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Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations
The success of antibodies targeting Programmed cell death protein 1 (PD-1) and its ligand L1 (PD-L1) in cancer treatment and the need for improving response rates has led to an increased demand for the development of combination therapies with anti-PD-1/PD-L1 blockers as a backbone. As more and more...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485537/ https://www.ncbi.nlm.nih.gov/pubmed/34598713 http://dx.doi.org/10.1186/s13046-021-02111-5 |
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author | Lemaire, Vincent Shemesh, Colby S. Rotte, Anand |
author_facet | Lemaire, Vincent Shemesh, Colby S. Rotte, Anand |
author_sort | Lemaire, Vincent |
collection | PubMed |
description | The success of antibodies targeting Programmed cell death protein 1 (PD-1) and its ligand L1 (PD-L1) in cancer treatment and the need for improving response rates has led to an increased demand for the development of combination therapies with anti-PD-1/PD-L1 blockers as a backbone. As more and more drugs with translational potential are identified, the number of clinical trials evaluating combinations has increased considerably and the demand to prioritize combinations having potential for success over the ones that are unlikely to be successful is rising. This review aims to address the unmet need to prioritize cancer immunotherapy combinations through comprehensive search of potential drugs and ranking them based on their mechanism of action, clinical efficacy and safety. As lung cancer is one of the most frequently studied cancer types, combinations that showed potential for the treatment of lung cancer were prioritized. A literature search was performed to identify drugs with potential in combination with PD-1/PD-L1 blockers and the drugs were ranked based on their mechanism of action and known clinical efficacy. Nineteen drugs or drug classes were identified from an internal list of lead molecules and were scored for their clinical potential. Efficacy and safety data from pivotal studies was summarized for the selected drugs. Further, overlap of mechanisms of action and adverse events was visualized using a heat map illustration to help screen drugs for combinations. The quantitative scoring methodology provided in this review could serve as a template for preliminary ranking of novel combinations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-021-02111-5. |
format | Online Article Text |
id | pubmed-8485537 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84855372021-10-04 Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations Lemaire, Vincent Shemesh, Colby S. Rotte, Anand J Exp Clin Cancer Res Review The success of antibodies targeting Programmed cell death protein 1 (PD-1) and its ligand L1 (PD-L1) in cancer treatment and the need for improving response rates has led to an increased demand for the development of combination therapies with anti-PD-1/PD-L1 blockers as a backbone. As more and more drugs with translational potential are identified, the number of clinical trials evaluating combinations has increased considerably and the demand to prioritize combinations having potential for success over the ones that are unlikely to be successful is rising. This review aims to address the unmet need to prioritize cancer immunotherapy combinations through comprehensive search of potential drugs and ranking them based on their mechanism of action, clinical efficacy and safety. As lung cancer is one of the most frequently studied cancer types, combinations that showed potential for the treatment of lung cancer were prioritized. A literature search was performed to identify drugs with potential in combination with PD-1/PD-L1 blockers and the drugs were ranked based on their mechanism of action and known clinical efficacy. Nineteen drugs or drug classes were identified from an internal list of lead molecules and were scored for their clinical potential. Efficacy and safety data from pivotal studies was summarized for the selected drugs. Further, overlap of mechanisms of action and adverse events was visualized using a heat map illustration to help screen drugs for combinations. The quantitative scoring methodology provided in this review could serve as a template for preliminary ranking of novel combinations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13046-021-02111-5. BioMed Central 2021-10-01 /pmc/articles/PMC8485537/ /pubmed/34598713 http://dx.doi.org/10.1186/s13046-021-02111-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Lemaire, Vincent Shemesh, Colby S. Rotte, Anand Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations |
title | Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations |
title_full | Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations |
title_fullStr | Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations |
title_full_unstemmed | Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations |
title_short | Pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations |
title_sort | pharmacology-based ranking of anti-cancer drugs to guide clinical development of cancer immunotherapy combinations |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485537/ https://www.ncbi.nlm.nih.gov/pubmed/34598713 http://dx.doi.org/10.1186/s13046-021-02111-5 |
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