To capitalize on the vast potential of patient genetic information to aid in assuring drug safety, a substantial effort is needed in both the training of healthcare professionals and the operational enablement of clinical environments. Our research aims to satisfy these needs through the development of a drug safety assurance information system (GeneScription) based on clinical genotyping that utilizes patient-specific genetic information to predict and prevent adverse drug responses. In this paper, we present the motivations for this work, the algorithms at the heart of GeneScription, and a discussion of our system and its uses. We also describe our efforts to validate GeneScription through its evaluation by practicing pharmacists and pharmacy professors and its repeated use in training pharmacists. The positive assessment of the GeneScription software tool by these domain experts provides strong validation of the importance, accuracy, and effectiveness of GeneScription. 1. Introduction The utilization of a clinical patient’s genetic data to aid diagnostic and prognostic healthcare represents the ultimate achievement of fifty years of genomic research. However, some operational, ethical, and educational challenges hinder the implementation of a societal-scale clinical genotyping system even though the technologies to carry out clinical genotyping do exist. To overcome these hurdles, we have developed a data management system (GeneScription) that utilizes patient-specific genotyping to predict and prevent adverse drug responses and thus supports the prescription drug process from physician to pharmacist to consumer. The system uses specific allelic variables associated with drug metabolism, as well as other common laboratory tests, to identify patients that are predisposed to an adverse drug reaction, and make recommendations as to the best course of action for a particular drug and patient. The GeneScription system represents the first software system of its kind in that it supports a key component of healthcare (prescription drugs) that is not ethically constrained by the prediction and prognosis of serious disease through patient-specific DNA variance and is therefore acceptable to the healthcare consumer. Moreover, since most practicing physicians and pharmacists were trained long before the utilization of human genomic information was seriously considered as a component of healthcare, educating these healthcare professionals is paramount to the future clinical genotyping adoption. To address this need, GeneScription also provides in depth training
References
[1]
Institute of Medicine Committee on Quality of Health Care in America, To Err Is Human: Building a Safer Health System, The National Academies Press, Washington, DC, USA, 2000.
[2]
J. Lazarou, B. H. Pomeranz, and P. N. Corey, “Incidence of adverse drug reactions in hospitalized patients: a meta- analysis of prospective studies,” Journal of the American Medical Association, vol. 279, no. 15, pp. 1200–1205, 1998.
[3]
T. J. Moore, M. R. Cohen, and C. D. Furberg, “Serious adverse drug events reported to the food and drug administration, 1998–2005,” Archives of Internal Medicine, vol. 167, no. 16, pp. 1752–1759, 2007.
[4]
K. Sawamura, Y. Suzuki, and T. Someya, “Effects of dosage and CYP2D6-mutated allele on plasma concentration of paroxetine,” European Journal of Clinical Pharmacology, vol. 60, no. 8, pp. 553–557, 2004.
[5]
G. P. Aithal, C. P. Day, P. J. L. Kesteven, and A. K. Daly, “Association of polymorphisms in the cytochrome P450 CYP2C9 with warfarin dose requirement and risk of bleeding complications,” Lancet, vol. 353, no. 9154, pp. 717–719, 1999.
[6]
M. I. Avigan, “Pharmacogenomic biomarkers of susceptibility to adverse drug reactions: just around the corner or pie in the sky?” Personalized Medicine, vol. 6, no. 1, pp. 67–78, 2009.
[7]
A. Doris, K. Ebmeier, and P. Shajahan, “Depressive illness,” Lancet, vol. 354, no. 9187, pp. 1369–1375, 1999.
[8]
T. A. Nguyen, J. G. Diodati, and C. Pharand, “Resistance to clopidogrel: a review of the evidence,” Journal of the American College of Cardiology, vol. 45, no. 8, pp. 1157–1164, 2005.
[9]
J. L. Mega, S. L. Close, S. D. Wiviott et al., “Cytochrome P-450 polymorphisms and response to clopidogrel,” New England Journal of Medicine, vol. 360, no. 4, pp. 354–362, 2009.
[10]
M. G. Aspinall and R. G. Hamermesh, “Realizing the promise of personalized medicine,” Harvard Business Review, vol. 85, no. 10, pp. 108–117, 2007.
[11]
W. K. Chung, “Implementation of genetics to personalize medicine,” Gender Medicine, vol. 4, no. 3, pp. 248–265, 2007.
[12]
M. D. Kane, J. A. Springer, and J. E. Sprague, “Drug safety assurance through clinical genotyping: near-term considerations for a system-wide implementation of personalized medicine,” Personalized Medicine, vol. 5, no. 4, pp. 387–397, 2008.
[13]
A. X. Garg, N. K. J. Adhikari, H. McDonald et al., “Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review,” Journal of the American Medical Association, vol. 293, no. 10, pp. 1223–1238, 2005.
[14]
A. Wright and D. F. Sittig, “A framework and model for evaluating clinical decision support architectures,” Journal of Biomedical Informatics, vol. 41, no. 6, pp. 982–990, 2008.
[15]
F. S. Dean, S. Linas, D. C. James et al., “The state of the art in clinical knowledge management: an inventory of tools and techniques,” International Journal of Medical Informatics, vol. 79, no. 1, pp. 44–57, 2010.
[16]
J. Overhage, C. J. McDonald, and J. G. Suico, “The regenstrief medical record system 2000: expanding the breadth and depth of a community wide EMR,” in Proceedings of the AMIA Symposium, p. 1173, 2000.
[17]
H. L. Chin and M. A. Krall, “Successful implementation of a comprehensive computer-based patient record system in Kaiser Permanente Northwest: strategy and experience,” Effective Clinical Practice, vol. 1, no. 2, pp. 51–60, 1998.
[18]
J. Jensen, “The effects of computerized provider order entry on medication turn-around time: a time-to-first dose study at the providence Portland Medical Center,” in Proceedings of the AMIA Annual Symposium, pp. 384–388, 2006.
[19]
G. Lechleitner, K. P. Pfeiffer, I. Wilhelmy, and M. Ball, “Cerner millennium: the innsbruck experience,” Methods of Information in Medicine, vol. 42, no. 1, pp. 8–15, 2003.
[20]
A. Naditz, “Telemedicine at the VA: VistA, MyHealtheVet, and other VA programs,” Telemedicine and e-Health, vol. 14, no. 4, pp. 330–332, 2008.
[21]
G. Hripcsak, “Arden Syntax for medical logic modules,” M.D. Computing, vol. 8, no. 2, pp. 76–78, 1991.
[22]
D. Wang, M. Peleg, S. W. Tu et al., “Design and implementation of the GLIF3 guideline execution engine,” Journal of Biomedical Informatics, vol. 37, no. 5, pp. 305–318, 2004.
[23]
S. W. Tu, J. R. Campbell, J. Glasgow et al., “The SAGE guideline model: achievements and overview,” Journal of the American Medical Informatics Association, vol. 14, no. 5, pp. 589–598, 2007.
[24]
K. Kawamoto and D. F. Lobach, “Design, implementation, use, and preliminary evaluation of Sebastian, a standards-based web service for clinical decision support,” in Proceedings of the AMIA Annual Symposium, pp. 380–384, 2005.
[25]
A. M. Marinaki, A. Ansari, J. A. Duley et al., “Adverse drug reactions to azathioptine therapy are associated with polymorphism in the gene encoding inosine triphosphate pyrophosphatase (ITPase),” Pharmacogenetics, vol. 14, no. 3, pp. 181–187, 2004.
[26]
L. J. Sheffield and H. Phillimore, “Clinical use of pharmacogenomic tests in 2009,” The Clinical Biochemistry Reviews, vol. 30, no. 7, pp. 55–65, 2009.
[27]
C. Varenhorst, S. James, D. Erlinge et al., “Genetic variation of CYP2C19 affects both pharmacokinetic and pharmacodynamic responses to clopidogrel but not prasugrel in aspirin-treated patients with coronary artery disease,” European Heart Journal, vol. 30, no. 14, pp. 1744–1752, 2009.
[28]
T. I. W. P. Consortium, “Estimation of the warfarin dose with clinical and pharmacogenetic data,” The New England Journal of Medicine, vol. 360, no. 8, pp. 753–764, 2009.
[29]
J. T. Den Dunnen and S. E. Antonarakis, “Mutation nomenclature extensions and suggestions to describe complex mutations: a discussion,” Human Mutation, vol. 15, no. 1, pp. 7–12, 2000.
[30]
B. P. King, T. I. Khan, G. P. Aithal, F. Kamali, and A. K. Daly, “Upstream and coding region CYP2C9 polymorphisms: correlation with warfarin dose and metabolism,” Pharmacogenetics, vol. 14, no. 12, pp. 813–822, 2004.
[31]
K. E. Thummel, D. D. Shen, N. Isoherranen, and H. E. Smith, “Design and optimization of dosage regimens: pharmacokinetic data,” in Goodman & Gilman’s The Pharmacological Basis of Therapeutics, McGraw Hill, New York, NY, USA, 2006.
[32]
Food and Drug Administration, Orange Book: Approved Drug Products with Therapeutic Equivalence Evaluations, 2010.
[33]
T. E. Klein, J. T. Chang, M. K. Cho, et al., “Integrating genotype and phenotype information: an overview of the PharmGKB project,” Pharmacogenomics Journal, vol. 1, no. 3, pp. 167–170, 2001.
[34]
A. B. Almarsdóttir, I. Bj?rnsdóttir, and J. M. Traulsen, “A lay prescription for tailor-made drugs - Focus group reflections on pharmacogenomics,” Health Policy, vol. 71, no. 2, pp. 233–241, 2005.
[35]
J. L. Bevan, J. A. Lynch, T. N. Dubriwny et al., “Informed lay preferences for delivery of racially varied pharmacogenomics,” Genetics in Medicine, vol. 5, no. 5, pp. 393–399, 2003.
[36]
J. A. Springer, J. Beever, N. Morar, J. E. Sprague, and M. D. Kane, “Ethics, privacy and the future of genetic information in healthcare information assurance and security,” in Information Assurance and Security Ethics in Complex Systems: Interdisciplinary Perspectives, M. J. Dark, Ed., Information Science Reference, Hershey, Pa, USA, 2011.
[37]
M. J. Dark, Information Assurance and Security Ethics in Complex Systems: Interdisciplinary Perspectives, Information Science Reference, Hershey, Pa, USA, 2011.
[38]
N. H. Lobas, P. W. Lepinski, and P. W. Abramowitz, “Effects of pharmaceutical care on medication cost and quality of patient care in an ambulatory-care clinic,” American Journal of Hospital Pharmacy, vol. 49, no. 7, pp. 1681–1688, 1992.
[39]
T. R. Pauley, M. J. Magee, and J. D. Cury, “Pharmacist-managed, physician-directed asthma management program reduces emergency department visits,” Annals of Pharmacotherapy, vol. 29, no. 1, pp. 5–9, 1995.
[40]
W. R. Doucette and T. N. Andersen, “Practitioner activities in patient education and drug therapy monitoring for community dwelling elderly patients,” Patient Education and Counseling, vol. 57, no. 2, pp. 204–210, 2005.