Interactions Between Orally Administered Drugs can be Predicted from a Combination of Machine Learning and Tissue Models

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https://doi.org/10.54133/ajms.v6i1.684

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References

Al-Janabi II, Fikrat HT, Mustafa RMA, Razzo FN, Borazan HN, Al-Taee SF. The effect of acetylsalicylic acid and acetaminophen on the solubility and absorption characteristics of nitrofurantoin. J Fac Med Baghdad. 1980;22(2):44-53.

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Al-Janabi II, Anber SA, Fikrat HT. In vitro detection of possible in vivo drug interactions Part 2: A study of the effect of hydrochlorothiazide and frusemide on the partition coefficient and solubility characteristics of propranolol hydrochloride. Pharmazie.1981;36(H.6):485-488.

Han K, Cao P, Wang Y, Xie F, Ma J, Yu M, et al. A Review of approaches for predicting drug-drug interactions based on machine learning. Front Pharmacol. 2022;12:814858. doi: 10.3389/fphar.2021.814858.

Zhang Y, Deng Z, Xu X, Feng Y, Junliang S. Application of artificial intelligence in drug-drug interactions prediction: A review. J Chem Inf Model. 2023. doi: 10.1021/acs.jcim.3c00582.

Shi Y, Reker D, Byrne JD, Kirtane AR, Hess K, Wang Z, et al. Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning. Nat Biomed Eng. 2024. doi: 10.1038/s41551-023-01128-9.

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Published

2024-03-05

How to Cite

Al-Janabi, I. I. (2024). Interactions Between Orally Administered Drugs can be Predicted from a Combination of Machine Learning and Tissue Models. Al-Rafidain Journal of Medical Sciences ( ISSN 2789-3219 ), 6(1), 200–201. https://doi.org/10.54133/ajms.v6i1.684

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