Translating clinical findings into knowledge in drug safety evaluation - drug induced liver injury prediction system (DILIps)

PLoS Computational Biology

Volumn 7, Issue 12, 2011, Pages

  Liu, Zhichao ^a   Shi, Qiang ^a   Ding, Don ^b   Kelly, Reagan ^b   Fang, Hong ^b   Tong, Weida ^a  

^a NATIONAL CENTER FOR TOXICOLOGICAL RESEARCH   (United States)

^b ICF INTERNATIONAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMMERCE; DATA MINING; DISEASES; DRUG INTERACTIONS; FORECASTING; PROTEINS; TOXICITY;

DRUG DEVELOPMENT; DRUG SAFETY; IN-SILICO MODELS; INJURY PREDICTION; LIVER INJURIES; LIVER TOXICITY; PREDICTION SYSTEMS; PROTEIN TARGETS; SAFETY EVALUATIONS; SIDE EFFECT;

MUSCULOSKELETAL SYSTEM;

ANTIINFECTIVE AGENT; ANTIINFLAMMATORY AGENT; DRUG;

ACCURACY; ADVERSE OUTCOME; ARTICLE; CHOLECYSTITIS; CHOLELITHIASIS; COMPUTER MODEL; CONTROLLED STUDY; DISEASE SEVERITY; DRUG MARKETING; DRUG RESEARCH; DRUG SAFETY; DRUG USE; FATTY LIVER; HEPATITIS; HEPATOBILIARY DISEASE; HEPATOMEGALY; HUMAN; HYPERBILIRUBINEMIA; JAUNDICE; LIVER CIRRHOSIS; LIVER FAILURE; LIVER FUNCTION TEST; LIVER NECROSIS; LIVER TOXICITY; PREDICTIVE VALIDITY; PREDICTIVE VALUE; PROTEIN TARGETING; RISK ASSESSMENT; RISK FACTOR; SIDE EFFECT; STRUCTURE ACTIVITY RELATION; TOXIC HEPATITIS; ANIMAL; BIOLOGICAL MODEL; DRUG EFFECT; FACTUAL DATABASE; LIVER; METABOLISM;

ANIMALS; ANTI-INFECTIVE AGENTS; ANTI-INFLAMMATORY AGENTS; DATABASES, FACTUAL; DRUG-INDUCED LIVER INJURY; HUMANS; LIVER; MODELS, BIOLOGICAL; PHARMACEUTICAL PREPARATIONS; PREDICTIVE VALUE OF TESTS;

EID: 84855288564     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002310     Document Type: Article

References (50)

1. Lee WM, Squires RH Jr, Nyberg SL, Doo E, Hoofnagle JH, (2008) Acute liver failure: Summary of a workshop. Hepatology 47: 1401-1415.
2. Olson H, Betton G, Robinson D, Thomas K, Monro A, et al. (2000) Concordance of the toxicity of pharmaceuticals in humans and in animals. Regul Toxicol Pharmacol 32: 56-67.
3. Kaplowitz N, (2005) Idiosyncratic drug hepatotoxicity. Nat Rev Drug Discov 4: 489-499.
4. McKenzie R, Fried MW, Sallie R, Conjeevaram H, Di Bisceglie AM, et al. (1995) Hepatic failure and lactic acidosis due to fialuridine (FIAU), an investigational nucleoside analogue for chronic hepatitis B. N Engl J Med 333: 1099-1105.
5. Navarro VJ, Senior JR, (2006) Drug-related hepatotoxicity. N Engl J Med 354: 731-739.
6. Shi Q, Hong H, Senior J, Tong W, (2010) Biomarkers for drug-induced liver injury. Expert Rev Gastroenterol Hepatol 4: 225-234.
7. Xu JHJ, Henstock PV, Dunn MC, Smith AR, Chabot JR, et al. (2008) Cellular imaging predictions of clinical drug-induced liver injury. Toxicol Sci 105: 97-105.
8. Hosomi H, Fukami T, Iwamura A, Nakajima M, Yokoi T, (2011) Development of A Highly Sensitive Cytotoxicity Assay System for CYP3A4-mediated Metabolic Activation. Drug Metab Dispos 39: 1388-1395.
9. Deng XM, Luyendyk JP, Ganey PE, Roth RA, (2009) Inflammatory Stress and Idiosyncratic Hepatotoxicity: Hints from Animal Models. Pharmacol Rev 61: 262-282.
10. Boelsterli UA, Lim PLK, (2007) Mitochondrial abnonnalities- A link to idiosyncratic drug hepatotoxicity? Toxicol Appl Pharmacol 220: 92-107.
11. Anderson N, Meier T, Borlak Jr, (2009) Toxicogenomics Applied to Cultures of Human Hepatocytes Enabled an Identification of Novel Petasites hybridus Extracts for the Treatment of Migraine with Improved Hepatobiliary Safety. Toxicol Sci 112: 507-520.
12. Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P, (2010) A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol 6: 6.
13. Chen M, Vijay V, Shi Q, Liu Z, Fang H, et al. (2011) FDA-approved drug labeling for the study of drug-induced liver injury. Drug Discov Today 16: 697-703.
14. Greene N, Fisk L, Naven RT, Note RR, Patel ML, et al. (2010) Developing Structure-Activity Relationships for the Prediction of Hepatotoxicity. Chem Res Toxicol 23: 1215-1222.
15. O'Brien PJ, Irwin W, Diaz D, Howard-Cofield E, Krejsa CM, et al. (2006) High concordance of drug-induced human hepatotoxicity with in vitro cytotoxicity measured in a novel cell-based model using high content screening. Arch Toxicol 80: 580-604.
16. Yildirim MA, Goh KI, Cusick ME, Barabasi AL, Vidal M, (2007) Drug-target network. Nat Biotechnol 25: 1119-1126.
17. Hopkins AL, (2009) Drug Discovery: Predicting promiscuity. Nature 462: 167-168.
18. Fourches D, Barnes JC, Day NC, Bradley P, Reed JZ, et al. (2010) Cheminformatics Analysis of Assertions Mined from Literature That Describe Drug-Induced Liver Injury in Different Species. Chem Res Toxicol 23: 171-183.
19. Ekins S, Williams AJ, Xu JJ, (2010) A Predictive Ligand-Based Bayesian Model for Human Drug-Induced Liver Injury. Drug Metab Dispos 38: 2302-2308.
20. (2009) Translational medicine. Nat Rev Drug Discov 8: 593-593.
21. Daly AK, Day CP, (2009) Genetic Association Studies in Drug-Induced Liver Injury. Semin Liver Dis 29: 400-411.
22. Yan B, Leung Y, Urbanski SJ, Myers RP, (2006) Rofecoxib-induced hepatotoxicity: A forgotten complication of the coxibs. Can J Gastroenterol 20: 351-355.
23. Singer JB, Lewitzky S, Leroy E, Yang F, Zhao XJ, et al. (2010) A genome-wide study identifies HLA alleles associated with lumiracoxib-related liver injury. Nat Genet 42: 711-U794.
24. Aithal GP, (2011) Hepatotoxicity related to antirheumatic drugs. Nat Rev Rheumatol 7: 139-150.
25. Nacher JC, Schwartz JM, (2008) A global view of drug-therapy interactions. BMC Pharmacol 8: 5-13.
26. Daly AK, Donaldson PT, Bhatnagar P, Shen YF, Pe'er I, et al. (2009) HLA-B(star)5701 genotype is a major determinant of drug-induced liver injury due to flucloxacillin. Nat Genet 41: 816-U871.
27. Thibaudeau J, Lepine J, Tojcic J, Duguay Y, Pelletier G, et al. (2006) Characterization of common UGT1A8, UGT1A9, and UGT2B7 variants with different capacities to inactivate mutagenic 4-hydroxylated metabolites of estradiol and estrone. Cancer Res 66: 125-133.
28. Duguay Y, Baar C, Skorpen F, Guillemette C, (2004) A novel functional polymorphism in the uridine diphosphate-glucuronosyltransferase 2B7 promoter with significant impact on promoter activity. Clin Pharmacol Ther 75: 223-233.
29. Daly AK, Aithal GP, Leathart JBS, Swainsbury RA, Dang TS, et al. (2007) Genetic susceptibility to diclofenac-induced hepatotoxicity: Contribution of UGT2B7, CYP2C8, and ABCC2 genotypes. Gastroenterology 132: 272-281.
30. Jensen LE, Wall AM, Cook M, Hoess K, Thorn CF, et al. (2004) A common ABCC2 promoter polymorphism is not a determinant of the risk of spina bifida. Birth Defects Res Part A 70: 396-399.
31. Morison WL, Baughman RD, Day RM, Forbes PD, Hoenigsmann H, et al. (1998) Consensus workshop on the toxic effects of long-term PUVA therapy. Arch Dermatol 134: 595-598.
32. Sharma SK, Balamurugan A, Saha PK, Pandey RM, Mehra NK, (2002) Evaluation of clinical and immunogenetic risk factors for the development of hepatotoxicity during antituberculosis treatment. Am J Respir Crit Care Med 166: 916-919.
33. Hirata K, Takagi H, Yamamoto M, Matsumoto T, Nishiya T, et al. (2008) Ticlopidine-induced hepatotoxicity is associated with specific human leukocyte antigen genomic subtypes in Japanese patients: a preliminary case-control study. Pharmacogenomics J 8: 29-33.
34. Kindmark A, Jawaid A, Harbron CG, Barratt BJ, Bengtsson OF, et al. (2008) Genome-wide pharmacogenetic investigation of a hepatic adverse event without clinical signs of immunopathology suggests an underlying immune pathogenesis. Pharmacogenomics J 8: 186-195.
35. O'Donohue J, Oien KA, Donaldson P, Underhill J, Clare M, et al. (2000) Co-amoxiclav jaundice: clinical and histological features and HLA class II association. Gut 47: 717-720.
36. Russmann S, Jetter A, Kullak-Ublick GA, (2010) Pharmacogenetics of Drug-Induced Liver Injury. Hepatology 52: 748-761.
37. Andrade RJ, Robles M, Ulzurrun E, Lucena MI, (2009) Drug-induced liver injury: insights from genetic studies. Pharmacogenomics 10: 1467-1487.
38. Wilke RA, Lin DW, Roden DM, Watkins PB, Flockhart D, et al. (2007) Identifying genetic risk factors for serious adverse drug reactions: current progress and challenges. Nat Rev Drug Discov 6: 904-916.
39. Hamburg MA, (2011) Advancing Regulatory Science. Science 331: 987.
40. Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, et al. (2008) DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res 36: D901-D906.
41. Wishart DS, Knox C, Guo AC, Shrivastava S, Hassanali M, et al. (2006) DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res 34: D668-D672.
42. Knox C, Law V, Jewison T, Liu P, Ly S, et al. (2011) DrugBank 3.0: a comprehensive resource for 'Omics' research on drugs. Nucleic Acids Res 39: D1035-D1041.
43. Bender A, Scheiber J, Glick M, Davies JW, Azzaoui K, et al. (2007) Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure. Chemmedchem 2: 861-873.
44. Crisman TJ, Parker CN, Jenkins JL, Scheiber J, Thoma M, et al. (2007) Understanding false positives in reporter gene assays: in silico chemogenomics approaches to prioritize cell-based HTS data. J Chem Inf Model 47: 1319-1327.
45. Glen RC, Bender A, Arnby CH, Carlsson L, Boyer S, et al. (2006) Circular fingerprints: Flexible molecular descriptors with applications from physical chemistry to ADME. Idrugs 9: 199-204.
46. Nettles JH, Jenkins JL, Bender A, Deng Z, Davies JW, et al. (2006) Bridging chemical and biological space: "Target fishing" using 2D and 3D molecular descriptors. J Med Chem 49: 6802-6810.
47. Nidhi, Glick M, Davies JW, Jenkins JL, (2006) Prediction of biological targets for compounds using multiple-category Bayesian models trained on chemogenomics databases. J Chem Inf Model 46: 1124-1133.
48. (2011) ATC The Anatomical Therapeutic Chemical (ATC) classification. WHO Collaborating Centre for Drug Statistics and Methodology Available:http://www.whocc.no/atcddd/.
49. Xu XYN, Feng Z, Schweiger TA, (2007) SCAN: a structrural clustrering algorithm for networks. pp. 824-833 In Proceedings of the 13th ACM SIGKDD international conference on Knowledge Discovery and Data Mining. San Jose, California, USA.
50. Cohen AM, Hersh WR, Dubay C, Spackman K, (2005) Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts. BMC Bioinformatics 6: 103.