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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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| 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 |