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10 results on '"Lentz, Frederike"'

2. Scaling Dose-Exposure-Response from Adults to Children

Author

Rusten, Ine Skottheim, Nordmark, Anna, Cole, Susan, Standing, Joseph F., Hietala, Sofia Friberg, Zhao, Wei, Gigante, Valeria, Hamberg, Anna Karin, Pons, Gérard, Garrido, María Jesús, Taminiau, Johannes, Benda, Norbert, Lentz, Frederike, Tshinanu, Flora Musuamba, Thomson, Andrew, Tomasi, Paolo, Ollivier, Cecile, Herold, Ralf, Manolis, Efthymios, Mahmood, Iftekhar, editor, and Burckart, Gilbert, editor

Published
2016
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3. Recent advances in methodology for clinical trials in small populations: the InSPiRe project

Author

Friede, Tim, Posch, Martin, Zohar, Sarah, Alberti, Corinne, Benda, Norbert, Comets, Emmanuelle, Day, Simon, Dmitrienko, Alex, Graf, Alexandra, Günhan, Burak Kürsad, Hee, Siew Wan, Lentz, Frederike, Madan, Jason, Miller, Frank, Ondra, Thomas, Pearce, Michael, Röver, Christian, Toumazi, Artemis, Unkel, Steffen, Ursino, Moreno, Wassmer, Gernot, and Stallard, Nigel

Published
2018
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5. A dose finding design for seizure reduction in neonates

Author

Ursino, Moreno, Yuan, Ying, Alberti, Corinne, Comets, Emmanuelle, Favrais, Geraldine, Friede, Tim, Lentz, Frederike, Stallard, Nigel, Zohar, Sarah, Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), The University of Texas M.D. Anderson Cancer Center [Houston], Paris Diderot - Paris 7 - UFR Lettres, Arts, Langues (UPD7 UFR LAC), Université Paris Diderot - Paris 7 (UPD7), Institut National de la Santé et de la Recherche Médicale (INSERM), AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), University Medical Center Göttingen (UMG), Federal Institute of Drugs and Medical Devices [Bonn], University of Warwick [Coventry], École pratique des hautes études (EPHE), and Zohar, Sarah

Subjects
[SDV] Life Sciences [q-bio], [STAT]Statistics [stat], Time to event, Efficacy, Newborns, Phase I–II, Toxicity constraints, RJ, [SDV]Life Sciences [q-bio], [STAT] Statistics [stat]
Abstract

International audience; Clinical trials in vulnerable populations are extremely difficult to conduct. A sequential phase I–II trial aimed at finding the appropriate dose of levetiracetam for treating neonatal seizures was planned with a maximum sample size of 50 newborns. Three primary outcomes are considered: efficacy and two types of toxicity that occur at the same time but are measured at different time points. In the case of failure, physicians could add a second agent as a rescue medication.The primary outcomes were modelled via a logistic model for efficacy and a weighted likelihood with pseudo-outcomes for the two toxicities taking into account the dependences under Bayesian inference. Simulations were conducted to assess the design properties.

Published
2018

6. Dose-finding methods for Phase I clinical trials using pharmacokinetics in small populations

Author

Ursino, Moreno, Zohar, Sarah, Lentz, Frederike, Alberti, Corinne, Friede, Tim, Stallard, Nigel, Comets, Emmanuelle, Centre de Recherche des Cordeliers (CRC), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Epidémiologie Clinique et Evaluation Economique Appliquées aux Populations Vulnérables (ECEVE (U1123 / UMR_S_1123)), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), University Medical Center Göttingen (UMG), Statistics and Epidemiology Unit [Coventry, UK] (Division of Health Sciences), University of Warwick [Coventry]-Warwick Medical School, University of Warwick [Coventry], Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Seventh Framework Programme. Grant Number: FP HEALTH 2013-602144, European Project: 602144,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,INSPIRE(2014), Université Paris Diderot - Paris 7 (UPD7)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Warwick Medical School, University of Warwick [Coventry]-University of Warwick [Coventry], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC), Université Paris Diderot - Paris 7 (UPD7)-École pratique des hautes études (EPHE)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital universitaire Robert-Debré [Paris]-Université Paris Diderot - Paris 7 (UPD7), and University Medical Center Göttingen

Subjects
Population Density, RM, Dose‐finding, Clinical Trials, Phase I as Topic, Maximum Tolerated Dose, [SDV]Life Sciences [q-bio], Dose-finding, Dose‐toxicity relationship, Research Design, Dose-toxicity relationship, Phase I clinical trials, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Humans, Computer Simulation, Pharmacokinetics, General, Research Paper
Abstract

International audience; The aim of phase I clinical trials is to obtain reliable information on safety, tolerability, pharmacokinetics (PK), and mechanism of action of drugs with the objective of determining the maximum tolerated dose (MTD). In most phase I studies, dose-finding and PK analysis are done separately and no attempt is made to combine them during dose allocation. In cases such as rare diseases, paediatrics, and studies in a biomarker-defined subgroup of a defined population, the available population size will limit the number of possible clinical trials that can be conducted. Combining dose-finding and PK analyses to allow better estimation of the dose-toxicity curve should then be considered. In this work, we propose, study, and compare methods to incorporate PK measures in the dose allocation process during a phase I clinical trial. These methods do this in different ways, including using PK observations as a covariate, as the dependent variable or in a hierarchical model. We conducted a large simulation study that showed that adding PK measurements as a covariate only does not improve the efficiency of dose-finding trials either in terms of the number of observed dose limiting toxicities or the probability of correct dose selection. However, incorporating PK measures does allow better estimation of the dose-toxicity curve while maintaining the performance in terms of MTD selection compared to dose-finding designs that do not incorporate PK information. In conclusion, using PK information in the dose allocation process enriches the knowledge of the dose-toxicity relationship, facilitating better dose recommendation for subsequent trials.

Published
2017

7. Directions for new developments on statistical design and analysis of small population group trials

Author

Hilgers, Ralf-Dieter, Roes, Kit, Stallard, Nigel, IDeAl, Asterix, Alberti, Corinne, Van Baal, Caroline, Benda, Norbert, Biesheuvel, Egbert, Burmann, CarlFredrik, Bogdan, Malgorzata, Comets, Emmanuelle, Day, Simon, Dette, Holger, Dmitrienko, Alex, Friede, Tim, Graf, Alexandra, Karlsson, Mats, Koch, Armin, König, Franz, Van Der Lee, JohannaH., Lentz, Frederike, Madan, Jason, Male, Christoph, Mentré, France, Miller, Frank, Molenberghs, Geert, Neuenschwander, Beat, Posch, Martin, Oosterwijk, Cor, Röver, Christian, Senn, Stephen, Torres, Ferran, Zohar, Sarah, RWTH Aachen University, University Medical Center [Utrecht], University of Warwick [Coventry], IDeAl, Asterix and InSPiRe project groups: Corinne Alberti, Caroline van Baal, Norbert Benda, Egbert Biesheuvel, CarlFredrik Burmann, Malgorzata Bogdan, Emmanuelle Comets, Simon Day, Holger Dette, Alex Dmitrienko, Tim Friede, Alexandra Graf, Mats Karlsson, Armin Koch, Franz König, JohannaH van der Lee, Frederike Lentz, Jason Madan, Christoph Male, France Mentré, Frank Miller, Geert Molenberghs, Beat Neuenschwander, Martin Posch, Cor Oosterwijk, Christian Röver, Stephen Senn, Ferran Torres, Sarah Zohar, Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH), and Duchange, Nathalie

Subjects
Statistical methods, Computer science, [SDV]Life Sciences [q-bio], Population, Pharmacology, Analysis of clinical trials, Poor adherence, 03 medical and health sciences, 0302 clinical medicine, Rare Diseases, Population Groups, Statistics, Humans, Genetics(clinical), Pharmacology (medical), 030212 general & internal medicine, education, Position Statement, Genetics (clinical), Medicine(all), education.field_of_study, Clinical Trials as Topic, Statistical design, Small population size, Small population clinical trials, General Medicine, Standard methods, R1, 3. Good health, Statistical analysis, Rare disease, EMA/CHMP Guideline on clinical trials in small populations, [SDV] Life Sciences [q-bio], Clinical trial, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Sample size determination, Data Interpretation, Statistical, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 030217 neurology & neurosurgery
Abstract

Orphanet journal of rare diseases : OJRD 11(1), 78 (2016). doi:10.1186/s13023-016-0464-5, Published by BioMed Central, London

Published
2016

9. Commentary on the MID3 Good Practices Paper.

Author

Manolis, Efthymios, Brogren, Jacob, Cole, Susan, Hay, Justin L., Nordmark, Anna, Karlsson, Kristin E., Lentz, Frederike, Benda, Norbert, Wangorsch, Gaby, Pons, Gerard, Zhao, Wei, Gigante, Valeria, Serone, Francesca, Standing, Joseph F., Dokoumetzidis, Aris, Vakkilainen, Juha, van den Heuvel, Michiel, Mangas Sanjuan, Victor, Taminiau, Johannes, and Kerwash, Essam

Subjects
DRUG development, MEDICAL practice, SIMULATION methods & models
Abstract

During the last 10 years the European Medicines Agency (EMA) organized a number of workshops on modeling and simulation, working towards greater integration of modeling and simulation (M&S) in the development and regulatory assessment of medicines. In the 2011 EMA - European Federation of Pharmaceutical Industries and Associations (EFPIA) Workshop on Modelling and Simulation, European regulators agreed to the necessity to build expertise to be able to review M&S data provided by companies in their dossier. This led to the establishment of the EMA Modelling and Simulation Working Group (MSWG). Also, there was agreement reached on the need for harmonization on good M&S practices and for continuing dialog across all parties. The MSWG acknowledges the initiative of the EFPIA Model-Informed Drug Discovery and Development (MID3) group in promoting greater consistency in practice, application, and documentation of M&S and considers the paper is an important contribution towards achieving this objective. [ABSTRACT FROM AUTHOR]

Published
2017
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10. Dose-finding methods for Phase I clinical trials using pharmacokinetics in small populations.

Author

Ursino M, Zohar S, Lentz F, Alberti C, Friede T, Stallard N, and Comets E

Subjects
Computer Simulation, Humans, Population Density, Clinical Trials, Phase I as Topic methods, Maximum Tolerated Dose, Pharmacokinetics, Research Design
Abstract

The aim of phase I clinical trials is to obtain reliable information on safety, tolerability, pharmacokinetics (PK), and mechanism of action of drugs with the objective of determining the maximum tolerated dose (MTD). In most phase I studies, dose-finding and PK analysis are done separately and no attempt is made to combine them during dose allocation. In cases such as rare diseases, paediatrics, and studies in a biomarker-defined subgroup of a defined population, the available population size will limit the number of possible clinical trials that can be conducted. Combining dose-finding and PK analyses to allow better estimation of the dose-toxicity curve should then be considered. In this work, we propose, study, and compare methods to incorporate PK measures in the dose allocation process during a phase I clinical trial. These methods do this in different ways, including using PK observations as a covariate, as the dependent variable or in a hierarchical model. We conducted a large simulation study that showed that adding PK measurements as a covariate only does not improve the efficiency of dose-finding trials either in terms of the number of observed dose limiting toxicities or the probability of correct dose selection. However, incorporating PK measures does allow better estimation of the dose-toxicity curve while maintaining the performance in terms of MTD selection compared to dose-finding designs that do not incorporate PK information. In conclusion, using PK information in the dose allocation process enriches the knowledge of the dose-toxicity relationship, facilitating better dose recommendation for subsequent trials., (© 2017 The Authors. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Published
2017
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