B01: Antithrombotic agents

ATC B01 antithrombotic agents for modelers: delayed effect is the default; benefit-risk is asymmetric.
Modified

September 21, 2026

Part of B: Blood and blood forming organs.

Delayed effect is the default. Vitamin K antagonists suppress synthesis of clotting factors [1], and irreversible antiplatelet agents outlast the drug [2], so effect follows the turnover of a protein or cell pool rather than plasma concentration. Turnover and indirect response models are the natural starting point [3,4].

The exception worth knowing. Direct oral anticoagulants inhibit an existing enzyme, so their effect on clotting assays tracks concentration with little delay and direct models are what is actually fitted [57].

Benefit-risk is asymmetric. Exposure-response detects the bleeding limb far more reliably than the efficacy limb, which is often flat across the range studied [8,9]. Covariates that raise exposure (renal function, body size, age, P-glycoprotein and CYP3A inhibitors) move bleeding first, which is why dose-reduction criteria are written in exactly those terms [10,11].

Mechanistic extrapolation. QSP models of the coagulation network, built from literature kinetics, are well established for predicting how anticoagulants shift thrombin generation and INR, extrapolating efficacy and bleeding risk across doses [12,13].

References

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Dayneka NL, Garg V, Jusko WJ. Comparison of four basic models of indirect pharmacodynamic responses. Journal of Pharmacokinetics and Biopharmaceutics 1993;21:457–78. https://doi.org/10.1007/BF01061691.
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Ooi QX, Wright DFB, Tait RC, Isbister GK, Duffull SB. A joint model for vitamin k-dependent clotting factors and anticoagulation proteins. Clinical Pharmacokinetics 2017;56:1555–66. https://doi.org/10.1007/s40262-017-0541-5.
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Nyberg J, Karlsson KE, Jönsson S, Yin O, Miller R, Karlsson MO, et al. Edoxaban exposure-response analysis and clinical utility index assessment in patients with symptomatic deep-vein thrombosis or pulmonary embolism. CPT: Pharmacometrics & Systems Pharmacology 2016;5:222–32. https://doi.org/10.1002/psp4.12077.
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Röshammar D, Nyberg J, Andersson T, Stanski D, Storey RF, Hamrén B. Exposure-response analyses supporting ticagrelor dosing recommendation in patients with prior myocardial infarction. The Journal of Clinical Pharmacology 2017;57:573–83. https://doi.org/10.1002/jcph.839.
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Terrier J, Gaspar F, Guidi M, Fontana P, Daali Y, Csajka C, et al. Population pharmacokinetic models for direct oral anticoagulants: A systematic review and clinical appraisal using exposure simulation. Clinical Pharmacology & Therapeutics 2022;112:353–63. https://doi.org/10.1002/cpt.2649.
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Lin S-Y, Liu Y-B, Ho L-T, Kuo C-H, Peng Y-F, Huang C-F, et al. Impact of age and factor Xa inhibitor concentrations on bleeding risk in patients with atrial fibrillation. Clinical Pharmacology & Therapeutics 2025;118:156–63. https://doi.org/10.1002/cpt.3654.
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Wajima T, Isbister GK, Duffull SB. A comprehensive model for the humoral coagulation network in humans. Clinical Pharmacology & Therapeutics 2009;86:290–8. https://doi.org/10.1038/clpt.2009.87.
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Burghaus R, Coboeken K, Gaub T, Kuepfer L, Sensse A, Siegmund H-U, et al. Evaluation of the efficacy and safety of rivaroxaban using a computer model for blood coagulation. PLoS ONE 2011;6:e17626. https://doi.org/10.1371/journal.pone.0017626.