Clinical trial simulation: A review

Clinical Pharmacology and Therapeutics

Volumn 88, Issue 2, 2010, Pages 166-182

  Holford, N ^a   Ma, S C ^a   Ploeger, B A ^b,c  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

^b LAP and P Consultants BV   (Netherlands)

^c LEIDEN UNIVERSITY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

3 [3 (3 METHOXYPHENYL) 2 PROPYNYLOXYIMINO] 1 AZABICYCLO[2.2.1]HEPTANE; ANTIARRHYTHMIC AGENT; CLOMIPRAMINE; CYCLOOXYGENASE 2 INHIBITOR; CYTOCHROME P450 2D6; DEXTROMETHORPHAN; DIGOXIN; DOCETAXEL; ETANERCEPT; FLUOXETINE; GABAPENTIN; HAE 1; IBUPROFEN; IVABRADINE; LEVODOPA; LITHIUM CARBONATE; MONOCLONAL ANTIBODY; NARATRIPTAN; OMALIZUMAB; OROSOMUCOID; OSTEOPROTEGERIN; PAROXETINE; PINDOLOL; PREGABALIN; SC 75416; SEROTONIN; SOTALOL; SUMATRIPTAN; TEDUGLUTIDE; UNCLASSIFIED DRUG; UNINDEXED DRUG;

ALLERGY; ALZHEIMER DISEASE; ANGINA PECTORIS; AREA UNDER THE CURVE; CHRONIC PAIN; CLINICAL TRIAL; CLINICAL TRIAL SIMULATION; COMPUTER PROGRAM; DEPRESSION; DOSAGE SCHEDULE COMPARISON; DRUG DOSE COMPARISON; DRUG DOSE ESCALATION; DRUG DOSE INCREASE; DRUG DOSE REDUCTION; DRUG EFFICACY; DRUG POTENCY; DRUG RESEARCH; DRUG SAFETY; DRUG SCREENING; DRUG USE; DRUG WITHDRAWAL; EXPERIMENTAL DESIGN; HUMAN; HYBRIDIZATION; JUVENILE RHEUMATOID ARTHRITIS; LUNG NON SMALL CELL CANCER; MIGRAINE; MODEL; NEUROPATHIC PAIN; PAIN; PARKINSON DISEASE; POSTOPERATIVE PAIN; PRIORITY JOURNAL; PROCESS DESIGN; PROCESS MODEL; REVIEW; SHORT BOWEL SYNDROME; SIMULATION; SINGLE DRUG DOSE; STOCHASTIC MODEL; SUPRAVENTRICULAR TACHYCARDIA; TASK PERFORMANCE; VALIDITY;

CLINICAL TRIALS AS TOPIC; COMPUTER SIMULATION; DRUG DISCOVERY; HUMANS; MODELS, STATISTICAL; PHARMACOKINETICS; PHARMACOLOGY, CLINICAL; RESEARCH DESIGN; SOFTWARE;

EID: 77954887077     PISSN: 00099236     EISSN: 15326535     Source Type: Journal    
DOI: 10.1038/clpt.2010.114     Document Type: Review

References (48)

1. Webster, P. Escalating costs and lengthy clinical trials are major concerns for researchers in the feld of drug discovery. The Medical News (2004).
2. Us Food and Drug Administration. Challenge and Opportunity on the Critical Path to New Medical Products (2004). Accessed 19 April 2010.
3. Holford, N.H., Kimko, H.C., Monteleone, J.P. & Peck, C.C. simulation of clinical trials. Annu. Rev. Pharmacol. Toxicol. 40, 209-234 (2000).
4. Brindley, P.G. & Dunn, W.F. simulation for clinical research trials: a theoretical outline. J. Crit. Care 24, 164-167 (2009).
5. Aarons, L., Karlsson, M.O., Mentré, F., Rombout, F., steimer, J.L. & van Peer, A.; COst B15 Experts. Role of modelling and simulation in Phase I drug development. Eur. J. Pharm. Sci. 13, 115-122 (2001).
6. Nyberg, J., svensson, A., Karlsson, M.O. & Hooker, A.C. Optimal Design of time-to-Event Models with an Emphasis on Dropouts in Disease Progression studies (2010). Accessed 19 April 2010
7. Holford, N.H.g., Hale, M., Ko, H.C., steimer, J.-L., sheiner, L.B. & Peck, C.C. simulation in Drug Development: good Practices. (1999). Accessed 19 April 2010. the Parkinson study group. Levodopa and the progression of Parkinson's disease. N. Engl. J. Med. 351, 2498-2508 (2004).
8. Beal, S., sheiner, L.B., Boeckmann, A. & Bauer, R.J. (eds.). NONMEM User's Guides (Icon Development solutions, Ellicott City, MD, 1989-2009)
9. Dickinson, G.L., Rezaee, S., Proctor, N.J., Lennard, M.S., tucker, G.T. & Rostami-Hodjegan, A. Incorporating in vitro information on drug metabolism into clinical trial simulations to assess the efect of CYP2D6 polymorphism on pharmacokinetics and pharmacodynamics: dextromethorphan as a model application. J. Clin. Pharmacol. 47, 175-186 (2007).
10. Rajman, I. PK/PD modelling and simulations: utility in drug development. Drug Discov. Today 13, 341-346 (2008).
11. Lalonde, R.L. et al. Model-based drug development. Clin. Pharmacol. Ther. 82, 21-32 (2007).
12. Chien, J.Y., Friedrich, S., Heathman, M.A., de Alwis, D.P. & sinha, V. Pharmacokinetics/Pharmacodynamics and the stages of drug development: role of modeling and simulation. AAPS J. 7, E544-E559 (2005).
13. Zhang, L. et al. Model-based drug development: the road to quantitative pharmacology. J. Pharmacokinet. Pharmacodyn. 33, 369-393 (2006)
14. Gobburu, J.V. & Marroum, P.J. Utilisation of pharmacokinetic- pharmacodynamic modelling and simulation in regulatory decision-making. Clin. Pharmacokinet. 40, 883-892 (2001).
15. Wang, Y. et al. Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004-2006. J. Clin. Pharmacol. 48, 146-156 (2008).
16. Desai, K., Boily, M.C., garnett, G.P., Mâsse, B.R., Moses, S. & Bailey, R.C. the role of sexually transmitted infections in male circumcision efectiveness against HIV-insights from clinical trial simulation. Emerg. Themes Epidemiol. 3, 19 (2006)
17. Läer, S. et al. Development of a safe and efective pediatric dosing regimen for sotalol based on population pharmacokinetics and pharmacodynamics in children with supraventricular tachycardia. J. Am. Coll. Cardiol. 46, 1322-1330 (2005)
18. Yim, D.S., Zhou, H., Buckwalter, M., Nestorov, I., Peck, C.C. & Lee, H. Population pharmacokinetic analysis and simulation of the time-concentration profle of etanercept in pediatric patients with juvenile rheumatoid arthritis. J. Clin. Pharmacol. 45, 246-256 (2005).
19. Ozawa, K., Minami, H. & sato, H. Clinical trial simulations for dosage optimization of docetaxel in patients with liver dysfunction, based on a log-binominal regression for febrile neutropenia. Yakugaku Zasshi 129, 749-757 (2009).
20. Chan, P.L., Nutt, J.G. & Holford, N.H. Levodopa slows progression of Parkinson's disease: external validation by clinical trial simulation. Pharm. Res. 24, 791-802 (2007).
21. Kuemmerle-Deschner, J.B. & Hornef, G. safety and efcacy of once-weekly application of Etanercept in children with juvenile idiopathic arthritis. Rheumatol. Int. 28, 153-156 (2007).
22. Giannini, E.H. et al. Long-term safety and efectiveness of etanercept in children with selected categories of juvenile idiopathic arthritis. Arthritis Rheum. 60, 2794-2804 (2009).
23. Ince, I., de Wildt, S.N, tibboel, D., Danhof, M. & Knibbe, C.A. tailor-made drug treatment for children: creation of an infrastructure for data-sharing and population PK-PD modeling. Drug Discov. Today 14, 316-320 (2009).
24. Anderson, B.J. & Holford, N.H. Mechanism-based concepts of size and maturity in pharmacokinetics. Annu. Rev. Pharmacol. Toxicol. 48, 303-332 (2008).
25. Rhodin, M.M. et al. Human renal function maturation: a quantitative description using weight and postmenstrual age. Pediatr. Nephrol. 24, 67-76 (2009).
26. Rubino, C.M. et al. Population pharmacokinetic model for gatifoxacin in pediatric patients. Antimicrob. Agents Chemother. 51, 1246-1252 (2007).
27. Mouksassi, M.S., Marier, J.F., Cyran, J. & Vinks, A.A. Clinical trial simulations in pediatric patients using realistic covariates: application to teduglutide, a glucagon-like peptide-2 analog in neonates and infants with short-bowel syndrome. Clin. Pharmacol. Ther. 86 667-671 (2009).
28. Sheiner, L.B. Learning versus confrming in clinical drug development. Clin. Pharmacol. Ther. 61, 275-291 (1997).
29. Gruwez, B., Dauphin, A. & tod, M. A mathematical model for paroxetine antidepressant efect time course and its interaction with pindolol. J. Pharmacokinet. Pharmacodyn. 32, 663-683 (2005)
30. Geretsegger, C., Bitterlich, W., stelzig, R., stuppaeck, C., Bondy, B. & Aichhorn, W. Paroxetine with pindolol augmentation: a double-blind, randomized, placebo-controlled study in depressed in-patients. Eur. Neuropsychopharmacol. 18, 141-146 (2008)
31. Putnam, W.S. et al. Use of quantitative pharmacology in the development of HAE1, a high-afnity anti-IgE monoclonal antibody. AAPS J. 10, 425-430 (2008).
32. Lockwood, P., Ewy, W., Hermann, D. & Holford, N. Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of efect; an example in Alzheimer's disease. Pharm. Res. 23, 2050-2059 (2006)
33. Kowalski, K.G., Olson, S., Remmers, A.E. & Hutmacher, M.M. Modeling and simulation to support dose selection and clinical development of sC-75416, a selective COX-2 inhibitor for the treatment of acute and chronic pain. Clin. Pharmacol. Ther. 83, 857-866 (2008).
34. Veyrat-Follet, C., Bruno, R., Olivares, R., Rhodes, G.R. & Chaikin, P. Clinical trial simulation of docetaxel in patients with cancer as a tool for dosage optimization. Clin. Pharmacol. Ther. 68, 677-687 (2000)
35. Gruwez, B., Poirier, M.F., Dauphin, A., Olié, J.P. & tod, M. A kinetic-pharmaco-dynamic model for clinical trial simulation of antidepressant action: application to clomipramine-lithium interaction. Contemp. Clin. Trials 28, 276-287 (2007).
36. Nestorov, I., graham, G., Dufull, S., Aarons, L., Fuseau, E. & Coates, P. Modeling and stimulation for clinical trial design involving a categorical response: a phase II case study with naratriptan. Pharm. Res. 18, 1210-1219 (2001).
37. Holford, N.H., Chan, P.L., Nutt, J.G., Kieburtz, K. & shoulson, I.; Parkinson study group. Disease progression and pharmacodynamics in Parkinson disease-evidence for functional protection with levodopa and other treatments. J. Pharmacokinet. Pharmacodyn. 33, 281-311 (2006).
38. Hauser, R.A. & Holford, N.H. Quantitative description of loss of clinical beneft following withdrawal of levodopa-carbidopa and bromocriptine in early Parkinson's disease. Mov. Disord. 17, 961-968 (2002).
39. Ploeger, B.A. & Holford, N.H. Washout and delayed start designs for identifying disease modifying efects in slowly progressive diseases using disease progression analysis. Pharm. Stat. 8, 225-238 (2009).
40. Lockwood, P.A., Cook, J.A., Ewy, W.E. & Mandema, J.W. the use of clinical trial simulation to support dose selection: application to development of a new treatment for chronic neuropathic. pain. Pharm. Res. 20, 1752-1759 (2003).
41. Chabaud, S., girard, P., Nony, P. & Boissel, J.P. Clinical trial simulation using therapeutic efect modeling: application to ivabradine efcacy in patients with angina pectoris. J. Pharmacokinet. Pharmacodyn. 29, 339-363 (2002).
42. Zierhut, M.L. et al. Population PK-PD model for Fc-osteoprotegerin in healthy postmenopausal women. J. Pharmacokinet. Pharmacodyn. 35, 379-399 (2008)
43. Tannenbaum, S.J., Holford, N.H., Lee, H., Peck, C.C. & Mould, D.R. simulation of correlated continuous and categorical variables using a single multivariate distribution. J. Pharmacokinet. Pharmacodyn. 33, 773-794 (2006)
44. Hennig, S., Nyberg, J., Hooker, A.C. & Karlsson, M.O. trial treatment length optimization with an emphasis on disease progression studies. J. Clin. Pharmacol. 49, 323-335 (2009)
45. Silber, H.E., Nyberg, J., Hooker, A.C. & Karlsson, M.O. Optimization of the intravenous glucose tolerance test in t2DM patients using optimal experimental design. J. Pharmacokinet. Pharmacodyn. 36, 281-295 (2009)
46. Zamuner, S. et al. Adaptive-optimal design in PEt occupancy studies. Clin. Pharmacol. Ther. 87, 563-571 (2010).
47. Innovative Medicines Initiative. Drug/Disease Modelling: Library & Framework (DDMLF) IMI-Call-2009-7 (2009).
48. De Ridder, F. Predicting the outcome of phase III trials using phase II data: a case study of clinical trial simulation in late stage drug development. Basic Clin. Pharmacol. Toxicol. 96, 235-241 (2005).