{"title":"Explaining in-vitro to in-vivo efficacy correlations in oncology pre-clinical development via a semi-mechanistic mathematical model.","authors":"Heinrich J Huber, Hitesh B Mistry","doi":"10.1007/s10928-023-09891-7","DOIUrl":"10.1007/s10928-023-09891-7","url":null,"abstract":"<p><p>In-vitro to in-vivo correlations (IVIVC), relating in-vitro parameters like IC50 to in-vivo drug exposure in plasma and tumour growth, are widely used in oncology for experimental design and dose decisions. However, they lack a deeper understanding of the underlying mechanisms. Our paper therefore focuses on linking empirical IVIVC relations for small-molecule kinase inhibitors with a semi-mechanistic tumour-growth model. We develop an approach incorporating parameters like the compound's peak-trough ratio (PTR), Hill coefficient of in-vitro dose-response curves, and xenograft-specific properties. This leads to formulas for determining efficacious doses for tumor stasis under linear pharmacokinetics equivalent to traditional empirical IVIVC relations, but enabling more systematic analysis. Our findings reveal that in-vivo xenograft-specific parameters, specifically the growth rate (g) and decay rate (d), along with the average exposure, are generally more significant determinants of tumor stasis and effective dose than the compound's peak-trough ratio. However, as the Hill coefficient increases, the dependency of tumor stasis on the PTR becomes more pronounced, indicating that the compound is more influenced by its maximum or trough values rather than the average exposure. Furthermore, we discuss the translation of our method to predict population dose ranges in clinical studies and propose a resistance mechanism that solely relies on specific in-vivo xenograft parameters instead of IC50 exposure coverage. In summary, our study aims to provide a more mechanistic understanding of IVIVC relations, emphasizing the importance of xenograft-specific parameters and PTR on tumor stasis.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":" ","pages":"169-185"},"PeriodicalIF":2.2,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10982099/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71482795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yanke Yu, Michael E Rothenberg, Han Ting Ding, Ari Brekkan, Gizette Sperinde, Brandon Harder, Rong Zhang, Ryan Owen, Nastya Kassir, Annemarie N Lekkerkerker
{"title":"Population pharmacokinetics and pharmacodynamics of efmarodocokin alfa (IL-22Fc).","authors":"Yanke Yu, Michael E Rothenberg, Han Ting Ding, Ari Brekkan, Gizette Sperinde, Brandon Harder, Rong Zhang, Ryan Owen, Nastya Kassir, Annemarie N Lekkerkerker","doi":"10.1007/s10928-023-09888-2","DOIUrl":"10.1007/s10928-023-09888-2","url":null,"abstract":"<p><p>Efmarodocokin alfa (IL-22Fc) is a fusion protein of human IL-22 linked to the crystallizable fragment (Fc) of human IgG4. It has been tested in multiple indications including inflammatory bowel disease (IBD). The purposes of the present analyses were to describe the population pharmacokinetics (PK) of efmarodocokin alfa and perform pharmacodynamic (PD) analysis on the longitudinal changes of the PD biomarker REG3A after efmarodocokin alfa treatment as well as identify covariates that affect efmarodocokin alfa PK and REG3A PD. The data used for this analysis included 182 subjects treated with efmarodocokin alfa in two clinical studies. The population PK and PD analyses were conducted sequentially. Efmarodocokin alfa concentration-time data were analyzed using a nonlinear mixed-effects modeling approach, and an indirect response model was adopted to describe the REG3A PD data with efmarodocokin alfa serum concentration linked to the increase in REG3A. The analysis software used were NONMEM and R. A 3-compartment model with linear elimination best described the PK of efmarodocokin alfa. The estimated population-typical value for clearance (CL) was 1.12 L/day, and volume of central compartment was 6.15 L. Efmarodocokin alfa CL increased with higher baseline body weight, C-reactive protein, and CL was 27.6% higher in IBD patients compared to healthy subjects. The indirect response PD model adequately described the longitudinal changes of REG3A after efmarodocokin alfa treatment. A popPK and PD model for efmarodocokin alfa and REG3A was developed and covariates affecting the PK and PD were identified.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":" ","pages":"141-153"},"PeriodicalIF":2.2,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49678761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Longitudinal modeling of efficacy response in patients with lupus nephritis receiving belimumab","authors":"","doi":"10.1007/s10928-024-09907-w","DOIUrl":"https://doi.org/10.1007/s10928-024-09907-w","url":null,"abstract":"<h3>Abstract</h3> <p>Belimumab was approved for active lupus nephritis (LN) in adults in the European Union and patients ≥ 5 years of age in the USA based on a Phase 3, double-blind, placebo-controlled, 104-week study. The study evaluated the efficacy of belimumab plus background standard therapy in adults with active LN using an intravenous (IV) dose of 10 mg/kg. A longitudinal analysis of Primary Efficacy Renal Response (PERR) and Complete Renal Response (CRR) was performed to assess whether patients with high proteinuria at the start of belimumab treatment would benefit from a higher dose. Responder probability was modeled as a logistic regression with probability a function of time and treatment (belimumab or placebo). Dropout risk at each visit was incorporated into a joint model of efficacy response; only efficacy data prior to dropout events (belimumab discontinuation, treatment failure, or withdrawal) were included. Average belimumab concentration over the first 4 and 12 weeks and baseline proteinuria were considered as continuous covariates. In general, renal response (PERR and CRR) over time was higher in patients receiving belimumab than in those receiving placebo. Baseline proteinuria was considered the most relevant predictor of renal response, with reduced efficacy in patients with increased proteinuria for both belimumab or placebo treatment. For belimumab-treated patients, belimumab exposure was not found to be an important predictor of renal response. In conclusion, the 10 mg/kg IV dose was considered appropriate in all patients and there was no evidence to suggest a higher response would be achieved by increasing the dose.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"53 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140323842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nikolaos Tsamandouras, Ruolun Qiu, Jim H. Hughes, Kevin Sweeney, John P. Prybylski, Christopher Banfield, Timothy Nicholas
{"title":"Employing zero-inflated beta distribution in an exposure-response analysis of TYK2/JAK1 inhibitor brepocitinib in patients with plaque psoriasis","authors":"Nikolaos Tsamandouras, Ruolun Qiu, Jim H. Hughes, Kevin Sweeney, John P. Prybylski, Christopher Banfield, Timothy Nicholas","doi":"10.1007/s10928-024-09901-2","DOIUrl":"https://doi.org/10.1007/s10928-024-09901-2","url":null,"abstract":"<p>Brepocitinib is an oral selective dual TYK2/JAK1 inhibitor and based on its cytokine inhibition profile is expected to provide therapeutic benefit in the treatment of plaque psoriasis. Efficacy data from a completed Phase 2a study in patients with moderate-to-severe plaque psoriasis were utilized to develop a population exposure-response model that can be employed to inform dose selection decisions for further clinical development. A modeling approach that employs the zero-inflated beta distribution was used to account for the bounded nature and distributional characteristics of the Psoriasis Area and Severity Index (PASI) score data. The developed exposure-response model provided an adequate description of the observed PASI scores across all the treatment arms tested and across both the induction and maintenance dosing periods of the study. In addition, the developed model exhibited a good predictive capacity with regard to the derived responder metrics (e.g., 75%/90%/100% improvement in PASI score [PASI75/90/100]). Clinical trial simulations indicated that the induction/maintenance dosing paradigm explored in this study does not offer any advantages from an efficacy perspective and that doses of 10, 30, and 60 mg once-daily may be suitable candidates for clinical evaluation in subsequent Phase 2b studies.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"80 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140016833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A population pharmacokinetics model of balovaptan to support dose selection in adult and pediatric populations","authors":"","doi":"10.1007/s10928-023-09898-0","DOIUrl":"https://doi.org/10.1007/s10928-023-09898-0","url":null,"abstract":"<h3>Abstract</h3> <p>Balovaptan is a brain-penetrating vasopressin receptor 1a antagonist previously investigated for the core symptoms of autism spectrum disorder (ASD). A population pharmacokinetic (PK) model of balovaptan was developed, initially to assist clinical dosing for adult and pediatric ASD studies and subsequently for new clinical indications including malignant cerebral edema (MCE) and post-traumatic stress disorder. The final model incorporates one-compartment disposition and describes time- and dose-dependent non-linear PK through empirical drug binding and a gut extraction component with turnover. An age effect on clearance observed in children was modeled by an asymptotic function that predicts adult-equivalent exposures at 40% of the adult dose for children aged 2–4 years, 70% for 5–9 years, and at the full adult dose for ≥ 10 years. The model was adapted for intravenous (IV) balovaptan dosing and combined with in vitro and ex vivo pharmacodynamic data to simulate brain receptor occupancy as a guide for dosing in a phase II trial of MCE prophylaxis after acute ischemic stroke. A sequence of three stepped-dose daily infusions of 50, 25 and 15 mg over 30 or 60 min was predicted to achieve a target occupancy of ≥ 80% in ≥ 95% of patients over a 3-day period. This model predicts both oral and IV balovaptan exposure across a wide age range and will be a valuable tool to analyze and predict its PK in new indications and target populations, including pediatric patients.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":"10 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139678853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juanjuan Jiang, Li Xu, Lin Chai, Li Zhang, Hong Liu, Yan Yan, Xiaoyuan Guan, Hui Sun, Lei Tian
{"title":"Population pharmacokinetic/pharmacodynamic modeling of nifekalant injection with varies dosing plan in Chinese volunteers: a randomized, blind, placebo-controlled study.","authors":"Juanjuan Jiang, Li Xu, Lin Chai, Li Zhang, Hong Liu, Yan Yan, Xiaoyuan Guan, Hui Sun, Lei Tian","doi":"10.1007/s10928-023-09882-8","DOIUrl":"10.1007/s10928-023-09882-8","url":null,"abstract":"<p><p>Nifekalant hydrochloride is a class III antiarrhythmic agent which could increase the duration of the action potential and the effective refractory period of ventricular and atrial myocytes by blocking the K<sup>+</sup> current. Nifekalant is used to prevent ventricular tachycardia/ventricular fibrillation. QT interval prolongation is the main measurable drug effect. However, due to the complicated dosing plan in clinic, the relationship among dosage, time, drug concentration and efficacy is not fully understood. In this study, a single-center, randomized, blind, dose-ascending, placebo-controlled study was conducted to explore the intrinsic characteristics of nifekalant injection in healthy Chinese volunteers by a population pharmacokinetic (PK)-pharmacodynamic (PD) model approach. 42 subjects were enrolled in this study and received one of three dose plans (loading dose on Day 1 (0.15, 0.3 or 0.5 mg/kg), loading dose followed by maintenance dose (0.2, 0.4 or 0.8 mg/kg/h) on Day 4) or vehicle. Blood samples were drawn for PK evaluation, and ECGs were recorded for QTc calculation at the designed timepoints. No Torsades de Pointes occurred during the study. The popPK model of nifekalant injection could be described by a two-compartment model with first-order elimination. The population mean clearance (CL) was 53.8 L/h. The population mean distribution volume of the central (V<sub>c</sub>) and peripheral (V<sub>p</sub>) compartments was 8.27 L and 45.6 L, respectively. A nonlinear dose-response (E<sub>max</sub>) model well described the pharmacodynamic effect (QTc interval prolongation) of nifekalant. The E<sub>max</sub> and EC<sub>50</sub> from current study were 101 ms and 342 ng/mL, respectively.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":" ","pages":"77-87"},"PeriodicalIF":2.5,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10328050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Wang, Tak Hung, Noelyn Hung, Paul Glue, Chris Jackson, Stephen Duffull
{"title":"Optimal sample selection applied to information rich, dense data.","authors":"David Wang, Tak Hung, Noelyn Hung, Paul Glue, Chris Jackson, Stephen Duffull","doi":"10.1007/s10928-023-09883-7","DOIUrl":"10.1007/s10928-023-09883-7","url":null,"abstract":"<p><p>Dense data can be classified into superdense information-poor data (type 1 dense data) and dense information-rich data (type 2 dense data). Arbitrary, random, or optimal thinning may be applied to type 1 dense data to minimise computational burden and statistical issues (such as autocorrelation). In contrast, a prospective or retrospective optimal design can be applied to type 2 dense data to maximise information gain from limited resources (capital and/or time). Here we describe a retrospective optimal selection strategy for quantification of unbound drug concentration from a discrete set of plasma samples where the total drug concentration has been measured.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":" ","pages":"33-37"},"PeriodicalIF":2.5,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9967411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peter L Bonate, Jeffrey S Barrett, Sihem Ait-Oudhia, Richard Brundage, Brian Corrigan, Stephen Duffull, Marc Gastonguay, Mats O Karlsson, Shinichi Kijima, Andreas Krause, Mark Lovern, Matthew M Riggs, Michael Neely, Daniele Ouellet, Elodie L Plan, Gauri G Rao, Joseph Standing, Justin Wilkins, Hao Zhu
{"title":"Correction to: Training the next generation of pharmacometric modelers: a multisector perspective.","authors":"Peter L Bonate, Jeffrey S Barrett, Sihem Ait-Oudhia, Richard Brundage, Brian Corrigan, Stephen Duffull, Marc Gastonguay, Mats O Karlsson, Shinichi Kijima, Andreas Krause, Mark Lovern, Matthew M Riggs, Michael Neely, Daniele Ouellet, Elodie L Plan, Gauri G Rao, Joseph Standing, Justin Wilkins, Hao Zhu","doi":"10.1007/s10928-023-09885-5","DOIUrl":"10.1007/s10928-023-09885-5","url":null,"abstract":"","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":" ","pages":"89"},"PeriodicalIF":2.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10164395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ari Brekkan, Rocío Lledo-Garcia, Brigitte Lacroix, Siv Jönsson, Mats O Karlsson, Elodie L Plan
{"title":"Characterization of anti-drug antibody dynamics using a bivariate mixed hidden-markov model by nonlinear-mixed effects approach.","authors":"Ari Brekkan, Rocío Lledo-Garcia, Brigitte Lacroix, Siv Jönsson, Mats O Karlsson, Elodie L Plan","doi":"10.1007/s10928-023-09890-8","DOIUrl":"10.1007/s10928-023-09890-8","url":null,"abstract":"<p><p>Biological therapies may act as immunogenic triggers leading to the formation of anti-drug antibodies (ADAs). Population pharmacokinetic (PK) models can be used to characterize the relationship between ADA and drug disposition but often rely on the ADA bioassay results, which may not be sufficiently sensitive to inform on this characterization.In this work, a methodology that could help to further elucidate the underlying ADA production and impact on the drug disposition was explored. A mixed hidden-Markov model (MHMM) was developed to characterize the underlying (hidden) formation of ADA against the biologic, using certolizumab pegol (CZP), as a test drug. CZP is a PEGylated Fc free TNF-inhibitor used in the treatment of rheumatoid arthritis and other chronic inflammatory diseases.The bivariate MHMM used information from plasma drug concentrations and ADA measurements, from six clinical studies (n = 845), that were correlated through a bivariate Gaussian function to infer about two hidden states; production and no-production of ADA influencing PK. Estimation of inter-individual variability was not supported in this case. Parameters associated with the observed part of the model were reasonably well estimated while parameters associated with the hidden part were less precise. Individual state sequences obtained using a Viterbi algorithm suggested that the model was able to determine the start of ADA production for each individual, being a more assay-independent methodology than traditional population PK. The model serves as a basis for identification of covariates influencing the ADA formation, and thus has the potential to identify aspects that minimize its impact on PK and/or efficacy.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":" ","pages":"65-75"},"PeriodicalIF":2.5,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10884144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71521891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peter L Bonate, Jeffrey S Barrett, Sihem Ait-Oudhia, Richard Brundage, Brian Corrigan, Stephen Duffull, Marc Gastonguay, Mats O Karlsson, Shinichi Kijima, Andreas Krause, Mark Lovern, Matthew M Riggs, Michael Neely, Daniele Ouellet, Elodie L Plan, Gauri G Rao, Joseph Standing, Justin Wilkins, Hao Zhu
{"title":"Training the next generation of pharmacometric modelers: a multisector perspective.","authors":"Peter L Bonate, Jeffrey S Barrett, Sihem Ait-Oudhia, Richard Brundage, Brian Corrigan, Stephen Duffull, Marc Gastonguay, Mats O Karlsson, Shinichi Kijima, Andreas Krause, Mark Lovern, Matthew M Riggs, Michael Neely, Daniele Ouellet, Elodie L Plan, Gauri G Rao, Joseph Standing, Justin Wilkins, Hao Zhu","doi":"10.1007/s10928-023-09878-4","DOIUrl":"10.1007/s10928-023-09878-4","url":null,"abstract":"<p><p>The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing. The field largely started when Lewis Sheiner and Stuart Beal published their seminal papers on population pharmacokinetics in the late 1970's and early 1980's and has continued to grow in impact and use since its inception. Physiological-based pharmacokinetics and systems pharmacology have grown rapidly in scope and impact in the last decade and machine learning is just on the horizon. While all these methodologies are categorized as pharmacometrics, no one person can be an expert in everything. So how do you train future pharmacometricians? Leading experts in academia, industry, contract research organizations, clinical medicine, and regulatory gave their opinions on how to best train future pharmacometricians. Their opinions were collected and synthesized to create some general recommendations.</p>","PeriodicalId":16851,"journal":{"name":"Journal of Pharmacokinetics and Pharmacodynamics","volume":" ","pages":"5-31"},"PeriodicalIF":2.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10531805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}