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Musuamba FT, Manolis E, Holford N, Cheung S, Friberg LE, Ogungbenro K, Posch M, Yates J, Berry S, Thomas N, Corriol-Rohou S, Bornkamp B, Bretz F, Hooker AC, Van der Graaf PH, Standing JF, Hay J, Cole S, Gigante V, Karlsson K, Dumortier T, Benda N, Serone F, Das S, Brochot A, Ehmann F, Hemmings R, Rusten IS. Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4-5 December 2014). CPT Pharmacometrics Syst Pharmacol 2017; 6:418-429. [PMID: 28722322 PMCID: PMC5529745 DOI: 10.1002/psp4.12196] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 03/27/2017] [Accepted: 03/27/2017] [Indexed: 02/05/2023]
Abstract
Inadequate dose selection for confirmatory trials is currently still one of the most challenging issues in drug development, as illustrated by high rates of late‐stage attritions in clinical development and postmarketing commitments required by regulatory institutions. In an effort to shift the current paradigm in dose and regimen selection and highlight the availability and usefulness of well‐established and regulatory‐acceptable methods, the European Medicines Agency (EMA) in collaboration with the European Federation of Pharmaceutical Industries Association (EFPIA) hosted a multistakeholder workshop on dose finding (London 4–5 December 2014). Some methodologies that could constitute a toolkit for drug developers and regulators were presented. These methods are described in the present report: they include five advanced methods for data analysis (empirical regression models, pharmacometrics models, quantitative systems pharmacology models, MCP‐Mod, and model averaging) and three methods for study design optimization (Fisher information matrix (FIM)‐based methods, clinical trial simulations, and adaptive studies). Pairwise comparisons were also discussed during the workshop; however, mostly for historical reasons. This paper discusses the added value and limitations of these methods as well as challenges for their implementation. Some applications in different therapeutic areas are also summarized, in line with the discussions at the workshop. There was agreement at the workshop on the fact that selection of dose for phase III is an estimation problem and should not be addressed via hypothesis testing. Dose selection for phase III trials should be informed by well‐designed dose‐finding studies; however, the specific choice of method(s) will depend on several aspects and it is not possible to recommend a generalized decision tree. There are many valuable methods available, the methods are not mutually exclusive, and they should be used in conjunction to ensure a scientifically rigorous understanding of the dosing rationale.
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Affiliation(s)
- F T Musuamba
- EMA Modelling and Simulation Working Group, London, UK.,Federal Agency for Medicines and Health Products, Brussels, Belgium.,UMR850 INSERM, Université de Limoges, Limoges, France
| | - E Manolis
- EMA Modelling and Simulation Working Group, London, UK.,European Medicines Agency, London, UK
| | - N Holford
- Department of Pharmacology & Clinical Pharmacology, University of Auckland, Auckland, New Zealand
| | | | | | | | - M Posch
- Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | | | - S Berry
- Berry consultants, Austin, Texas, USA
| | | | | | | | - F Bretz
- Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.,Novartis, London, UK
| | | | - P H Van der Graaf
- Leiden Academic Centre for Drug Research, Leiden, The Netherlands.,Certara QSP, Canterbury, UK
| | - J F Standing
- EMA Modelling and Simulation Working Group, London, UK.,University College London, London, UK
| | - J Hay
- EMA Modelling and Simulation Working Group, London, UK.,Medicines and Healthcare Products Regulatory Agency, London, UK
| | - S Cole
- EMA Modelling and Simulation Working Group, London, UK.,Medicines and Healthcare Products Regulatory Agency, London, UK
| | - V Gigante
- EMA Modelling and Simulation Working Group, London, UK.,Agenzia Italiana del Farmaco, Roma, Italy
| | - K Karlsson
- EMA Modelling and Simulation Working Group, London, UK.,Medical Products Agency, Uppsala, Sweden
| | | | - N Benda
- EMA Modelling and Simulation Working Group, London, UK.,Bundesinstitut für Arzneimittel und Medizinprodukte, Bonn, Germany
| | - F Serone
- EMA Modelling and Simulation Working Group, London, UK.,Agenzia Italiana del Farmaco, Roma, Italy
| | - S Das
- AstraZeneca UK Limited, London, UK
| | | | - F Ehmann
- European Medicines Agency, London, UK
| | - R Hemmings
- Medicines and Healthcare Products Regulatory Agency, London, UK
| | - I Skottheim Rusten
- EMA Modelling and Simulation Working Group, London, UK.,Norvegian Medicines Agency, Oslo, Norway
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Nguyen THT, Mouksassi MS, Holford N, Al-Huniti N, Freedman I, Hooker AC, John J, Karlsson MO, Mould DR, Pérez Ruixo JJ, Plan EL, Savic R, van Hasselt JGC, Weber B, Zhou C, Comets E, Mentré F. Model Evaluation of Continuous Data Pharmacometric Models: Metrics and Graphics. CPT Pharmacometrics Syst Pharmacol 2017; 6:87-109. [PMID: 27884052 PMCID: PMC5321813 DOI: 10.1002/psp4.12161] [Citation(s) in RCA: 228] [Impact Index Per Article: 32.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Revised: 10/10/2016] [Accepted: 11/09/2016] [Indexed: 12/17/2022]
Abstract
This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used.
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Affiliation(s)
- T H T Nguyen
- INSERM, IAME, UMR 1137, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | | | - N Holford
- Department of Pharmacology and Clinical Pharmacology, University of Auckland, Auckland, New Zealand
| | - N Al-Huniti
- Quantitative Clinical Pharmacology, AstraZeneca, Waltham, Massachusetts, USA
| | - I Freedman
- Dr Immanuel Freedman Inc., Harleysville, Pennsylvania, USA
| | - A C Hooker
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - J John
- Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Washington, DC, USA
| | - M O Karlsson
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - D R Mould
- Projections Research Inc., Phoenixville, Pennsylvania, USA
| | - J J Pérez Ruixo
- The Janssen Pharmaceutical Companies of Johnson & Johnson, Belgium
| | | | - R Savic
- Department of Bioengineering and Therapeutic Sciences, University of California - San Francisco, San Francisco, California, USA
| | - J G C van Hasselt
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - B Weber
- Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, USA
| | - C Zhou
- Genentech, San Francisco, California, USA
| | - E Comets
- INSERM, IAME, UMR 1137, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.,INSERM CIC 1414, Rennes, France, University Rennes-1, Rennes, France
| | - F Mentré
- INSERM, IAME, UMR 1137, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
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Scheinman MM, Remedios P, Cheitlin MD, Peters RW, Holford N, Desai J, Abbott JA. Effects of antiarrhythmic drugs on atrioventricular conduction in patients with acute myocardial infarction. Circulation 1980; 62:20-8. [PMID: 7379282 DOI: 10.1161/01.cir.62.1.20] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Three hundred fifty-eight of 429 (83%) consecutive patients with acute myocardial infarction (MI) and a normal PR interval received various antiarrhythmic drugs (AD), including lidocaine and/or procainamide, quinidine, digoxin, propranolol or disopyramide. There was no significant difference in the incidence of progression to any degree of atrioventricular (AV) block or to higher degrees of AV block (Mobitz II or third-degree AV block) between those treated and not treated with AD: 38 of 358 (11%) and six of 358 (1.7%) with AD vs 11 of 71 (15%) and two of 71 (2.8%) in the untreated group, respectively. Similarly, there was no significant difference in progression between treated and untreated patients with anterior MI, 14 of 144 (10%) vs five of 32 (16%); inferior MI, 21 of 111 (19%) vs five of 26 (19%), or subendocardial MI, three of 103 (3%) vs one of 12 (8%). Bundle branch block (BBB) (without AV block) was initially present in 89 of 249 (21%). The incidence of AV block (seven of 24, 30%) was higher in treated patients with newly acquired BBB (27 patients) than in the untreated patients (none of three, p less than 0.05). The commonly used ADs did not adversely affect AV conduction in patients with acute MI with narrow QRS and either normal, first-degree, or Mobitz I AV block. Moreover, no subset of patients grouped by infarct location, specific AD used, or BBB (except perhaps for those with newly acquired BBB) appeared to be at risk of development of AV block during AD therapy.
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