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Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches
The coronavirus disease 2019 (COVID‐19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID‐19 public health emergency, any protocol change...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111087/ https://www.ncbi.nlm.nih.gov/pubmed/35411692 http://dx.doi.org/10.1002/psp4.12795 |
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author | Gong, Yuqing Feng, Kairui Zhang, Peijue Lee, Jieon Pan, Yuzhuo Zhang, Zhen Ni, Zhanglin Bai, Tao Yoon, Miyoung Li, Bing Kim, Carol Y. Fang, Lanyan Zhao, Liang |
author_facet | Gong, Yuqing Feng, Kairui Zhang, Peijue Lee, Jieon Pan, Yuzhuo Zhang, Zhen Ni, Zhanglin Bai, Tao Yoon, Miyoung Li, Bing Kim, Carol Y. Fang, Lanyan Zhao, Liang |
author_sort | Gong, Yuqing |
collection | PubMed |
description | The coronavirus disease 2019 (COVID‐19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID‐19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID‐19‐interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID‐19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID‐19‐interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a “batch” effect to the mixed effects model may be used when a significant “batch” effect was found in interrupted four‐way crossover studies. However, such alternative method is not applicable for interrupted two‐way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19‐interrupted studies could be case‐specific. |
format | Online Article Text |
id | pubmed-9111087 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91110872022-05-17 Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches Gong, Yuqing Feng, Kairui Zhang, Peijue Lee, Jieon Pan, Yuzhuo Zhang, Zhen Ni, Zhanglin Bai, Tao Yoon, Miyoung Li, Bing Kim, Carol Y. Fang, Lanyan Zhao, Liang CPT Pharmacometrics Syst Pharmacol Research The coronavirus disease 2019 (COVID‐19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID‐19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID‐19‐interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID‐19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID‐19‐interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a “batch” effect to the mixed effects model may be used when a significant “batch” effect was found in interrupted four‐way crossover studies. However, such alternative method is not applicable for interrupted two‐way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19‐interrupted studies could be case‐specific. John Wiley and Sons Inc. 2022-04-20 2022-07 /pmc/articles/PMC9111087/ /pubmed/35411692 http://dx.doi.org/10.1002/psp4.12795 Text en Published 2022. This article is a U.S. Government work and is in the public domain in the USA. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Gong, Yuqing Feng, Kairui Zhang, Peijue Lee, Jieon Pan, Yuzhuo Zhang, Zhen Ni, Zhanglin Bai, Tao Yoon, Miyoung Li, Bing Kim, Carol Y. Fang, Lanyan Zhao, Liang Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches |
title | Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches |
title_full | Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches |
title_fullStr | Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches |
title_full_unstemmed | Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches |
title_short | Quantitative methods and modeling to assess COVID‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches |
title_sort | quantitative methods and modeling to assess covid‐19‐interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111087/ https://www.ncbi.nlm.nih.gov/pubmed/35411692 http://dx.doi.org/10.1002/psp4.12795 |
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