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Cited by 482

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Validation of in-vitro bioassay methods: Application in herbal drug research

·2021·Profiles of Drug Substances, Excipients and Related Methodology

Abstract

This present review described the validation method of in-vitro bioassay for its application in herbal drug research. Seven sequencing steps that can be taken for performing a valid bioassay include: literature survey, sample stability evaluation, Biosystem performance testing, Sample performance evaluation, determination of 50% effective concentration or cytotoxic concentrations, selective index evaluation, and determination of accurate relative potency of sample. Detailed methods and acceptance criteria for each step are described herein. Method calculations of the relative potency of sample using European Pharmacopeia 10.0, 5.3 (2020) were recommended instead of using United States Pharmacopeia 42 (2019). For having reliable data and conclusions, all methods (chemical and bioassay) need to be first validated before any data collection. Absence of any validation method may results in incorrect conclusions and bias.

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Metadata

Venue
Profiles of Drug Substances, Excipients and Related Methodology
Publisher
Elsevier
Published
2021
Volume
46
Pages
273-307
ISSN
1871-5125 (ISSN-L)
OpenAlex
W3081667723
Cited by
482
References
48
FWCI
102.84
Type
book chapter
Language
en
Open access
closed

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CoChat. (2026). Citation check: Validation of in-vitro bioassay methods: Application in herbal drug research. https://app.cochat.ai/papers/10.1016/bs.podrm.2020.07.005
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Validation of in-vitro bioassay methods: Application in herbal drug research. (2021). Profiles of Drug Substances, Excipients and Related Methodology. https://doi.org/10.1016/bs.podrm.2020.07.005

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.