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Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics
Indication extension or repositioning of drugs can, if done well, provide a faster, cheaper, and derisked route to the approval of new therapies, creating new options to address pockets of unmet medical need for patients and offering the potential for significant commercial and clinical benefits. We...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214305/ https://www.ncbi.nlm.nih.gov/pubmed/35755863 http://dx.doi.org/10.1016/j.patter.2022.100496 |
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author | Das, Sayoni Taylor, Krystyna Beaulah, Simon Gardner, Steve |
author_facet | Das, Sayoni Taylor, Krystyna Beaulah, Simon Gardner, Steve |
author_sort | Das, Sayoni |
collection | PubMed |
description | Indication extension or repositioning of drugs can, if done well, provide a faster, cheaper, and derisked route to the approval of new therapies, creating new options to address pockets of unmet medical need for patients and offering the potential for significant commercial and clinical benefits. We look at the promises and challenges of different repositioning strategies and the disease insights and scalability that new high-resolution patient stratification methodologies can bring. This is exemplified by a systematic analysis of all development candidates and on-market drugs, which identified 477 indication extension opportunities across 30 chronic disease areas, each supported by patient stratification biomarkers. This illustrates the potential that new artificial intelligence (AI) and combinatorial analytics methods have to enhance the rate and cost of innovation across the drug discovery industry. |
format | Online Article Text |
id | pubmed-9214305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-92143052022-06-23 Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics Das, Sayoni Taylor, Krystyna Beaulah, Simon Gardner, Steve Patterns (N Y) Perspective Indication extension or repositioning of drugs can, if done well, provide a faster, cheaper, and derisked route to the approval of new therapies, creating new options to address pockets of unmet medical need for patients and offering the potential for significant commercial and clinical benefits. We look at the promises and challenges of different repositioning strategies and the disease insights and scalability that new high-resolution patient stratification methodologies can bring. This is exemplified by a systematic analysis of all development candidates and on-market drugs, which identified 477 indication extension opportunities across 30 chronic disease areas, each supported by patient stratification biomarkers. This illustrates the potential that new artificial intelligence (AI) and combinatorial analytics methods have to enhance the rate and cost of innovation across the drug discovery industry. Elsevier 2022-06-10 /pmc/articles/PMC9214305/ /pubmed/35755863 http://dx.doi.org/10.1016/j.patter.2022.100496 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Perspective Das, Sayoni Taylor, Krystyna Beaulah, Simon Gardner, Steve Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics |
title | Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics |
title_full | Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics |
title_fullStr | Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics |
title_full_unstemmed | Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics |
title_short | Systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics |
title_sort | systematic indication extension for drugs using patient stratification insights generated by combinatorial analytics |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214305/ https://www.ncbi.nlm.nih.gov/pubmed/35755863 http://dx.doi.org/10.1016/j.patter.2022.100496 |
work_keys_str_mv | AT dassayoni systematicindicationextensionfordrugsusingpatientstratificationinsightsgeneratedbycombinatorialanalytics AT taylorkrystyna systematicindicationextensionfordrugsusingpatientstratificationinsightsgeneratedbycombinatorialanalytics AT beaulahsimon systematicindicationextensionfordrugsusingpatientstratificationinsightsgeneratedbycombinatorialanalytics AT gardnersteve systematicindicationextensionfordrugsusingpatientstratificationinsightsgeneratedbycombinatorialanalytics |