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Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities
Model‐informed drug development (MIDD) approaches have rapidly advanced in drug development in recent years. Additionally, the Prescription Drug User Fee Act (PDUFA) VI has specific commitments to further enhance MIDD. Tumor growth dynamic (TGD) modeling, as one of the commonly utilized MIDD approac...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7438808/ https://www.ncbi.nlm.nih.gov/pubmed/32589767 http://dx.doi.org/10.1002/psp4.12542 |
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author | Al‐Huniti, Nidal Feng, Yan Yu, Jingyu (Jerry) Lu, Zheng Nagase, Mario Zhou, Diansong Sheng, Jennifer |
author_facet | Al‐Huniti, Nidal Feng, Yan Yu, Jingyu (Jerry) Lu, Zheng Nagase, Mario Zhou, Diansong Sheng, Jennifer |
author_sort | Al‐Huniti, Nidal |
collection | PubMed |
description | Model‐informed drug development (MIDD) approaches have rapidly advanced in drug development in recent years. Additionally, the Prescription Drug User Fee Act (PDUFA) VI has specific commitments to further enhance MIDD. Tumor growth dynamic (TGD) modeling, as one of the commonly utilized MIDD approaches in oncology, fulfills the purposes to accelerate the drug development, to support new drug and biologics license applications, and to guide the market access. Increasing knowledge of TGD modeling methodologies, encouraging applications in clinical setting for patients’ survival, and complementing assessment of regulatory review for submissions, together fueled promising potentials for imminent enhancement of TGD in oncology. This review is to comprehensively summarize the history of TGD, and present case examples of the recent advance of TGD modeling (mixture model and joint model), as well as the TGD impact on regulatory decisions, thus illustrating challenges and opportunities. Additionally, this review presents the future perspectives for TGD approach. |
format | Online Article Text |
id | pubmed-7438808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74388082020-08-21 Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities Al‐Huniti, Nidal Feng, Yan Yu, Jingyu (Jerry) Lu, Zheng Nagase, Mario Zhou, Diansong Sheng, Jennifer CPT Pharmacometrics Syst Pharmacol Reviews Model‐informed drug development (MIDD) approaches have rapidly advanced in drug development in recent years. Additionally, the Prescription Drug User Fee Act (PDUFA) VI has specific commitments to further enhance MIDD. Tumor growth dynamic (TGD) modeling, as one of the commonly utilized MIDD approaches in oncology, fulfills the purposes to accelerate the drug development, to support new drug and biologics license applications, and to guide the market access. Increasing knowledge of TGD modeling methodologies, encouraging applications in clinical setting for patients’ survival, and complementing assessment of regulatory review for submissions, together fueled promising potentials for imminent enhancement of TGD in oncology. This review is to comprehensively summarize the history of TGD, and present case examples of the recent advance of TGD modeling (mixture model and joint model), as well as the TGD impact on regulatory decisions, thus illustrating challenges and opportunities. Additionally, this review presents the future perspectives for TGD approach. John Wiley and Sons Inc. 2020-07-22 2020-08 /pmc/articles/PMC7438808/ /pubmed/32589767 http://dx.doi.org/10.1002/psp4.12542 Text en © 2020 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the http://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 | Reviews Al‐Huniti, Nidal Feng, Yan Yu, Jingyu (Jerry) Lu, Zheng Nagase, Mario Zhou, Diansong Sheng, Jennifer Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities |
title | Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities |
title_full | Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities |
title_fullStr | Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities |
title_full_unstemmed | Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities |
title_short | Tumor Growth Dynamic Modeling in Oncology Drug Development and Regulatory Approval: Past, Present, and Future Opportunities |
title_sort | tumor growth dynamic modeling in oncology drug development and regulatory approval: past, present, and future opportunities |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7438808/ https://www.ncbi.nlm.nih.gov/pubmed/32589767 http://dx.doi.org/10.1002/psp4.12542 |
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