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Artificial intelligence-driven approach for patient-focused drug development

Patients' increasing digital participation provides an opportunity to pursue patient-centric research and drug development by understanding their needs. Social media has proven to be one of the most useful data sources when it comes to understanding a company's potential audience to drive...

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Autores principales: Karmalkar, Prathamesh, Gurulingappa, Harsha, Spies, Erica, Flynn, Jennifer A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601646/
https://www.ncbi.nlm.nih.gov/pubmed/37899963
http://dx.doi.org/10.3389/frai.2023.1237124
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author Karmalkar, Prathamesh
Gurulingappa, Harsha
Spies, Erica
Flynn, Jennifer A.
author_facet Karmalkar, Prathamesh
Gurulingappa, Harsha
Spies, Erica
Flynn, Jennifer A.
author_sort Karmalkar, Prathamesh
collection PubMed
description Patients' increasing digital participation provides an opportunity to pursue patient-centric research and drug development by understanding their needs. Social media has proven to be one of the most useful data sources when it comes to understanding a company's potential audience to drive more targeted impact. Navigating through an ocean of information is a tedious task where techniques such as artificial intelligence and text analytics have proven effective in identifying relevant posts for healthcare business questions. Here, we present an enterprise-ready, scalable solution demonstrating the feasibility and utility of social media-based patient experience data for use in research and development through capturing and assessing patient experiences and expectations on disease, treatment options, and unmet needs while creating a playbook for roll-out to other indications and therapeutic areas.
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spelling pubmed-106016462023-10-27 Artificial intelligence-driven approach for patient-focused drug development Karmalkar, Prathamesh Gurulingappa, Harsha Spies, Erica Flynn, Jennifer A. Front Artif Intell Artificial Intelligence Patients' increasing digital participation provides an opportunity to pursue patient-centric research and drug development by understanding their needs. Social media has proven to be one of the most useful data sources when it comes to understanding a company's potential audience to drive more targeted impact. Navigating through an ocean of information is a tedious task where techniques such as artificial intelligence and text analytics have proven effective in identifying relevant posts for healthcare business questions. Here, we present an enterprise-ready, scalable solution demonstrating the feasibility and utility of social media-based patient experience data for use in research and development through capturing and assessing patient experiences and expectations on disease, treatment options, and unmet needs while creating a playbook for roll-out to other indications and therapeutic areas. Frontiers Media S.A. 2023-10-12 /pmc/articles/PMC10601646/ /pubmed/37899963 http://dx.doi.org/10.3389/frai.2023.1237124 Text en Copyright © 2023 Karmalkar, Gurulingappa, Spies and Flynn. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Karmalkar, Prathamesh
Gurulingappa, Harsha
Spies, Erica
Flynn, Jennifer A.
Artificial intelligence-driven approach for patient-focused drug development
title Artificial intelligence-driven approach for patient-focused drug development
title_full Artificial intelligence-driven approach for patient-focused drug development
title_fullStr Artificial intelligence-driven approach for patient-focused drug development
title_full_unstemmed Artificial intelligence-driven approach for patient-focused drug development
title_short Artificial intelligence-driven approach for patient-focused drug development
title_sort artificial intelligence-driven approach for patient-focused drug development
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601646/
https://www.ncbi.nlm.nih.gov/pubmed/37899963
http://dx.doi.org/10.3389/frai.2023.1237124
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