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Structure and Optimization of Checkpoint Inhibitors
With the advent of checkpoint inhibitor treatment for various cancer types, the optimization of drug selection, pharmacokinetics and biomarker assays is an urgent and as yet unresolved dilemma for clinicians, pharmaceutical companies and researchers. Drugs which inhibit cytotoxic T-lymphocyte associ...
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Published in: | Cancers 2019-12, Vol.12 (1), p.38 |
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description | With the advent of checkpoint inhibitor treatment for various cancer types, the optimization of drug selection, pharmacokinetics and biomarker assays is an urgent and as yet unresolved dilemma for clinicians, pharmaceutical companies and researchers. Drugs which inhibit cytotoxic T-lymphocyte associated protein-4 (CTLA-4), such as ipilimumab and tremelimumab, programmed cell death protein-1 (PD-1), such as nivolumab and pembrolizumab, and programmed cell death ligand-1 (PD-L1), such as atezolizumab, durvalumab and avelumab, each appear to have varying pharmacokinetics and clinical activity in different cancer types. Each drug differs in terms of dosing, which becomes an issue when drug comparisons are attempted. Here, we examine the various checkpoint inhibitors currently used and in development. We discuss the antibodies and their protein targets, their pharmacokinetics as measured in various tumor types, and their binding affinities to their respective antigens. We also examine the various dosing regimens for these drugs and how they differ. Finally, we examine new developments and methods to optimize delivery and efficacy in the field of checkpoint inhibitors, including non-fucosylation, prodrug formations, bispecific antibodies, and newer small molecule and peptide checkpoint inhibitors. |
doi_str_mv | 10.3390/cancers12010038 |
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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 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Drugs which inhibit cytotoxic T-lymphocyte associated protein-4 (CTLA-4), such as ipilimumab and tremelimumab, programmed cell death protein-1 (PD-1), such as nivolumab and pembrolizumab, and programmed cell death ligand-1 (PD-L1), such as atezolizumab, durvalumab and avelumab, each appear to have varying pharmacokinetics and clinical activity in different cancer types. Each drug differs in terms of dosing, which becomes an issue when drug comparisons are attempted. Here, we examine the various checkpoint inhibitors currently used and in development. We discuss the antibodies and their protein targets, their pharmacokinetics as measured in various tumor types, and their binding affinities to their respective antigens. We also examine the various dosing regimens for these drugs and how they differ. 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Doi, Jeffrey ; Hansen, Aaron R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c421t-8265dadcb28ff24ddb7f49d6b53b9c6929569da0056700d155537989b733ca003</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Antibodies</topic><topic>Antigens</topic><topic>Apoptosis</topic><topic>Binding sites</topic><topic>Bispecific antibodies</topic><topic>Cancer therapies</topic><topic>Cell death</topic><topic>CTLA-4 protein</topic><topic>Cytotoxicity</topic><topic>Dosage</topic><topic>Drugs</topic><topic>Immune checkpoint</topic><topic>Immunoglobulins</topic><topic>Kinases</topic><topic>Licenses</topic><topic>Ligands</topic><topic>Lymphocytes</topic><topic>Lymphocytes T</topic><topic>Melanoma</topic><topic>Metastasis</topic><topic>PD-1 protein</topic><topic>PD-L1 protein</topic><topic>Pembrolizumab</topic><topic>Pharmacokinetics</topic><topic>Proteins</topic><topic>Review</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Picardo, Sarah L</creatorcontrib><creatorcontrib>Doi, Jeffrey</creatorcontrib><creatorcontrib>Hansen, Aaron R</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>Biological Sciences</collection><collection>ProQuest Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Picardo, Sarah L</au><au>Doi, Jeffrey</au><au>Hansen, Aaron R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Structure and Optimization of Checkpoint Inhibitors</atitle><jtitle>Cancers</jtitle><addtitle>Cancers (Basel)</addtitle><date>2019-12-21</date><risdate>2019</risdate><volume>12</volume><issue>1</issue><spage>38</spage><pages>38-</pages><issn>2072-6694</issn><eissn>2072-6694</eissn><abstract>With the advent of checkpoint inhibitor treatment for various cancer types, the optimization of drug selection, pharmacokinetics and biomarker assays is an urgent and as yet unresolved dilemma for clinicians, pharmaceutical companies and researchers. 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subjects | Antibodies Antigens Apoptosis Binding sites Bispecific antibodies Cancer therapies Cell death CTLA-4 protein Cytotoxicity Dosage Drugs Immune checkpoint Immunoglobulins Kinases Licenses Ligands Lymphocytes Lymphocytes T Melanoma Metastasis PD-1 protein PD-L1 protein Pembrolizumab Pharmacokinetics Proteins Review Tumors |
title | Structure and Optimization of Checkpoint Inhibitors |
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