藥物不良反應是個造成上百萬死亡的嚴重問題，根據研究指出，藥物不良反應是在藥物相關產業上市後藥物造成死亡最主要的原因之一。在美國，它是每年造成十萬人死亡的第四大死因；根據研究(1, 2, 3)指出，非同義單核苷酸多態性有最高的可能性影響一個人是否會對某特定藥物有不良反應。在此篇論文當中，我們設計了一個結合了SIDER, DART以及dbSNP三個資料庫以及運用到SIFT去預測是否有氨基酸變異的流程。我們運用此流程去預測藥物是否有氨基酸變異，並且找出與某特定藥物不良反應最有可能相關的非同義單核苷酸多態性，找出那些與某特定藥物不良反應最有可能相關的非同義單核苷酸多態性候選人是我們的目的，生物學家可以利用此篇論文的方法縮小研究範圍，針對此篇論文設計流程找出的非同義單核苷酸多態性研究。在本篇論文出產之前，尚沒有一個完整針對非同義單核苷酸多態性與藥物不良反應的計算方法或者流程提出，我們希望這設計出的流程可以幫助生物學家更有效率的對藥物不良反應與非同義單核苷酸多態性的關聯做研究。

Adverse drug reactions are a serious problem, causing millions of death. According to report, adverse drug reaction is one of the main failure causes in industries such as drug withdrawal and development when a drug has been distributed to the market. Adverse drug reaction is the fourth leading cause of death in the United States, causing 100,000 deaths each year; nevertheless, adverse drug reactions occur depending on the individual. According to reports(1)(2)(3), it is nsSNP that has the highest possibility to determine whether a person will suffer adverse drug reaction when taking certain drugs.

In our work, we designed a flow that incorporates the databases(SIDER, DART, dbSNP) and amino acid substitution prediction tool(SIFT) to make predictions about what nsSNPs might have the correlation with certain adverse drug reactions, and thus bio-techies may have these candidates to do clinical experiments. Before our work, there hasn’t been any methodology or flow proposed for the correlation between adverse drug reactions and nsSNPs. We hope our work can help improve the efficiency in bio-techies’ research on the adverse drug reactions.

I. Reference Thesis
[1] Lei Chen, Tao Huang, Jian Zhang, Ming-Yue Zheng, Kai-Yan Feng, Yu-Dong Cai, and Kuo-Chen Chou, Predicting Drugs Side Effects Based on Chemical-Chemical Interactions and Protein-Chemical Interactions, BioMed Research International, Volume 2013 (2013), 8 pages
[2] Yoshihiro Yamanishi, Edouard Pauwels, and Masaaki Kotera, Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces, Journal of Chemical Information and Modeling, 2012, 52(12), pp.3284-3292
[3] Michael Kuhn, Monica Campillos, Ivica Letunic, Lars Juhl Jensen, and Peer Bork, A side effect resource to capture phenotypic effects of drugs, Molecular Systems Biology, 2009
[4] Pauline C. Ng and Steven Henikoff, Predicting the Effects of Amino Acid Substitutions on Protein Function, Annu Rev. Genomics Hum. Genet, 2006. July, pp.61-80
[5] Ng PC Hnikoff S. SIFT: predicting amino acid changes that affect protein function, Nucleic Acids Res., 2003 Jul, pp.3812-3814
[6] L. Z Sun, Z. L. Ji, X. Chen, J. F. Wang and Y. Z. Chen, ADME-AP: a database of ADME associated proteins, Bioinformatics Application Note, 2002, Vol. 18 pp. 1699-1700
[7] Ng, P.C. and Henikoff, S. Accounting for human polymorphisms predicted to affect protein function. Genome Res., (2002), 12, 436-446.
[8] Bairoch,A. and Apweiler,R. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res.,(2000) , 28, 45-48
[9] Sherry,S.T., Ward,M.H., Kholodov, M.,Baker, J., Phan,L., Smigielski, E.M. and Sirotkin,K. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res., (2001), 29, 308-311
[10] Nachman, Michael W. (2001). “Single nucleotide polymorphisms and recombination rate in humans”. Trends in genetics 17 (9): 481-485. doi:10. 1016/S0168-9525(01)02409-X. PMID 11525814
[11] Barreiro LB, Laval G, Quach H, Patin E, Quintana-Murci L. (2008). “Natural selection has driven population differentiation in modern humans”. Nature Genetics 40 (3): 340-345. Doi:10.1038/ng.78. PMID 18246066
[12] Adverse Drug Events, Adverse Drug Reactions and Medication Errors. VA Center for Medication Safety And VHA Pharmacy Benefits Managament Strategic Healthcare Group and the Medical Advisory Panel, November 2006
[13] Nicholas P., et. Al, A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports, J Am Med Inform Assoc 2012; 19:79e85
[14] Jill U. Adams, Ph.D. 2008 Nature Education Citation: Adams, J. Pharmacogenomics and personalized medicine, Nature Education (2008 ); 1(1):194
[15] Z.L. Ji, L.Y. Han, C.W. Yap, L.Z. Sun, X. Chen, and Y.Z. Chen. DART: Drug Adverse Reaction Target Database. Drug Safety 2003; 26 (10): 685-690.
[16] New genetic framework could help explain drug side effects, Emily Carlson, April 20, 2010, NIH(National Institute of General Medical Sciences)
[17] Genetic-screening trial could reduce drug side effects, June 24, 2011, The University of Manchester
[18] Gene link to multiple sclerosis explains drug side effects, July 9, 2012,
[19] The Genetics of Drug Side Effects, UNC Health Care and UNC School of Medicine, Feb. 2014
[20] Adzhubei I, Jordan DM Sunyaev SR. Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum genet, Chapter 7:Unit7.20 (2013).
[21] Ramensky V, Bork P, Sunyaev S. Human non-sysnonymous SNPs: server and survey. Nucleic Acids Res 30(17): 3894-3900 (2002).
[22] Sunyae SR, Eisenhaber F, Rodchenkov IV, Eisenhaber B, Tumanyan VG, Kuznetsov EN. PSIC: profile extraction from sequence alignments with position-specific counts of independent observations. Protein Eng 12(5): 387-394(1999).
[23] Russel A. Wike, Debboe W. Lin, Dan M. Roden, Paul B. Watkins, Davd Flockhart, Issam Zineh, Kathleen M. Giacomini, and Ronal M. Krauss, Identifying genetic risk factors for serious adverse drug reactions: current progress and challenges, PMC Oct 19, (2009), Nat rev Drug Discov. Nov 2007: 6(11): 904-916

II. Website/ English Report & Essay
<1> SNPedia: http://www.snpedia.com/index.php/SNPedia
<2> Wikipedia: http://en.wikipedia.org
<3> dbSNP: http://www.ncbi.nlm.nih.gov/SNP/
<4> DART: http://bidd.nus.edu.sg/group/drt/dart.asp
<5> ADME-AP: http://bidd.nus.edu.sg/group/admeap/admeap.asp
<6> SIFT: http://sift.jcvi.org/www/SIFT_dbSNP.html
<7> Polyphen 2: http://genetics.bwh.harvard.edu/pph2/
<8> Top 10 Weirdest Prescription Drug Side Effects by Shanna Freeman
http://health.howstuffworks.com/medicine/medication/10-weird-prescription-drug-side-effect.htm
<9> 10 Worst Prescription Drug Side Effects by Grace Murano 11/20/2009
http://www.oddee.com/item_96885.aspx

IV. 中文文章、報導 (Chinese Report)
(1) 台灣研究團隊締造個人化醫療成功範例 用要前基因篩檢可預防嚴重藥物副作用 發稿時間：中華民國100年03月28日 新聞聯繫人：沈志陽博士，中央研究院生物醫學研究所研究員、林美惠，中央研究院總辦事處公共事務組，發稿單位：公共事務組 http://www.sinica.edu.tw/manage/gatenews/showsingle.php?_op=?rid:3990
(2) 藥物基因體學對個人化醫藥發展的影響 作者：王大維 年份：民國九十三年七月 服務單位：工研院經資中心 http://yearbook.stpi.org.tw/biotech/8-01-01.html
(3) 個人化醫療的時代：應用藥物基因體學治療癌症 作者：鄭文軒 BIOMEDICINE(生物醫學期刊)
http://www.idealversion.com/bt/archives/bm-08-08r.pdf
(4) 色素性視網膜炎 Retinitis Pigmentosa 彙整：吳明純
編審：簡穎秀/胡務亮醫師 民國97年11月27日 http://www.genes-at-taiwan.com.tw/genehelp/database/disease/Retinitis_Pigmentosa-980313.htm
(5) 黏多醣症的分類 資料提供：英國MPS協會 馬偕紀念醫院小兒科
林炫沛醫師審譯 台大醫院基因醫學部版權所有 2013 http://www.genes-at-taiwan.com.tw/genehelp/database/disease/MPS_new1.htm
(6) 基因檢測與藥物過敏的預防 台大醫院 健康電子報 藥劑部藥師黃玉婷 2014年05月78期 http://epaper.ntuh.gov.tw/health/201405/project_3.html
(7) 基因篩檢防癲癇用藥副作用預防醫學新典範 國際厚生健康園區 2011/3/28 下午05:45:00 http://www.24drs.com/Special_Report/Epilepsy/5_article.asp?who=7418&table=daily
(8) 個人化醫療- 基因與藥物反應 林佩珊博士(Dr May Lam) 香港大學李嘉誠醫學院 藥理及藥劑學系講師 http://www.med.hku.hk/publiclecture/pl2013b/Public%20Lecture_Nov2013_upload.pdf
(9) 用藥前基因篩檢可防藥物副作用 YAHOO健康新聞 台灣新生報 記者王柏楊 http://biotech.ncue.edu.tw/2011_100a1_translation/knowledge14.htm
(10) 全球投入藥理學研究 找對基因, 吃對藥 2005-11 康健雜誌 84期 http://www.commonhealth.com.tw/article/article.action?id=5016707&page=1
(11) 談大腸直腸癌的藥物基因體學 癌症新探35期 作者臺北榮總內科部血液腫瘤科 王緯書醫師 http://cisc.twbbs.org/lifetype/index.php?op=ViewArticle&articleId=1582&blogId=1
(12) 個人化標靶藥 追擊癌細胞《明報》D06 健康專線
http://www.cancer-fund.org/tc/cancer_news_211.html
(13) 什麼藥吃不得，基因告訴你《科學發展》2008年11月，431期，76 ~ 77頁
http://scitechvista.most.gov.tw/zh-tw/Articles/C/0/1/10/1/1169.htm
(14) 吃藥副作用與基因類型有關 華南植物園科普網
http://kepu.scbg.ac.cn/kepudongtai/articleread.asp?articleid=8456
(15) 用藥前測基因 癲癇病患免藥害 中研院生陳珮、沈志陽、院士陳垣崇 中央(中央社記者陳清芳台北28日電) 2011/03/28 10:28
http://delightdetox1268.pixnet.net/blog/post/280274354-%E6%9C%8D%E8%97%A5%E5%89%8D%E5%85%88%E5%81%9A%E5%9F%BA%E5%9B%A0%E6%AA%A2%E6%B8%AC%EF%BC%8C%E7%9E%AD%E8%A7%A3%E9%AB%94%E8%B3%AA%EF%BC%8C%E5%8F%AF%E4%BB%A5%E6%B8%9B%E5%B0%91%E8%87%B4
(16) 基因檢測揪「惡客」 肺癌治療有對策 記者許家瑋/優活健康網
http://www.canceraway.org.tw/page.asp?IDno=1876
(17) 「安樂普利諾」副作用多 學者：服藥前先測基因【2013-07-02】
資料來源: udn 健康醫藥 聯合報> 記者修瑞瑩/ 台南報導
http://www.tainan-pharmacist.org.tw/news_index_1.php?id=71&title=%E3%80%8C%E5%AE%89%E6%A8%82%E6%99%AE%E5%88%A9%E8%AB%BE%E3%80%8D%E5%89%AF%E4%BD%9C%E7%94%A8%E5%A4%9A%E3%80%80%E5%AD%B8%E8%80%85%EF%BC%9A%E6%9C%8D%E8%97%A5%E5%89%8D%E5%85%88%E6%B8%AC%E5%9F%BA%E5%9B%A0
(18) 基因檢測 處藥更快更準 2013-11-20
http://news.singtao.ca/toronto/2013-11-20/city1384943988d4800120.html
(19) 肺癌患者基因突變 標靶藥延壽一倍
http://paper.wenweipo.com/2011/08/22/HK1108220042.htm
(20) 港大發現肝癌的“抑癌基因” 來源: 全球華人愛癌新藥網 發佈時間: 2005/10/10 11:41:00
http://www.anticancer.com.hk/Detail.aspx?id=902694