Modeling and Simulation in the Development of Cardiovascular Agents

Part of the AAPS Advances in the Pharmaceutical Sciences Series book series (AAPS, volume 1)


Cardiovascular pharmacology encompasses a wide range of diseases. With most agents in this therapeutic area, there are specific therapeutic targets for biomarkers such as systolic blood pressure or LDL cholesterol levels that need to be met to ensure adequate clinical response in patients. Overdoses of these agents may be associated with toxicity. Modeling and simulation have proven to be valuable tools to target and adjust doses in patients. Because most cardiovascular agents are adaptively dosed based on individual response, the dose adjustment strategy must be implemented for model evaluation and simulation. This chapter reviews the cardiovascular pharmacology areas of treatment of hypercholesterolemia, stroke and hypertension, and applications of modeling and simulation in these disease states.


International Normalize Ratio Poor Metabolizers Extensive Metabolizers Precursor Pool Clinical Trial Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to acknowledge Professor Stuart Beal for his suggestion of the “indescribable” mixture model, and Ms. Tracey Thomas for help in formatting and preparing this chapter.


  1. Ahn JE, French J (2009) Longitudinal model-based meta-analysis with NONMEM. ACoP Meeting Mystic CT USA.
  2. Bailey JM, Lu W, Levy JH, Ramsay JG, Shore-Lesserson L, Prielipp RC, Brister NW, Roach GW, Jolin-Mellgard A, Nordlander M (2002) Clevidipine in adult cardiac surgical patients: a dose-finding study. Anesthesiology 96(5):1086–1094PubMedCrossRefGoogle Scholar
  3. Beal SL, Sheiner LB, Boeckmann AJ (1989–2006) NONMEM Users Guides, ICON Development Solutions, Ellicott City, MDGoogle Scholar
  4. Bellosta S, Ferri N, Bernini F, Paoletti R, Corsini A (2000) Non-lipid-related effects of statins. Ann Med 32:164–176PubMedCrossRefGoogle Scholar
  5. Blum CB (1994) Comparison of properties of four inhibitors of 3-hydroxy-3-methylglutaryl-coenzyme A reductase. Am J Cardiol 73:3D–11DPubMedCrossRefGoogle Scholar
  6. Brott T, Adams HP, Olinger CP, Marler JR, Barsan WG, Biller J, Spilker J, Holleran R, Eberle R, Hertzberg V (1989) Measurements of acute cerebral infarction: a clinical examination scale. Stroke 20:864–870PubMedCrossRefGoogle Scholar
  7. Bullock R, Zauner A, Myseros JS, Marmarou A, Woodward JJ, Young HF (1995a) Evidence for prolonged release of excitatory amino acids in severe human head trauma relationship to clinical events. Ann NY Acad Sci 765:290–297PubMedCrossRefGoogle Scholar
  8. Bullock R, Zauner A, Woodward J, Young HF (1995b) Massive persistent release of excitatory amino acids following human occlusive stroke. Stroke 26:2187–2189PubMedCrossRefGoogle Scholar
  9. Chabaud S, Girard P, Nony P, Boissel JP (2002) Clinical trial simulation using therapeutic effect modeling: application to ivabradine efficacy in patients with angina pectoris. J Pharmacokinet Pharmacodyn 29(4):339–363PubMedCrossRefGoogle Scholar
  10. Choi DW (1988) Glutamate neurotoxicity and diseases of the nervous system. Neuron 1(8):623–634PubMedCrossRefGoogle Scholar
  11. Cote R, Hachinski V, Shurvell B, Norris JW, Wolfson C (1986) The Canadian Neurological Scale: a preliminary study in acute stroke. Stroke 17:731–736PubMedCrossRefGoogle Scholar
  12. Dayneka NL, Garg V, Jusko WJ (1993) Comparison of four basic models of indirect pharmacodynamic responses. J Pharmacokinet Biopharm 21(4):457–478PubMedCrossRefGoogle Scholar
  13. Faltaos DW, Urien S, Carreau V, Chauvenet M, Hulot JS, Giral P, Bruckert E, Lechat P (2006) Use of an indirect effect model to describe the LDL cholesterol-lowering effect by statins in hypercholesterolaemic patients. Fundam Clin Pharmacol 20(3):321–330PubMedCrossRefGoogle Scholar
  14. FDA (1998) Guidance for industry: E9 statistical principles for clinical trialsGoogle Scholar
  15. FDA (2007) New labeling information for warfarin (marketed as Coumadin). Accessed 16 Aug 2007
  16. FDA (2007) FDA approves updated warfarin (Coumadin) prescribing information [press release]. Accessed 16 Aug 2007
  17. Fiorelli M, Alperovitch A, Argentino C, Sacchetti ML, Toni D, Sette G, Cavalletti C, Gori MC, Fieschi C (1995) Prediction of long-term outcome in the early hours following acute ischemic stroke. Arch Neurol 52:250–255PubMedCrossRefGoogle Scholar
  18. Friberg LE, Karlsson MO (2003) Mechanistic models for myelosuppression. Invest New Drugs 21(2):183–194PubMedCrossRefGoogle Scholar
  19. Gabrielsson J, Jusko WJ, Alari L (2000) Modelling of dose-response-time data: four examples of estimating the turnover parameters and generating kinetic functions from response profiles. Biopharm Drug Dispos 2:41–52CrossRefGoogle Scholar
  20. Geyskes GG, Boer P, Dorhout Mees EJ (1979) Clonidine withdrawal. Mechanism and frequency of rebound hypertension. Br J Clin Pharmacol 7(1):55–62PubMedCrossRefGoogle Scholar
  21. Green B, Duffull SB (2003) Development of a dosing strategy for enoxaparin in obese patients. Br J Clin Pharmacol 56(1):96–103PubMedCrossRefGoogle Scholar
  22. Grotta J (1997) Lubeluzole treatment of Acute Ischemic Stroke. Stroke 28:2338–2346PubMedCrossRefGoogle Scholar
  23. Guyton AC (1991) Blood pressure control—special role of the kidneys and body fluids. Science 252:1813–1816PubMedCrossRefGoogle Scholar
  24. Hamberg AK, Dahl ML, Barban M, Scordo MG, Wadelius M, Pengo V, Padrini R, Jonsson EN (2007) A PK-PD model for predicting the impact of age, CYP2C9, and VKORC1 genotype on individualization of warfarin therapy. Clin Pharmacol Ther 81(4):529–538PubMedCrossRefGoogle Scholar
  25. Hammer GB, Verghese ST, Drover DR, Yaster M, Tobin JR (2008) Pharmacokinetics and pharmacodynamics of fenoldopam mesylate for blood pressure control in pediatric patients. BMC Anesthesiol 8:6PubMedCrossRefGoogle Scholar
  26. Holford NH (2005) The visual predictive check – superiority to standard diagnostic (Rorschach) plots PAGE.
  27. Hunninghake DB (1992) HMG-CoA reductase inhibitors. Curr Opin Lipidol 3:22–28CrossRefGoogle Scholar
  28. Jackson SP, Nesbitt WS, Kulkarni S (2003) Signaling events underlying thrombus formation. J Thromb Haemost Jul 1(7):1602–1612CrossRefGoogle Scholar
  29. Jacqmin P, Gieschke R, Jordan P, Steimer JL, Goggin T, Pillai G (2001) Modeling drug induced changes in biomarkers without using drug concentrations: introducing the K-PD model. 10th Population Approach Group Conference, Basel, Switzerland,
  30. Johnson RJ, Herrera-Acosta J, Schreiner GF, Rodriguez-Iturbe B (2002) Subtle acquired renal injury as a mechanism of salt-sensitive hypertension. N Engl J Med 346:913–923PubMedCrossRefGoogle Scholar
  31. Johnson K, Shah A, Jaw J, Baxter J, Prakash C (2003) Metabolism, pharmacokinetics, and excretion of a highly selective NMDA receptor antagonist, traxoprodil, in human cytochrome P450 2D6 extensive and poor metabolizers. Drug Metab Dispos 31:76–87PubMedCrossRefGoogle Scholar
  32. Jonsson F, Marshall S, Krams M, Jonsson E (2005) A longitudinal model for non-monotonic clinical assessment scale data. J Pharmacokinet Pharmacodyn 32(5–6):795–815 (21)PubMedCrossRefGoogle Scholar
  33. Karlsson MO, Sheiner LB (1993) The importance of modeling interoccasion variability in population pharmacokinetic analyses. J Pharmacokinet Biopharm 21:735–750PubMedCrossRefGoogle Scholar
  34. Kearon C, Hirsh J (1997) Management of anticoagulation before and after elective surgery. N Engl J Med 336(21):1506–1511PubMedCrossRefGoogle Scholar
  35. Lalonde RL, Kowalski KG, Hutmacher MM, Ewy W, Nichols DJ, Milligan PA, Corrigan BW, Lockwood PA, Marshall SA, Benincosa LJ, Tensfeldt TG, Parivar K, Amantea M, Glue P, Koide H, Miller R (2007) (2007) Model-based drug development. Clin Pharmacol Ther 82(1):21–32PubMedCrossRefGoogle Scholar
  36. LaRosa JC, He J, Vupputuri S (1999) Effect of statins on risk of coronary disease: a meta-analysis of randomized controlled trials. JAMA, J Am Med Assoc 282(24):2340–2346CrossRefGoogle Scholar
  37. Laurent S, Kingwell B, Bank A, Weber M, Struijker-Boudier H (2002) Clinical applications of arterial stiffness: therapeutics and pharmacology. Am J Hypertens 15(5):453–458PubMedCrossRefGoogle Scholar
  38. Lennernäs H, Fager G (1997) Pharmacodynamics and pharmacokinetics of the HMG-CoA reductase inhibitors. Similarities and differences\. Clin Pharmacokinet 32(5):403–425PubMedCrossRefGoogle Scholar
  39. Lindenstrom E, Boysen G, Christiansen LW, Hansen BR, Nielsen PW (1991) Reliability of Scandinavian Stroke Scale. Cerebrovasc Dis 1:103–107CrossRefGoogle Scholar
  40. Mason RP, Walter MF, Day C, Jacob RF (2006) Active metabolite of atorvastatin inhibits membrane cholesterol domain formation by an antioxidant mechanism. J Biol Chem 281:9337–9345PubMedCrossRefGoogle Scholar
  41. McConnaughey MM, McConnaughey JS, Ingenito AJ (1999) Practical considerations of the pharmacology of angiotensin receptor blockers. J Clin Pharmacol 39:547–559PubMedCrossRefGoogle Scholar
  42. Merlini PA, Bauer KA, Oltrona L, Ardissino D, Cattaneo M, Belli C, Mannucci PM, Rosenberg RD (1994) Persistent activation of coagulation mechanism in unstable angina and myocardial infarction. Circulation 90(1):61–68PubMedCrossRefGoogle Scholar
  43. Monyer H, Sprengel R, Schoepfer R, Herb A, Higuchi M, Lomeli H, Burnashev N, Sakmann B, Seeburg PH (1992) Heteromeric NMDA receptors: molecular and functional distinction of subtypes. Science 256:1217–1221PubMedCrossRefGoogle Scholar
  44. Mould D (2007) Developing models of disease progression. In: Ette EI, Williams PJ (eds) Pharmacometrics: the science of quantitative pharmacology. Wiley, Hoboken, NJ, pp 547–581CrossRefGoogle Scholar
  45. Muir KW, Weir CJ, Murray GD, Povey C, Lees KR (1996) Comparison of neurological scales and scoring systems for acute stroke prognosis. Stroke 27:1817–1820PubMedCrossRefGoogle Scholar
  46. Pillai G, Gieschke R, Goggin T, Jacqmin P, Schimmer RC, Steimer JL (2004) A semimechanistic and mechanistic population PK-PD model for biomarker response to ibandronate, a new bisphosphonate for the treatment of osteoporosis. Br J Clin Pharmacol 58(6):618–631PubMedCrossRefGoogle Scholar
  47. Porchet HC, Piletta P, Dayer P (1992) Pharmacokinetic-pharmacodynamic modeling of the effects of clonidine on pain threshold, blood pressure, and salivary flow. Eur J Clin Pharmacol 42(6):655–661PubMedCrossRefGoogle Scholar
  48. Rosenberg PA, Aizenman E (1989) Hundred-fold increase in neuronal vulnerability to glutamate toxicity in astrocyte-poor cultures of rat cerebral cortex. Neurosci Lett 103:162–168PubMedCrossRefGoogle Scholar
  49. Salinger DH, Shen DD, Thummel K, Wittkowsky AK, Vicini P, Veenstra DL (2009) Pharmacogenomic trial design: use of a PK/PD model to explore warfarin dosing interventions through clinical trial simulation. Pharmacogenet Genomics 19(12):965–971PubMedCrossRefGoogle Scholar
  50. Scandinavian Stroke Study Group (1985) Multicenter trial of hemodilution in ischemic stroke: background and study protocol. Stroke 16:885–890CrossRefGoogle Scholar
  51. Schachter M (2004) Chemical, pharmacokinetic and pharmacodynamic properties of statins: an update. Fundam Clin Pharmacol 19(1):117–125CrossRefGoogle Scholar
  52. Schwarz UI, Ritchie MD, Bradford Y, Li C, Dudek SM, Frye-Anderson A, Kim RB, Roden DM, Stein CM (2008) Genetic determinants of response to warfarin during initial anticoagulation. N Engl J Med 358(10):999–1008PubMedCrossRefGoogle Scholar
  53. Sconce EA, Khan TI, Wynne HA, Avery P, Monkhouse L, King BP, Wood P, Kesteven P, Daly AK, Kamali F (2005) The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood 106:2329–2333PubMedCrossRefGoogle Scholar
  54. Seiler SM, Bernatowicz MS (2003) Peptide-derived protease-activated receptor-1 (PAR-1) antagonists. Curr Med Chem 1:1–11Google Scholar
  55. Sharma A, Ebling WF, Jusko WJ (1998) Precursor-dependent indirect pharmacodynamic response model for tolerance and rebound phenomena. J Pharm Sci 87(12):1577–1584PubMedCrossRefGoogle Scholar
  56. Stancu C, Sima A (2001) Statins: mechanism of action and effects. J Cell Mol Med 5(4):378–387PubMedCrossRefGoogle Scholar
  57. Steinhubl SR, Moliterno DJ (2005) The role of the platelet in the pathogenesis of atherothrombosis. Am J Cardiovasc Drugs 5(6):399–408PubMedCrossRefGoogle Scholar
  58. Stergiou GS (2004) Angiotensin receptor blockade in the challenging era of systolic hypertension. J Human Hypertens 18:837–847CrossRefGoogle Scholar
  59. Theilmeier G, Michiels C, Spaepen E, Vreys I, Collen D, Vermylen J, Hoylaerts MF (2002) Endothelial von Willebrand factor recruits platelets to atherosclerosis-prone sites in response to hypercholesterolemia. Blood 99(12):4486–4493PubMedCrossRefGoogle Scholar
  60. Unadkat JD, Sheiner LB, Hennis PJ, Cronnelly R, Miller RD, Sharma M (1986) An integrated model for the interaction of muscle relaxants with their antagonists. J Appl Physiol 61(4):1593–1598PubMedGoogle Scholar
  61. Verotta D, Beal SL, Sheiner LB (1989) Semi parametric approach to pharmacokinetic-pharmacodynamic data. Am J Physiol 256(4 Pt 2):R1005–R1010PubMedGoogle Scholar
  62. Whelan HT, Cook JD, Amlie-Lefond CM, Hovinga CA, Chan AK, Ichord RN, Deveber GA, Thall PF (2008) Practical model-based dose finding in early-phase clinical trials: optimizing tissue plasminogen activator dose for treatment of ischemic stroke in children. Stroke 39(9):2627–2636PubMedCrossRefGoogle Scholar
  63. Williams D, Feely J (2002) Pharmacokinetic-pharmacodynamic drug interactions with HMG-CoA reductase inhibitors. Clin Pharmacokinet 41(5):343–370PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Projections Research Inc.PhoenixvilleUSA

Personalised recommendations