CPT: Pharmacometrics & Systems Pharmacology最新文献

{"title":"Immunogenicity dynamics and covariate effects after satralizumab administration predicted with a hidden Markov model","authors":"Rory Leisegang,&nbsp;Hanna E. Silber Baumann,&nbsp;Siân Lennon-Chrimes,&nbsp;Hajime Ito,&nbsp;Kazuhiro Miya,&nbsp;Jean-Christophe Genin,&nbsp;Elodie L. Plan","doi":"10.1002/psp4.13230","DOIUrl":"10.1002/psp4.13230","url":null,"abstract":"<p>Immunogenicity is the propensity of a therapeutic protein to generate an immune response to itself. While reporting of antidrug antibodies (ADAs) is increasing, model-based analysis of such data is seldom performed. Model-based characterization of factors affecting the emergence and dissipation of ADAs may inform drug development and/or improve understanding in clinical practice. This analysis aimed to predict ADA dynamics, including the potential influence of individual covariates, following subcutaneous satralizumab administration. Satralizumab is a humanized IgG2 monoclonal recycling IL-6 receptor antagonist antibody approved for treating neuromyelitis optica spectrum disorder (NMOSD). Longitudinal pharmacokinetic (PK) and ADA data from 154 NMOSD patients in two pivotal Phase 3 studies (NCT02028884, NCT02073279) and PK data from one Phase 1 study (SA-001JP) in 72 healthy volunteers were available for this analysis. An existing population PK model was adapted to derive steady-state concentration without ADA for each patient. A mixed hidden Markov model (mHMM) was developed whereby three different states were identified: one absorbing Markov state for non-ADA developer, and two dynamic and inter-connected Markov states—transient ADA negative and positive. Satralizumab exposure and body mass index impacted transition probabilities and, therefore, the likelihood of developing ADAs. In conclusion, the mHMM model was able to describe the time course of ADA development and identify patterns of ADA development in NMOSD patients following treatment with satralizumab, which may allow for the formulation of strategies to reduce the emergence or limit the impact of ADA in the clinical setting.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"13 12","pages":"2171-2184"},"PeriodicalIF":3.1,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/psp4.13230","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142388733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A model-informed clinical trial simulation tool with a graphical user interface for Duchenne muscular dystrophy.","authors":"Jongjin Kim, Juan Francisco Morales, Sanghoon Kang, Marian Klose, Rebecca J Willcocks, Michael J Daniels, Ramona Belfiore-Oshan, Glenn A Walter, William D Rooney, Krista Vandenborne, Sarah Kim","doi":"10.1002/psp4.13246","DOIUrl":"10.1002/psp4.13246","url":null,"abstract":"<p><p>Quantitative model-based clinical trial simulation tools play a critical role in informing study designs through simulation before actual execution. These tools help drug developers explore various trial scenarios in silico to select a clinical trial design to detect therapeutic effects more efficiently, therefore reducing time, expense, and participants' burden. To increase the usability of the tools, user-friendly and interactive platforms should be developed to navigate various simulation scenarios. However, developing such tools challenges researchers, requiring expertise in modeling and interface development. This tutorial aims to address this gap by guiding developers in creating tailored R Shiny apps, using an example of a model-based clinical trial simulation tool that we developed for Duchenne muscular dystrophy (DMD). In this tutorial, the structural framework, essential controllers, and visualization techniques for analysis are described, along with key code examples such as criteria selection and power calculation. A virtual population was created using a machine learning algorithm to enlarge the available sample size to simulate clinical trial scenarios in the presented tool. In addition, external validation of the simulated outputs was conducted using a placebo arm of a recently published DMD trial. This tutorial will be particularly useful for developing clinical trial simulation tools based on DMD progression models for other end points and biomarkers. The presented strategies can also be applied to other diseases.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142364738","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":"Physiology-based pharmacokinetic model with relative transcriptomics to evaluate tissue distribution and receptor occupancy of anifrolumab","authors":"Pradeep Sharma,&nbsp;David W. Boulton,&nbsp;Lynn N. Bertagnolli,&nbsp;Weifeng Tang","doi":"10.1002/psp4.13245","DOIUrl":"10.1002/psp4.13245","url":null,"abstract":"<p>Type I interferons contribute to the pathogenesis of several autoimmune disorders, including systemic lupus erythematosus (SLE), systemic sclerosis, cutaneous lupus erythematosus, and myositis. Anifrolumab is a monoclonal antibody that binds to subunit 1 of the type I interferon receptor (IFNAR1). Results of phase IIb and phase III trials led to the approval of intravenous anifrolumab 300 mg every 4 weeks (Q4W) alongside standard therapy in patients with moderate-to-severe SLE. Here, we built a population physiology-based pharmacokinetic (PBPK) model of anifrolumab by utilizing the physiochemical properties of anifrolumab, binding kinetics to the Fc gamma neonatal receptor, and target-mediated drug disposition properties. A novel relative transcriptomics approach was employed to determine IFNAR1 expression in tissues (blood, skin, gastrointestinal tract, lungs, and muscle) using mRNA abundances from bioinformatic databases. The IFNAR1 expression and PBPK model were validated by testing their ability to predict clinical pharmacokinetics over a large dose range from different clinical scenarios after subcutaneous and intravenous anifrolumab dosing. The validated PBPK model predicted high unbound local concentrations of anifrolumab in blood, skin, gastrointestinal tract, lungs, and muscle, which exceeded its IFNAR1 dissociation equilibrium constant values. The model also predicted high IFNAR1 occupancy with subcutaneous and intravenous anifrolumab dosing. The model predicted more sustained IFNAR1 occupancy ≥90% with subcutaneous anifrolumab 120 mg once-weekly dosing vs. intravenous 300 mg Q4W dosing. The results informed the dosing of phase III studies of anifrolumab in new indications and present a novel approach to PBPK modeling coupled with relative transcriptomics in simulating pharmacokinetics of therapeutic monoclonal antibodies.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 1","pages":"105-117"},"PeriodicalIF":3.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706429/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142364740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interim analysis, a tool to enhance efficiency of pharmacokinetic studies: Pharmacokinetics of rifampicin in lactating mother–infant pairs","authors":"Aida N. Kawuma,&nbsp;Francis Williams Ojara,&nbsp;Allan Buzibye,&nbsp;Barbara Castelnuovo,&nbsp;Jovia C. Tabwenda,&nbsp;Jacqueline Kyeyune,&nbsp;Christine Turyahabwe,&nbsp;Simon Peter Asiimwe,&nbsp;Johnson Magoola,&nbsp;Lubbe Wiesner,&nbsp;Ritah Nakijoba,&nbsp;Catriona Waitt","doi":"10.1002/psp4.13247","DOIUrl":"10.1002/psp4.13247","url":null,"abstract":"<p>Pharmacokinetic studies are important for understanding drug disposition in the human body. However, pregnant and lactating women are often excluded from primary pharmacokinetic studies and as such there is often limited dosing information regarding drug use in pregnant and/or lactating women. The objectives of this interim analysis were to define the transfer of rifampicin to a breastfed infant and to determine the area under the concentration–time curve of rifampicin in maternal plasma, breastmilk and infant plasma. Performing this interim analysis enabled us to substantiate whether prior assumptions we made on several study design issues including patient sample size and pharmacokinetic sampling times held and whether we needed to amend our protocol or not. We enrolled lactating mothers on treatment for tuberculosis with their breastfeeding infants (below 12 months of age), performed intensive pharmacokinetic sampling (0–24 h post-dose) on plasma samples from both the mother, infant(s) and breastmilk samples from the mother on two separate occasions (once during the initiation phase and another during the continuation phase of tuberculosis treatment). The initial study design, including sampling times, was informed by a stochastic simulation and estimation exercise, with very limited prior breastmilk data. An interim analysis after recruiting 6 mother–infant pairs ascertained that our initial assumptions were ideal for achieving our study objectives and no amendments to the sampling times were necessary. Initial data from 6 mother–infant pairs show that rifampicin penetrates breastmilk with an approximate milk-to-plasma ratio of 0.169 and 0.189 on two separate visits. However, it was undetectable in most infants.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"13 11","pages":"1915-1923"},"PeriodicalIF":3.1,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/psp4.13247","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142361274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PBPK modeling: What is the role of CYP3A4 expression in the gastrointestinal tract to accurately predict first-pass metabolism?","authors":"Justine Henriot,&nbsp;André Dallmann,&nbsp;François Dupuis,&nbsp;Jérémy Perrier,&nbsp;Sebastian Frechen","doi":"10.1002/psp4.13249","DOIUrl":"10.1002/psp4.13249","url":null,"abstract":"<p>Gastrointestinal first-pass metabolism plays an important role in bioavailability and in drug–drug interactions. Physiologically-based pharmacokinetic (PBPK) modeling is a powerful tool to integrate these processes mechanistically. However, a correct bottom-up prediction of GI first-pass metabolism is challenging and depends on various model parameters like the level of enzyme expression and the basolateral intestinal mucosa permeability (<i>P</i>_mucosa). This work aimed to investigate if cytochrome P450 (CYP) 3A4 expression could help predict the first-pass effect using PBPK modeling or whether additional factors like <i>P</i>_mucosa do play additional roles using PBPK modeling. To this end, a systematic review of the absolute CYP3A expression in the human gastrointestinal tract and liver was conducted. The resulting CYP3A4 expression profile and two previously published profiles were applied to PBPK models of seven CYP3A4 substrates (alfentanil, alprazolam, felodipine, midazolam, sildenafil, triazolam, and verapamil) built-in PK-Sim®. For each compound, it was assessed whether first-pass metabolism could be adequately predicted based on the integrated CYP3A4 expression profile alone or whether an optimization of <i>P</i>_mucosa was required. Evaluation criteria were the precision of the predicted interstudy bioavailabilities and area under the concentration–time curves. It was found that none of the expression profiles provided upfront an adequate description of the extent of GI metabolism and that optimization of <i>P</i>_mucosa as a compound-specific parameter improved the prediction of most models. Our findings indicate that a pure bottom-up prediction of gastrointestinal first-pass metabolism is currently not possible and that compound-specific features like <i>P</i>_mucosa must be considered as well.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 1","pages":"130-141"},"PeriodicalIF":3.1,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142364739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immunostimulatory/Immunodynamic model of mRNA-1273 to guide pediatric vaccine dose selection","authors":"Vijay Ivaturi,&nbsp;Husain Attarwala,&nbsp;Weiping Deng,&nbsp;Baoyu Ding,&nbsp;Sabine Schnyder Ghamloush,&nbsp;Bethany Girard,&nbsp;Javid Iqbal,&nbsp;Saugandhika Minnikanti,&nbsp;Honghong Zhou,&nbsp;Jacqueline Miller,&nbsp;Rituparna Das","doi":"10.1002/psp4.13237","DOIUrl":"10.1002/psp4.13237","url":null,"abstract":"<p>COVID-19 vaccines, including mRNA-1273, have been rapidly developed and deployed. Establishing the optimal dose is crucial for developing a safe and effective vaccine. Modeling and simulation have the potential to play a key role in guiding the selection and development of the vaccine dose. In this context, we have developed an immunostimulatory/immunodynamic (IS/ID) model to quantitatively characterize the neutralizing antibody titers elicited by mRNA-1273 obtained from three clinical studies. The developed model was used to predict the optimal vaccine dose for future pediatric trials. A 25-μg primary vaccine series was predicted to meet non-inferiority criteria in young children (aged 2–5 years) and infants (aged 6–23 months). The geometric mean titers and geometric mean ratios for this dose level predicted using the IS/ID model a priori matched those observed in the pediatric clinical study. These findings demonstrate that IS/ID models represent a novel approach to guide data-driven clinical dose selection of vaccines.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 1","pages":"42-51"},"PeriodicalIF":3.1,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-host modeling of dengue virus and non-structural protein 1 and the effects of ivermectin in patients with acute dengue fever","authors":"Junjie Ding,&nbsp;Dumrong Mairiang,&nbsp;Dararat Prayongkul,&nbsp;Chunya Puttikhunt,&nbsp;Sansanee Noisakran,&nbsp;Nattapong Kaewjiw,&nbsp;Adisak Songjaeng,&nbsp;Tanapan Prommool,&nbsp;Nattaya Tangthawornchaikul,&nbsp;Nasikarn Angkasekwinai,&nbsp;Yupin Suputtamongkol,&nbsp;Keswadee Lapphra,&nbsp;Kulkanya Chokephaibulkit,&nbsp;Nicholas J. White,&nbsp;Panisadee Avirutnan,&nbsp;Joel Tarning","doi":"10.1002/psp4.13233","DOIUrl":"10.1002/psp4.13233","url":null,"abstract":"<p>The increased incidence of dengue poses a substantially global public health challenge. There are no approved antiviral drugs to treat dengue infections. Ivermectin, an old anti-parasitic drug, had no effect on dengue viremia, but reduced the dengue non-structural protein 1 (NS1) in a clinical trial. This is potentially important, as NS1 may play a causal role in the pathogenesis of severe dengue. This study established an in-host model to characterize the plasma kinetics of dengue virus and NS1 with host immunity and evaluated the effects of ivermectin, using a population pharmacokinetic–pharmacodynamic (PK–PD) modeling approach, based on two studies in acute dengue fever: a placebo-controlled ivermectin study in 250 adult patients and an ivermectin PK–PD study in 24 pediatric patients. The proposed model described adequately the observed ivermectin pharmacokinetics, viral load, and NS1 data. Bodyweight was a significant covariate on ivermectin pharmacokinetics. We found that ivermectin reduced NS1 with an EC₅₀ of 67.5 μg/mL. In silico simulations suggested that ivermectin should be dosed within 48 h after fever onset, and that a daily dosage of 800 μg/kg could achieve substantial NS1 reduction. The in-host dengue model is useful to assess the drug effect in antiviral drug development for dengue fever.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"13 12","pages":"2196-2209"},"PeriodicalIF":3.1,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/psp4.13233","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The population pharmacokinetics of dolutegravir co-administered with rifampicin in Thai people living with HIV: Assessment of alternative dosing regimens","authors":"Baralee Punyawudho,&nbsp;Anan Chanruang,&nbsp;Thornthun Ueaphongsukkit,&nbsp;Sivaporn Gatechompol,&nbsp;Sasiwimol Ubolyam,&nbsp;Yong Soon Cho,&nbsp;Jae Gook Shin,&nbsp;Anchalee Avihingsanon","doi":"10.1002/psp4.13244","DOIUrl":"10.1002/psp4.13244","url":null,"abstract":"<p>Tuberculosis is the most common opportunistic infection in individuals with HIV, and rifampicin is crucial in the treatment of tuberculosis. Drug–drug interactions complicate the use of DTG in HIV/TB co-infection, which makes drug administration more difficult. This study aimed to develop the population pharmacokinetic model of DTG when co-administered with rifampicin. The developed model was further used to investigate different dosing regimens. Forty HIV/TB-co-infected participants receiving DTG 50 mg once daily (OD) with food or DTG 50 mg twice daily (b.i.d.) without food were included in the analysis. Intensive pharmacokinetic samples were collected. The data were analyzed using a nonlinear mixed-effects modeling approach. A total of 332 DTG concentrations from 40 PLWH were analyzed. The pharmacokinetics of DTG co-administered with rifampicin can be best described by a one-compartment model with first-order absorption (incorporating lag time) and elimination. Total bilirubin was the only covariate that significantly affected CL/F. DTG 50 mg b.i.d. results in the highest proportion of individuals achieving in vitro IC₉₀ of 0.064 mg/L and in vivo EC₉₀ of 0.3 mg/L, while more than 90% of individuals receiving DTG 100 mg OD would achieve the in vitro IC₉₀ target. Therefore, DTG 100 mg OD could serve as an alternative regimen by minimizing the difficulty of drug administration. However, its clinical efficacy requires additional evaluation.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 1","pages":"95-104"},"PeriodicalIF":3.1,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706422/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In memoriam Lambertus (“Bert”) A. Peletier 29 March 1937–16 December 2023: Furthering quantitative pharmacology through applied mathematics","authors":"Meindert Danhof,&nbsp;Piet H. van der Graaf,&nbsp;Teun M. Post,&nbsp;Sandra A. G. Visser,&nbsp;Klaas P. Zuideveld,&nbsp;Stephan Schmidt","doi":"10.1002/psp4.13236","DOIUrl":"10.1002/psp4.13236","url":null,"abstract":"&lt;p&gt;On December 16, 2023, our respected, beloved colleague, and friend prof.dr.ir. Lambertus (&lt;i&gt;Bert) A. Peletier&lt;/i&gt; passed away after a brief illness. Bert was an eminent mathematician with a broad interest in natural sciences. He received great international esteem for his fundamental research on partial differential equations. A list of his scientific publications can be found at https://scholargps.com/scholars/36194565598852/lambertus-a-peletier for further reading. Throughout his career as mathematician, several prestigious honors were bestowed upon him. He was elected as a member of the Royal Netherlands Academy of Arts and Sciences (KNAW) in 1999. In 2013, he received a knighthood in the Order of the Netherlands Lion (RNL).&lt;/p&gt;&lt;p&gt;In an interview with Ionica Smeets in 2015 (“Het keerpunt van Bert Peletier. De intellectuele bevrediging is anders, maar net zo groot.” Nieuw Archief voor Wiskunde (in Dutch). https://www.nieuwarchief.nl/serie5/pdf/naw5-2015-16-3-213.pdf), Bert reflected on his academic career. As the son of an engineer, Bert had an innate interest in technology, fuelled by the ambition to engage in a study at the Technical University of Delft. On the recommendation of his math teacher, he chose to study theoretical physics rather than pure mathematics. The choice of physics was based on his belief that mathematics is best understood in the context of real-life examples. Throughout his academic career, Bert continued to seek out opportunities for discussion and debate with colleagues, adhering to the motto of one of his unknown American colleagues: Science is the pursuit of knowledge in the company of friends.&lt;/p&gt;&lt;p&gt;After his graduation, from the newly established Eindhoven University of Technology, Bert spent a year at the Massachusetts Institute of Technology (MIT) in Boston. It was the place where he became inspired by academic life and debate. It made him decide to pursue a career in academia rather than in industry. In 1967, he obtained his PhD at the Eindhoven University of Technology. The title of his thesis was “On a class of wave equations.” After the completion of his PhD thesis and internships at the University of Sussex (UK) and the University of Minnesota (USA), he was appointed full professor of analysis and applied mathematics at Leiden University in 1977 from where he retired in 2002.&lt;/p&gt;&lt;p&gt;Just before his retirement from Leiden University, Bert accidentally met a pharmacist who had come across a publication by a group of Swedish researchers on mathematical modeling of drug effects. This pharmacist challenged Bert with the words: “If they can do this in Sweden, then you should be able to do this as well.” The very next day, Bert called Meindert Danhof, Professor at the Leiden Academic Centre for Drug Research (LACDR). He learnt that LACDR had an active research program in pharmacokinetics and pharmacokinetic–pharmacodynamic (PK–PD) modeling and simulation with a unique infrastructure to generate high-density drug","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"13 10","pages":"1611-1614"},"PeriodicalIF":3.1,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494821/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mathematical model of the relationship between pH holding time and erosive esophagitis healing rates","authors":"Colin W. Howden,&nbsp;Carmelo Scarpignato,&nbsp;Eckhard Leifke,&nbsp;Darcy J. Mulford,&nbsp;Gezim Lahu,&nbsp;Axel Facius,&nbsp;Yuhong Yuan,&nbsp;Richard Hunt","doi":"10.1002/psp4.13235","DOIUrl":"10.1002/psp4.13235","url":null,"abstract":"<p>Effective suppression of gastric acid secretion promotes healing of erosive esophagitis. Treatment guidelines recommend proton pump inhibitors (PPIs) and histamine H₂–receptor antagonists (H₂RAs). Emerging evidence also supports potassium-competitive acid blockers (P-CABs). The aim was to construct a mathematical model to examine the relationship between pH holding time ratios (HTRs) and erosive esophagitis healing rates with H₂RAs, PPIs and P-CABs. By literature search, we identified studies of H₂RAs, PPIs or P-CABs that reported mean pH &gt;4 HTRs at steady state (days 5–8) and erosive esophagitis healing rates after 4 and/or 8 weeks. We aggregated treatments by drug class and developed a non-linear, mixed-effects model to explore the relationship between pH &gt;4 HTRs and healing rates. The pH dataset included 82 studies (4297 participants; 201 dosage arms); healing rate data came from 103 studies (43,417 patients; 196 treatment arms). P-CABs achieved the longest periods with intragastric pH &gt;4, and the highest healing rates after 4 and 8 weeks. The predicted probabilities of achieving ≥90% healing rates at 8 weeks were 74.1% for P-CABs, 17.3% for PPIs and 0% for H₂RAs. P-CABs provide the longest duration with intragastric pH &gt;4 and, accordingly, the highest healing rates of erosive esophagitis.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":"14 1","pages":"28-41"},"PeriodicalIF":3.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706433/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}