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Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model

Objective: This study aimed to explore the factors affecting the bioequivalence of test and reference insulin preparations so as to provide a scientific basis for the consistency evaluation of the quality and efficacy of insulin biosimilars. Methods: A randomized, open, two-sequence, single-dose, cr...

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Autores principales: Shao, Huarui, Tao, Yi, Tang, Chengyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106704/
https://www.ncbi.nlm.nih.gov/pubmed/37077814
http://dx.doi.org/10.3389/fphar.2023.1143928
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author Shao, Huarui
Tao, Yi
Tang, Chengyong
author_facet Shao, Huarui
Tao, Yi
Tang, Chengyong
author_sort Shao, Huarui
collection PubMed
description Objective: This study aimed to explore the factors affecting the bioequivalence of test and reference insulin preparations so as to provide a scientific basis for the consistency evaluation of the quality and efficacy of insulin biosimilars. Methods: A randomized, open, two-sequence, single-dose, crossover design was used in this study. Subjects were randomly divided into TR or RT groups in equal proportion. The glucose infusion rate and blood glucose were measured by a 24-h glucose clamp test to evaluate the pharmacodynamic parameters of the preparation. The plasma insulin concentration was determined by liquid chromatography–mass spectrometry (LC-MS/MS) to evaluate pharmacokinetic parameters. WinNonlin 8.1 and SPSS 23.0 were applied for PK/PD parameter calculation and statistical analysis. The structural equation model (SEM) was constructed to analyze the influencing factors of bioequivalence by using Amos 24.0. Results: A total of 177 healthy male subjects aged 18–45 years were analyzed. Subjects were assigned to the equivalent group (N = 55) and the non-equivalent group (N = 122) by bioequivalence results, according to the EMA guideline. Univariate analysis showed statistical differences in albumin, creatinine, T(max), bioactive substance content, and adverse events between the two groups. In the structural equation model, adverse events (β = 0.342; p < 0.001) and bioactive substance content (β = −0.189; p = 0.007) had significant impacts on the bioequivalence of two preparations, and the bioactive substance content significantly affected adverse events (β = 0.200; p = 0.007). Conclusion: A multivariate statistical model was used to explore the influencing factors for the bioequivalence of two preparations. According to the result of the structural equation model, we proposed that adverse events and bioactive substance content should be optimized for consistency evaluation of the quality and efficacy of insulin biosimilars. Furthermore, bioequivalence trials of insulin biosimilars should strictly obey inclusion and exclusion criteria to ensure the consistency of subjects and avoid confounding factors affecting the equivalence evaluation.
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spelling pubmed-101067042023-04-18 Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model Shao, Huarui Tao, Yi Tang, Chengyong Front Pharmacol Pharmacology Objective: This study aimed to explore the factors affecting the bioequivalence of test and reference insulin preparations so as to provide a scientific basis for the consistency evaluation of the quality and efficacy of insulin biosimilars. Methods: A randomized, open, two-sequence, single-dose, crossover design was used in this study. Subjects were randomly divided into TR or RT groups in equal proportion. The glucose infusion rate and blood glucose were measured by a 24-h glucose clamp test to evaluate the pharmacodynamic parameters of the preparation. The plasma insulin concentration was determined by liquid chromatography–mass spectrometry (LC-MS/MS) to evaluate pharmacokinetic parameters. WinNonlin 8.1 and SPSS 23.0 were applied for PK/PD parameter calculation and statistical analysis. The structural equation model (SEM) was constructed to analyze the influencing factors of bioequivalence by using Amos 24.0. Results: A total of 177 healthy male subjects aged 18–45 years were analyzed. Subjects were assigned to the equivalent group (N = 55) and the non-equivalent group (N = 122) by bioequivalence results, according to the EMA guideline. Univariate analysis showed statistical differences in albumin, creatinine, T(max), bioactive substance content, and adverse events between the two groups. In the structural equation model, adverse events (β = 0.342; p < 0.001) and bioactive substance content (β = −0.189; p = 0.007) had significant impacts on the bioequivalence of two preparations, and the bioactive substance content significantly affected adverse events (β = 0.200; p = 0.007). Conclusion: A multivariate statistical model was used to explore the influencing factors for the bioequivalence of two preparations. According to the result of the structural equation model, we proposed that adverse events and bioactive substance content should be optimized for consistency evaluation of the quality and efficacy of insulin biosimilars. Furthermore, bioequivalence trials of insulin biosimilars should strictly obey inclusion and exclusion criteria to ensure the consistency of subjects and avoid confounding factors affecting the equivalence evaluation. Frontiers Media S.A. 2023-04-03 /pmc/articles/PMC10106704/ /pubmed/37077814 http://dx.doi.org/10.3389/fphar.2023.1143928 Text en Copyright © 2023 Shao, Tao and Tang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Shao, Huarui
Tao, Yi
Tang, Chengyong
Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model
title Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model
title_full Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model
title_fullStr Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model
title_full_unstemmed Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model
title_short Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model
title_sort factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106704/
https://www.ncbi.nlm.nih.gov/pubmed/37077814
http://dx.doi.org/10.3389/fphar.2023.1143928
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