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In Silico Prediction of Fraction Unbound in Human Plasma from Chemical Fingerprint Using Automated Machine Learning
[Image: see text] Predicting the fraction unbound of a drug in plasma plays a significant role in understanding its pharmacokinetic properties during in vitro studies of drug design and discovery. Owing to the gaining reliability of machine learning in biological predictive models and development of...
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| Pubblicato in: | ACS Omega |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
American Chemical Society
2021
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| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7970465/ https://ncbi.nlm.nih.gov/pubmed/33748592 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/acsomega.0c05846 |
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