Contribution of Modeling and Simulation in the Regulatory Review and Decision-Making: U.S. FDA Perspective

  • Christine E. Garnett
  • Joo Yeon Lee
  • Jogarao V. S. Gobburu
Part of the AAPS Advances in the Pharmaceutical Sciences Series book series (AAPS, volume 1)


The Division of Pharmacometrics at the U.S. FDA engages in regulatory reviews, research and policy development. During 2000–2008, over 50% of pharmacometric reviews of 198 NDA and BLA applications influenced approval and safety decisions. During this time, pharmacometric analyses were used in pediatric dose selection, and approval of doses not directly studied in effectiveness trials. Additionally, pharmacometrics has been used in FDA advice on protocol design to optimize dosing regimens based on benefit-risk for clinical testing, and to provide confirmatory evidence of effectiveness. Current research projects aim to solve drug development challenges and develop policies grounded in pharmacometric principles and methodologies.


Pulmonary Arterial Hypertension Pediatric Indication Dose Selection Regulatory Review Pediatric Dose 
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.


  1. Advisory Committee Meeting (2006) Celebrex® (celocoxib) Application No. 020998. Accessed 29 Nov 2006
  2. Benjamin DK Jr, Smith PB, Jadhav P, Gobburu JV, Murphy MD, Hasselblad V, Baker-Smith C, Califf RM, Li JS (2008) Pediatric antihypertensive trial failures: analysis of end points and dose range. Hypertension 51:834–840PubMedCrossRefGoogle Scholar
  3. Bhattaram VA, Booth BP, Ramchandani RP, Beasley BN, Wang Y, Tandon V, Duan JZ, Baweja RK, Marroum PJ, Uppoor RS, Rahman NA, Sahajwalla CG, Powell JR, Mehta MU, Gobburu JV (2005) Impact of pharmacometrics on drug approval and labeling decisions: a survey of 42 new drug applications. AAPS J 7:E503–E512PubMedCrossRefGoogle Scholar
  4. Bhattaram VA, Bonapace C, Chilukuri DM, Duan JZ, Garnett C, Gobburu JV, Jang SH, Kenna L, Lesko LJ, Madabushi R, Men Y, Powell JR, Qiu W, Ramchandani RP, Tornoe CW, Wang Y, Zheng JJ (2007) Impact of pharmacometric reviews on new drug approval and labeling decisions–a survey of 31 new drug applications submitted between 2005 and 2006. Clin Pharmacol Ther 81:213–221PubMedCrossRefGoogle Scholar
  5. Bhattaram VA, Siddiqui O, Kapcala LP, Gobburu JV (2009) Endpoints and analyses to discern disease-modifying drug effects in early Parkinson's disease. AAPS J 11:456–464PubMedCrossRefGoogle Scholar
  6. Booth BP, Rahman A, Dagher R, Griebel D, Lennon S, Fuller D, Sahajwalla C, Mehta M, Gobburu JV (2007) Population pharmacokinetic-based dosing of intravenous busulfan in pediatric patients. J Clin Pharmacol 47:101–111PubMedCrossRefGoogle Scholar
  7. Drug Approval Package (2005) Zemplar® Capsules (paricalcitrol) Application No. Accessed 25 May 2005
  8. Drug Approval Package (2008a) Cimzia® (certolizumab pegol) Application No. 125160. Accessed 28 Apr 2008
  9. Drug Approval Package (2008b) Cleviprex® (clevidipine butyrate) Application No. 022156. Accessed 1 Aug 2008
  10. Drug Approval Package (2008c) Xenazine® Tablets (tetrabenazine) Application No. 021894. Accessed 18 Aug 2008
  11. Florian FA, Tornoe CW, Brundage R, Parekh A, Garnett CE (2010) Population PK and concentration-QTc models for moxifloxacin: pooled analysis of 20 thorough QT studies. J Clin Pharmacol In press.Google Scholar
  12. Food and Drug Administration (1998) Guidance for industry: providing clinical evidence of effectiveness for human drug and biological products.
  13. Food and Drug Administration (1999) Guidance for industry: population pharmacokinetics.
  14. Food and Drug Administration (2003) Guidance for industry: exposure-response relationships – study design, data analysis, and regulatory applications. U.S. Department of Health and Human Services, Food and Drug Administration.
  15. Food and Drug Administration (2004) FDA critical path initatives white paper: innovation or stagnation? Challenge and opportunity on the critical path to new medical productsGoogle Scholar
  16. Garnett CE, Beasley N, Bhattaram VA, Jadhav PR, Madabushi R, Stockbridge N, Tornoe CW, Wang Y, Zhu H, Gobburu JV (2008) Concentration-QT relationships play a key role in the evaluation of proarrhythmic risk during regulatory review. J Clin Pharmacol 48:13–18PubMedCrossRefGoogle Scholar
  17. Gieschke R, Reigner BG, Steimer JL (1997) Exploring clinical study design by computer simulation based on pharmacokinetic/pharmacodynamic modelling. Int J Clin Pharmacol Ther 35:469–474PubMedGoogle Scholar
  18. Gobburu JV, Lesko LJ (2009) Quantitative disease, drug, and trial models. Annu Rev Pharmacol Toxicol 49:291–301PubMedCrossRefGoogle Scholar
  19. Hale MD, Nicholls AJ, Bullingham RE, Hene R, Hoitsma A, Squifflet JP, Weimar W, Vanrenterghem Y, Van de Woude FJ, Verpooten GA (1998) The pharmacokinetic-pharmacodynamic relationship for mycophenolate mofetil in renal transplantation. Clin Pharmacol Ther 64:672–683PubMedCrossRefGoogle Scholar
  20. Humira® Label (2007) Humira® (adalimumab) Injection Application No. 125057. Accessed 27 Feb 2007
  21. International Conference Harmonization (1994) E4: Dose-Response Information to Support Drug Registration.
  22. International Conference Harmonization (2005) E14: The clinical evaluation of QT/QTc interval prolongation and proarrhythmic potential for non-antiarrhythmic drugs.
  23. Jadhav PR, Zhang J, Gobburu JV (2009) Leveraging prior quantitative knowledge in guiding pediatric drug development: a case study. Pharm Stat 8:216–224PubMedCrossRefGoogle Scholar
  24. Jadhav PR, Burckart GJ, Choe S, Estes K, Huang SM, Lu S, Lesko LJ, Liu Q, Mulugenta L, Mummaneni P, Tandon V, Gobburu JV, Wang Y (2010a) Defining the quality of pediatric pharmacokinetic studies. Clin Pharmacol Ther In press.Google Scholar
  25. Jadhav PR, Burckart G.J., Lesko LJ, Gobburu JV (2010b) Paediatric Drug Development and Clinical Pharmacology. Drug Development In press.Google Scholar
  26. Jusko WJ, Ko HC (1994) Physiologic indirect response models characterize diverse types of pharmacodynamic effects. Clin Pharmacol Ther 56:406–419PubMedCrossRefGoogle Scholar
  27. Kola I, Landis J (2004) Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 3:711–715PubMedCrossRefGoogle Scholar
  28. Krall RL, Engleman KH, Ko HC, Peck CC (1998) Clinical trial modeling and simulation – Work in progress. Drug Information J 32:971–976Google Scholar
  29. Krzyzanski W, Jusko WJ (1997) Mathematical formalism for the properties of four basic models of indirect pharmacodynamic responses. J Pharmacokinet Biopharm 25:107–123PubMedCrossRefGoogle Scholar
  30. 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) Model-based drug development. Clin Pharmacol Ther 82:21–32PubMedCrossRefGoogle Scholar
  31. Li F, Nandy P, Chien S, Noel GJ, Tornoe CW (2010) Pharmacometrics-based dose selection of levofloxacin as a treatment for post-exposure inhalational anthrax in children. Antimicrob Agents Chemother 54:375–379PubMedCrossRefGoogle Scholar
  32. Madabushi R, Cox DS, Hossain M, Boyle DA, Patel BR, Young G, Choi YM, Gobburu JV (2010) Pharmacokinetic and pharmacodynamic basis for effective argatroban dosing in pediatrics. J Clin PharmacolGoogle Scholar
  33. Miller R, Ewy W, Corrigan BW, Ouellet D, Hermann D, Kowalski KG, Lockwood P, Koup JR, Donevan S, El-Kattan A, Li CS, Werth JL, Feltner DE, Lalonde RL (2005) How modeling and simulation have enhanced decision making in new drug development. J Pharmacokinet Pharmacodyn 32:185–197PubMedCrossRefGoogle Scholar
  34. Olson SC, Bockbrader H, Boyd RA, Cook J, Koup JR, Lalonde RL, Siedlik PH, Powell JR (2000) Impact of population pharmacokinetic-pharmacodynamic analyses on the drug development process: experience at Parke-Davis. Clin Pharmacokinet 38:449–459PubMedCrossRefGoogle Scholar
  35. Peck CC (1992a) Population approach in pharmacokinetics and pharmacodynamics: FDA view. Conference on new strategies in drug development and clinical evaluation: the population approach, Manchester, England, September 1991. Published by the Commission of the European Communities: European cooperation in the field of scientific and technical research, 157–168Google Scholar
  36. Peck CC (1992b) Streamlining clinical testing: presented at first Princeton conference on drug development, October 1991. Lasagna L (ed) Published by Excerpta Medica, Inc., Princeton, NJ, 33–35Google Scholar
  37. Peck CC (1997) Drug development: improving the process. Food Drug Law J 52(2):163–167PubMedGoogle Scholar
  38. Peck CC, Barr WH, Benet LZ, Collins J, Desjardins RE, Furst DE, Harter JG, Levy G, Ludden T, Rodman JH (1992) Opportunities for integration of pharmacokinetics, pharmacodynamics, and toxicokinetics in rational drug development. Clin Pharmacol Ther 51:465–473PubMedCrossRefGoogle Scholar
  39. Reigner BG, Williams PE, Patel IH, Steimer JL, Peck C, van Brummelen P (1997) An evaluation of the integration of pharmacokinetic and pharmacodynamic principles in clinical drug development. Experience within Hoffmann La Roche. Clin Pharmacokinet 33:142–152PubMedCrossRefGoogle Scholar
  40. Rock EP, Finkle J, Fingert HJ, Booth BP, Garnett CE, Grant S, Justice RL, Kovacs RJ, Kowey PR, Rodriguez I, Sanhai WR, Strnadova C, Targum SL, Tsong Y, Uhl K, Stockbridge N (2009) Assessing proarrhythmic potential of drugs when optimal studies are infeasible. Am Heart J 157(827–36):836Google Scholar
  41. Sheiner LB, Stanski DR, Vozeh S, Miller RD, Ham J (1979) Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine. Clin Pharmacol Ther 25:358–371PubMedGoogle Scholar
  42. Sotalol Label (2009) Sotalol HCl Application No. 022306. Accessed 2 Jul 2009
  43. Taylor DW, Bosch EG (1990) CTS: a clinical trials simulator. Stat Med 9:787–801PubMedCrossRefGoogle Scholar
  44. Tornoe CW, Tworzyanski JJ, Imoisili MA, Alexander JJ, Korth-Bradley JM, Gobburu JV (2007) Optimising piperacillin/tazobactam dosing in paediatrics. Int J Antimicrob Agents 30:320–324PubMedCrossRefGoogle Scholar
  45. Tornoe CW, Garnett CE, Wang Y, Florian JA, Li M, Gobburu JV (2010) Creation of knowledge management system for QT analyses. J Clin Pharmacol In pressGoogle Scholar
  46. Wang Y, Bhattaram AV, Jadhav PR, Lesko LJ, Madabushi R, Powell JR, Qiu W, Sun H, Yim DS, Zheng JJ, Gobburu JV (2008) Leveraging prior quantitative knowledge to guide drug development decisions and regulatory science recommendations: impact of FDA pharmacometrics during 2004-2006. J Clin Pharmacol 48:146–156PubMedCrossRefGoogle Scholar
  47. Wang Y, Garnett CE (2010) Letter to the editor: statistical issues of QT prolongation assessment based on linear concentration modeling by Yi Tsong et al. J Biopharm Stat 20:689–692PubMedCrossRefGoogle Scholar
  48. Wang Y, Sung C, Dartois C, Ramchandani R, Booth BP, Rock E, Gobburu J (2009) Elucidation of relationship between tumor size and survival in non-small-cell lung cancer patients can aid early decision making in clinical drug development. Clin Pharmacol Ther 86:167–174PubMedCrossRefGoogle Scholar
  49. Yan LK, Zhang J, Ng MJ, Dang Q (2010) Statistical characteristics of moxifloxacin-induced QTc effect. J Biopharm Stat 20:497–507PubMedCrossRefGoogle Scholar
  50. Zhang L, Sinha V, Forgue ST, Callies S, Ni L, Peck R, Allerheiligen SR (2006) Model-based drug development: the road to quantitative pharmacology. J Pharmacokinet Pharmacodyn 33:369–393PubMedCrossRefGoogle Scholar
  51. Zhu H, Wang Y, Gobburu JV, Garnett CE (2010) Considerations for clinical trial design and data analysis of thorough QT studies using drug–drug interactions. J Clin Pharmacol. doi: 10.1177/0091270009358710 Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Christine E. Garnett
    • 1
  • Joo Yeon Lee
  • Jogarao V. S. Gobburu
  1. 1.Center for Drug Evaluation and ResearchFood and Drug AdministrationSilver SpringUSA

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