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Machine Learning Uncovers Food- and Excipient-Drug Interactions

Cell Reports(2020)10.1016/j.celrep.2020.02.094Source: DataRank Database

Machine Learning Uncovers Food- and Excipient-Drug Interactions is a research paper published in Cell Reports (2020). On theSindex it has a DataRank of 0. It has been cited 61 times.

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Open Access61 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (7 grants)Topics (28)IDs (PubMed, PMC)Annotations (2)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (9)

Yunhua Shi ORCID,Ameya R. Kirtane ORCID,Kaitlyn Hess ORCID,Grace Zhong ORCID,Evan Crane

Live enrichment

PubMed:32187543 PMC:PMC7179333

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Grant: P2EZP3_168827

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Grant: P300P2_177833

National Institutes of Health

Grant: EB000244

Swiss National Science Foundation

Grant: 168827

NIBIB NIH HHS

Grant: R01 EB000244

NIBIB NIH HHS

Grant: R37 EB000244

Pharmaceutical Research and Manufacturers of America Foundation

MeSH Terms

AnimalsMice, Inbred BALB CSwineHumansDiterpenesGlucuronosyltransferasePharmaceutical PreparationsExcipientsBiological AssayDrug InteractionsUnited States Food and Drug AdministrationFoodUnited StatesFemaleHep G2 CellsMachine LearningATP Binding Cassette Transporter, Subfamily B, Member 1AbietanesRetinyl Esters

Keywords

PharmacologyPharmacokineticsDrug DeliveryMachine LearningVirtual ScreeningFood-drug InteractionsData ScienceInactive IngredientsExcipient-drug Interactions