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Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments
New antibiotic combinations are needed to improve the treatment of tuberculosis. Larkins-Ford and colleagues share a framework that combines in vitro pairwise drug response data and machine learning to rationally prioritize combinations for clinical development.(1)
| 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/PMC9512690/ https://www.ncbi.nlm.nih.gov/pubmed/36130481 http://dx.doi.org/10.1016/j.xcrm.2022.100745 |
| _version_ | 1784797886718935040 |
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| author | Patterson, Sarah Palmer, Adam |
| author_facet | Patterson, Sarah Palmer, Adam |
| author_sort | Patterson, Sarah |
| collection | PubMed |
| description | New antibiotic combinations are needed to improve the treatment of tuberculosis. Larkins-Ford and colleagues share a framework that combines in vitro pairwise drug response data and machine learning to rationally prioritize combinations for clinical development.(1) |
| format | Online Article Text |
| id | pubmed-9512690 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Elsevier |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-95126902022-09-28 Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments Patterson, Sarah Palmer, Adam Cell Rep Med Preview New antibiotic combinations are needed to improve the treatment of tuberculosis. Larkins-Ford and colleagues share a framework that combines in vitro pairwise drug response data and machine learning to rationally prioritize combinations for clinical development.(1) Elsevier 2022-09-20 /pmc/articles/PMC9512690/ /pubmed/36130481 http://dx.doi.org/10.1016/j.xcrm.2022.100745 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| spellingShingle | Preview Patterson, Sarah Palmer, Adam Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments |
| title | Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments |
| title_full | Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments |
| title_fullStr | Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments |
| title_full_unstemmed | Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments |
| title_short | Predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments |
| title_sort | predicting in vivo activity of combination therapies from in vitro drug pairs in diverse environments |
| topic | Preview |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512690/ https://www.ncbi.nlm.nih.gov/pubmed/36130481 http://dx.doi.org/10.1016/j.xcrm.2022.100745 |
| work_keys_str_mv | AT pattersonsarah predictinginvivoactivityofcombinationtherapiesfrominvitrodrugpairsindiverseenvironments AT palmeradam predictinginvivoactivityofcombinationtherapiesfrominvitrodrugpairsindiverseenvironments |