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      Evaluation of model‐based bioequivalence approach for single sample pharmacokinetic studies

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          Abstract

          In a traditional pharmacokinetic (PK) bioequivalence (BE) study, a two‐way crossover study is conducted, PK parameters (namely the area under the time‐concentration curve [AUC] and the maximal concentration [ C max ]) are obtained by noncompartmental analysis (NCA), and the BE analysis is performed using the two one‐sided test (TOST) method. For ophthalmic drugs, however, only one sample of aqueous humor, in one eye, per eye can be obtained in each patient, which precludes the traditional BE analysis. To circumvent this issue, the U.S. Food and Drug Administration (FDA) has proposed an approach coupling NCA with either parametric or nonparametric bootstrap (NCA bootstrap). The model‐based TOST (MB‐TOST) has previously been proposed and evaluated successfully for various settings of sparse PK BE studies. In this paper, we evaluate, via simulations, MB‐TOST in the specific setting of single sample PK BE study and compare its performance to NCA bootstrap. We performed BE study simulations using a published PK model and parameter values and evaluated multiple scenarios, including study design (parallel or crossover), sampling times (5 or 10 spread across the dosing interval), and geometric mean ratio (of 0.8, 0.9, 1, and 1.25). Using the simulated structural PK model, MB‐TOST performed similarly to NCA bootstrap for AUC. For C max , the latter tended to be conservative and less powerful. Our research suggests that MB‐TOST may be considered as an alternative BE approach for single sample PK studies, provided that the PK model is correctly specified and the test drug has the same structural model as the reference drug.

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          A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability.

          The statistical test of hypothesis of no difference between the average bioavailabilities of two drug formulations, usually supplemented by an assessment of what the power of the statistical test would have been if the true averages had been inequivalent, continues to be used in the statistical analysis of bioavailability/bioequivalence studies. In the present article, this Power Approach (which in practice usually consists of testing the hypothesis of no difference at level 0.05 and requiring an estimated power of 0.80) is compared to another statistical approach, the Two One-Sided Tests Procedure, which leads to the same conclusion as the approach proposed by Westlake based on the usual (shortest) 1-2 alpha confidence interval for the true average difference. It is found that for the specific choice of alpha = 0.05 as the nominal level of the one-sided tests, the two one-sided tests procedure has uniformly superior properties to the power approach in most cases. The only cases where the power approach has superior properties when the true averages are equivalent correspond to cases where the chance of concluding equivalence with the power approach when the true averages are not equivalent exceeds 0.05. With appropriate choice of the nominal level of significance of the one-sided tests, the two one-sided tests procedure always has uniformly superior properties to the power approach. The two one-sided tests procedure is compared to the procedure proposed by Hauck and Anderson.
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            Nonlinear mixed effects models for repeated measures data.

            We propose a general, nonlinear mixed effects model for repeated measures data and define estimators for its parameters. The proposed estimators are a natural combination of least squares estimators for nonlinear fixed effects models and maximum likelihood (or restricted maximum likelihood) estimators for linear mixed effects models. We implement Newton-Raphson estimation using previously developed computational methods for nonlinear fixed effects models and for linear mixed effects models. Two examples are presented and the connections between this work and recent work on generalized linear mixed effects models are discussed.
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              Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose

              Several software tools are available that facilitate the use of the NONMEM software and extend its functionality. This tutorial shows how three commonly used and freely available tools, Pirana, PsN, and Xpose, form a tightly integrated workbench for modeling and simulation with NONMEM. During the tutorial, we provide some guidance on what diagnostics we consider most useful in pharmacokinetic model development and how to construct them using these tools.

                Author and article information

                Contributors
                julie.bertrand@inserm.fr
                Journal
                CPT Pharmacometrics Syst Pharmacol
                CPT Pharmacometrics Syst Pharmacol
                10.1002/(ISSN)2163-8306
                PSP4
                CPT: Pharmacometrics & Systems Pharmacology
                John Wiley and Sons Inc. (Hoboken )
                2163-8306
                27 April 2023
                July 2023
                : 12
                : 7 ( doiID: 10.1002/psp4.v12.7 )
                : 904-915
                Affiliations
                [ 1 ] INSERM, IAME Université de Paris Paris France
                [ 2 ] Département Epidémiologie Biostatistiques et Recherche Clinique AP‐HP, Hôpital Bichat Paris France
                [ 3 ] METRICS: Evaluation of Health Technologies and Medical Practices University of Lille, CHU Lille, ULR 2694 Lille France
                [ 4 ] Division of Quantitative Methods and Modeling, Office of Research Standards, Office of Generic Drugs Center for Drug Evaluation and Research, Food and Drug Administration Silver Spring Maryland 20993 USA
                [ 5 ] Office of Biostatistics, Office of Translational Sciences Center for Drug Evaluation and Research, U.S. Food and Drug Administration Silver Spring Maryland 20993 USA
                Author notes
                [*] [* ] Correspondence

                Julie Bertrand, INSERM, IAME, Université de Paris, Paris F‐75018, France.

                Email: julie.bertrand@ 123456inserm.fr

                Author information
                https://orcid.org/0000-0002-2304-9910
                https://orcid.org/0000-0002-4278-2974
                https://orcid.org/0000-0001-7537-9615
                https://orcid.org/0000-0002-0257-9082
                https://orcid.org/0000-0002-7045-1275
                https://orcid.org/0000-0002-6568-1041
                Article
                PSP412960 PSP-2022-0118
                10.1002/psp4.12960
                10349197
                37114321
                771f2bf9-6564-4b67-b757-9e8897c2b4dc
                © 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 02 March 2023
                : 08 June 2022
                : 03 March 2023
                Page count
                Figures: 3, Tables: 2, Pages: 12, Words: 6719
                Categories
                Article
                Research
                Articles
                Custom metadata
                2.0
                July 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.2 mode:remove_FC converted:15.07.2023

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