No Cover Image

Journal article 400 views 63 downloads

A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development / Gareth Healey, Asa Frostell, Tim Fagge, Deya Gonzalez, R. Conlan, Steve Conlan

Antibodies, Volume: 8, Issue: 1, Start page: 7

Swansea University Authors: Gareth Healey, Deya Gonzalez, Steve Conlan

  • 48095.pdf

    PDF | Version of Record

    Released under the terms of a Creative Commons Attribution License (CC-BY).

    Download (3.32MB)

Check full text

DOI (Published version): 10.3390/antib8010007

Abstract

Antibodies, antibody-like molecules, and therapeutics incorporating antibodies as a targeting moiety, such as antibody-drug conjugates, offer significant potential for the development of highly efficacious drugs against a wide range of disorders. Despite some success, truly harnessing the superior t...

Full description

Published in: Antibodies
ISSN: 2073-4468
Published: 2019
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa48095
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2019-01-09T04:59:59Z
last_indexed 2020-06-16T19:00:27Z
id cronfa48095
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2020-06-16T15:56:33.4241010</datestamp><bib-version>v2</bib-version><id>48095</id><entry>2019-01-08</entry><title>A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development</title><swanseaauthors><author><sid>5926519f89187489cfd5e1478aa188b1</sid><ORCID>0000-0001-9531-1220</ORCID><firstname>Gareth</firstname><surname>Healey</surname><name>Gareth Healey</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>bafdf635eb81280304eedf4b18e65d4e</sid><ORCID>0000-0002-1838-6752</ORCID><firstname>Deya</firstname><surname>Gonzalez</surname><name>Deya Gonzalez</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>0bb6bd247e32fb4249de62c0013b51cb</sid><ORCID>0000-0002-2562-3461</ORCID><firstname>Steve</firstname><surname>Conlan</surname><name>Steve Conlan</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2019-01-08</date><deptcode>BMS</deptcode><abstract>Antibodies, antibody-like molecules, and therapeutics incorporating antibodies as a targeting moiety, such as antibody-drug conjugates, offer significant potential for the development of highly efficacious drugs against a wide range of disorders. Despite some success, truly harnessing the superior targeting properties of these molecules requires a platform from which to effectively identify the best candidates for drug development. To streamline the development of antibody-drug conjugates targeting gynecological cancers within our laboratory, we incorporated surface plasmon resonance analysis (Biacore&#x2122; T200) into our development toolkit. Antibodies, selected based on positive ELISA screens as suitable for development as antibody-drug conjugates, were evaluated using surface plasmon resonance to determine a wide range of characteristics including specificity, kinetics/affinity, the effect of linker binding, the impact of the drug to antibody ratio, and the effect of endosomal pH on antibody-antigen binding. Analysis revealed important kinetics data and information regarding the effect of conjugation and endosomal pH on our antibody candidates that correlated with cell toxicity and antibody internalization data. As well as explaining observations from cell-based assays regarding antibody-drug conjugate efficacies, these data also provide important information regarding intelligent antibody selection and antibody-drug conjugate design. This study demonstrates the application of surface plasmon resonance technology as a platform, where detailed information can be obtained, supporting the requirements for rapid and high-throughput screening that will enable enhanced antibody-drug conjugate development.</abstract><type>Journal Article</type><journal>Antibodies</journal><volume>8</volume><journalNumber>1</journalNumber><paginationStart>7</paginationStart><publisher/><issnElectronic>2073-4468</issnElectronic><keywords/><publishedDay>7</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2019</publishedYear><publishedDate>2019-01-07</publishedDate><doi>10.3390/antib8010007</doi><url/><notes/><college>COLLEGE NANME</college><department>Biomedical Sciences</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BMS</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2020-06-16T15:56:33.4241010</lastEdited><Created>2019-01-08T21:09:42.0977622</Created><authors><author><firstname>Gareth</firstname><surname>Healey</surname><orcid>0000-0001-9531-1220</orcid><order>1</order></author><author><firstname>Asa</firstname><surname>Frostell</surname><order>2</order></author><author><firstname>Tim</firstname><surname>Fagge</surname><order>3</order></author><author><firstname>Deya</firstname><surname>Gonzalez</surname><orcid>0000-0002-1838-6752</orcid><order>4</order></author><author><firstname>R.</firstname><surname>Conlan</surname><order>5</order></author><author><firstname>Steve</firstname><surname>Conlan</surname><orcid>0000-0002-2562-3461</orcid><order>6</order></author></authors><documents><document><filename>0048095-18012019133043.pdf</filename><originalFilename>48095.pdf</originalFilename><uploaded>2019-01-18T13:30:43.0400000</uploaded><type>Output</type><contentLength>3428493</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><embargoDate>2019-01-17T00:00:00.0000000</embargoDate><documentNotes>Released under the terms of a Creative Commons Attribution License (CC-BY).</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
spelling 2020-06-16T15:56:33.4241010 v2 48095 2019-01-08 A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development 5926519f89187489cfd5e1478aa188b1 0000-0001-9531-1220 Gareth Healey Gareth Healey true false bafdf635eb81280304eedf4b18e65d4e 0000-0002-1838-6752 Deya Gonzalez Deya Gonzalez true false 0bb6bd247e32fb4249de62c0013b51cb 0000-0002-2562-3461 Steve Conlan Steve Conlan true false 2019-01-08 BMS Antibodies, antibody-like molecules, and therapeutics incorporating antibodies as a targeting moiety, such as antibody-drug conjugates, offer significant potential for the development of highly efficacious drugs against a wide range of disorders. Despite some success, truly harnessing the superior targeting properties of these molecules requires a platform from which to effectively identify the best candidates for drug development. To streamline the development of antibody-drug conjugates targeting gynecological cancers within our laboratory, we incorporated surface plasmon resonance analysis (Biacore™ T200) into our development toolkit. Antibodies, selected based on positive ELISA screens as suitable for development as antibody-drug conjugates, were evaluated using surface plasmon resonance to determine a wide range of characteristics including specificity, kinetics/affinity, the effect of linker binding, the impact of the drug to antibody ratio, and the effect of endosomal pH on antibody-antigen binding. Analysis revealed important kinetics data and information regarding the effect of conjugation and endosomal pH on our antibody candidates that correlated with cell toxicity and antibody internalization data. As well as explaining observations from cell-based assays regarding antibody-drug conjugate efficacies, these data also provide important information regarding intelligent antibody selection and antibody-drug conjugate design. This study demonstrates the application of surface plasmon resonance technology as a platform, where detailed information can be obtained, supporting the requirements for rapid and high-throughput screening that will enable enhanced antibody-drug conjugate development. Journal Article Antibodies 8 1 7 2073-4468 7 1 2019 2019-01-07 10.3390/antib8010007 COLLEGE NANME Biomedical Sciences COLLEGE CODE BMS Swansea University 2020-06-16T15:56:33.4241010 2019-01-08T21:09:42.0977622 Gareth Healey 0000-0001-9531-1220 1 Asa Frostell 2 Tim Fagge 3 Deya Gonzalez 0000-0002-1838-6752 4 R. Conlan 5 Steve Conlan 0000-0002-2562-3461 6 0048095-18012019133043.pdf 48095.pdf 2019-01-18T13:30:43.0400000 Output 3428493 application/pdf Version of Record true 2019-01-17T00:00:00.0000000 Released under the terms of a Creative Commons Attribution License (CC-BY). true eng
title A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development
spellingShingle A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development
Gareth, Healey
Deya, Gonzalez
Steve, Conlan
title_short A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development
title_full A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development
title_fullStr A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development
title_full_unstemmed A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development
title_sort A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development
author_id_str_mv 5926519f89187489cfd5e1478aa188b1
bafdf635eb81280304eedf4b18e65d4e
0bb6bd247e32fb4249de62c0013b51cb
author_id_fullname_str_mv 5926519f89187489cfd5e1478aa188b1_***_Gareth, Healey
bafdf635eb81280304eedf4b18e65d4e_***_Deya, Gonzalez
0bb6bd247e32fb4249de62c0013b51cb_***_Steve, Conlan
author Gareth, Healey
Deya, Gonzalez
Steve, Conlan
author2 Gareth Healey
Asa Frostell
Tim Fagge
Deya Gonzalez
R. Conlan
Steve Conlan
format Journal article
container_title Antibodies
container_volume 8
container_issue 1
container_start_page 7
publishDate 2019
institution Swansea University
issn 2073-4468
doi_str_mv 10.3390/antib8010007
document_store_str 1
active_str 0
description Antibodies, antibody-like molecules, and therapeutics incorporating antibodies as a targeting moiety, such as antibody-drug conjugates, offer significant potential for the development of highly efficacious drugs against a wide range of disorders. Despite some success, truly harnessing the superior targeting properties of these molecules requires a platform from which to effectively identify the best candidates for drug development. To streamline the development of antibody-drug conjugates targeting gynecological cancers within our laboratory, we incorporated surface plasmon resonance analysis (Biacore™ T200) into our development toolkit. Antibodies, selected based on positive ELISA screens as suitable for development as antibody-drug conjugates, were evaluated using surface plasmon resonance to determine a wide range of characteristics including specificity, kinetics/affinity, the effect of linker binding, the impact of the drug to antibody ratio, and the effect of endosomal pH on antibody-antigen binding. Analysis revealed important kinetics data and information regarding the effect of conjugation and endosomal pH on our antibody candidates that correlated with cell toxicity and antibody internalization data. As well as explaining observations from cell-based assays regarding antibody-drug conjugate efficacies, these data also provide important information regarding intelligent antibody selection and antibody-drug conjugate design. This study demonstrates the application of surface plasmon resonance technology as a platform, where detailed information can be obtained, supporting the requirements for rapid and high-throughput screening that will enable enhanced antibody-drug conjugate development.
published_date 2019-01-07T04:02:31Z
_version_ 1717733741439221760
score 10.842861