本文選題：心血管藥物　切入點：藥物不良反應(yīng)　出處：《吉林大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：目的:構(gòu)建我國心血管藥物不良反應(yīng)中英文本體知識庫,系統(tǒng)性表示心血管藥物不良反應(yīng),為心血管藥物不良反應(yīng)的系統(tǒng)性分析與知識發(fā)現(xiàn)提供資源、奠定基礎(chǔ);基于本體分析心血管藥物不良反應(yīng)發(fā)生模式;開發(fā)數(shù)據(jù)挖掘算法對藥物引起不良反應(yīng)的類效應(yīng)進行知識發(fā)現(xiàn)。方法:根據(jù)我國《新編藥物學(xué)》(第17版)在相關(guān)網(wǎng)站收集我國目前使用的心血管藥物,收集心血管藥物說明書,提取藥品說明書中的藥物和不良反應(yīng)信息并翻譯。將不良反應(yīng)信息映射到不良反應(yīng)本體OAE(the Ontology of Adverse Events),對于OAE中沒有的不良反應(yīng)術(shù)語,注釋后添加到OAE中,同時將藥物信息映射到藥物本體NDF-RT(The National Drug File-Reference Terminology)。通過本體構(gòu)建工具Onto Fox和Ontorat構(gòu)建心血管藥物不良反應(yīng)中英文本體OCVDAE(The Ontology of Cardiovascular Drug Adverse Events),構(gòu)建本體時將NDF-RT中的藥物成分和作用機制分類集成到OCVDAE中,并建立藥物—不良反應(yīng)之間的聯(lián)系。基于本體統(tǒng)計分析心血管藥物不良反應(yīng)發(fā)生模式,包括藥物類別、不良反應(yīng)類別、常見不良反應(yīng)等。然后,通過數(shù)據(jù)挖掘算法(即統(tǒng)計學(xué)算法),包括藥物類別中不良反應(yīng)比率(drug proportional class level ratio,PCR),藥物類水平比例報告比值比法(the drug class level proportional reporting ratio,C-PRR),藥物類水平卡方(the drug class-χ2,C-χ2)、每類藥物中包含的藥物數(shù)量閾值及熱圖等方法,基于OCVDAE的分類、藥物成分和作用機制分類,挖掘有統(tǒng)計意義的不良反應(yīng)類效應(yīng)。最后,通過Pub Med中的文獻對所發(fā)現(xiàn)的部分類效應(yīng)知識進行驗證。結(jié)果:共收集了265種心血管藥物及相應(yīng)說明書,提取了1383個中文不良反應(yīng)術(shù)語,對應(yīng)802個英文不良反應(yīng)術(shù)語,其中391個可在OAE中找到并映射,其余的411個英文術(shù)語注釋后添加到OAE中,形成了新的OAE術(shù)語。共有194種藥物映射到了NDF-RT。構(gòu)建的OCVDAE可在http://www.ontobee.org/ontology/和http://purl.bioontology.org/ontology/OCVDAE網(wǎng)站公開獲取。OCVDAE中包括194種藥物,736個英文不良反應(yīng)術(shù)語。265種心血管藥物涉及9種藥物類別,802個英文不良反應(yīng)術(shù)語涉及27種不良反應(yīng)類別,常見的前10種不良反應(yīng)包括頭痛、惡心、疲乏等�；赑CR的熱圖分析,發(fā)現(xiàn)了多數(shù)藥物類別對“行為與神經(jīng)不良反應(yīng)”和“消化系統(tǒng)不良反應(yīng)”具有類效應(yīng)�；诮y(tǒng)計方法發(fā)現(xiàn)1種藥物成分類別“脂類”藥物(包括阿托伐他汀、氟伐他汀、非諾貝特)引起8種不良反應(yīng)(如肌痛、肌病、肌炎等),具有類效應(yīng),3種藥物作用機制類別(如膽固醇合成抑制劑)引起5種不良反應(yīng)(如厭食、腹瀉等),具有類效應(yīng)。文獻驗證了部分知識發(fā)現(xiàn)結(jié)果。結(jié)論:本研究系統(tǒng)性地收集了我國心血管藥物及說明書中的心血管藥物相關(guān)的不良反應(yīng)。通過復(fù)用現(xiàn)有本體OAE和NDF-RT中的術(shù)語,以及添加術(shù)語及心血管藥物—不良反應(yīng)關(guān)系,構(gòu)建了心血管藥物不良反應(yīng)中英文本體OCVDAE�；诒倔w分析了心血管藥物不良反應(yīng)的發(fā)生模式。并提出使用PCR,C-PRR,C-χ2及藥物數(shù)量閾值等方法進行藥物不良反應(yīng)類效應(yīng)的知識發(fā)現(xiàn)。
[Abstract]:Objective: to construct the adverse reaction of cardiovascular drugs in China English ontology knowledge base, said the adverse cardiovascular drug system, systematic analysis and knowledge for the cardiovascular response to drug discovery and provide resources, lay the foundation for ontology analysis; cardiovascular adverse drug reaction model based on data mining algorithm; development effect caused by adverse reactions to drugs for knowledge discovery. Methods: according to China's "new materia medica > (SEVENTEENTH EDITION) collection of cardiovascular drugs in use at present in China at the website, collect the cardiovascular drugs manual extraction of drug drug instruction and the adverse reactions and adverse reactions. The information translation information is mapped to the adverse reactions (the Ontology of Adverse OAE body Events in terms of adverse reactions), not in OAE, annotated and added to the OAE, while the drug information is mapped to the drug NDF-RT (The Natio Nal Drug File-Reference Terminology). Onto Fox and Ontorat building construction tools adverse cardiovascular drugs in English ontology OCVDAE (The Ontology of Cardiovascular body by Drug Adverse Events), will build the ontology drug ingredients and mechanism of NDF-RT in the class is integrated into OCVDAE, and set up between adverse drug reactions - contact body statistics. Analysis of the occurrence pattern of cardiovascular adverse reactions based drugs, including drug categories, adverse reaction categories, common adverse reactions. Then, through the data mining algorithm (i.e. statistical algorithm), including adverse drug reaction categories (drug proportional class level ratio ratio, PCR), drug level proportional reporting ratio method (the drug class level proportional reporting ratio, C-PRR), drug level chi square (the drug class- x 2, C- x 2), drugs containing each drug class in number The amount of threshold and thermal methods, OCVDAE based classification, classification and mechanism of drug ingredients, adverse reaction effects have statistical significance mining. Finally, to validate the part class effect of knowledge discovered by Pub Med in the literature. Results: a total of 265 kinds of cardiovascular drugs and the corresponding instructions, from 1383 a Chinese adverse reaction term, corresponding to the 802 English adverse reaction terms, 391 of which can be found in OAE and mapping, notes 411 English remaining after the term is added to the OAE, OAE formed a new term. There are 194 kinds of drugs mapped to NDF-RT. OCVDAE constructed in http://www.ontobee.org/ontology/ and http://purl.bioontology.org/ontology/OCVDAE's public website acquisition includes 194 kinds of drug.OCVDAE, 736 English adverse reaction term.265 cardiovascular drugs involving 9 drug categories, 802 English adverse reaction The term relates to 27 kinds of adverse reaction categories, 10 common adverse reactions include headache, nausea, fatigue and so on. Based on the analysis of the PCR image, found that most drug categories has effect on the adverse reaction behavior and the nervous and digestive system adverse reactions. 1 drug ingredients category "lipid" Drug Statistics based on the method (including atorvastatin, fluvastatin and fenofibrate) caused by 8 kinds of adverse reactions (such as myalgia, myopathy, myositis, etc.) with effect, 3 kinds of mechanism of drug action categories (such as cholesterol synthesis inhibitor) caused by 5 kinds of adverse reactions (such as anorexia, diarrhea, etc.) with literature class effect. To verify the results of knowledge. Conclusion: This study systematically collected adverse cardiovascular drugs and cardiovascular drugs instructions in China related. By reusing the existing ontology OAE and NDF-RT terms, and adding terms The adverse reaction and cardiovascular drugs, establish ontology analysis model based on the cardiovascular response to drug adverse reactions in cardiovascular medicine English ontology OCVDAE.. And put forward the use of PCR, C-PRR, C- x 2 and the amount of drugs threshold for adverse drug reaction effects of knowledge discovery.

【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R972

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