Evidence map›Paper›PMID 20727161›Full record

ArticleChinese medicine2010

A comprehensive platform for quality control of botanical drugs (PhytomicsQC): a case study of Huangqin Tang (HQT) and PHY906.

Robert Tilton, Anthony A Paiva, Jing-Qu Guan, Rajendra Marathe, Zaoli Jiang, Winfried van Eyndhoven, Jeffrey Bjoraker, Zachary Prusoff, Hailong Wang, Shwu-Huey Liu and 1 more

Abstract read
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Article in Chinese medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed.

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  10. Cancer Biomarkers for Integrative Oncology.Current oncology reports · 2019
    Review
  11. Herbal Medicines for Irinotecan-Induced Diarrhea.Frontiers in pharmacology · 2019
    Review
  12. Molecules (Basel, Switzerland) · 2018
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Robert TiltonDepartment of Pharmacology, Yale University School Of Medicine, New Haven, CT 06510, USA. yccheng@yale.edu.
Anthony A Paiva
Jing-Qu Guan
Rajendra Marathe
Zaoli Jiang
Winfried van Eyndhoven
Jeffrey Bjoraker
Zachary Prusoff
Hailong Wang
Shwu-Huey Liu
Yung-Chi Cheng

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEstablishing botanical extracts as globally-accepted polychemical medicines and a new paradigm for disease treatment, requires the development of high-level quality control metrics. Based on comprehensive chemical and biological fingerprints correlated with pharmacology, we propose a general approach called PhytomicsQC to botanical quality control.

methodsIncorporating the state-of-the-art analytical methodologies, PhytomicsQC was employed in this study and included the use of liquid chromatography/mass spectrometry (LC/MS) for chemical characterization and chemical fingerprinting, differential cellular gene expression for bioresponse fingerprinting and animal pharmacology for in vivo validation. A statistical pattern comparison method, Phytomics Similarity Index (PSI), based on intensities and intensity ratios, was used to determine the similarity of the chemical and bioresponse fingerprints among different manufactured batches.

resultsEighteen batch samples of Huangqin Tang (HQT) and its pharmaceutical grade version (PHY906) were analyzed using the PhytomicsQC platform analysis. Comparative analysis of the batch samples with a clinically tested standardized batch obtained values of PSI similarity between 0.67 and 0.99.

conclusionWith rigorous quality control using analytically sensitive and comprehensive chemical and biological fingerprinting, botanical formulations manufactured under standardized manufacturing protocols can produce highly consistent batches of products.

Identifiers

PMID20727161
PMCPMC2940884

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.