Skip to main content
SpringerLink
Log in

Towards Personalized Antithrombotic Treatments: Focus on P2Y12 Inhibitors and Direct Oral Anticoagulants

  • Review Article
  • Published:
Clinical Pharmacokinetics Aims and scope Submit manuscript

Abstract

Oral anticoagulants and antiplatelet drugs are commonly prescribed to lower the risk of cardiovascular diseases, such as venous and arterial thrombosis, which represent the leading causes of mortality worldwide. A significant percentage of patients taking antithrombotics will nevertheless experience bleeding or recurrent ischemic events, and this represents a major public health issue. Cardiovascular medicine is now questioning the one-size-fits-all policy, and more personalized approaches are increasingly being considered. However, the available tools are currently limited and they are only moderately able to predict clinical events or have a significant impact on clinical outcomes. Predicting concentrations of antithrombotics in blood could be an effective means of personalization as they have been associated with bleeding and recurrent ischemia. Target concentration interventions could take advantage of physiologically based pharmacokinetic (PBPK) and population-based pharmacokinetic (POPPK) models, which are increasingly used in clinical settings and have attracted the interest of governmental regulatory agencies, to propose dosages adapted to specific population characteristics. These models have the benefit of combining parameters from different sources, such as experimental in vitro data and patients’ demographic, genetic, and physiological in vivo data, to characterize the dose–concentration relationships of compounds of interest. As such, they can be used to predict individual drug exposure. In the near future, these models could therefore be a valuable means of predicting personalized antithrombotic blood concentrations and, hopefully, of preventing clinical non-response or bleeding in a given patient. Existing approaches for personalization of antithrombotic prescriptions will be reviewed using practical examples for P2Y12 inhibitors and direct oral anticoagulants. The review will additionally focus on the existing PBPK and POPPK models for these two categories of drugs. Lastly, we address potential scenarios for their implementation in clinics, along with the main limitations and challenges.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Sibbing D, Spannagl M. Direct oral anticoagulants and antiplatelet agents. Clinical relevance and options for laboratory testing. Hamostaseologie. 2014;34(1):78–84.

    Article  CAS  PubMed  Google Scholar 

  2. World Health Organization. The top 10 causes of death. 2017 (updated). https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death. Accessed 1 Jun 2019.

  3. Houser SR. The American Heart Association’s New Institute for Precision Cardiovascular Medicine. Circulation. 2016;134(24):1913–4.

    Article  PubMed  Google Scholar 

  4. Lee CW, Ahn JM, Park DW, Kang SJ, Lee SW, Kim YH, et al. Optimal duration of dual antiplatelet therapy after drug-eluting stent implantation: a randomized, controlled trial. Circulation. 2014;129(3):304–12.

    Article  CAS  PubMed  Google Scholar 

  5. Larsen TB, Skjoth F, Nielsen PB, Kjaeldgaard JN, Lip GY. Comparative effectiveness and safety of non-VKA oral anticoagulants and warfarin in patients with atrial fibrillation: propensity weighted nationwide cohort study. BMJ. 2016;353:i3189.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Ntaios G, Papavasileiou V, Diener HC, Makaritsis K, Michel P. Nonvitamin-K-antagonist oral anticoagulants in patients with atrial fibrillation and previous stroke or transient ischemic attack: a systematic review and meta-analysis of randomized controlled trials. Stroke. 2012;43(12):3298–304.

    Article  CAS  PubMed  Google Scholar 

  7. Valgimigli M, Bueno H, Byrne RA, Collet JP, Costa F, Jeppsson A, et al. 2017 ESC focused update on dual antiplatelet therapy in coronary artery disease developed in collaboration with EACTS: the Task Force for dual antiplatelet therapy in coronary artery disease of the European Society of Cardiology (ESC) and of the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2018;39(3):213–60.

    Article  PubMed  Google Scholar 

  8. Levine GN, Bates ER, Bittl JA, Brindis RG, Fihn SD, Fleisher LA, et al. 2016 ACC/AHA guideline focused update on duration of dual antiplatelet therapy in patients with coronary artery disease: a report of the American College of Cardiology/American Heart Association Task Force on clinical practice guidelines: an update of the 2011 ACCF/AHA/SCAI Guideline for Percutaneous Coronary Intervention, 2011 ACCF/AHA Guideline for Coronary Artery Bypass Graft Surgery, 2012 ACC/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the diagnosis and management of patients with stable ischemic heart disease, 2013 ACCF/AHA guideline for the management of ST-elevation myocardial infarction, 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes, and 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery. Circulation. 2016;134(10):e123–55.

    Article  PubMed  Google Scholar 

  9. Lee CH, Cheng CL, Kao Yang YH, Chao TH, Chen JY, Li YH. Cardiovascular and bleeding risks in acute myocardial infarction newly treated with ticagrelor vs. clopidogrel in Taiwan. Circ J. 2018;82(3):747–56.

    Article  CAS  PubMed  Google Scholar 

  10. Zeymer U, Widimsky P, Danchin N, Lettino M, Bardaji A, Barrabes JA, et al. P2Y12 receptor inhibitors in patients with non-ST-elevation acute coronary syndrome in the real world: use, patient selection, and outcomes from contemporary European registries. Eur Heart J Cardiovasc Pharmacother. 2016;2(4):229–43.

    Article  CAS  PubMed  Google Scholar 

  11. Alexopoulos D, Xanthopoulou I, Deftereos S, Hamilos M, Sitafidis G, Kanakakis I, et al. Contemporary antiplatelet treatment in acute coronary syndrome patients undergoing percutaneous coronary intervention: 1-year outcomes from the GReek AntiPlatElet (GRAPE) Registry. J Thromb Haemost. 2016;14(6):1146–54.

    Article  CAS  PubMed  Google Scholar 

  12. Ako J, Morino Y, Okuizumi K, Usami M, Nakamura M. Japanese postmarketing surveillance of clopidogrel in patients with non-ST-segment elevation acute coronary syndrome, stable angina, old myocardial infarction, and ST-segment elevation myocardial infarction after percutaneous coronary intervention in a real-life setting: the final report (J-PLACE Final). Cardiovasc Interv Ther. 2016;31(2):101–13.

    Article  CAS  PubMed  Google Scholar 

  13. Beyer-Westendorf J, Forster K, Pannach S, Ebertz F, Gelbricht V, Thieme C, et al. Rates, management, and outcome of rivaroxaban bleeding in daily care: results from the Dresden NOAC registry. Blood. 2014;124(6):955–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Graham DJ, Reichman ME, Wernecke M, Hsueh YH, Izem R, Southworth MR, et al. Stroke, bleeding, and mortality risks in elderly medicare beneficiaries treated with dabigatran or rivaroxaban for nonvalvular atrial fibrillation. JAMA Intern Med. 2016;176(11):1662–71.

    Article  PubMed  Google Scholar 

  15. Sahlen A, Varenhorst C, Lagerqvist B, Renlund H, Omerovic E, Erlinge D, et al. Outcomes in patients treated with ticagrelor or clopidogrel after acute myocardial infarction: experiences from SWEDEHEART registry. Eur Heart J. 2016;37(44):3335–42.

    Article  CAS  PubMed  Google Scholar 

  16. Shehab N, Lovegrove MC, Geller AI, Rose KO, Weidle NJ, Budnitz DS. US emergency department visits for outpatient adverse drug events, 2013–2014. JAMA. 2016;316(20):2115–25.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Shehab N, Sperling LS, Kegler SR, Budnitz DS. National estimates of emergency department visits for hemorrhage-related adverse events from clopidogrel plus aspirin and from warfarin. Arch Intern Med. 2010;170(21):1926–33.

    Article  PubMed  Google Scholar 

  18. Van Staa TP, Setakis E, Di Tanna GL, Lane DA, Lip GY. A comparison of risk stratification schemes for stroke in 79,884 atrial fibrillation patients in general practice. J Thromb Haemost. 2011;9(1):39–48.

    Article  PubMed  Google Scholar 

  19. Matteau A, Yeh RW, Camenzind E, Steg PG, Wijns W, Mills J, et al. Balancing long-term risks of ischemic and bleeding complications after percutaneous coronary intervention with drug-eluting stents. Am J Cardiol. 2015;116(5):686–93.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Yeh RW, Secemsky EA, Kereiakes DJ, Normand SL, Gershlick AH, Cohen DJ, et al. Development and validation of a prediction rule for benefit and harm of dual antiplatelet therapy beyond 1 year after percutaneous coronary intervention. JAMA. 2016;315(16):1735–49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Costa F, van Klaveren D, James S, Heg D, Raber L, Feres F, et al. Derivation and validation of the predicting bleeding complications in patients undergoing stent implantation and subsequent dual antiplatelet therapy (PRECISE-DAPT) score: a pooled analysis of individual-patient datasets from clinical trials. Lancet. 2017;389(10073):1025–34.

    Article  PubMed  Google Scholar 

  22. Steinberg BA, Shrader P, Pieper K, Thomas L, Allen LA, Ansell J, et al. Frequency and outcomes of reduced dose non-vitamin K antagonist anticoagulants: results from ORBIT-AF II (The Outcomes Registry for Better Informed Treatment of Atrial Fibrillation II). J Am Heart Assoc. 2018;7(4):e007633.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Parikh RB, Schwartz JS, Navathe AS. Beyond genes and molecules—a precision delivery initiative for precision medicine. N Engl J Med. 2017;376(17):1609–12.

    Article  PubMed  Google Scholar 

  24. Nimmesgern E, Benediktsson I, Norstedt I. Personalized Medicine in Europe. Clin Transl Sci. 2017;10(2):61–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Jameson JL, Longo DL. Precision medicine–personalized, problematic, and promising. N Engl J Med. 2015;372(23):2229–34.

    Article  CAS  PubMed  Google Scholar 

  26. Neumann FJ, Sousa-Uva M, Ahlsson A, Alfonso F, Banning AP, Benedetto U, et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. Eur Heart J. 2019;40(2):87–165.

    Article  PubMed  Google Scholar 

  27. Yusuf S, Zhao F, Mehta SR, Chrolavicius S, Tognoni G, Fox KK, et al. Effects of clopidogrel in addition to aspirin in patients with acute coronary syndromes without ST-segment elevation. N Engl J Med. 2001;345(7):494–502.

    Article  CAS  PubMed  Google Scholar 

  28. Wiviott SD, Braunwald E, McCabe CH, Montalescot G, Ruzyllo W, Gottlieb S, et al. Prasugrel versus clopidogrel in patients with acute coronary syndromes. N Engl J Med. 2007;357(20):2001–15.

    Article  CAS  PubMed  Google Scholar 

  29. Wallentin L, Becker RC, Budaj A, Cannon CP, Emanuelsson H, Held C, et al. Ticagrelor versus clopidogrel in patients with acute coronary syndromes. N Engl J Med. 2009;361(11):1045–57.

    Article  CAS  PubMed  Google Scholar 

  30. European Medecines Agency. Plavix product information. Last updated 5 Dec 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/plavix#product-information-section. Accessed 1 Jun 2019.

  31. European Medecines Agency. Brilique product information. Last updated 30 May 2017. https://www.ema.europa.eu/en/medicines/human/EPAR/brilique#product-information-section. Accessed 1 Jun 2019.

  32. European Medecines Agency. Efient product information. Last updated 18 Jan 2019. https://www.ema.europa.eu/en/medicines/human/EPAR/efient#product-information-section. Accessed 1 Jun 2019.

  33. Eikelboom JW, Mehta SR, Anand SS, Xie C, Fox KA, Yusuf S. Adverse impact of bleeding on prognosis in patients with acute coronary syndromes. Circulation. 2006;114(8):774–82.

    Article  PubMed  Google Scholar 

  34. Secemsky EA, Matteau A, Yeh RW, Steg PG, Camenzind E, Wijns W, et al. Comparison of short- and long-term cardiac mortality in early versus late stent thrombosis (from Pooled PROTECT Trials). Am J Cardiol. 2015;115(12):1678–84.

    Article  PubMed  Google Scholar 

  35. Mallouk N, Labruyere C, Reny JL, Chapelle C, Piot M, Fontana P, et al. Prevalence of poor biological response to clopidogrel: a systematic review. Thromb Haemost. 2012;107(3):494–506.

    Article  CAS  PubMed  Google Scholar 

  36. Wallentin L, Varenhorst C, James S, Erlinge D, Braun OO, Jakubowski JA, et al. Prasugrel achieves greater and faster P2Y12receptor-mediated platelet inhibition than clopidogrel due to more efficient generation of its active metabolite in aspirin-treated patients with coronary artery disease. Eur Heart J. 2008;29(1):21–30.

    Article  CAS  PubMed  Google Scholar 

  37. Gurbel PA, Bliden KP, Butler K, Tantry US, Gesheff T, Wei C, et al. Randomized double-blind assessment of the ONSET and OFFSET of the antiplatelet effects of ticagrelor versus clopidogrel in patients with stable coronary artery disease: the ONSET/OFFSET study. Circulation. 2009;120(25):2577–85.

    Article  CAS  PubMed  Google Scholar 

  38. Hulot JS, Bura A, Villard E, Azizi M, Remones V, Goyenvalle C, et al. Cytochrome P450 2C19 loss-of-function polymorphism is a major determinant of clopidogrel responsiveness in healthy subjects. Blood. 2006;108(7):2244–7.

    Article  CAS  PubMed  Google Scholar 

  39. Bauer T, Bouman HJ, van Werkum JW, Ford NF, ten Berg JM, Taubert D. Impact of CYP2C19 variant genotypes on clinical efficacy of antiplatelet treatment with clopidogrel: systematic review and meta-analysis. BMJ. 2011;343:d4588.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Grosdidier C, Quilici J, Loosveld M, Camoin L, Moro PJ, Saut N, et al. Effect of CYP2C19*2 and *17 genetic variants on platelet response to clopidogrel and prasugrel maintenance dose and relation to bleeding complications. Am J Cardiol. 2013;111(7):985–90.

    Article  CAS  PubMed  Google Scholar 

  41. Cuisset T, Loosveld M, Morange PE, Quilici J, Moro PJ, Saut N, et al. CYP2C19*2 and *17 alleles have a significant impact on platelet response and bleeding risk in patients treated with prasugrel after acute coronary syndrome. JACC Cardiovasc Interv. 2012;5(12):1280–7.

    Article  PubMed  Google Scholar 

  42. Angiolillo DJ, Badimon JJ, Saucedo JF, Frelinger AL, Michelson AD, Jakubowski JA, et al. A pharmacodynamic comparison of prasugrel vs. high-dose clopidogrel in patients with type 2 diabetes mellitus and coronary artery disease: results of the Optimizing anti-Platelet Therapy In diabetes MellitUS (OPTIMUS)-3 Trial. Eur Heart J. 2011;32(7):838–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Muller C, Caillard S, Jesel L, El Ghannudi S, Ohlmann P, Sauleau E, et al. Association of estimated GFR with platelet inhibition in patients treated with clopidogrel. Am J Kidney Dis. 2012;59(6):777–85.

    Article  CAS  PubMed  Google Scholar 

  44. Mavrakanas TA, Alam A, Reny JL, Fontana P. Platelet reactivity in stable cardiovascular patients with chronic kidney disease. Platelets. 2018;29(5):455–62.

    Article  CAS  PubMed  Google Scholar 

  45. Gurbel PA, Bliden KP, Tantry US. Effect of clopidogrel with and without eptifibatide on tumor necrosis factor-alpha and C-reactive protein release after elective stenting: results from the CLEAR PLATELETS 1b study. J Am Coll Cardiol. 2006;48(11):2186–91.

    Article  CAS  PubMed  Google Scholar 

  46. Fontana P, Senouf D, Mach F. Biological effect of increased maintenance dose of clopidogrel in cardiovascular outpatients and influence of the cytochrome P450 2C19*2 allele on clopidogrel responsiveness. Thromb Res. 2008;121(4):463–8.

    Article  CAS  PubMed  Google Scholar 

  47. Geisler T, Grass D, Bigalke B, Stellos K, Drosch T, Dietz K, et al. The residual platelet aggregation after deployment of intracoronary stent (PREDICT) score. J Thromb Haemost. 2008;6(1):54–61.

    Article  CAS  PubMed  Google Scholar 

  48. Shuldiner AR, O’Connell JR, Bliden KP, Gandhi A, Ryan K, Horenstein RB, et al. Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA. 2009;302(8):849–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Fontana P, Berdague P, Castelli C, Nolli S, Barazer I, Fabbro-Peray P, et al. Clinical predictors of dual aspirin and clopidogrel poor responsiveness in stable cardiovascular patients from the ADRIE study. J Thromb Haemost. 2010;8(12):2614–23.

    Article  CAS  PubMed  Google Scholar 

  50. Combescure C, Fontana P, Mallouk N, Berdague P, Labruyere C, Barazer I, et al. Clinical implications of clopidogrel non-response in cardiovascular patients: a systematic review and meta-analysis. J Thromb Haemost. 2010;8(5):923–33.

    CAS  PubMed  Google Scholar 

  51. Tantry US, Bonello L, Aradi D, Price MJ, Jeong YH, Angiolillo DJ, et al. Consensus and update on the definition of on-treatment platelet reactivity to adenosine diphosphate associated with ischemia and bleeding. J Am Coll Cardiol. 2013;62(24):2261–73.

    Article  CAS  PubMed  Google Scholar 

  52. Aradi D, Kirtane A, Bonello L, Gurbel PA, Tantry US, Huber K, et al. Bleeding and stent thrombosis on P2Y12-inhibitors: collaborative analysis on the role of platelet reactivity for risk stratification after percutaneous coronary intervention. Eur Heart J. 2015;36(27):1762–71.

    Article  CAS  PubMed  Google Scholar 

  53. Bonello L, Camoin-Jau L, Armero S, Com O, Arques S, Burignat-Bonello C, et al. Tailored clopidogrel loading dose according to platelet reactivity monitoring to prevent acute and subacute stent thrombosis. Am J Cardiol. 2009;103(1):5–10.

    Article  CAS  PubMed  Google Scholar 

  54. Price MJ, Berger PB, Teirstein PS, Tanguay JF, Angiolillo DJ, Spriggs D, et al. Standard- vs high-dose clopidogrel based on platelet function testing after percutaneous coronary intervention: the GRAVITAS randomized trial. JAMA. 2011;305(11):1097–105.

    Article  CAS  PubMed  Google Scholar 

  55. Collet JP, Cuisset T, Range G, Cayla G, Elhadad S, Pouillot C, et al. Bedside monitoring to adjust antiplatelet therapy for coronary stenting. N Engl J Med. 2012;367(22):2100–9.

    Article  CAS  PubMed  Google Scholar 

  56. Trenk D, Stone GW, Gawaz M, Kastrati A, Angiolillo DJ, Muller U, et al. A randomized trial of prasugrel versus clopidogrel in patients with high platelet reactivity on clopidogrel after elective percutaneous coronary intervention with implantation of drug-eluting stents: results of the TRIGGER-PCI (Testing Platelet Reactivity In Patients Undergoing Elective Stent Placement on Clopidogrel to Guide Alternative Therapy With Prasugrel) study. J Am Coll Cardiol. 2012;59(24):2159–64.

    Article  CAS  PubMed  Google Scholar 

  57. Gurbel PA, Jeong YH, Navarese EP, Tantry US. Platelet-mediated thrombosis: from bench to bedside. Circ Res. 2016;118(9):1380–91.

    Article  CAS  PubMed  Google Scholar 

  58. Reny JL, Berdague P, Poncet A, Barazer I, Nolli S, Fabbro-Peray P, et al. Antiplatelet drug response status does not predict recurrent ischemic events in stable cardiovascular patients: results of the Antiplatelet Drug Resistances and Ischemic Events study. Circulation. 2012;125(25):3201–10.

    Article  CAS  PubMed  Google Scholar 

  59. Zhou Y, Wang Y, Wu Y, Huang C, Yan H, Zhu W, et al. Individualized dual antiplatelet therapy based on platelet function testing in patients undergoing percutaneous coronary intervention: a meta-analysis of randomized controlled trials. BMC Cardiovasc Disord. 2017;17(1):157.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Norgard NB, Dinicolantonio JJ. Clopidogrel, prasugrel, or ticagrelor? a practical guide to use of antiplatelet agents in patients with acute coronary syndromes. Postgrad Med. 2013;125(4):91–102.

    Article  PubMed  Google Scholar 

  61. Varenhorst C, Eriksson N, Johansson A, Barratt BJ, Hagstrom E, Akerblom A, et al. Effect of genetic variations on ticagrelor plasma levels and clinical outcomes. Eur Heart J. 2015;36(29):1901–12.

    Article  CAS  PubMed  Google Scholar 

  62. Franken CC, Kaiser AF, Kruger JC, Overbeck K, Mugge A, Neubauer H. Cytochrome P450 2B6 and 2C9 genotype polymorphism–a possible cause of prasugrel low responsiveness. Thromb Haemost. 2013;110(1):131–40.

    Article  CAS  PubMed  Google Scholar 

  63. Wallentin L, James S, Storey RF, Armstrong M, Barratt BJ, Horrow J, et al. Effect of CYP2C19 and ABCB1 single nucleotide polymorphisms on outcomes of treatment with ticagrelor versus clopidogrel for acute coronary syndromes: a genetic substudy of the PLATO trial. Lancet. 2010;376(9749):1320–8.

    Article  CAS  PubMed  Google Scholar 

  64. Payne CD, Li YG, Small DS, Ernest CS 2nd, Farid NA, Jakubowski JA, et al. Increased active metabolite formation explains the greater platelet inhibition with prasugrel compared to high-dose clopidogrel. J Cardiovasc Pharmacol. 2007;50(5):555–62.

    Article  CAS  PubMed  Google Scholar 

  65. Hagihara K, Kazui M, Kurihara A, Yoshiike M, Honda K, Okazaki O, et al. A possible mechanism for the differences in efficiency and variability of active metabolite formation from thienopyridine antiplatelet agents, prasugrel and clopidogrel. Drug Metab Dispos. 2009;37(11):2145–52.

    Article  CAS  PubMed  Google Scholar 

  66. Ferri N, Corsini A, Bellosta S. Pharmacology of the new P2Y12 receptor inhibitors: insights on pharmacokinetic and pharmacodynamic properties. Drugs. 2013;73(15):1681–709.

    Article  CAS  PubMed  Google Scholar 

  67. Deharo P, Cuisset T. Monitoring platelet function: what have we learned from randomized clinical trials? Cardiovasc Diagn Ther. 2018;8(5):621–9.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Sibbing D, Aradi D, Jacobshagen C, Gross L, Trenk D, Geisler T, et al. Guided de-escalation of antiplatelet treatment in patients with acute coronary syndrome undergoing percutaneous coronary intervention (TROPICAL-ACS): a randomised, open-label, multicentre trial. Lancet. 2017;390(10104):1747–57.

    Article  CAS  PubMed  Google Scholar 

  69. Cuisset T, Deharo P, Quilici J, Johnson TW, Deffarges S, Bassez C, et al. Benefit of switching dual antiplatelet therapy after acute coronary syndrome: the TOPIC (timing of platelet inhibition after acute coronary syndrome) randomized study. Eur Heart J. 2017;38(41):3070–8.

    Article  CAS  PubMed  Google Scholar 

  70. Kupka D, Sibbing D. De-escalation of P2Y12 receptor inhibitor therapy after acute coronary syndromes in patients undergoing percutaneous coronary intervention. Korean Circ J. 2018;48(10):863–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Cayla G, Cuisset T, Silvain J, Leclercq F, Manzo-Silberman S, Saint-Etienne C, et al. Platelet function monitoring to adjust antiplatelet therapy in elderly patients stented for an acute coronary syndrome (ANTARCTIC): an open-label, blinded-endpoint, randomised controlled superiority trial. Lancet. 2016;388(10055):2015–22.

    Article  CAS  PubMed  Google Scholar 

  72. Sibbing D, Gross L, Trenk D, Jacobshagen C, Geisler T, Hadamitzky M, et al. Age and outcomes following guided de-escalation of antiplatelet treatment in acute coronary syndrome patients undergoing percutaneous coronary intervention: results from the randomized TROPICAL-ACS trial. Eur Heart J. 2018;39(29):2749–58.

    Article  CAS  PubMed  Google Scholar 

  73. Gross L, Trenk D, Jacobshagen C, Krieg A, Gawaz M, Massberg S, et al. Genotype-phenotype association and impact on outcomes following guided de-escalation of anti-platelet treatment in acute coronary syndrome patients: the TROPICAL-ACS genotyping substudy. Thromb Haemost. 2018;118(9):1656–67.

    Article  PubMed  Google Scholar 

  74. Vranckx P, Valgimigli M, Juni P, Hamm C, Steg PG, Heg D, et al. Ticagrelor plus aspirin for 1 month, followed by ticagrelor monotherapy for 23 months vs aspirin plus clopidogrel or ticagrelor for 12 months, followed by aspirin monotherapy for 12 months after implantation of a drug-eluting stent: a multicentre, open-label, randomised superiority trial. Lancet. 2018;392(10151):940–9.

    Article  CAS  PubMed  Google Scholar 

  75. Rozemeijer R, Voskuil M, Greving JP, Bots ML, Doevendans PA, Stella PR. Short versus long duration of dual antiplatelet therapy following drug-eluting stents: a meta-analysis of randomised trials. Neth Heart J. 2018;26(5):242–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Collet JP, Silvain J, Barthelemy O, Range G, Cayla G, Van Belle E, et al. Dual-antiplatelet treatment beyond 1 year after drug-eluting stent implantation (ARCTIC-Interruption): a randomised trial. Lancet. 2014;384(9954):1577–85.

    Article  CAS  PubMed  Google Scholar 

  77. Park SJ, Park DW, Kim YH, Kang SJ, Lee SW, Lee CW, et al. Duration of dual antiplatelet therapy after implantation of drug-eluting stents. N Engl J Med. 2010;362(15):1374–82.

    Article  CAS  PubMed  Google Scholar 

  78. Valgimigli M, Campo G, Monti M, Vranckx P, Percoco G, Tumscitz C, et al. Short- versus long-term duration of dual-antiplatelet therapy after coronary stenting: a randomized multicenter trial. Circulation. 2012;125(16):2015–26.

    Article  CAS  PubMed  Google Scholar 

  79. Mauri L, Kereiakes DJ, Yeh RW, Driscoll-Shempp P, Cutlip DE, Steg PG, et al. Twelve or 30 months of dual antiplatelet therapy after drug-eluting stents. N Engl J Med. 2014;371(23):2155–66.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Costa F, Valgimigli M. The optimal duration of dual antiplatelet therapy after coronary stent implantation: to go too far is as bad as to fall short. Cardiovasc Diagn Ther. 2018;8(5):630–46.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Petrie A, Sabin C. Medical statistics at a glance. 3rd ed. New York: Wiley Blackwell; 2009.

    Google Scholar 

  82. Patrono C. The P2Y12 receptor: no active metabolite, no party. Nat Rev Cardiol. 2009;6(4):271–2.

    Article  CAS  PubMed  Google Scholar 

  83. Roshammar D, Nyberg J, Andersson T, Stanski D, Storey RF, Hamren B. Exposure-response analyses supporting ticagrelor dosing recommendation in patients with prior myocardial infarction. J Clin Pharmacol. 2017;57(5):573–83.

    Article  PubMed  CAS  Google Scholar 

  84. Nutescu EA, Burnett A, Fanikos J, Spinler S, Wittkowsky A. Pharmacology of anticoagulants used in the treatment of venous thromboembolism. J Thromb Thrombolysis. 2016;41(1):15–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Kirchhof P, Benussi S, Kotecha D, Ahlsson A, Atar D, Casadei B, et al. 2016 ESC guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Eur Heart J. 2016;37(38):2893–962.

    Article  PubMed  Google Scholar 

  86. January CT, Wann LS, Calkins H, Chen LY, Cigarroa JE, Cleveland JC Jr, et al. AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation. Circulation. 2019. https://doi.org/10.1161/cir.0000000000000665(Epub 28 Jan 2019).

    Article  PubMed  Google Scholar 

  87. Di Nisio M, van Es N, Buller HR. Deep vein thrombosis and pulmonary embolism. Lancet. 2016;388(10063):3060–73.

    Article  PubMed  Google Scholar 

  88. Kearon C, Akl EA, Ornelas J, Blaivas A, Jimenez D, Bounameaux H, et al. Antithrombotic therapy for VTE disease: CHEST guideline and expert panel report. Chest. 2016;149(2):315–52.

    Article  PubMed  Google Scholar 

  89. European Medecines Agency. Pradaxa product information. Last updated 15 June 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/pradaxa#product-information-section. Accessed 1 Jun 2019.

  90. European Medecines Agency. Xarelo product information. Last updated 6 Sep 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/xarelto#product-information-section. Accessed 1 Jun 2019.

  91. European Medecines Agency. Eliquis product information. Last updated 3 Sept 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/eliquis#product-information-section. Accessed 1 Jun 2019.

  92. European Medecines Agency. Lixiana product information. Last updated 8 Oct 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/lixiana#product-information-section. Accessed 1 Jun 2019.

  93. De Caterina R, Lip GYH. The non-vitamin K antagonist oral anticoagulants (NOACs) and extremes of body weight-a systematic literature review. Clin Res Cardiol. 2017;106(8):565–72.

    Article  PubMed  CAS  Google Scholar 

  94. Dhar A, Mullish BH, Thursz MR. Anticoagulation in chronic liver disease. J Hepatol. 2017;66(6):1313–26.

    Article  PubMed  Google Scholar 

  95. Weber J, Olyaei A, Shatzel J. The efficacy and safety of direct oral anticoagulants in patients with chronic renal insufficiency: a review of the literature. Eur J Haematol. 2019;102(4):312–8.

    Article  CAS  PubMed  Google Scholar 

  96. Huisman MV, Ferreira M, Feuring M, Fraessdorf M, Klok FA. Less abnormal uterine bleeding with dabigatran than warfarin in women treated for acute venous thromboembolism. J Thromb Haemost. 2018;16(9):1775–8.

    Article  CAS  PubMed  Google Scholar 

  97. Cheung KS, Leung WK. Gastrointestinal bleeding in patients on novel oral anticoagulants: risk, prevention and management. World J Gastroenterol. 2017;23(11):1954–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Ramos-Esquivel A. Monitoring anticoagulant therapy with new oral agents. World J Methodol. 2015;5(4):212–5.

    Article  PubMed  PubMed Central  Google Scholar 

  99. Gong IY, Kim RB. Importance of pharmacokinetic profile and variability as determinants of dose and response to dabigatran, rivaroxaban, and apixaban. Can J Cardiol. 2013;29(7 Suppl):S24–33.

    Article  PubMed  Google Scholar 

  100. Testa S, Tripodi A, Legnani C, Pengo V, Abbate R, Dellanoce C, et al. Plasma levels of direct oral anticoagulants in real life patients with atrial fibrillation: results observed in four anticoagulation clinics. Thromb Res. 2016;137:178–83.

    Article  CAS  PubMed  Google Scholar 

  101. Storelli F, Daali Y, Desmeules J, Reny JL, Fontana P. Pharmacogenomics of oral antithrombotic drugs. Curr Pharm Des. 2016;22(13):1933–49.

    Article  CAS  PubMed  Google Scholar 

  102. Pare G, Eriksson N, Lehr T, Connolly S, Eikelboom J, Ezekowitz MD, et al. Genetic determinants of dabigatran plasma levels and their relation to bleeding. Circulation. 2013;127(13):1404–12.

    Article  CAS  PubMed  Google Scholar 

  103. Ueshima S, Hira D, Fujii R, Kimura Y, Tomitsuka C, Yamane T, et al. Impact of ABCB1, ABCG2, and CYP3A5 polymorphisms on plasma trough concentrations of apixaban in Japanese patients with atrial fibrillation. Pharmacogenet Genomics. 2017;27(9):329–36.

    Article  CAS  PubMed  Google Scholar 

  104. Eikelboom JW, Connolly SJ, Bosch J, Dagenais GR, Hart RG, Shestakovska O, et al. Rivaroxaban with or without aspirin in stable cardiovascular disease. N Engl J Med. 2017;377(14):1319–30.

    Article  CAS  PubMed  Google Scholar 

  105. US Food and Drug Administration. Briefing information Set, for the October 30, 2014, meeting of the Cardiovascular and Renal Drugs Advisory Committee. https://wayback.archive-it.org/7993/20170405211258/https:/www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/CardiovascularandRenalDrugsAdvisoryCommittee/UCM421612.pdf. Accessed 1 Jun 2019.

  106. US Food and Drug Administration. Briefing information Xrt, for the September 8, 2011, meeting of the Cardiovascular and Renal Drugs Advisory Committee. https://wayback.archive-it.org/7993/20170405211959/https:/www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/CardiovascularandRenalDrugsAdvisoryCommittee/UCM270796.pdf. Accessed 1 Jun 2019.

  107. Center for Drug Evaluation and Research. Clinical pharmacology review NDA 202-155, December 2012. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2012/202155Orig1s000ClinPharmR.pdf. Accessed 1 Jun 2019.

  108. Reilly PA, Lehr T, Haertter S, Connolly SJ, Yusuf S, Eikelboom JW, et al. The effect of dabigatran plasma concentrations and patient characteristics on the frequency of ischemic stroke and major bleeding in atrial fibrillation patients: the RE-LY Trial (Randomized Evaluation of Long-Term Anticoagulation Therapy). J Am Coll Cardiol. 2014;63(4):321–8.

    Article  CAS  PubMed  Google Scholar 

  109. Testa S, Paoletti O, Legnani C, Dellanoce C, Antonucci E, Cosmi B, et al. Low drug levels and thrombotic complications in high-risk atrial fibrillation patients treated with direct oral anticoagulants. J Thromb Haemost. 2018;16(5):842–8.

    Article  CAS  PubMed  Google Scholar 

  110. Camm AJ, Lip GY, De Caterina R, Savelieva I, Atar D, Hohnloser SH, et al. 2012 focused update of the ESC guidelines for the management of atrial fibrillation: an update of the 2010 ESC Guidelines for the management of atrial fibrillation–developed with the special contribution of the European Heart Rhythm Association. Europace. 2012;14(10):1385–413.

    Article  PubMed  Google Scholar 

  111. January CT, Wann LS, Alpert JS, Calkins H, Cigarroa JE, Cleveland JC Jr, et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society. Circulation. 2014;130(23):2071–104.

    Article  PubMed  Google Scholar 

  112. Olesen JB, Lip GY, Hansen ML, Hansen PR, Tolstrup JS, Lindhardsen J, et al. Validation of risk stratification schemes for predicting stroke and thromboembolism in patients with atrial fibrillation: nationwide cohort study. BMJ. 2011;342:d124.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Maheshwari A, Norby FL, Roetker NS, Soliman EZ, Koene RJ, Rooney MR, et al. Refining prediction of atrial fibrillation-related stroke using the P2-CHA2DS2-VASc score. Circulation. 2019;139(2):180–91.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Gage BF, Yan Y, Milligan PE, Waterman AD, Culverhouse R, Rich MW, et al. Clinical classification schemes for predicting hemorrhage: results from the National Registry of Atrial Fibrillation (NRAF). Am Heart J. 2006;151(3):713–9.

    Article  PubMed  Google Scholar 

  115. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJ, Lip GY. A novel user-friendly score (HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest. 2010;138(5):1093–100.

    Article  PubMed  Google Scholar 

  116. Fang MC, Go AS, Chang Y, Borowsky LH, Pomernacki NK, Udaltsova N, et al. A new risk scheme to predict warfarin-associated hemorrhage: the ATRIA (Anticoagulation and Risk Factors in Atrial Fibrillation) study. J Am Coll Cardiol. 2011;58(4):395–401.

    Article  PubMed  PubMed Central  Google Scholar 

  117. Gomes T, Mamdani MM, Holbrook AM, Paterson JM, Hellings C, Juurlink DN. Rates of hemorrhage during warfarin therapy for atrial fibrillation. CMAJ. 2013;185(2):E121–7.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Lip GYH, Skjoth F, Nielsen PB, Kjaeldgaard JN, Larsen TB. The HAS-BLED, ATRIA, and ORBIT Bleeding scores in atrial fibrillation patients using non-vitamin K antagonist oral anticoagulants. Am J Med. 2018;131(5):574.e13–27.

    Article  Google Scholar 

  119. Rostami-Hodjegan A. Physiologically based pharmacokinetics joined with in vitro–in vivo extrapolation of ADME: a marriage under the arch of systems pharmacology. Clin Pharmacol Ther. 2012;92(1):50–61.

    Article  CAS  PubMed  Google Scholar 

  120. Wilbaux M, Fuchs A, Samardzic J, Rodieux F, Csajka C, Allegaert K, et al. Pharmacometric approaches to personalize use of primarily renally eliminated antibiotics in preterm and term neonates. J Clin Pharmacol. 2016;56(8):909–35.

    Article  CAS  PubMed  Google Scholar 

  121. Csajka C, Crettol S, Guidi M, Eap CB. Population genetic-based pharmacokinetic modeling of methadone and its relationship with the QTc interval in opioid-dependent patients. Clin Pharmacokinet. 2016;55(12):1521–33.

    Article  CAS  PubMed  Google Scholar 

  122. Nekka F, Csajka C, Wilbaux M, Sanduja S, Li J, Pfister M. Pharmacometrics-based decision tools facilitate mHealth implementation. Expert Rev Clin Pharmacol. 2017;10(1):39–46.

    Article  CAS  PubMed  Google Scholar 

  123. Klopp-Schulze L, Joerger M, Wicha SG, Ter Heine R, Csajka C, Parra-Guillen ZP, et al. Exploiting pharmacokinetic models of tamoxifen and endoxifen to identify factors causing subtherapeutic concentrations in breast cancer patients. Clin Pharmacokinet. 2018;57(2):229–42.

    Article  CAS  PubMed  Google Scholar 

  124. de Velde F, Mouton JW, de Winter BCM, van Gelder T, Koch BCP. Clinical applications of population pharmacokinetic models of antibiotics: challenges and perspectives. Pharmacol Res. 2018;134:280–8.

    Article  PubMed  CAS  Google Scholar 

  125. Smits A, De Cock RF, Allegaert K, Vanhaesebrouck S, Danhof M, Knibbe CA. Prospective evaluation of a model-based dosing regimen for amikacin in preterm and term neonates in clinical practice. Antimicrob Agents Chemother. 2015;59(10):6344–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Hamberg AK, Hellman J, Dahlberg J, Jonsson EN, Wadelius M. A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children. BMC Med Inform Decis Mak. 2015;15:7.

    Article  PubMed  PubMed Central  Google Scholar 

  127. Deng J, Vozmediano V, Rodriguez M, Cavallari LH, Schmidt S. Genotype-guided dosing of warfarin through modeling and simulation. Eur J Pharm Sci. 2017;109S:S9–14.

    Article  PubMed  CAS  Google Scholar 

  128. Liesenfeld KH, Lehr T, Dansirikul C, Reilly PA, Connolly SJ, Ezekowitz MD, et al. Population pharmacokinetic analysis of the oral thrombin inhibitor dabigatran etexilate in patients with non-valvular atrial fibrillation from the RE-LY trial. J Thromb Haemost. 2011;9(11):2168–75.

    Article  CAS  PubMed  Google Scholar 

  129. Girgis IG, Patel MR, Peters GR, Moore KT, Mahaffey KW, Nessel CC, et al. Population pharmacokinetics and pharmacodynamics of rivaroxaban in patients with non-valvular atrial fibrillation: results from ROCKET AF. J Clin Pharmacol. 2014;54(8):917–27.

    Article  CAS  PubMed  Google Scholar 

  130. Leil TA, Frost C, Wang X, Pfister M, LaCreta F. Model-based exposure-response analysis of apixaban to quantify bleeding risk in special populations of subjects undergoing orthopedic surgery. CPT Pharmacomet Syst Pharmacol. 2014;3:e136.

    Article  CAS  Google Scholar 

  131. Niebecker R, Jonsson S, Karlsson MO, Miller R, Nyberg J, Krekels EH, et al. Population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism–the Hokusai-VTE phase 3 study. Br J Clin Pharmacol. 2015;80(6):1374–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Chang M, Yu Z, Shenker A, Wang J, Pursley J, Byon W, et al. Effect of renal impairment on the pharmacokinetics, pharmacodynamics, and safety of apixaban. J Clin Pharmacol. 2016;56(5):637–45.

    Article  CAS  PubMed  Google Scholar 

  133. Koretsune Y, Yamashita T, Kimura T, Fukuzawa M, Abe K, Yasaka M. Short-term safety and plasma concentrations of edoxaban in Japanese patients with non-valvular atrial fibrillation and severe renal impairment. Circ J. 2015;79(7):1486–95.

    Article  PubMed  Google Scholar 

  134. Yoshioka H, Sato H, Hatakeyama H, Hisaka A. Model-based meta-analysis to evaluate optimal doses of direct oral factor Xa inhibitors in atrial fibrillation patients. Blood Adv. 2018;2(10):1066–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Moser BA, LaBell ES, Chigutsa E, Jakubowski JA, Small DS. Population pharmacokinetic and exposure-response analyses of prasugrel in pediatric patients with sickle cell anemia. Clin Pharmacokinet. 2018;57(2):243–54.

    Article  CAS  PubMed  Google Scholar 

  136. Zhao P, Zhang L, Grillo JA, Liu Q, Bullock JM, Moon YJ, et al. Applications of physiologically based pharmacokinetic (PBPK) modeling and simulation during regulatory review. Clin Pharmacol Ther. 2011;89(2):259–67.

    Article  CAS  PubMed  Google Scholar 

  137. Djebli N, Fabre D, Boulenc X, Fabre G, Sultan E, Hurbin F. Physiologically based pharmacokinetic modeling for sequential metabolism: effect of CYP2C19 genetic polymorphism on clopidogrel and clopidogrel active metabolite pharmacokinetics. Drug Metab Dispos. 2015;43(4):510–22.

    Article  CAS  PubMed  Google Scholar 

  138. Shebley M, Sandhu P, Emami Riedmaier A, Jamei M, Narayanan R, Patel A, et al. Physiologically based pharmacokinetic model qualification and reporting procedures for regulatory submissions: a consortium perspective. Clin Pharmacol Ther. 2018;104(1):88–110.

    Article  PubMed  PubMed Central  Google Scholar 

  139. Rostami-Hodjegan A. Reverse translation in PBPK and QSP: going backwards in order to go forward with confidence. Clin Pharmacol Ther. 2018;103(2):224–32.

    Article  PubMed  Google Scholar 

  140. Jamei M. Recent advances in development and application of physiologically-based pharmacokinetic (PBPK) models: a transition from academic curiosity to regulatory acceptance. Curr Pharmacol Rep. 2016;2:161–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Luzon E, Blake K, Cole S, Nordmark A, Versantvoort C, Berglund EG. Physiologically based pharmacokinetic modeling in regulatory decision-making at the European Medicines Agency. Clin Pharmacol Ther. 2017;102(1):98–105.

    Article  CAS  PubMed  Google Scholar 

  142. European Medecines Agency. Guideline on the qualification and reporting of physiologically based pharmacokinetic (PBPK) modelling and simulation simulation. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2016/07/WC500211315.pdf. 2016. Accessed 1 Jun 2019.

  143. US Food and Drug Administration. Physiologically based pharmacokinetic analyses—format and content guidance for industry. 2018. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/physiologically-based-pharmacokinetic-analyses-format-and-content-guidance-industry. Accessed 1 Jun 2019.

  144. Marsousi N, Samer CF, Fontana P, Reny JL, Rudaz S, Desmeules JA, et al. Coadministration of ticagrelor and ritonavir: toward prospective dose adjustment to maintain an optimal platelet inhibition using the PBPK approach. Clin Pharmacol Ther. 2016;100(3):295–304.

    Article  CAS  PubMed  Google Scholar 

  145. Fan J, Zhang X, Zhao L. Utility of physiologically based pharmacokinetic absorption modeling to predict the impact of salt-to-base conversion on prasugrel HCl product bioequivalence in the presence of proton pump inhibitors. AAPS J. 2017;19(5):1479–86.

    Article  CAS  PubMed  Google Scholar 

  146. Xu R, Ge W, Jiang Q. Application of physiologically based pharmacokinetic modeling to the prediction of drug-drug and drug-disease interactions for rivaroxaban. Eur J Clin Pharmacol. 2018;74(6):755–65.

    Article  CAS  PubMed  Google Scholar 

  147. Polasek TM, Tucker GT, Sorich MJ, Wiese MD, Mohan T, Rostami-Hodjegan A, et al. Prediction of olanzapine exposure in individual patients using physiologically based pharmacokinetic modelling and simulation. Br J Clin Pharmacol. 2018;84(3):462–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Darwich AS, Ogungbenro K, Vinks AA, Powell JR, Reny JL, Marsousi N, et al. Why has model-informed precision dosing not yet become common clinical reality? Lessons from the past and a roadmap for the future. Clin Pharmacol Ther. 2017;101(5):646–56.

    Article  CAS  PubMed  Google Scholar 

  149. Yourman L, Concato J, Agostini JV. Use of computer decision support interventions to improve medication prescribing in older adults: a systematic review. Am J Geriatr Pharmacother. 2008;6(2):119–29.

    Article  PubMed  Google Scholar 

  150. Handler SM, Altman RL, Perera S, Hanlon JT, Studenski SA, Bost JE, et al. A systematic review of the performance characteristics of clinical event monitor signals used to detect adverse drug events in the hospital setting. J Am Med Inform Assoc. 2007;14(4):451–8.

    Article  PubMed  PubMed Central  Google Scholar 

  151. Beeler PE, Bates DW, Hug BL. Clinical decision support systems. Swiss Med Wkly. 2014;144:w14073.

    PubMed  Google Scholar 

  152. Fritz D, Ceschi A, Curkovic I, Huber M, Egbring M, Kullak-Ublick GA, et al. Comparative evaluation of three clinical decision support systems: prospective screening for medication errors in 100 medical inpatients. Eur J Clin Pharmacol. 2012;68(8):1209–19.

    Article  PubMed  Google Scholar 

  153. Chazard E, Preda C, Merlin B, Ficheur G, Consortium P, Beuscart R. Data-mining-based detection of adverse drug events. Stud Health Technol Inform. 2009;150:552–6.

    PubMed  Google Scholar 

  154. Ohno-Machado L, Nadkarni P, Johnson K. Natural language processing: algorithms and tools to extract computable information from EHRs and from the biomedical literature. J Am Med Inform Assoc. 2013;20(5):805.

    Article  PubMed  PubMed Central  Google Scholar 

  155. Polepalli Ramesh B, Belknap SM, Li Z, Frid N, West DP, Yu H. Automatically recognizing medication and adverse event information from food and drug administration’s adverse event reporting system narratives. JMIR Med Inform. 2014;2(1):e10.

    Article  PubMed  PubMed Central  Google Scholar 

  156. Iqbal E, Mallah R, Jackson RG, Ball M, Ibrahim ZM, Broadbent M, et al. Identification of adverse drug events from free text electronic patient records and information in a large mental health case register. PLoS One. 2015;10(8):e0134208.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  157. Sibbing D, Angiolillo DJ, Huber K. Antithrombotic therapy for acute coronary syndrome: past, present and future. Thromb Haemost. 2017;117(7):1240–8.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was performed within the framework of the Swiss National Science Foundation’s PNR74 Project 407440_167381 on the ‘Automated detection of adverse drug events from older inpatients’ electronic medical records using structured data’.

Author information

Authors and Affiliations

  1. Division of General Internal Medicine, Geneva University Hospitals, Geneva, Switzerland

    Jean Terrier & Jean-Luc Reny

  2. Geneva Platelet Group, Faculty of Medicine, University of Geneva, Geneva, Switzerland

    Jean Terrier, Youssef Daali, Pierre Fontana & Jean-Luc Reny

  3. School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland

    Youssef Daali & Chantal Csajka

  4. Clinical Pharmacology and Toxicology Service, Anesthesiology, Pharmacology and Intensive Care Department, Geneva University Hospitals, Geneva, Switzerland

    Youssef Daali

  5. Division of Angiology and Haemostasis, Geneva University Hospitals, Geneva, Switzerland

    Pierre Fontana

  6. Division of Internal Medicine and Rehabilitation, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1205, Geneva, Switzerland

    Jean-Luc Reny

Authors
  1. Jean Terrier
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Youssef Daali
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pierre Fontana
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chantal Csajka
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jean-Luc Reny
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jean-Luc Reny.

Ethics declarations

Funding

No external funding was used in the preparation of this manuscript.

Conflict of interest

Jean Terrier, Youssef Daali, Pierre Fontana, Chantal Csajka, and Jean-Luc Reny declare that they have no potential conflicts of interest that may be relevant to the contents of this manuscript.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Terrier, J., Daali, Y., Fontana, P. et al. Towards Personalized Antithrombotic Treatments: Focus on P2Y12 Inhibitors and Direct Oral Anticoagulants. Clin Pharmacokinet 58, 1517–1532 (2019). https://doi.org/10.1007/s40262-019-00792-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40262-019-00792-y

Search

Navigation