1B interactions, whereas both C_maxR and AUCR were applicable for inhibitors with long t_1/2. The current study provides a harmonized CP-I PBPK model, together with recommendations to support the optimal design of prospective clinical trials for the assessment of OATP1B-mediated DDIs using this biomarker.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Pharmacokinetic/Pharmacodynamic and Exposure-Response Modeling of Garadacimab in Healthy Volunteers and Patients With Hereditary Angioedema.","authors":"Ramon Garcia, Shen Cheng, Fiona Glassman, Ankur Sharma, Bernardo De Miguel-Lillo, Matthew Wiens, Curtis Johnston, John-Philip Lawo, Ingo Pragst, Jonathan French, Dan Polhamus, Partha Nandy","doi":"10.1002/psp4.70009","DOIUrl":"https://doi.org/10.1002/psp4.70009","url":null,"abstract":"<p><p>Hereditary angioedema (HAE) is a rare genetic disease that manifests as recurrent, unpredictable, and potentially life-threatening attacks of angioedema. Garadacimab is a first-in-class, fully human, monoclonal antibody targeting activated factor XII (FXIIa) that is under clinical development for the long-term prophylaxis of HAE attacks. We developed population pharmacokinetic (PK)/pharmacodynamic (PD)/exposure-response (ER) models using pooled data across clinical studies to quantify the relationship between garadacimab concentration and the relative risk of HAE attacks and to support the rationale for 200 mg once-monthly dosing. The PK of garadacimab was adequately characterized by a two-compartment model with first-order absorption and elimination. The PD, as analyzed by FXIIa-mediated kallikrein activity, was adequately characterized by a direct inhibitory response model. PK/PD parameters were generally consistent across multiple covariates. ER analysis based on a repeated-time-to-event model showed that administration of garadacimab 200 mg subcutaneously (SC) once monthly results in 75% of patients reaching the target therapeutic threshold (90% reduction in relative risk of attack vs. run-in). Use of a loading dose (two 200 mg SC injections) as the first administration achieved steady-state PK exposures and PD response, with 85% of patients having exposures surpassing the therapeutic threshold. The models support the use of garadacimab 200 mg SC once-monthly dosing in patients aged ≥ 12 years, with no need for dose adjustments, and indicate that, due to the achievement of garadacimab steady-state exposures after the first administration, the use of a loading dose may facilitate the early onset of protection against HAE attacks, as observed in clinical studies.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143556188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Item Response Modeling and Artificial Neural Network for Differentiation of Parkinson's Patients and Subjects Without Evidence of Dopaminergic Deficit.","authors":"Leticia Arrington, Sven C van Dijkman, Elodie L Plan, Mats O Karlsson","doi":"10.1002/psp4.70000","DOIUrl":"https://doi.org/10.1002/psp4.70000","url":null,"abstract":"<p><p>Approximately 15% of patients suspected of having Parkinson's disease (PD) present dopamine active transporter (DaT) scans without evidence of dopaminergic deficits (SWEDD), most of which will never develop PD. Leveraging Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores from the Parkinson's Progression Markers Initiative, three different models of varying complexity, (total score, item response theory (IRT) and artificial neural network (ANN)) were evaluated to determine their ability to differentiate between PD and SWEDDs. Each of the models provided as output a predicted probability of having PD (P_DeNoPD). Both the IRT and ANN methods performed well as classifiers; ROC AUC > 80%, sensitivity > 93%, and precision ~90% when assuming a probability cutoff of P_DeNoPD ≥ 50%. Specificity was 43% and 38% for IRT and ANN respectively. Matthews correlation coefficient (MCC) was also evaluated as a metric to address potential bias of majority positive class. At all cutoffs at or above 50%, the IRT and ANN model performed similarly and achieved a MCC of at least 0.3, indicating at least a moderate positive relationship for classifier performance. In contrast, the total score model was a poor classifier, for all metrics and cutoffs. Using item-level data the proposed methodologies differentiated PD patients from SWEDDs with a degree of sensitivity and specificity that may compete with clinical examination and could aid in selecting DaTscan candidates. The choice of cutoff criteria, quality metric, and classifier model are contingent upon specific clinical needs.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143566314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Postmarketing Assessment of Antibody-Drug Conjugates: Proof-of-Concept Using Model-Based Meta-Analysis and a Clinical Utility Index Approach.","authors":"Innocent Gerald Asiimwe, Nour Chtiba, Samer Mouksassi, Goonaseelan Colin Pillai, Raimund M Peter, Eunice Yuen, Venkatesh Pilla Reddy","doi":"10.1002/psp4.70013","DOIUrl":"https://doi.org/10.1002/psp4.70013","url":null,"abstract":"<p><p>Antibody-drug conjugates (ADCs) are a promising class of targeted cancer therapies. However, they need careful dose optimization to maximize effectiveness and minimize side effects. Sometimes, safety issues may only become apparent after approval, so ongoing evaluation is important. This study aimed to assess the benefit-risk profiles of two approved trastuzumab-drug conjugates: trastuzumab emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd). A systematic search of MEDLINE on May 1, 2024, identified clinical trials reporting the pharmacokinetics, pharmacodynamics, safety, and efficacy of T-DM1 and T-DXd. Summary-level data from 103 trials was used along with model-based meta-analysis to develop population pharmacokinetic and exposure-response models for both ADCs. The study combined the objective response rate (ORR) and dose-limiting toxicity (DLT) into a composite score called the clinical utility index (CUI) to determine optimal drug exposures and doses that maximize the benefit-risk balance. Different ORR/DLT weights and CUI thresholds representing desired minimum effect size were tested in three scenarios (\"only phase I trials,\" \"phase I/II trials,\" and \"all phases\"). Using a CUI threshold of 10%, the approved T-DM1 dose of 3.6 mg/kg for breast cancer was found to align with an efficacy-safety (ORR-DLT) ratio of 81:19 with all phases. Applying these weights to the T-DXd analyses successfully predicted the approved T-DXd dose (5.4 mg/kg, breast cancer), showing a CUI improvement compared to the 3.2 mg/kg dose of 8.3%, 8.2%, and 2.4% in the three respective scenarios. Overall, this proof-of-concept assessment of ADCs can save time and costs for pharmaceutical companies and optimize dosing to maximize patient benefit.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143556190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Adefovir PBPK Model to Assess Biomarker-Informed OAT1 Drug-Drug Interaction and Effect of Chronic Kidney Disease.","authors":"Shawn Pei Feng Tan, Huaying Wu, Amin Rostami-Hodjegan, Daniel Scotcher, Aleksandra Galetin","doi":"10.1002/psp4.70010","DOIUrl":"https://doi.org/10.1002/psp4.70010","url":null,"abstract":"<p><p>Evaluation of transporter-mediated drug-drug interactions (DDI) with endogenous biomarkers, coupled with physiologically-based pharmacokinetic modeling (PBPK) is envisioned to replace or reduce dedicated DDI clinical trials with clinical probe substrates. The current study developed a PBPK model of adefovir (OAT1 clinical probe) by incorporating experimental measurements of adefovir passive diffusion and OAT1-mediated transport in a mechanistic kidney model for in vitro-in vivo extrapolation of its secretion and renal clearance. The adefovir model was verified with clinical data from nine studies (188 subjects) investigating a range of adefovir intravenous and adefovir-dipivoxil oral doses in White, Japanese, and Chinese populations with healthy renal function. A previously verified probenecid model, incorporating in vivo OAT1/3 inhibitory constant estimated using OAT1/3 endogenous biomarker (4-pyridoxic acid) clinical data, was utilized. The ratio of adefovir maximal plasma concentrations (C_maxR) and area under the curve (AUCR) after mid-to-high single oral doses of probenecid was predicted within the stringent Guest criterion. With the lowest probenecid dose (0.5 g), adefovir AUCR and C_maxR were slightly overpredicted but still within a 1.5-fold error. Application of the adefovir model to patients with severe chronic kidney disease (CKD) accounted for our previously recommended additional 50% decrease in OAT1 activity beyond the decline of glomerular filtration rate. The model successfully predicted 3-fold higher adefovir C_max and 6-fold higher AUC in patients with severe CKD relative to healthy individuals. This study reinforces the role of PBPK modeling to predict transporter-mediated DDI (coupled with biomarker-informed approach to optimize in vivo inhibitory constant) and the effect of renal impairment on OAT1/3 drugs in lieu of clinical studies.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physiologically Based Pharmacokinetic Model of Tyrosine Kinase Inhibitors to Predict Target Site Penetration, with PET-Guided Verification.","authors":"Suzanne van der Gaag, Tamara Jordens, Maqsood Yaqub, Robbin Grijseels, Daan W van Valkengoed, Evelien N de Langen, Ruben van den Broek, Victor L J L Thijssen, Adrianus J de Langen, Mathilde C M Kouwenhoven, Idris Bahce, Bart A Westerman, N Harry Hendrikse, Imke H Bartelink","doi":"10.1002/psp4.70006","DOIUrl":"https://doi.org/10.1002/psp4.70006","url":null,"abstract":"<p><p>Osimertinib, a tyrosine kinase inhibitor (TKI), treats non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations. However, its efficacy may vary due to heterogeneous drug distribution, assessable through microdosed radiolabeled drugs and positron emission tomography (PET). Precision dosing using microdosed TKI-PET encounters challenges due to pharmacokinetic (PK) variations between micro- and therapeutic doses. This study aims to predict osimertinib's tissue concentration-time profiles for both microdose and therapeutic dose scenarios using a whole-body physiologically based pharmacokinetic (PBPK) model, which incorporates nonlinear PK processes and target site occupancy. A target site PBPK model for osimertinib was developed to predict drug distribution across various tissues, including lung tumor, based on a previously published PBPK model. The model incorporated tissue-specific parameters and accounted for both linear and nonlinear pharmacokinetic processes, including EGFR-binding dynamics and tumor dynamics. Model predictions were verified with microdosed [¹¹C]C-osimertinib PET imaging data and clinical pharmacokinetic profiles to assess accuracy and reliability. The developed target site-PBPK model accurately predicted osimertinib pharmacokinetics across multiple (tumor) tissues and dose levels within 2-fold error compared to observed PET data. This study underscores the utility of PBPK modeling in predicting osimertinib's pharmacokinetics across diverse tissues, offering insights into drug distribution and predictions of target engagement in NSCLC patients using microdose PET imaging data. The developed model serves as a promising tool for optimizing dosing strategies and evaluating novel EGFR-TKIs in NSCLC treatment.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Population Pharmacokinetic Model to Inform Extension of the Eteplirsen Dosing Regimen Across the Broad DMD Population.","authors":"Yogesh Patel, Larry Orogun, Nicole Yocum, Louise R Rodino-Klapac, Lilly East","doi":"10.1002/psp4.70001","DOIUrl":"https://doi.org/10.1002/psp4.70001","url":null,"abstract":"<p><p>Duchenne muscular dystrophy (DMD) is characterized by progressive, irreversible muscle damage that usually leads to premature death from cardiac or respiratory failure. Eteplirsen is a phosphorodiamidate morpholino oligomer and the first antisense oligonucleotide (ASO) approved for the treatment of patients with exon 51 skip-amenable DMD. This analysis presents the first population pharmacokinetics (PK) modeling and simulation performed for the ASO drug class in DMD. Study objectives were to characterize the population PK of eteplirsen in patients with DMD across a broad age range and to identify the impact of covariates on eteplirsen exposure to guide clinical dosing. Plasma concentration data were pooled from six clinical studies of male patients with DMD across the age range of 6 months to 4 years (1 study) and 4-16 years (5 studies). Doses ranged from 0.5 to 50 mg/kg/week across different studies. A three-compartment model with a linear elimination described the eteplirsen plasma concentration data well. Body weight effect on all PK parameters and eGFR, and age (≤ 4 years vs. > 4 years) effect on systemic clearance were key determinants of variability in the final model. Simulations showed similar exposures for eteplirsen (30 mg/kg intravenously once weekly) across different age groups (0.5 to < 2, 2 to < 4, 4 to < 7, and 7 to ≤ 16 years). These findings support the existing eteplirsen dosing paradigm of uniform weight-based dosing at 30 mg/kg/week across the broad age range of the target DMD population (6 months to adolescence).</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-Informed Drug Development of a Sustained Release Formulation of Flucytosine in the Treatment of Cryptococcal Meningitis: A Case Study Using Physiologically Based Pharmacokinetic Modeling.","authors":"Johanna Eriksson, Erik Sjögren, Jean-Yves Gillon, Henri Caplain, Vishal Goyal, Vijay Satam, Stephen Robinson, Isabela Ribeiro, Marylore Chenel","doi":"10.1002/psp4.13309","DOIUrl":"10.1002/psp4.13309","url":null,"abstract":"<p><p>This paper presents a case study demonstrating the application of model-informed drug development (MIDD) and early modeling integration in the development of a sustained release (SR) formulation of flucytosine for cryptococcal meningoencephalitis (CM) in HIV-infected patients. The study aimed to showcase the value of physiologically based pharmacokinetic (PBPK) modeling and physiologically based biopharmaceutics modeling (PBBM) in guiding decisions and optimizing therapeutic strategies throughout drug development. The MIDD strategy started with a PBPK model based on limited literature data, iteratively refined informed by data from two Phase 1 clinical studies with various flucytosine formulations under different prandial conditions in healthy participants, enhancing model reliability. The PBPK/PBBM model played a substantial role in guiding SR prototype formulation design, dose selection for studies in healthy participants, and dosage determination for an upcoming Phase 2 clinical study in patients, with a focus on low-weight patients. The flexibility of MIDD allowed quick assessments of ancillary questions during the program. Ad hoc simulations evaluated strategies such as adding a loading dose for SR treatment and assessing drug exposure in unconscious patients, contributing to optimized therapeutic approaches. In conclusion, this case study emphasizes the benefits of MIDD and early model integration in drug development. PBPK/PBBM modeling facilitated informed decisions, leading to successful design and dosing of an SR flucytosine formulation for CM treatment. Continuous knowledge integration within MIDD ensured model adaptability and reliability, demonstrating its value in addressing evolving challenges and optimizing therapeutic outcomes.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143491153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Precision Dosing of Lamotrigine During Pregnancy: Physiologically Based Pharmacokinetic Modeling and Simulation.","authors":"Yudie Qian, Wanhong Wu, Chengjie Ke, Siting Liu, Jiarui Chen, Yuying Chen, Xianzhong Guo, Weiwei Lin","doi":"10.1002/psp4.70007","DOIUrl":"https://doi.org/10.1002/psp4.70007","url":null,"abstract":"<p><p>Lamotrigine is a commonly used anti-seizure medication in pregnant women. However, its pharmacokinetics (PK) during pregnancy markedly change, increasing the frequency of seizures and endangering the safety of the mother and fetus. Meanwhile, insufficient PK data on lamotrigine during pregnancy hinders its dose adjustment. This study aimed to predict the maternal and fetal PK of lamotrigine and provide recommendations for dose adjustment. A physiologically based pharmacokinetic (PBPK) model of lamotrigine was constructed using PK-Sim and MoBi and validated with clinical data. The area under the steady-state concentration-time curve (AUC) for lamotrigine decreased by 66.5%, 71.1%, and 81.2% during early, mid, and late pregnancy, respectively, compared with non-pregnant conditions. To achieve effective exposure, three, three, and five times the baseline dose were recommended during early, mid, and late pregnancy, respectively. The fetal PK was best predicted using the isolated cotyledon perfusion method compared to the Caco-2 cell permeability and MoBi default methods. Based on the fetal risk concentration (4.87 mg/L), during early, mid, and late pregnancy, the maximum recommended once-daily dosage should not exceed 400, 500, and 700 mg, respectively, and the twice-daily dosage should not exceed 300, 400, and 600 mg, respectively. The significant decrease in lamotrigine exposure may increase the frequency of seizures in pregnant women. Therefore, prompt dose adjustment is recommended to control seizures while ensuring fetal safety.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}