Research progress of drug knowledge bases based on medical research and clinical application

doi:10.3877/cma.j.issn.1674-0785.2021.01.014

Abstract

Abstract:

The drug knowledge base is constructed based on artificial intelligence algorithms, which is used to integrate existing drug knowledge and tap effective knowledge. Currently, drug knowledge bases have been used in clinical research such as antimicrobial drug supervision, rational drug guidance, health management intervention, and clinical decision support. Based on the drug knowledge bases, researchers perform scientific research such as adverse drug reaction analysis, drug repurposing, drug resistance analysis, system pharmacogenomics analysis, and so on. In this paper, we review the progress of the drug knowledge bases in scientific and clinical research, in order to shed some light on the further application and development of the drug knowledge bases.

Key words: Drug knowledge bases, Artificial intelligence, Medical applications

Wenjie Pan, Zeyu Yin, Wanxin Hou, Jawad Hussain, Yuanpeng Zhang, Min Yao, Li Wang. Research progress of drug knowledge bases based on medical research and clinical application[J]. Chinese Journal of Clinicians(Electronic Edition), 2021, 15(01): 72-78.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://zhlcyszz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1674-0785.2021.01.014

https://zhlcyszz.cma-cmc.com.cn/EN/Y2021/V15/I01/72

Figures/Tables 1

References 57

1	Zhu Y, Elemento O, Pathak J, et al. Drug knowledge bases and their applications in biomedical informatics research [J]. Brief Bioinform, 2019, 20(4): 1308-1321.
2	Del Fiol G, Rocha BH, Kuperman GJ, et al. Comparison of two knowledge bases on the detection of drug-drug interactions [C]. Los Angeles, CA: Proc AMIA Symp, 2000: 171-175.
3	Norby U, Kallen K, Eiermann B, et al. Drugs and birth defects: a knowledge database providing risk assessments based on national health registers [J]. Eur J Clin Pharmacol, 2013, 69(4): 889-899.
4	杨美洁, 张兴, 熊相超. 基于本体技术的高血压知识库平台构建 [J]. 医学信息学杂志, 2019, 40(4): 55-58.
5	徐帆, 曾苏. 药品属性分类知识库的构建及其在我院药事管理数据分析中的应用 [J]. 中国药房, 2019, 30(20): 2737-2741.
6	陈瑶, 吴红, 葛卫红, 等. 基于深度学习模型的我国药品不良反应报告实体关系抽取研究 [J]. 中国药科大学学报, 2019, 50(6): 753-759.
7	Sosa DN, Derry A, Guo M, et al. A literature-based knowledge graph embedding method for identifying drug repurposing opportunities in rare diseases [J]. Pac Symp Biocomput, 2020, 25: 463-474.
8	桑盛田, 杨志豪, 刘晓霞, 等. 融合知识图谱与深度学习的药物发现方法 [J]. 模式识别与人工智能, 2018, 31(12): 1103-1110.
9	黄锦元. 基于人工神经网络的药学知识库数据挖掘研究 [J]. 信息化建设, 2015, 18(8): 276-277.
10	王一敏, 梁治钢. 基于免疫遗传算法的抗菌药物数据挖掘 [J]. 计算机系统应用, 2017, 26(3): 156-161.
11	Lin SF, Xiao KT, Huang YT, et al. Analysis of adverse drug reactions using drug and drug target interactions and graph-based methods [J]. Artif Intell Med, 2010, 48(2-3): 161-166.
12	Fung KW, KapusniK-Uner J, Cunningham J, et al. Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support [J]. J Am Med Inform Assoc, 2017, 24(4): 806-812.
13	Waagmeester A, Stupp G, Burgstaller-Muehlbacher S, et al. Wikidata as a knowledge graph for the life sciences [J]. Elife, 2020, 9: e52614.
14	Hur J, Zhao C, Bai JP. Systems pharmacological analysis of drugs inducing stevens-johnson syndrome and toxic epidermal necrolysis [J]. Chem Res Toxicol, 2015, 28(5): 927-934.
15	Xie B, Zheng CJ, Han LY, et al. PharmGED pharmacogenetic effect database [J]. Clin Pharmacol Ther, 2007, 81(1): 29.
16	Taboureau O, Nielsen SK, Audouze K, et al. ChemProt: a disease chemical biology database [J]. Nucleic Acids Res, 2011, 39(Database issue): D367-372.
17	Przydzial MJ, Bhhatarai B, Koleti A, et al. GPCR ontology: development and application of a G protein-coupled receptor pharmacology knowledge framework [J]. Bioinformatics, 2013, 29(24): 3211-3219.
18	张春梅, 唐丽燕, 李东晓, 等. 中医药机构知识库在科研管理中的应用探索 [J]. 中国中医药信息杂志, 2019, 26(3): 4-7.
19	Kumar R, Chaudhary K, Gupta S, et al. CancerDR: cancer drug resistance database [J]. Sci Rep, 2013, 3: 1445.
20	Gupta S, Mishra M, Sen N, et al. DbMDR: a relational database for multidrug resistance genes as potential drug targets [J]. Chem Biol Drug Des, 2011, 78(4): 734-738.
21	Xu Q, Liu K, Lin X, et al. ADMETNet: The knowledge base of pharmacokinetics and toxicology network [J]. J Genet Genomics, 2017, 44(5): 273-276.
22	Coker EA, Mitsopoulos C, Tym JE, et al. canSAR: update to the cancer translational research and drug discovery knowledgebase [J]. Nucleic Acids Res, 2019, 47(D1): D917-D922.
23	廖莉, 许晓强, 许宇璐, 等. 基于"德尔菲法"构建儿童安全用药指导知识库 [J]. 中国现代医生, 2019, 57(22): 93-97.
24	陈鑫, 曹征, 林色奇, 等. 女性中医健康干预知识库的构建研究 [J]. 世界科学技术-中医药现代化, 2018, 20(10): 1798-1802.
25	黄智生, 缪崇, 胡青, 等. 川崎病知识图谱构建研究 [J]. 中国数字医学, 2018, 13(9): 28-31.
26	苟玲, 张艺帆, 陆遥, 等. 基于本体的抗生素临床管理知识库的建立 [J]. 中国数字医学, 2015, 10(10): 88-91.
27	葛彩霞, 张寅升, 陈维红, 等. 药物不良反应知识库的建设以及统计分析 [J]. 中国医院药学杂志, 2015, 35(9): 765-769.
28	Xu R, Wang Q. Automatic construction of a large-scale and accurate drug-side-effect association knowledge base from biomedical literature [J]. J Biomed Inform, 2014, 51: 191-199.
29	杨洁, 黄智生, 胡青, 等. 抑郁障碍知识图谱中抗抑郁药不良反应知识整合及其应用 [J]. 中国数字医学, 2017, 12(6): 2-4, 10.
30	Grandy CA, Donnan JR, Peddle JT, et al. A systematic assessment of the availability and clinical drug information coverage of machine-readable clinical drug data sources for building knowledge translation products [J]. J Am Med Inform Assoc, 2018, 25(9): 1240-1247.
31	张顺香, 张世尧, 王银. 基于术语提取的药品作用冲突自动检测模型 [J]. 安徽理工大学学报(自然科学版), 2016, 36(5): 46-53.
32	Yokoyama S, Sugimoto Y, Nakagawa C, et al. integrative analysis of clinical and bioinformatics databases to identify anticancer properties of digoxin [J]. Sci Rep, 2019, 9(1): 16597.
33	Malas TB, Vlietstra WJ, Kudrin R, et al. Drug prioritization using the semantic properties of a knowledge graph [J]. Sci Rep, 2019, 9(1): 6281.
34	Hussain S, Kenigsberg BB, Danahey K, et al. Disease-drug database for pharmacogenomic-based prescribing [J]. Clin Pharmacol Ther, 2016, 100(2): 179-190.
35	Paolini GV, Shapland RH, Van Hoorn WP, et al. Global mapping of pharmacological space [J]. Nat Biotechnol, 2006, 24(7): 805-815.
36	Du J, Li X. A knowledge graph of combined drug therapies using semantic predications from biomedical literature: algorithm development [J]. JMIR Med Inform, 2020, 8(4): e18323.
37	Wang YY, Chen WH, Xiao PP, et al. GEAR: a database of genomic elements associated with drug resistance [J]. Sci Rep, 2017, 7: 44085.
38	Ghose AK, Herbertz T, Salvino JM, et al. Knowledge-based chemoinformatic approaches to drug discovery [J]. Drug Discov Today, 2006, 11(23-24): 1107-1114.
39	杨全军, 张剑萍, 郁静, 等. 医院结构化药学决策知识库建设实践与应用成效分析 [J]. 中国现代应用药学, 2020, 37(4): 490-495.
40	邵晨, 褚燕琦, 崔晓辉, 等. 医嘱前置审核对住院患者用药安全性的影响 [J]. 临床药物治疗杂志, 2020, 18(1): 51-54.
41	李瑞荣, 辛海莉, 孙艳. 医院门诊合理用药临床决策支持系统的构建与实施 [J]. 中国药业, 2020, 29(6): 74-76.
42	张丽, 杨耀芳, 朱建萍, 等. 基于社区医院信息认证平台的慢性胃炎用药智能化管理 [J]. 中国医药导刊, 2019, 21(1): 55-59.
43	张丽, 杨耀芳, 朱建萍, 等. 消化系统用药知识库智能化管理系统的应用 [J]. 中国药师, 2019, 22(2): 378-380.
44	金蕾, 杨耀芳, 魏新萍, 等. 糖尿病用药知识库智能化管理系统的开发 [J]. 中国药师, 2017, 20(4): 705-708.
45	Send AF, AL-Ayyash A, Schecher S, et al. Development of a standardized knowledge base to generate individualized medication plans automatically with drug administration recommendations [J]. Br J Clin Pharmacol, 2013, 76(Suppl 1): 37-46.
46	任炳楠, 董占军, 吴惠珍, 等. 用药信息管理系统、方法及终端设备 [P]. 中国: CN108648792A, 2018-10-12.
47	梁国威. 知识库驱动的临床用药监控系统研究 [D]. 杭州: 浙江大学, 2015.
48	董军, 王欣, 李军, 等. 临床决策支持系统的构建与应用 [J]. 中国卫生质量管理, 2016, 23(3): 16-19.
49	朱定局. 基于知识库的药物定制方法和系统 [P]. 中国: CN106126889A, 2016-11-16.
50	陈拥军, 刘鼎, 陈泓伶, 等. 闭环控制的抗菌药物使用监管干预一体化系统设计与实现 [J]. 医疗卫生装备, 2017, 38(10): 42-44, 51.
51	范小红, 纪灏, 王丽杨, 等. 智能化抗菌药物临床应用全过程管理系统设计与应用 [J]. 中国医疗设备, 2013, 28(8): 75-78.
52	王选锭, 陈建群, 俞剑, 等. 医院抗菌药物临床使用知识库智能控制系统 [P]. 中国: CN103235874A, 2013-08-07.
53	王一敏, 梁治钢. 基于区域云平台抗菌药物医疗信息系统 [J]. 中国新通信, 2016, 18(19): 143-145.
54	金蕾, 杨耀芳, 汤春红, 等. 社区医院用不同分级管理抗菌药物知识库智能化管理系统开发 [J]. 中国全科医学, 2018, 21(11): 1382-1386.
55	梁治钢, 王一敏. 深度学习在抗菌药物数据分析中的应用 [J]. 中国新通信, 2019, 21(14): 147-148.
56	梁治钢, 王一敏. 深度学习在电子病历抗菌药物使用方法分类中的应用 [J]. 计算机系统应用, 2019, 28(8): 71-77.
57	王一敏, 梁治钢. 基于BI的个性化抗菌药物用药体系的设计 [J]. 电子技术与软件工程, 2016,5(18): 58-59.

应用类别	应用领域	药物知识库
医学科研	不良反应分析	Anatomical therapeutic chemical classification（ATC）^[11]
		drug target ontology（DTO）^[11]
	潜在的药物相互作用分析	First DataBank（FDB）^[12]
		Micromedex^[12]
		Multum^[12]
	药物重利用	GNBR^[7]
		Wikidata^[13]
	药物基因组研究	全基因组转录表达数据库^[14]
		PharmGED数据库^[15]
		ChemProt数据库^[16]
		GPCR本体数据库^[17]
	科研管理	中医药机构知识库^[18]
	耐药性研究	CancerDR^[19]
		DbMDR^[20]
	药物发现	ADMETNet^[21]
		canSAR^[22]
医学临床	合理用药指导	儿童用药指导知识库^[23]
	健康管理干预	中医健康状况干预知识库^[24]
	临床决策	川崎病知识图谱^[25]
	抗菌药物监管	抗菌药物知识库^[26]

应用类别	应用领域	药物知识库
医学科研	不良反应分析	Anatomical therapeutic chemical classification（ATC）^[11]
		drug target ontology（DTO）^[11]
	潜在的药物相互作用分析	First DataBank（FDB）^[12]
		Micromedex^[12]
		Multum^[12]
	药物重利用	GNBR^[7]
		Wikidata^[13]
	药物基因组研究	全基因组转录表达数据库^[14]
		PharmGED数据库^[15]
		ChemProt数据库^[16]
		GPCR本体数据库^[17]
	科研管理	中医药机构知识库^[18]
	耐药性研究	CancerDR^[19]
		DbMDR^[20]
	药物发现	ADMETNet^[21]
		canSAR^[22]
医学临床	合理用药指导	儿童用药指导知识库^[23]
	健康管理干预	中医健康状况干预知识库^[24]
	临床决策	川崎病知识图谱^[25]
	抗菌药物监管	抗菌药物知识库^[26]

[1]	Meifang Zhang, Ying Tan, Qiaozhen Zhu, Xin Wen, Ying Yuan, Yue Qin, Hongbo Guo, Lingxiu Hou, Wenlan Huang, Guiyan Peng, Shengli Li. Artificial intelligence-based quality control of mid-sagittal plane ultrasound images for first trimester fetal crown-rump length [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2023, 20(09): 945-950.
[2]	Feifei Yang, Xixiang Lin, Yixin Chen, Qiushuang Wang, Liwei Zhang, Xu Chen, Meiqing Zhang, Shuhua Wang, Kunlun He. Automatic detection of regional wall motion abnormalities by echocardiography based on deep learning [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2023, 20(04): 424-429.
[3]	Wei Tang, Rongquan He, Suning Huang. Application of deep learning in imaging for diagnosis, treatment and prognosis prediction of breast cancer [J]. Chinese Journal of Breast Disease(Electronic Edition), 2023, 17(06): 323-328.
[4]	Shuaihua Fan, Wei Guo, Jun Guo. Current situation and prospect of application of decision tree algorithm based on machine learning in prognosis prediction of bloodstream infection [J]. Chinese Journal of Experimental and Clinical Infectious Diseases(Electronic Edition), 2023, 17(05): 289-293.
[5]	Hui Zhang, Min Cai, Xiangya Huang. Clinical application of digital technology and artificial intelligence in maxillary sinus floor augmentation [J]. Chinese Journal of Stomatological Research(Electronic Edition), 2023, 17(04): 244-252.
[6]	Liangyue Pang, Huancai Lin. Application of artificial intelligence in the field of dental caries [J]. Chinese Journal of Stomatological Research(Electronic Edition), 2023, 17(03): 162-166.
[7]	Xiaowei Xing, Yuchen Liu, Bing Zhao, Minggang Wang. A research on predictive value of convolutional neural network based on preoperative abdominal CT for recurrence of incisional hernia after surgical repair [J]. Chinese Journal of Hernia and Abdominal Wall Surgery(Electronic Edition), 2023, 17(06): 677-681.
[8]	Xiaowei Xing, Yuchen Liu, Minggang Wang. Application and prospects of artificial intelligence technology in the field of hernia and abdominal wall surgery [J]. Chinese Journal of Hernia and Abdominal Wall Surgery(Electronic Edition), 2023, 17(04): 390-393.
[9]	Bing Han, Jinyang Gu. Research and application prospect of deep learning neural network in diagnosis and treatments for liver cancer [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(05): 480-485.
[10]	Manshi Lei, Sisi Deng, Xinrong Wang, Jinbin Huang, Qing Xiang, Anni Xiong, Zhan'ao Meng. Application of artificial intelligence-assisted compression sensing technology in upper abdominal fat-suppressed T2WI sequence [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(05): 551-556.
[11]	Yunpeng Ge, Hongyuan Cui, Jinghai Song. Application of artificial intelligence in diagnosis, treatment and prognosis of primary liver cancer [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(04): 367-371.
[12]	Xiaodong Wang, Kai Wang, Zhao Ge. Research progress of computer vision in improvement of therapeutic effect of liver transplantation for liver cancer [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(04): 361-366.
[13]	Ya Tian, Meilong Wu, Xiaobin Feng. Artificial intelligence in diagnosis and treatments for hepatocellular carcinoma [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(03): 258-262.
[14]	Jingke Li, Yanchun Zhang, Jiayi Wu, Xiuyu Ren. Deep learning for diabetic retinopathy screening, classification and management [J]. Chinese Journal of Ophthalmologic Medicine(Electronic Edition), 2023, 13(04): 241-246.
[15]	Ping Hu, Tengfeng Yan, Haizhu Zhou, Xingen Zhu. Advances in artificial intelligence be applied to early diagnose intracranial hemorrhage and hematoma segmentation [J]. Chinese Journal of Cerebrovascular Diseases(Electronic Edition), 2023, 17(04): 410-416.

Please choose a citation manager

Content to export