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Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing

Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a challenge in many therapeutic areas. Larger and mor...

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Autores principales: Oni‐Orisan, Akinyemi, Srinivas, Nithya, Mehta, Krina, Das, Jesmin Lohy, Nguyen, Thu T., Tison, Geoffrey H., Bauer, Scott R., Burian, Maria, Funk, Ryan S., Graham, Richard A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8212753/
https://www.ncbi.nlm.nih.gov/pubmed/33421282
http://dx.doi.org/10.1111/cts.12973
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author Oni‐Orisan, Akinyemi
Srinivas, Nithya
Mehta, Krina
Das, Jesmin Lohy
Nguyen, Thu T.
Tison, Geoffrey H.
Bauer, Scott R.
Burian, Maria
Funk, Ryan S.
Graham, Richard A.
author_facet Oni‐Orisan, Akinyemi
Srinivas, Nithya
Mehta, Krina
Das, Jesmin Lohy
Nguyen, Thu T.
Tison, Geoffrey H.
Bauer, Scott R.
Burian, Maria
Funk, Ryan S.
Graham, Richard A.
author_sort Oni‐Orisan, Akinyemi
collection PubMed
description Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a challenge in many therapeutic areas. Larger and more diverse study populations are necessary to discover additional biomarkers that provide the resolution needed for a more tailored dose. To generate and accommodate large datasets of drug response phenotypes, time‐ and cost‐efficient strategies are necessary. In particular, a multitude of technological advances that originated for purposes outside of biomedical research (electronic health records, direct‐to‐consumer genetic testing, social media, mobile devices, and machine learning) have made it easier to communicate, connect, and gather information from consumers. Although these technologies have been used with success in the health sciences for an array of purposes, these resources have not been fully capitalized on for precision dosing. This perspective will touch on how these innovations can be used as data sources, data collection tools, and data processing tools for drug‐response phenotypes with a unique focus on advancing biomarker‐driven precision dosing.
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spelling pubmed-82127532021-06-25 Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing Oni‐Orisan, Akinyemi Srinivas, Nithya Mehta, Krina Das, Jesmin Lohy Nguyen, Thu T. Tison, Geoffrey H. Bauer, Scott R. Burian, Maria Funk, Ryan S. Graham, Richard A. Clin Transl Sci Position Paper Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a challenge in many therapeutic areas. Larger and more diverse study populations are necessary to discover additional biomarkers that provide the resolution needed for a more tailored dose. To generate and accommodate large datasets of drug response phenotypes, time‐ and cost‐efficient strategies are necessary. In particular, a multitude of technological advances that originated for purposes outside of biomedical research (electronic health records, direct‐to‐consumer genetic testing, social media, mobile devices, and machine learning) have made it easier to communicate, connect, and gather information from consumers. Although these technologies have been used with success in the health sciences for an array of purposes, these resources have not been fully capitalized on for precision dosing. This perspective will touch on how these innovations can be used as data sources, data collection tools, and data processing tools for drug‐response phenotypes with a unique focus on advancing biomarker‐driven precision dosing. John Wiley and Sons Inc. 2021-02-12 2021-05 /pmc/articles/PMC8212753/ /pubmed/33421282 http://dx.doi.org/10.1111/cts.12973 Text en © 2021 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Position Paper
Oni‐Orisan, Akinyemi
Srinivas, Nithya
Mehta, Krina
Das, Jesmin Lohy
Nguyen, Thu T.
Tison, Geoffrey H.
Bauer, Scott R.
Burian, Maria
Funk, Ryan S.
Graham, Richard A.
Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing
title Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing
title_full Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing
title_fullStr Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing
title_full_unstemmed Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing
title_short Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing
title_sort leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker‐driven precision dosing
topic Position Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8212753/
https://www.ncbi.nlm.nih.gov/pubmed/33421282
http://dx.doi.org/10.1111/cts.12973
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