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Mirjam N Trame, Matthew Riggs, Kostas Biliouris, Dhananjay Marathe, Jerome Mettetal, Teun M Post, Matthew L Rizk, Sandra A G Visser, Cynthia J Musante
No abstract text is available yet for this article.
May 15, 2018: CPT: Pharmacometrics & Systems Pharmacology
Elizabeth A Lakota, Cornelia B Landersdorfer, Roger L Nation, Jian Li, Keith S Kaye, Gauri G Rao, Alan Forrest
Polymyxin B is used as an antibiotic of last resort for patients with multidrug-resistant Gram-negative bacterial infections; however, it carries a significant risk of nephrotoxicity. Herein we present a polymyxin B therapeutic window based on target area under the concentration-time curve (AUC) values and an adaptive feedback control algorithm (algorithm) which allows for the personalization of polymyxin B dosing. The upper bound of this therapeutic window was determined through a pharmacometric meta-analysis of polymyxin B nephrotoxicity data, and the lower bound was derived from murine thigh-infection pharmacokinetic/pharmacodynamic studies...
May 14, 2018: Antimicrobial Agents and Chemotherapy
A M Novakovic, A Thorsted, E Schindler, S Jönsson, A Munafo, M O Karlsson
The aim of this work was to assess the relationship between the absolute lymphocyte count (ALC), and disability (as measured by the Expanded Disability Status Scale [EDSS]) and occurrence of relapses, 2 efficacy endpoints, respectively, in patients with remitting-relasping multiple sclerosis. Data for ALC, EDSS, and relapse rate were available from 1319 patients receiving placebo and/or cladribine tablets. Pharmacodynamic models were developed to characterize the time course of the endpoints. ALC-related measures were then evaluated as predictors of the efficacy endpoints...
May 10, 2018: Journal of Clinical Pharmacology
Sebastian G Wicha, Oskar Clewe, Robin J Svensson, Stephen H Gillespie, Yanmin Hu, Anthony R M Coates, Ulrika S H Simonsson
A crucial step for accelerating tuberculosis drug development is bridging the gap between pre-clinical and clinical trials. In this study, we developed a pre-clinical model-informed translational approach to predict drug effects across pre-clinical systems and early clinical trials using the in vitro-based Multistate Tuberculosis Pharmacometric (MTP) model using rifampicin as an example. The MTP model predicted rifampicin biomarker response observed in (i) a hollow-fiber infection model, (ii) a murine study to determine PK/PD indices, and (iii) several clinical phase IIa early bactericidal activity (EBA) studies...
April 26, 2018: Clinical Pharmacology and Therapeutics
Sujit Nair, Adrián LLerena
No abstract text is available yet for this article.
April 24, 2018: Drug Metabolism and Personalized Therapy
Emilie Schindler, Lena E Friberg, Bertram L Lum, Bei Wang, Angelica Quartino, Chunze Li, Sandhya Girish, Jin Y Jin, Mats O Karlsson
PURPOSE: An item response theory (IRT) pharmacometric framework is presented to characterize Functional Assessment of Cancer Therapy-Breast (FACT-B) data in locally-advanced or metastatic breast cancer patients treated with ado-trastuzumab emtansine (T-DM1) or capecitabine-plus-lapatinib. METHODS: In the IRT model, four latent well-being variables, based on FACT-B general subscales, were used to describe the physical, social/family, emotional and functional well-being...
April 19, 2018: Pharmaceutical Research
Charlotte I S Barker, Joseph F Standing, Lauren E Kelly, Lauren Hanly Faught, Allison C Needham, Michael J Rieder, Saskia N de Wildt, Martin Offringa
Optimising the dosing of medicines for neonates and children remains a challenge. The importance of pharmacokinetic (PK) and pharmacodynamic (PD) research is recognised both in medicines regulation and paediatric clinical pharmacology, yet there remain barriers to undertaking high-quality PK and PD studies. While these studies are essential in understanding the dose-concentration-effect relationship and should underpin dosing recommendations, this review examines how challenges affecting the design and conduct of paediatric pharmacological studies can be overcome using targeted pharmacometric strategies...
April 19, 2018: Archives of Disease in Childhood
Ayaka Kitamura, Ryohei Takata, Shin Aizawa, Hajime Watanabe, Tadashi Wada
Drug development involves pharmacometric experiments in animals. Such experiments should limit animal pain and stress. Conventional murine models of atopic dermatitis (AD) used in drug development are generated by weekly painting of hapten on dorsal skin for 5 weeks. The present study aimed to develop a protocol that involves less animal distress. The experiments focused on serum total IgE levels, which are a marker of AD. The conventional protocol induced ever rising IgE levels. Experiments with extended intervals between sensitizations showed that IgE peaked ~5 days after the second sensitization, after which it returned to the control level within 12-19 days...
April 16, 2018: Scientific Reports
Stéphanie Leroux, Valéry Elie, Wei Zhao, Sophie Magreault, Evelyne Jacqz-Aigrain
Drug evaluation in children is difficult for many well-identified reasons and many drugs are still used off-label. Innovative approaches are particularly adapted to the paediatric and neonatal populations, as clinical trials are difficult to conduct, need adapted designs in order to define the optimal dosage regimen in many diseases and therapeutic areas. Population approaches to define pharmacokinetics and pharmacokinetic/pharmacodynamics are now more currently used to define dosing regimens, adapted to the different paediatric and neonatal age groups, that allow to increase efficacy and reduce toxicity, by taking into account factors explaining variability in drug response...
February 16, 2018: Thérapie
José Luis Piñana, Alejandro Perez-Pitarch, Beatriz Guglieri-Lopez, Estela Giménez, Juan Carlos Hernandez-Boluda, María José Terol, Rafael Ferriols-Lisart, Carlos Solano, David Navarro
Sirolimus appears to protect against CMV in organ transplant recipients. The effect of this drug in allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipients remains unexplored. By means of multivariate continuous-time Markov model analyses, we identified three independent covariates which significantly impacted the risk of CMV DNAemia: recipient/donor CMV serostatus, tacrolimus exposure and sirolimus exposure. CMV seropositive recipients with CMV seronegative donors had a significantly higher probability of having detectable CMV DNAemia...
March 30, 2018: American Journal of Transplantation
Simon Buatois, Sebastian Ueckert, Nicolas Frey, Sylvie Retout, France Mentré
In drug development, pharmacometric approaches consist in identifying via a model selection (MS) process the model structure that best describes the data. However, making predictions using a selected model ignores model structure uncertainty, which could impair predictive performance. To overcome this drawback, model averaging (MA) takes into account the uncertainty across a set of candidate models by weighting them as a function of an information criterion. Our primary objective was to use clinical trial simulations (CTSs) to compare model selection (MS) with model averaging (MA) in dose finding clinical trials, based on the AIC information criterion...
March 29, 2018: AAPS Journal
Cristiana Larizza, Elisa Borella, Lorenzo Pasotti, Palma Tartaglione, Mike Smith, Stuart Moodie, Paolo Magni
The Drug Disease Model Resources (DDMoRe) Interoperability Framework (IOF) enables pharmacometric model encoding and execution via Model Description Language (MDL) and R language, through the ddmore package. Through its components and converter plugins, the IOF can execute pharmacometric tasks using different target tools, starting from a single MDL-encoded model. In this article, we present the WinBUGS plugin and show how its integration in the IOF enables an easy implementation of complex Bayesian workflows...
March 25, 2018: CPT: Pharmacometrics & Systems Pharmacology
Xiajing Gong, Meng Hu, Liang Zhao
Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data...
May 2018: Clinical and Translational Science
Peijuan Zhu, Sherwin K B Sy, Andrej Skerjanec
This article provides an overview of four case studies to demonstrate the utility of pharmacometric analysis in biosimilar development to help design sensitive clinical pharmacology studies for the demonstration of biosimilarity. The two major factors that determine the sensitivity of a clinical pharmacokinetic/pharmacodynamic (PK/PD) study to demonstrate biosimilarity are the size of the potential difference to be detected (signal) and the inter-subject variability (noise), both of which can be characterized and predicted using pharmacometric approaches...
March 7, 2018: AAPS Journal
Sebastian Ueckert
Composite assessments aim to combine different aspects of a disease in a single score and are utilized in a variety of therapeutic areas. The data arising from these evaluations are inherently discrete with distinct statistical properties. This tutorial presents the framework of the item response theory (IRT) for the analysis of this data type in a pharmacometric context. The article considers both conceptual (terms and assumptions) and practical questions (modeling software, data requirements, and model building)...
April 2018: CPT: Pharmacometrics & Systems Pharmacology
Kumpal Madrasi, Fang Li, Myong-Jin Kim, Snehal Samant, Stephen Voss, Theresa Kehoe, E Dennis Bashaw, Hae Young Ahn, Yaning Wang, Jeffy Florian, Stephan Schmidt, Lawrence J Lesko, Li Li
Osteoporosis is a disorder of the bones in which they are weakened to the extent that they become more prone to fracture. There are various forms of osteoporosis: some of them are induced by drugs, and others occur as a chronic progressive disorder as an individual gets older. As the median age of the population rises across the world, the chronic form of the bone disease is drawing attention as an important worldwide health issue. Developing new treatments for osteoporosis and comparing them with existing treatments are complicated processes due to current acceptance by regulatory authorities of bone mineral density (BMD) and fracture risk as clinical end points, which require clinical trials to be large, prolonged, and expensive to determine clinically significant impacts in BMD and fracture risk...
May 2018: Journal of Clinical Pharmacology
Catharine C Bulik, Justin C Bader, Li Zhang, Scott A Van Wart, Christopher M Rubino, Sujata M Bhavnani, Kim L Sweeney, Paul G Ambrose
The original version of this article contained incorrect Supplementary Files. The correct Supplementary Files are published with this erratum.
April 2018: Journal of Pharmacokinetics and Pharmacodynamics
Cyrielle Dumont, Giulia Lestini, Hervé Le Nagard, France Mentré, Emmanuelle Comets, Thu Thuy Nguyen, For The Pfim Group
BACKGROUND AND OBJECTIVE: Nonlinear mixed-effect models (NLMEMs) are increasingly used for the analysis of longitudinal studies during drug development. When designing these studies, the expected Fisher information matrix (FIM) can be used instead of performing time-consuming clinical trial simulations. The function PFIM is the first tool for design evaluation and optimization that has been developed in R. In this article, we present an extended version, PFIM 4.0, which includes several new features...
March 2018: Computer Methods and Programs in Biomedicine
Anne Kümmel, Peter L Bonate, Jasper Dingemanse, Andreas Krause
Supporting decision making in drug development is a key purpose of pharmacometric models. Pharmacokinetic models predict exposures under alternative posologies or in different populations. Pharmacodynamic models predict drug effects based on exposure to drug, disease, or other patient characteristics. Estimation uncertainty is commonly reported for model parameters; however, prediction uncertainty is the key quantity for clinical decision making. This tutorial reviews confidence and prediction intervals with associated calculation methods, encouraging pharmacometricians to report these routinely...
February 1, 2018: CPT: Pharmacometrics & Systems Pharmacology
Marissa F Dockendorf, Ryan C Vargo, Ferdous Gheyas, Anne S Y Chain, Manash S Chatterjee, Larissa A Wenning
Cardiovascular disease remains a significant global health burden, and development of cardiovascular drugs in the current regulatory environment often demands large and expensive cardiovascular outcome trials. Thus, the use of quantitative pharmacometric approaches which can help enable early Go/No Go decision making, ensure appropriate dose selection, and increase the likelihood of successful clinical trials, have become increasingly important to help reduce the risk of failed cardiovascular outcomes studies...
January 20, 2018: Journal of Pharmacokinetics and Pharmacodynamics
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