Advertisement

Key Elements in Adverse Drug Reactions Safety Signals: Application of Legal Strategies

  • Brian ChenEmail author
  • John Restaino
  • Elizabeth Tippett
Chapter
Part of the Cancer Treatment and Research book series (CTAR, volume 171)

Abstract

Adverse drug reactions, or unintended and harmful outcomes related to the administration of a pharmaceutical product, are a major public health concern, particularly for cancer patients. If counted as a separate cause of death, adverse drug reactions would represent the fourth leading cause of death in the United States. Several legal strategies are available to help mitigate their occurrences and to compensate victims for the harm that results from adverse events. Prior to FDA approval of a drug, the limited size and duration of clinical trials often fail to detect adverse drug reactions. However, after FDA approval, pharmacovigilance efforts are bolstered by recent expansions of FDA post-marketing regulatory powers codified in the 2007 Food and Drug Administration Amendments Act, as well as advances in big data analytics that improve adverse signal detection through data mining of large electronic health records. For victims of adverse drug reactions, tort lawsuits filed in the courts help compensate for the harm suffered and may also serve as warnings to manufacturers to improve drug safety to avoid future legal liability. While encouraging developments have occurred, new and existing legal structures to mitigate and compensate for adverse drug reactions must continue to be refined given increasingly complex pharmaceutical agents.

Keywords

Adverse drug reactions Federal law State tort law Food and Drug Administration Drug safety Pharmacovigilance Electronic data mining 

References

  1. 1.
    Allison M. Reinventing clinical trials. Nat Biotech. 2012;30(1):41–9.CrossRefGoogle Scholar
  2. 2.
    Almenoff JS, et al. Novel statistical tools for monitoring the safety of marketed drugs. Clin Pharmacol Ther 2007;82:157–166.CrossRefGoogle Scholar
  3. 3.
    Aspden P, et al. Preventing medication errors. Washington, DC: National Academies Press; 2007.Google Scholar
  4. 4.
    Bailey S, et al. Prospective data mining of six products in the US FDA adverse event reporting system. Drug Saf. 2010;33(2):139–46.PubMedCrossRefGoogle Scholar
  5. 5.
    Behrman RE, et al. Developing the sentinel system—a national resource for evidence development. N Engl J Med. 2011;364(6):498–9.PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Bombardier, C. (2000) “Comparison of Gastrointestinal Toxicity of Rofecoxib and Naproxen in Patients with Rheumatoid Arthritis,” 340:1520 New England Journal of Medicine.Google Scholar
  7. 7.
    Breckenridge A, et al. New horizons in pharmaceutical regulation. Nat Rev Drug Discov. 2012;11(7):501–2.PubMedCrossRefGoogle Scholar
  8. 8.
    Carpenter D, et al. The complications of controlling agency time discretion: FDA review deadlines and postmarket drug safety. Am J Polit Sci. 2012;56(1):98–114.CrossRefGoogle Scholar
  9. 9.
    Center for Drug Evaluation and Research. U.S. Food and drug administration, statement of Sandra Kweder before the United States Senate Committee on Finance, 108th Congress, Second Session. 2004.Google Scholar
  10. 10.
    Chandler v. Simpson (2000), 100 Wash.App. 1034.Google Scholar
  11. 11.
    Ciociola AA, et al. How drugs are developed and approved by the FDA: current process and future directions. Am J Gastroenterol. 2014;109(5):620–3.CrossRefGoogle Scholar
  12. 12.
    Desai CK, et al. An evaluation of knowledge, attitude, and practice of adverse drug reaction reporting among prescribers at a tertiary care hospital. Perspect Clin Res. 2011;2(4):129.PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Duijnhoven RG, et al. Number of patients studied prior to approval of new medicines: a database analysis. PLoS Med. 2013;10(3):e1001407.PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Edwards IR, Aronson JK. Adverse drug reactions: definitions, diagnosis, and management. The Lancet. 2000;356(9237):1255–9.CrossRefGoogle Scholar
  15. 15.
    El Emam K, et al. A secure distributed logistic regression protocol for the detection of rare adverse drug events. J Am Med Inform Assoc. 2013;20(3):453–61.PubMedCrossRefGoogle Scholar
  16. 16.
    Faich G, Morris J. Adverse reaction signaling and disproportionality analysis: an update. Drug Inf J. 2012;46(6):708–714.CrossRefGoogle Scholar
  17. 17.
    FDA. FDA Adverse Event Reporting System (FAERS) statistics. Retrieved 7 June 2016 from http://www.fda.gov/drugs/guidancecomplianceregulatoryinformation/surveillance/adversedrugeffects/ucm070093.htm (2014).
  18. 18.
    FDA Letter 1. Letter from Joyce Korvick to Alaven Pharmaceuticals. Retrieved 8 June 2016 from http://www.accessdata.fda.gov/drugsatfda_docs/appletter/2009/017854s052_021793s005ltr.pdf (2009).
  19. 19.
    Fine LA. Drug safety surveillance: Pharmacovigilance in FDA/CDER. Retrieved 8 June 2016 from http://www.fda.gov/downloads/AboutFDA/WorkingatFDA/FellowshipInternshipGraduateFacultyPrograms/PharmacyStudentExperientialProgramCDER/UCM340626.pdf. (2013).
  20. 20.
    Food and Drug Administration Amendments Act of 2007, 21 U.S.C. § 355 et seq.Google Scholar
  21. 21.
    Food and Drug Administration. Risk Evaluation and Mitigation Strategies (REMS). Retrieved 28 Nov 2018 from https://www.fda.gov/Drugs/DrugSafety/REMS/default.htm. (2010)
  22. 22.
    Gagne JJ, et al. Active safety monitoring of new medical products using electronic healthcare data: selecting alerting rules. Epidemiology (Cambridge, Mass.). 2012;23(2):238.Google Scholar
  23. 23.
    Government Accountability Office. Drug safety: improvement needed in FDA’s postmarket decision-making and oversight process. GAO-06-402. Washington, DC: GAO; 2006.Google Scholar
  24. 24.
    Greenfieldboyce N. Big data peeps at your medical records to find drug problems. Retrieved 8 June 2016 from http://www.npr.org/sections/health-shots/2014/07/21/332290342/big-data-peeps-at-your-medical-records-to-find-drug-problems (2014).
  25. 25.
    Hakala A, et al. Accessibility of trial reports for drugs stalling in development: a systematic assessment of registered trials (2015).PubMedCrossRefGoogle Scholar
  26. 26.
    Harpaz R, et al. Mining multi-item drug adverse effect associations in spontaneous reporting systems. BMC Bioinformatics. 2010;11(Suppl 9):S7.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Harpaz R, et al. Novel data-mining methodologies for adverse drug event discovery and analysis. Clin Pharmacol Ther. 2012;91(6):1010–21.PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Harpaz R, et al. Combing signals from spontaneous reports and electronic health records for detection of adverse drug reactions. J Am Med Inform Assoc. 2013;20:413–9.PubMedCrossRefGoogle Scholar
  29. 29.
    Harpaz R, et al. Performance of pharmacovigilance signal-detection algorithms for the FDA adverse event reporting system. Clin Pharmacol Ther. 2013;93(6):539–46.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Hochberg A, Hauben M. Time-to-signal comparison for drug safety data-mining algorithms vs. traditional signaling criteria. Clin. Pharmacol Ther. 2009;85(6):600–606.CrossRefGoogle Scholar
  31. 31.
    Hutt P, Merrill R, Grossman L. Food and drug law (2007).Google Scholar
  32. 32.
    In Re Vioxx Litigation, 395 N.J. Super. 358, 928 A.2d 935 (2007)Google Scholar
  33. 33.
    Iyer SV, et al. Learning signals of adverse drug-drug interactions from the Unstructured Text of Electronic Health Records. AMIA Summits on Transl Sci Proc. 2013;2013:83.Google Scholar
  34. 34.
    Johnson JR, et al. Accelerated approval of oncology products: the food and drug administration experience. J Natl Cancer Inst. 2011;103(8):636–44.PubMedCrossRefGoogle Scholar
  35. 35.
    Kaplan S, Staffa JA, Dal Pan GJ. Duration of therapy with metoclopramide: a prescription claims data study. Pharmacoepidemiol Drug Saf. 2007;16:878–81.PubMedCrossRefGoogle Scholar
  36. 36.
    Kesselheim AS, et al. Existing FDA pathways have potential to ensure early access to, and appropriate use of, specialty drugs. Health Aff. 2014;33(10):1770–8.CrossRefGoogle Scholar
  37. 37.
    Lexchin J. New drugs and safety: what happened to new active substances approved in Canada between 1995 and 2010? Arch Intern Med. 2012;172(21):1680–1.PubMedCrossRefGoogle Scholar
  38. 38.
    Light DW, Lexchin J. Why do cancer drugs get such an easy ride? BMJ. 2015;350:h2068.PubMedCrossRefGoogle Scholar
  39. 39.
    Light DW, et al. Institutional corruption of pharmaceuticals and the myth of safe and effective drugs. J Law Med Ethics. 2013;41(3):590–600.PubMedCrossRefGoogle Scholar
  40. 40.
    Lindquist M. VigiBase, the WHO global ICSR database system: basic facts. Drug Inf J. 2008;42(5):409–19.CrossRefGoogle Scholar
  41. 41.
    Liu M, et al. Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs. J Am Med Inform Assoc. 2012;19(e1):e28–35.PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Liu M, et al. Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records. J Am Med Inform Assoc. 2013;20(3):420–6.PubMedCrossRefGoogle Scholar
  43. 43.
    Lynberg MC, Khoury MJ, Lammer EJ, Walker KO, Cordero JF, Erickson JD. Sensitivity, specificity and positive predictive value of multiple malformations in isotretinoin embryopathy surveillance. Teratology. 1990;42(5):513–9.PubMedCrossRefGoogle Scholar
  44. 44.
    Marengoni A, Onder G. Guidelines, polypharmacy, and drug-drug interactions in patients with multimorbidity. BMJ. 2015;350:h1059.PubMedCrossRefGoogle Scholar
  45. 45.
    McGuire S. US Department of Agriculture and US Department of Health and Human Services, Dietary Guidelines for Americans, 2010. Washington, DC: US Government Printing Office, January 2011. Adv Nutr: An Int Rev J. 2011;2(3):293–294.Google Scholar
  46. 46.
    Mini-Sentinel. About mini-sentinel: background. Retrieved 8 June 2015 from http://www.mini-sentinel.org/about_us/default.aspx (2014).
  47. 47.
    Moore TJ, et al., editors. ISMP quarter watch. Horsham, PA: Institute for Safe Medication Practices; 2012.Google Scholar
  48. 48.
    Moses C, et al. Pharmacovigilance: an active surveillance system to proactively identify risks for adverse events. Popul Health Manag. 2013;16(3):147–9.PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    O’Reilly, Van Tassel. Food and drug administration. 4th ed; 2014.Google Scholar
  50. 50.
    Pal SN, et al. WHO strategy for collecting safety data in public health programmes: complementing spontaneous reporting systems. Drug Saf. 2013;36(2):75–81.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Pasricha PJ, Pelivanov N. Drug insight: from disturbed motility to disordered movement: a review of the clinical benefits and medicolegal risks of metoclopramide. Nat Clin Pract Gastroenterol Hepatol. 2006;3(3):138.PubMedCrossRefGoogle Scholar
  52. 52.
    Psaty B. Statement before the United States Senate Committee on Finance, 108th Congress, Second Session. 2004.Google Scholar
  53. 53.
    Phelps v. Wyeth, Inc. 938 F. Supp. 2d 1055 (2013).Google Scholar
  54. 54.
    Poluzzi E, et al. Drug-induced torsades de pointes: data mining of the public version of the FDA Adverse Event Reporting System (AERS). Pharmacoepidemiol Drug Saf. 2009;18(6):512–8.PubMedCrossRefGoogle Scholar
  55. 55.
    Robb MA, et al. The US food and drug administration’s sentinel initiative: expanding the horizons of medical product safety. Pharmacoepidemiol Drug Saf. 2012;21(S1):9–11.CrossRefGoogle Scholar
  56. 56.
    Rosenstern v. Allergan. 987 F. Supp. 2d 795 (2013).Google Scholar
  57. 57.
    Schuemie MJ. Methods for drug safety signal detection in longitudinal observational databases: LGPS and LEOPARD. Pharmacoepidemiol Drug Saf. 2011;20(3):292–9.PubMedCrossRefGoogle Scholar
  58. 58.
    Schuemie MJ, et al. Using electronic health care records for drug safety signal detection: a comparative evaluation of statistical methods. Med Care. 2012;50(10):890–7.PubMedCrossRefGoogle Scholar
  59. 59.
    Sherman RE, et al. Expediting drug development—the FDA’s new “Breakthrough Therapy” designation. N Engl J Med. 2013;369(20):1877–80.PubMedCrossRefGoogle Scholar
  60. 60.
    Star K, et al. Longitudinal medical records as a complement to routine drug safety signal analysis. Pharmacoepidemiol Drug Saf. 2015;24(5):486–94.PubMedPubMedCentralCrossRefGoogle Scholar
  61. 61.
    Stephenson C. Yaz, Yasmin may cost Bayer $1.2 billion. Lawyers Weekly USA. 2012.Google Scholar
  62. 62.
    Strandell J, et al. The development and evaluation of triage algorithms for early discovery of adverse drug interactions. Drug Saf. 2013;36(5):371–88.PubMedCrossRefGoogle Scholar
  63. 63.
    Tomlin A, et al. Methods for retrospective detection of drug safety signals and adverse events in electronic general practice records. Drug Saf. 2012;35(9):733–43.PubMedCrossRefGoogle Scholar
  64. 64.
    Trifirò G, et al. Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: why and how? J Intern Med. 2014;275(6):551–61.PubMedCrossRefGoogle Scholar
  65. 65.
    Vioxx Litigation. In re: Vioxx products liability litigation, 501 F. Supp. 2d 776 (E.D. La. 2007).Google Scholar
  66. 66.
    Wahab IA, et al. Comparing time to adverse drug reaction signals in a spontaneous reporting database and a claims database: a case study of rofecoxib-induced myocardial infarction and rosiglitazone-induced heart failure signals in Australia. Drug Saf. 2014;37(1):53–64.CrossRefGoogle Scholar
  67. 67.
    Wang H-W, et al. An experimental investigation of masking in the US FDA adverse event reporting system database. Drug Saf. 2010;33(12):1117–33.PubMedCrossRefGoogle Scholar
  68. 68.
    WHO. International drug monitoring: the role of national centres. Tech Rep Serv WHO. 1972;492.Google Scholar
  69. 69.
    Yoon D, et al. Detection of adverse drug reaction signals using an electronic health records database: comparison of the laboratory extreme abnormality ratio (CLEAR) algorithm. Clin Pharmacol Ther. 2012;91(3):467–74.PubMedCrossRefGoogle Scholar
  70. 70.
    Zorych I, et al. Disproportionality methods for pharmacovigilance in longitudinal observational databases. Stat Methods Med Res. 2013;22(1):39–56.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of South CarolinaColumbiaUSA

Personalised recommendations