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CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM
Interventional clinical trials in glioblastoma (GBM) have been consistently disappointing, attributable to various factors such as ineffective therapies, inadequate trial designs including lack of control arms, or enrollment criteria that do not represent real-world practice. Novel paradigms for cli...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354222/ http://dx.doi.org/10.1093/noajnl/vdac078.039 |
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author | Ledford, Aubrey Smith, Ashley DesRochers, Tessa Vibat, Cecile Rose |
author_facet | Ledford, Aubrey Smith, Ashley DesRochers, Tessa Vibat, Cecile Rose |
author_sort | Ledford, Aubrey |
collection | PubMed |
description | Interventional clinical trials in glioblastoma (GBM) have been consistently disappointing, attributable to various factors such as ineffective therapies, inadequate trial designs including lack of control arms, or enrollment criteria that do not represent real-world practice. Novel paradigms for clinical trial design(s) in GBM are desperately needed to produce clinically useful patient outcomes. KIYATEC has developed a patient- and tumor-specific technology platform to evaluate cellular response(s) to therapeutics using 3D cell culture methods that provide functional, patient-specific response predictions. Employing KIYATEC’s technology to screen compounds against both primary patient-, and PDX-derived specimens, enables clinical prioritization of early-stage assets most likely to have therapeutic response in vivo. In addition, KIYATEC’s 3D Predict™ Glioma test has shown clinical correlation of test-predicted response(s) and clinical outcomes in GBM patients. Incorporating KIYATEC’s 3D ex vivo technology into GBM therapeutic development is positioned to accelerate more successful trial results by 1) identifying early-stage compounds likely to possess clinical effects in vivo, and 2) prospectively identifying patients expected to have a clinical response to therapeutics in development. 3D Predict Glioma provides patient-specific responses within 7-10 days of tissue acquisition, providing an avenue for test integration into adaptive clinical trials, whereby functional characterization could provide gating information relating to trial execution. Specifically, functional response prediction may play a pivotal role in identifying newly diagnosed patients who might derive greater benefit from clinical trials compared to standard of care and by optimizing effective therapeutic selection in the recurrent setting. Therefore, a priori knowledge of an early-stage assets’ potential, combined with therapeutic sensitivity of individual patient tissue, may facilitate a new era for adaptive clinical trial design by assimilating KIYATEC’s analytically and clinically validated test into various steps of clinical trial execution such as randomization, stratification, therapy-switching, or compound addition/discontinuation. |
format | Online Article Text |
id | pubmed-9354222 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-93542222022-08-09 CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM Ledford, Aubrey Smith, Ashley DesRochers, Tessa Vibat, Cecile Rose Neurooncol Adv Supplement Abstracts Interventional clinical trials in glioblastoma (GBM) have been consistently disappointing, attributable to various factors such as ineffective therapies, inadequate trial designs including lack of control arms, or enrollment criteria that do not represent real-world practice. Novel paradigms for clinical trial design(s) in GBM are desperately needed to produce clinically useful patient outcomes. KIYATEC has developed a patient- and tumor-specific technology platform to evaluate cellular response(s) to therapeutics using 3D cell culture methods that provide functional, patient-specific response predictions. Employing KIYATEC’s technology to screen compounds against both primary patient-, and PDX-derived specimens, enables clinical prioritization of early-stage assets most likely to have therapeutic response in vivo. In addition, KIYATEC’s 3D Predict™ Glioma test has shown clinical correlation of test-predicted response(s) and clinical outcomes in GBM patients. Incorporating KIYATEC’s 3D ex vivo technology into GBM therapeutic development is positioned to accelerate more successful trial results by 1) identifying early-stage compounds likely to possess clinical effects in vivo, and 2) prospectively identifying patients expected to have a clinical response to therapeutics in development. 3D Predict Glioma provides patient-specific responses within 7-10 days of tissue acquisition, providing an avenue for test integration into adaptive clinical trials, whereby functional characterization could provide gating information relating to trial execution. Specifically, functional response prediction may play a pivotal role in identifying newly diagnosed patients who might derive greater benefit from clinical trials compared to standard of care and by optimizing effective therapeutic selection in the recurrent setting. Therefore, a priori knowledge of an early-stage assets’ potential, combined with therapeutic sensitivity of individual patient tissue, may facilitate a new era for adaptive clinical trial design by assimilating KIYATEC’s analytically and clinically validated test into various steps of clinical trial execution such as randomization, stratification, therapy-switching, or compound addition/discontinuation. Oxford University Press 2022-08-05 /pmc/articles/PMC9354222/ http://dx.doi.org/10.1093/noajnl/vdac078.039 Text en © The Author(s) 2022. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Supplement Abstracts Ledford, Aubrey Smith, Ashley DesRochers, Tessa Vibat, Cecile Rose CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM |
title | CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM |
title_full | CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM |
title_fullStr | CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM |
title_full_unstemmed | CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM |
title_short | CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM |
title_sort | clrm-19 using functional precision medicine to guide clinical trial enrollment in gbm |
topic | Supplement Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354222/ http://dx.doi.org/10.1093/noajnl/vdac078.039 |
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