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CPT: Pharmacometrics & Systems Pharmacology

Fabrizia D'Antonio, Suzanne Reeves, Yucheng Sheng, Emma McLachlan, Carlo de Lena, Robert Howard, Julie Bertrand
The presence of psychosis is associated with more rapid decline in Alzheimer's disease (AD), but the impact of paranoid (persecutory delusions) and misidentification (misperceptions and/or hallucinations) subtypes of psychosis on the speed of decline in AD is still unclear. Here we analysed data on Alzheimer's Disease Neuroimaging Initiative (ADNI)2 participants with late mild cognitive impairment or AD and we described individual trajectories of Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog) scores using a semi-mechanistic, logistic model, with a mixed effects based approach, which accounted for drop-out, and adjusted for baseline Mini Mental State Examination scores...
February 19, 2019: CPT: Pharmacometrics & Systems Pharmacology
Felix Stader, Melissa A Penny, Marco Siccardi, Catia Marzolini
Physiologically based pharmacokinetic (PBPK) models are useful tools to predict clinical scenarios for special populations for whom there are high hurdles to conduct clinical trials such as children or the elderly. However, coding of a PBPK model in a mathematical programming language can be challenging. This tutorial illustrates how to build a whole-body PBPK model in Matlab® to answer specific pharmacological questions involving drug disposition, and magnitudes of drug-drug interactions in different patient populations...
February 18, 2019: CPT: Pharmacometrics & Systems Pharmacology
James A Rogers
I was delighted to participate as a speaker and panel discussant at the 2018 American Conference on Pharmacometrics in a session devoted to dialogue between "pharmacometric modelers" and "statisticians". In the current perspective I reprise the major points of my talk, which addressed the possibility of drawing valid causal inferences from observational data. I augment this reprise with brief remarks comparing diagrammatic conventions in pharmacometrics to those used in formal causal diagrams...
February 14, 2019: CPT: Pharmacometrics & Systems Pharmacology
Guillermo Anda-Jáuregui, Brett A McGregor, Kai Guo, Junguk Hur
Drug-induced peripheral neuropathy (DIPN) is a side effect of a variety of therapeutic agents, which can affect therapeutic adherence and lead to regimen modifications, impacting patient quality of life. The molecular mechanisms involved in the development of this condition have yet to be completely described in the literature. We used a computational network pharmacology approach to explore the Connectivity Map, a large collection of transcriptional profiles from drug perturbation experiments to identify common genes affected by peripheral neuropathy-inducing drugs (NID)...
February 14, 2019: CPT: Pharmacometrics & Systems Pharmacology
Hannah Britz, Nina Hanke, Anke-Katrin Volz, Olav Spigset, Matthias Schwab, Thomas Eissing, Thomas Wendl, Sebastian Frechen, Thorsten Lehr
This study provides whole-body PBPK models of the strong index CYP1A2 inhibitor and moderate CYP3A4 inhibitor fluvoxamine and of the sensitive CYP1A2 substrate theophylline. Both models were built and thoroughly evaluated for their application in DDI prediction in a network of perpetrator and victim drugs, combining them with previously developed models of caffeine (sensitive index CYP1A2 substrate), rifampicin (moderate CYP1A2 inducer) and midazolam (sensitive index CYP3A4 substrate). Simulation of all reported clinical DDI studies for combinations of these 5 drugs shows that the presented models reliably predict the observed drug concentrations, resulting in 7/8 of the predicted DDI AUC ratios (AUC during DDI/AUC control) and 7/7 of the predicted DDI Cmax ratios (Cmax during DDI/Cmax control) within twofold of the observed values...
February 14, 2019: CPT: Pharmacometrics & Systems Pharmacology
Qier Wu, Sheila-Annie Peters
Physiologically-based pharmacokinetic (PBPK) models are increasingly applied for pediatric dose selection along with traditional methods such as allometry and population pharmacokinetic (popPK) models. Here, we report a retrospective evaluation of the three methods. Pediatric popPK models sourced from literature for a subset of 8 compounds, were used to predict clearances for children <2 years when they were within the modelled age range (interpolation, N = 11) or including those outside the modelled age range (interpolation and extrapolation, N = 18)...
February 14, 2019: CPT: Pharmacometrics & Systems Pharmacology
France Mentré
CPT: Pharmacometrics & System Pharmacology (PSP) was launched by the American Society for Clinical Pharmacology and Therapeutics (ASCPT) in 2012. Piet van der Graaf, PhD, PharmD, the first Editor-in-Chief (EIC) of the journal built an impressive editorial team of which I was proud to be part of since the beginning. In August 2018, the ASCPT Board of Directors and Dr van der Graaf approached me to ask whether I would consider taking the role of EIC. This article is protected by copyright. All rights reserved...
February 14, 2019: CPT: Pharmacometrics & Systems Pharmacology
Rui Zhu, Bill Poland, Russ Wada, Qi Liu, Luna Musib, Daniel Maslyar, Eunpi Cho, Wei Yu, Han Ma, Jin Yan Jin, Nageshwar Budha
The aims of this work were to characterize ipatasertib exposure-response (E-R) relationships in a phase II study and to quantitatively assess benefit-risk using a clinical utility index (CUI) approach to support ipatasertib phase III dose selection in patients with metastatic castration-resistant prostate cancer (mCRPC). Logistic regression and Cox proportional-hazards models characterized E-R relationships for safety and efficacy endpoints, respectively. Exposure metrics with and without considering dose interruptions/reductions (modifications) were tested in the E-R models...
February 14, 2019: CPT: Pharmacometrics & Systems Pharmacology
Ping Zhao, Jonathan Arm, Lyou-Fu Ma, Stephen Ward, David Hermann, David Wesche, Dan Hartman, Steven Kern
Infectious diseases continue to threaten the lives of young children in low and middle-income countries (LMICs). Pediatric assessment of anti-infectives for these children should be initiated early. This assessment can center around an iterative dose-selection process that is informed by an integrated prediction platform based on physiologically-based pharmacokinetic and pharmacodynamic (PBPK-PD) models. This article is protected by copyright. All rights reserved.
February 3, 2019: CPT: Pharmacometrics & Systems Pharmacology
Daniel C Kirouac, Brian Cicali, Stephan Schmidt
Provision of model code is required for publication in CPT:PSP, enabling QSP model availability. A searchable repository of published QSP models would enhance model accessibility. We assess the feasibility of establishing such a resource, based on 18 QSP models published in this journal. However, due to the diversity of software platforms (9), file formats and functionality, such a resource is pre-mature. We evaluated 12 of the models (those coded in R, PK-Sim/MOBI and Matlab) for functionality. Of the 12, only 4 were executable, in that figures from the associated manuscript could be generated via a 'run' script...
January 29, 2019: CPT: Pharmacometrics & Systems Pharmacology
Elke H J Krekels, Elisa A M Calvier, Piet H van der Graaf, Catherijne A J Knibbe
Although children cannot be considered small adults due to nonlinear processes underlying the pharmacokinetics of drugs, pediatric doses are typically still expressed per kilogram. We use a physiologically based pharmacokinetic (PBPK) workflow to assess the accuracy of linear scaling of plasma clearance (CLp) for hypothetical drugs with ranges of realistic parameter values in pediatric patients of different ages. The results are compared with 0.75 fixed allometric scaling (AS 0.75). Linear CLp scaling is accurate down to the age of 1 month for drugs undergoing glomerular filtration, except when these drugs are highly bound to alpha-1-acid glycoprotein (AGP)...
January 28, 2019: CPT: Pharmacometrics & Systems Pharmacology
Manuel Ibarra, Teresa Dalla Costa, Paula Schaiquevich, Rodrigo Cristofoletti, Ignacio Hernández González, Nicte S Fajardo-Robledo, Marcela Aragón Novoa, Marisín Pecchio, Ignacio Cortinez, Iñaki F Trocóniz, Elba M Romero-Tejeda
This report provides a brief description of the 2018 RedIF Congress that took place in Guadalajara (Mexico), on November 7-9. The meeting aimed to foster modeling & simulation approaches for drug development, regulatory sciences and clinical application in Latin America. Organizations that cosponsored the meeting were: University of Guadalajara, International Society of Pharmacometrics (ISoP), International Pharmaceutical Federation (FIP), Clinic of Chronic Diseases and Special Procedures (CECyPE), Zurich Pharma, Pharmet (Pharmometrica), Lixoft and ICON...
January 25, 2019: CPT: Pharmacometrics & Systems Pharmacology
Ronald Niebecker, Hugo Maas, Alexander Staab, Matthias Freiwald, Mats O Karlsson
Models were developed to characterize the relationship between afatinib exposure and diarrhoea and rash/acne adverse event (AEs) trajectories, and their predictive ability was assessed. Based on pooled data from seven phase II/III clinical studies including 998 patients, mixed-effects models for ordered categorical data were applied to describe daily AE severity. Clinical trial simulation (CTS) aided by trial execution models was used for internal and external model evaluation. The final exposure-safety model consisted of longitudinal logistic regression models with first-order Markov elements for both AEs...
January 25, 2019: CPT: Pharmacometrics & Systems Pharmacology
Willem J van den Brink, Robin Hartman, Dirk-Jan van den Berg, Gunnar Flik, Belén Gonzalez-Amoros, Nanda Koopman, Jeroen Elassais-Schaap, Piet Hein van der Graaf, Thomas Hankemeier, Elizabeth C M de Lange
A key challenge in the development of central nervous system drugs is the availability of drug target specific blood-based biomarkers. As a new approach, we applied cluster-based pharmacokinetic/pharmacodynamic (PK/PD) analysis in brain extracellular fluid (brainECF ) and plasma simultaneously after 0, 0.17, and 0.86 mg/kg of the dopamine D2/3 agonist quinpirole (QP) in rats. We measured 76 biogenic amines in plasma and brainECF after single and 8-day administration, to be analyzed by cluster-based PK/PD analysis...
January 24, 2019: CPT: Pharmacometrics & Systems Pharmacology
Lourdes Cucurull-Sanchez, Michael J Chappell, Vijayalakshmi Chelliah, S Y Amy Cheung, Gianne Derks, Mark Penney, Alex Phipps, Rahuman S Malik-Sheriff, Jon Timmis, Marcus J Tindall, Piet H van der Graaf, Paolo Vicini, James W T Yates
The lack of standardisation in the way that QSP models are developed, tested and documented hinders their reproducibility, re-usability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial and regulatory frameworks. This paper presents a minimum set of recommendations from the UK QSP Network in order to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment. This article is protected by copyright...
January 22, 2019: CPT: Pharmacometrics & Systems Pharmacology
Kosuke Doki, Sibylle Neuhoff, Amin Rostami-Hodjegan, Masato Homma
Plasma concentrations of dabigatran (DAB), an active principle of prodrug dabigatran etexilate (DABE), are increased by renal impairment (RI) or co-administration of a P-glycoprotein (P-gp) inhibitor. Since the combined effects of drug-drug interactions (DDIs) and RI have not been evaluated by means of clinical studies, the decision of DABE dosing for RI patients receiving P-gp inhibitors is empirical at its best. We conducted virtual DDI studies between DABE and the P-gp inhibitor verapamil in RI populations using physiologically-based pharmacokinetic (PBPK) modeling...
January 18, 2019: CPT: Pharmacometrics & Systems Pharmacology
Aksana K Jones, Ahmed Hamed Salem, Kevin J Freise
The use of model-based drug development (MBDD) has been demonstrated to improve the efficiency of clinical trial design. However, MBDD complexity can limit its use, particularly early in clinical development. In this tutorial a simple and generalizable exposure-response analysis approach to determine the power for dose ranging studies is presented and described. We identified situations where higher power and sample size reduction is achieved by utilizing the exposure-response powering methodology compared to conventional power calculations...
January 18, 2019: CPT: Pharmacometrics & Systems Pharmacology
Roberto Gomeni, Lanyan Lucy Fang, Françoise Bressolle-Gomeni, Thomas J Spencer, Stephen V Faraone, Andrew Babiskin
The net benefit of a treatment can be defined by the relationship between clinical improvement and risk of adverse events: the benefit-risk ratio. The optimization of the benefit-risk ratio can be achieved by identifying the most adequate dose (and/or dosage regimen) jointly with the best performing in-vivo release properties of a drug. A general in-silico tool is presented for identifying the dose, the in-vitro and the in-vivo release properties that maximize the benefit-risk ratio using convolution-based modeling, an exposure-response model, and a surface response analysis...
January 18, 2019: CPT: Pharmacometrics & Systems Pharmacology
Rajanikanth Madabushi, Yaning Wang, Issam Zineh
Model-informed drug development (MIDD) has recently garnered much attention as a potential enabler of efficient drug development. In their recent article, Jain et al. describe barriers and opportunities to achieve the full potential of MIDD. The authors point out well-accepted and promising new applications of MIDD in drug development and regulatory evaluation. There is arguably a greater appreciation of the benefits and promise of MIDD now more than ever. As noted by the authors, this is reflected by the inclusion of MIDD-related performance goals in the latest congressionally reauthorized Prescription Drug User Fee Act (PDUFA) VI...
December 23, 2018: CPT: Pharmacometrics & Systems Pharmacology
Lucy Hutchinson, Bernhard Steiert, Antoine Soubret, Jonathan Wagg, Alex Phipps, Richard Peck, Jean-Eric Charoin, Benjamin Ribba
Recent advances in machine learning (ML) have led to enthusiasm about its use throughout the biopharmaceutical industry. ML methods can be applied to a wide range of problems and have the potential to revolutionize aspects of drug development. The incorporation of ML in modeling and simulation (M+S) has been eagerly anticipated and in this perspective we highlight examples where ML and M+S approaches can be integrated as complementary parts of a clinical pharmacology workflow. This article is protected by copyright...
December 14, 2018: CPT: Pharmacometrics & Systems Pharmacology
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