An initial ingredient analysis of drugs approved by China food and drug administration

Haodi Li; Qingcai Chen; Buzhou Tang; Dong Huang; Xiaolong Wang; Zengjian Liu

doi:10.1007/978-981-10-3168-7_10

An initial ingredient analysis of drugs approved by China food and drug administration

Haodi Li
, Qingcai Chen
, Buzhou Tang^*
, Dong Huang
, Xiaolong Wang
, Zengjian Liu

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Drug is an important part of medicine. Drug knowledge bases tha organize and manage drugs have attracted considerable attention, and have been widely used in human health care in many countries and regions. There are also a large number of electronic drug knowledge bases publicly available. In China, however, there is hardly any publicly available well-structured drug knowledge base, may due to two different types of medicine: Chinese traditional medicine (CTM) and modern medicine (ME). In order to build an electronic knowledge base of drugs approved by China Food and Drug Administration (CFDA), we developed a preliminary ingredient drug analysis system. This system collects all drug names from the website of CFDA, obtains their manuals from three medical websites, extracts the ingredients of drugs, and analyses the distribution of the extracted ingredients. Totally, 12,918 out of 19,490 drug manuals were collected. Evaluation on randomly selected 50 drug manuals shows that the system achieves an F-score of 95.46% on ingredient extraction. According to the distribution of the extraction ingredients, we find that ingredient multiplexing is very common in medicine, especially in herbal medicine, which may provide a clue for drug safety as taking more than one type of drug that contains partially the same ingredients may cause overtaking the same ingredients.

Original language	English
Title of host publication	Knowledge Graph and Semantic Computing
Subtitle of host publication	Semantic, Knowledge, and Linked Big Data - 1st China Conference, CCKS 2016, Revised Selected Papers
Editors	Le Sun, Haixun Wang, Tieyun Qian, Tong Ruan, Heng Ji, Huajun Chen
Publisher	Springer Verlag
Pages	104-109
Number of pages	6
ISBN (Print)	9789811031670
DOIs	https://doi.org/10.1007/978-981-10-3168-7_10
State	Published - 2016
Externally published	Yes
Event	1st China Conference on Knowledge Graph and Semantic Computing, CCKS 2016 - Beijing, China Duration: 19 Sep 2016 → 22 Sep 2016

Publication series

Name	Communications in Computer and Information Science
Volume	650
ISSN (Print)	1865-0929

Conference

Conference	1st China Conference on Knowledge Graph and Semantic Computing, CCKS 2016
Country/Territory	China
City	Beijing
Period	19/09/16 → 22/09/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Chinese traditional medicine
Drug ingredient extraction
Drug knowledge base

Access to Document

10.1007/978-981-10-3168-7_10

Cite this

Li, H., Chen, Q., Tang, B., Huang, D., Wang, X., & Liu, Z. (2016). An initial ingredient analysis of drugs approved by China food and drug administration. In L. Sun, H. Wang, T. Qian, T. Ruan, H. Ji, & H. Chen (Eds.), Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data - 1st China Conference, CCKS 2016, Revised Selected Papers (pp. 104-109). (Communications in Computer and Information Science; Vol. 650). Springer Verlag. https://doi.org/10.1007/978-981-10-3168-7_10

Li, Haodi ; Chen, Qingcai ; Tang, Buzhou et al. / An initial ingredient analysis of drugs approved by China food and drug administration. Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data - 1st China Conference, CCKS 2016, Revised Selected Papers. editor / Le Sun ; Haixun Wang ; Tieyun Qian ; Tong Ruan ; Heng Ji ; Huajun Chen. Springer Verlag, 2016. pp. 104-109 (Communications in Computer and Information Science).

@inproceedings{f11631b13f674d72a6396f5d7f9ff6ae,

title = "An initial ingredient analysis of drugs approved by China food and drug administration",

abstract = "Drug is an important part of medicine. Drug knowledge bases tha organize and manage drugs have attracted considerable attention, and have been widely used in human health care in many countries and regions. There are also a large number of electronic drug knowledge bases publicly available. In China, however, there is hardly any publicly available well-structured drug knowledge base, may due to two different types of medicine: Chinese traditional medicine (CTM) and modern medicine (ME). In order to build an electronic knowledge base of drugs approved by China Food and Drug Administration (CFDA), we developed a preliminary ingredient drug analysis system. This system collects all drug names from the website of CFDA, obtains their manuals from three medical websites, extracts the ingredients of drugs, and analyses the distribution of the extracted ingredients. Totally, 12,918 out of 19,490 drug manuals were collected. Evaluation on randomly selected 50 drug manuals shows that the system achieves an F-score of 95.46\% on ingredient extraction. According to the distribution of the extraction ingredients, we find that ingredient multiplexing is very common in medicine, especially in herbal medicine, which may provide a clue for drug safety as taking more than one type of drug that contains partially the same ingredients may cause overtaking the same ingredients.",

keywords = "Chinese traditional medicine, Drug ingredient extraction, Drug knowledge base",

author = "Haodi Li and Qingcai Chen and Buzhou Tang and Dong Huang and Xiaolong Wang and Zengjian Liu",

note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2016.; 1st China Conference on Knowledge Graph and Semantic Computing, CCKS 2016 ; Conference date: 19-09-2016 Through 22-09-2016",

year = "2016",

doi = "10.1007/978-981-10-3168-7\_10",

language = "英语",

isbn = "9789811031670",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "104--109",

editor = "Le Sun and Haixun Wang and Tieyun Qian and Tong Ruan and Heng Ji and Huajun Chen",

booktitle = "Knowledge Graph and Semantic Computing",

address = "德国",

}

Li, H, Chen, Q , Tang, B, Huang, D, Wang, X & Liu, Z 2016, An initial ingredient analysis of drugs approved by China food and drug administration. in L Sun, H Wang, T Qian, T Ruan, H Ji & H Chen (eds), Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data - 1st China Conference, CCKS 2016, Revised Selected Papers. Communications in Computer and Information Science, vol. 650, Springer Verlag, pp. 104-109, 1st China Conference on Knowledge Graph and Semantic Computing, CCKS 2016, Beijing, China, 19/09/16. https://doi.org/10.1007/978-981-10-3168-7_10

An initial ingredient analysis of drugs approved by China food and drug administration. / Li, Haodi; Chen, Qingcai ; Tang, Buzhou et al.
Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data - 1st China Conference, CCKS 2016, Revised Selected Papers. ed. / Le Sun; Haixun Wang; Tieyun Qian; Tong Ruan; Heng Ji; Huajun Chen. Springer Verlag, 2016. p. 104-109 (Communications in Computer and Information Science; Vol. 650).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An initial ingredient analysis of drugs approved by China food and drug administration

AU - Li, Haodi

AU - Chen, Qingcai

AU - Tang, Buzhou

AU - Huang, Dong

AU - Wang, Xiaolong

AU - Liu, Zengjian

N1 - Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2016.

PY - 2016

Y1 - 2016

N2 - Drug is an important part of medicine. Drug knowledge bases tha organize and manage drugs have attracted considerable attention, and have been widely used in human health care in many countries and regions. There are also a large number of electronic drug knowledge bases publicly available. In China, however, there is hardly any publicly available well-structured drug knowledge base, may due to two different types of medicine: Chinese traditional medicine (CTM) and modern medicine (ME). In order to build an electronic knowledge base of drugs approved by China Food and Drug Administration (CFDA), we developed a preliminary ingredient drug analysis system. This system collects all drug names from the website of CFDA, obtains their manuals from three medical websites, extracts the ingredients of drugs, and analyses the distribution of the extracted ingredients. Totally, 12,918 out of 19,490 drug manuals were collected. Evaluation on randomly selected 50 drug manuals shows that the system achieves an F-score of 95.46% on ingredient extraction. According to the distribution of the extraction ingredients, we find that ingredient multiplexing is very common in medicine, especially in herbal medicine, which may provide a clue for drug safety as taking more than one type of drug that contains partially the same ingredients may cause overtaking the same ingredients.

AB - Drug is an important part of medicine. Drug knowledge bases tha organize and manage drugs have attracted considerable attention, and have been widely used in human health care in many countries and regions. There are also a large number of electronic drug knowledge bases publicly available. In China, however, there is hardly any publicly available well-structured drug knowledge base, may due to two different types of medicine: Chinese traditional medicine (CTM) and modern medicine (ME). In order to build an electronic knowledge base of drugs approved by China Food and Drug Administration (CFDA), we developed a preliminary ingredient drug analysis system. This system collects all drug names from the website of CFDA, obtains their manuals from three medical websites, extracts the ingredients of drugs, and analyses the distribution of the extracted ingredients. Totally, 12,918 out of 19,490 drug manuals were collected. Evaluation on randomly selected 50 drug manuals shows that the system achieves an F-score of 95.46% on ingredient extraction. According to the distribution of the extraction ingredients, we find that ingredient multiplexing is very common in medicine, especially in herbal medicine, which may provide a clue for drug safety as taking more than one type of drug that contains partially the same ingredients may cause overtaking the same ingredients.

KW - Chinese traditional medicine

KW - Drug ingredient extraction

KW - Drug knowledge base

UR - https://www.scopus.com/pages/publications/85006025179

U2 - 10.1007/978-981-10-3168-7_10

DO - 10.1007/978-981-10-3168-7_10

M3 - 会议稿件

AN - SCOPUS:85006025179

SN - 9789811031670

T3 - Communications in Computer and Information Science

SP - 104

EP - 109

BT - Knowledge Graph and Semantic Computing

A2 - Sun, Le

A2 - Wang, Haixun

A2 - Qian, Tieyun

A2 - Ruan, Tong

A2 - Ji, Heng

A2 - Chen, Huajun

PB - Springer Verlag

T2 - 1st China Conference on Knowledge Graph and Semantic Computing, CCKS 2016

Y2 - 19 September 2016 through 22 September 2016

ER -

Li H, Chen Q , Tang B, Huang D, Wang X, Liu Z. An initial ingredient analysis of drugs approved by China food and drug administration. In Sun L, Wang H, Qian T, Ruan T, Ji H, Chen H, editors, Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data - 1st China Conference, CCKS 2016, Revised Selected Papers. Springer Verlag. 2016. p. 104-109. (Communications in Computer and Information Science). doi: 10.1007/978-981-10-3168-7_10

An initial ingredient analysis of drugs approved by China food and drug administration

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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