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Screening for regenerative therapy responders in heart failure

Risk of outcome variability challenges therapeutic innovation. Selection of the most suitable candidates is predicated on reliable response indicators. Especially for emergent regenerative biotherapies, determinants separating success from failure in achieving disease rescue remain largely unknown....

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Detalles Bibliográficos
Autores principales: Yamada, Satsuki, Jeon, Ryounghoon, Garmany, Armin, Behfar, Atta, Terzic, Andre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Medicine Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8252977/
https://www.ncbi.nlm.nih.gov/pubmed/34169733
http://dx.doi.org/10.2217/bmm-2020-0683
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author Yamada, Satsuki
Jeon, Ryounghoon
Garmany, Armin
Behfar, Atta
Terzic, Andre
author_facet Yamada, Satsuki
Jeon, Ryounghoon
Garmany, Armin
Behfar, Atta
Terzic, Andre
author_sort Yamada, Satsuki
collection PubMed
description Risk of outcome variability challenges therapeutic innovation. Selection of the most suitable candidates is predicated on reliable response indicators. Especially for emergent regenerative biotherapies, determinants separating success from failure in achieving disease rescue remain largely unknown. Accordingly, (pre)clinical development programs have placed increased emphasis on the multi-dimensional decoding of repair capacity and disease resolution, attributes defining responsiveness. To attain regenerative goals for each individual, phenotype-based patient selection is poised for an upgrade guided by new insights into disease biology, translated into refined surveillance of response regulators and deep learning-amplified clinical decision support.
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spelling pubmed-82529772021-07-07 Screening for regenerative therapy responders in heart failure Yamada, Satsuki Jeon, Ryounghoon Garmany, Armin Behfar, Atta Terzic, Andre Biomark Med Special Report Risk of outcome variability challenges therapeutic innovation. Selection of the most suitable candidates is predicated on reliable response indicators. Especially for emergent regenerative biotherapies, determinants separating success from failure in achieving disease rescue remain largely unknown. Accordingly, (pre)clinical development programs have placed increased emphasis on the multi-dimensional decoding of repair capacity and disease resolution, attributes defining responsiveness. To attain regenerative goals for each individual, phenotype-based patient selection is poised for an upgrade guided by new insights into disease biology, translated into refined surveillance of response regulators and deep learning-amplified clinical decision support. Future Medicine Ltd 2021-06-25 2021-06 /pmc/articles/PMC8252977/ /pubmed/34169733 http://dx.doi.org/10.2217/bmm-2020-0683 Text en © 2021 Andre Terzic https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License (https://creativecommons.org/licenses/by-nc-nd/4.0/)
spellingShingle Special Report
Yamada, Satsuki
Jeon, Ryounghoon
Garmany, Armin
Behfar, Atta
Terzic, Andre
Screening for regenerative therapy responders in heart failure
title Screening for regenerative therapy responders in heart failure
title_full Screening for regenerative therapy responders in heart failure
title_fullStr Screening for regenerative therapy responders in heart failure
title_full_unstemmed Screening for regenerative therapy responders in heart failure
title_short Screening for regenerative therapy responders in heart failure
title_sort screening for regenerative therapy responders in heart failure
topic Special Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8252977/
https://www.ncbi.nlm.nih.gov/pubmed/34169733
http://dx.doi.org/10.2217/bmm-2020-0683
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