Skip to main content
The AAPS Journal logoLink to The AAPS Journal
. 2005 Oct 5;7(2):E475–E487. doi: 10.1208/aapsj070248

Population pharmacokinetic studies in pediatrics: Issues in design and analysis

Bernd Meibohm 1,, Stephanie Läer 2, John C Panetta 1,3, Jeffrey S Barrett 4
PMCID: PMC2750985  PMID: 16353925

Abstract

The current review addresses the following 3 frequently encountered challenges in the design and analysis of population pharmacokinetic studies in pediatrics: (1) body size adjustments during the development of pharmacostatistical models, (2) design and validation of limited sampling strategies, and (3) the integration of historical priors in data analysis and trial simulation. Size adjustments with empiric approaches based on body weight or body surface area have frequently proven as a pragmatic tool to overcome large size differences in a pediatric study population. Allometric size adjustments, however, provide a more mechanistic, physiologically based approach that, if used a priori, allows delineation of the effect of size from that of other covariates that show a high degree of collinearity. The frequent lack of dense data sets in pediatric clinical pharmacology because of ethical and logistic constraints in study design can be overcome with the application of D-optimality-based limited sampling schemes in combination with Bayesian and nonlinear mixed-effects modeling approaches. Empirically based dose selection and clinical trial designs for pediatric clinical pharmacology studies can be improved by applying clinical trial simulation techniques, especially if they integrate adult and pediatric in vitro and/or in vivo data as historic priors. Although integration of these concepts and techniques in population pharmacokinetic analyses is not only limited to pediatric research, their application allows researchers to overcome some major hurdles frequently encountered in pharmacokinetic studies in pediatrics and, thus, provides the basis for additional clinical pharmacology research in this previously insufficiently studied fraction of the general population.

Keywords: population pharmacokinetics, pediatrics, body size, sparse sampling, clinical trial simulation

Full Text

The Full Text of this article is available as a PDF (360.5 KB).

References

  • 1.Grasela TH, Sheiner LB, Rambeck B, et al. Steady-state pharmacokinetics of phenytoin from routinely collected patient data. Clin Pharmacokinet. 1983;8:355–364. doi: 10.2165/00003088-198308040-00006. [DOI] [PubMed] [Google Scholar]
  • 2.Grasela TH, Donn SM. Neonatal population pharmacokinetics of phenobarbital derived from routine clinical data. Dev Pharmacol Ther. 1985;8:374–383. doi: 10.1159/000457062. [DOI] [PubMed] [Google Scholar]
  • 3.Kelman AW, Thomson AH, Whiting B, et al. Estimation of gentamicin elearance and volume of distribution in neonates and young children. Br J Clin Pharmacol. 1984;18:685–692. doi: 10.1111/j.1365-2125.1984.tb02530.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Roberts R, Rodriguez W, Murphy D, Crescenzi T. Pediatric drug labeling: improving the safety and efficacy of pediatric therapies. JAMA. 2003;290:905–911. doi: 10.1001/jama.290.7.905. [DOI] [PubMed] [Google Scholar]
  • 5.General Considerations for Pediatric Pharmacokinetic Studies for Drugs and Biological Products—Draft Guidance. Rockville: Food and Drug Administration, Center for Drug Evaluation and Research; 1998. [Google Scholar]
  • 6.Rajagopalan P, Gastonguay MR. Population pharmacokinetics of ciprofloxacin in pediatric patients. J Clin Pharmacol. 2003;43:698–710. [PubMed] [Google Scholar]
  • 7.Chatelut E, Boddy AV, Peng B, et al. Population pharmacokinetics of carboplatin in children. Clin Pharmacol Ther. 1996;59:436–443. doi: 10.1016/S0009-9236(96)90113-7. [DOI] [PubMed] [Google Scholar]
  • 8.Ette EI, Ludden TM. Population pharmacokinetic modeling: the importance of informative graphics. Pharm Res. 1995;12:1845–1855. doi: 10.1023/A:1016215116835. [DOI] [PubMed] [Google Scholar]
  • 9.Ette EI, Williams P, Fadiran E, Ajayi FO, Onyiah LC. The process of knowledge discovery from large pharmacokinetic data sets. J Clin Pharmacol. 2001;41:25–34. doi: 10.1177/00912700122009809. [DOI] [PubMed] [Google Scholar]
  • 10.Bonate PL. The effect of collinearity on parameter estimates in nonlinear mixed effect models. Pharm Res. 1999;16:709–717. doi: 10.1023/A:1018828709196. [DOI] [PubMed] [Google Scholar]
  • 11.Gusella M, Toso S, Ferrazzi E, Ferrari M, Padrini R. Relationships between body composition parameters and fluorouracil pharmacokinetics. Br J Clin Pharmacol. 2002;54:131–139. doi: 10.1046/j.1365-2125.2002.01598.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Kanamori M, Takahashi H, Echizen H. Developmental changes in the liver weight-and body weight-normalized clearance of theophylline, phenytoin and cyclosporine in children. Int J Clin Pharmacol Ther. 2002;40:485–492. doi: 10.5414/cpp40485. [DOI] [PubMed] [Google Scholar]
  • 13.Green B, Duffull SB. What is the best size descriptor to use for pharmacokinetic studies in the obese? Br J Clin Pharmacol. 2004;58:119–133. doi: 10.1111/j.1365-2125.2004.02157.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Mahmood I. Allometric issues in drug development. J Pharm Sci. 1999;88:1101–1106. doi: 10.1021/js9902163. [DOI] [PubMed] [Google Scholar]
  • 15.Bonate PL, Howard D. Prospective allometric scaling: does the emperor have clothes? J Clin Pharmacol. 2000;40:335–340. doi: 10.1177/00912700022009017. [DOI] [PubMed] [Google Scholar]
  • 16.Mahmood I. Interspecies scaling: predicting oral clearance in humans. Am J Ther. 2002;9:35–42. doi: 10.1097/00045391-200201000-00008. [DOI] [PubMed] [Google Scholar]
  • 17.West GB, Brown JH, Enquist BJ. The fourth dimension of life: fractal geometry and allometric scaling of organisms. Science. 1999;284:1677–1679. doi: 10.1126/science.284.5420.1677. [DOI] [PubMed] [Google Scholar]
  • 18.West GB, Brown JH, Enquist BJ. A general model for the origin of allometric scaling laws in biology. Science. 1997;276:122–126. doi: 10.1126/science.276.5309.122. [DOI] [PubMed] [Google Scholar]
  • 19.Weibel ER. Physiology: the pitfalls of power laws. Nature. 2002;417:131–132. doi: 10.1038/417131a. [DOI] [PubMed] [Google Scholar]
  • 20.Holford NH. A size standard for pharmacokinetics. Clin Pharmacokinet. 1996;30:329–332. doi: 10.2165/00003088-199630050-00001. [DOI] [PubMed] [Google Scholar]
  • 21.Anderson BJ, Woollard GA, Holford NH. A model for size and age changes in the pharmacokinetics of paracetamol in neonates, infants and children. Br J Clin Pharmacol. 2000;50:125–134. doi: 10.1046/j.1365-2125.2000.00231.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Hu TM, Hayton WL. Allometric scaling of xenobiotic clearance: uncertainty versus universality. AAPS PharmSci. 2001;3:E29–E29. doi: 10.1208/ps030429. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Boxenbaum H. Interspecies scaling, allometry, physiological time, and the ground plan of pharmacokinetics. J Pharmacokinet Biopharm. 1982;10:201–227. doi: 10.1007/BF01062336. [DOI] [PubMed] [Google Scholar]
  • 24.Anderson BJ, McKee AD, Holford NH. Size, myths and the clinical pharmacokinetics of analgesia in paediatric patients. Clin Pharmacokinet. 1997;33:313–327. doi: 10.2165/00003088-199733050-00001. [DOI] [PubMed] [Google Scholar]
  • 25.Kleiber M. Body size and metabolism.Hilgardia. 1932;6315–6353.
  • 26.McMahon T. Size and shape in biology. Science. 1973;179:1201–1204. doi: 10.1126/science.179.4079.1201. [DOI] [PubMed] [Google Scholar]
  • 27.Anderson BJ, Holford NH, Woollard GA, chan PL. Paracetamol plasma and cerebrospinal fluid pharmacokinetics in children. Br J Clin Pharmacol. 1998;46:237–243. doi: 10.1046/j.1365-2125.1998.00780.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Agutter PS, Wheatley DN. Metabolic scaling: consensus or controversy?Theor Biol Med Model. 2004:1–13. [DOI] [PMC free article] [PubMed]
  • 29.Darveau CA, Suarez RK, Andrews RD, Hochachka PW. Allometric cascade as a unifying principle of body mass effects on metabolism. Nature. 2002;417:166–170. doi: 10.1038/417166a. [DOI] [PubMed] [Google Scholar]
  • 30.Rodman JH. Pharmacokinetic variability in the adolescent: implications of body size and organ function for dosage regimen design. J Adolesc Health. 1994;15:654–662. doi: 10.1016/S1054-139X(94)90633-5. [DOI] [PubMed] [Google Scholar]
  • 31.Bailey JM, Hoffman TM, Wessel DL, et al. A population pharmacokinetic analysis of milrinone in pediatric patients after cardiac surgery. J Pharmacokinet Pharmacodyn. 2004;31:43–59. doi: 10.1023/B:JOPA.0000029488.45177.48. [DOI] [PubMed] [Google Scholar]
  • 32.Martin-Suarez A, Falcao AC, Outeda M, et al. Population pharmacokinetics of digoxin in pediatric patients. Ther Drug Monit. 2002;24:742–745. doi: 10.1097/00007691-200212000-00010. [DOI] [PubMed] [Google Scholar]
  • 33.Schaefer HG, Stass H, Wedgwood J, et al. Pharmacokinetics of ciprofloxacin in pediatric cystic fibrosis patients. Antimicrob Agents Chemother. 1996;40:29–34. doi: 10.1128/aac.40.1.29. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Christensen ML, Mottern RK, Jabbour JT, Fuseau E. Pharmacokinetics of sumatriptan nasal spray in children. J Clin Pharmacol. 2004;44:359–367. doi: 10.1177/0091270004263467. [DOI] [PubMed] [Google Scholar]
  • 35.Dubois D, Dubois E. A formula to estimate the approximate surface area if height and weight be known.Arch Int Med. 1916;17863–17871.
  • 36.Gehan EA, George SL. Estimation of human body surface area from height and weight. Cancer Chemother Rep. 1970;54:225–235. [PubMed] [Google Scholar]
  • 37.Mosteller RD. Simplified calculation of body-surface area. N Engl J Med. 1987;317:1098–1098. doi: 10.1056/NEJM198710223171717. [DOI] [PubMed] [Google Scholar]
  • 38.Shi J, Ludden TM, Melikian AP, Gastonguay MR, Hinderling PH. Population pharmacokinetics and pharmacodynamics of sotalol in pediatric patients with supraventricular or ventricular tachyarrhythmia. J Pharmacokinet Pharmacodyn. 2001;28:555–575. doi: 10.1023/A:1014412521191. [DOI] [PubMed] [Google Scholar]
  • 39.Sallas WM, Milosavljev S, D'Souza J, Hossain M. Pharmacokinetic drug interactions in children taking oxcarbazepine. Clin Pharmacol Ther. 2003;74:138–149. doi: 10.1016/S0009-9236(03)00124-3. [DOI] [PubMed] [Google Scholar]
  • 40.Reilly JJ, Workman P. Normalisation of anti-cancer drug dosage using body weight and surface area: is it worthwhile? A review of theoretical and practical considerations. Cancer Chemother Pharmacol. 1993;32:411–418. doi: 10.1007/BF00685883. [DOI] [PubMed] [Google Scholar]
  • 41.Yukawa E, Satou M, Nonaka T, et al. Pharmacoepidemiologic investigation of clonazepam relative clearance by mixed-effect modeling using routine clinical pharmacokinetic data in Japanese patients. J Clin Pharmacol. 2002;42:81–88. doi: 10.1177/0091270002042001009. [DOI] [PubMed] [Google Scholar]
  • 42.Mandema JW, Verotta D, Sheiner LB. Building population pharmacokinetic-pharmacodynamic models. I. Models for covariate effects. J Pharmacokinet Biopharm. 1992;20:511–528. doi: 10.1007/BF01061469. [DOI] [PubMed] [Google Scholar]
  • 43.Capparelli EV, Englund JA, Connor JD, et al. Population pharmacokinetics and pharmacodynamics of zidovudine in HIV-infected infants and children. J Clin Pharmacol. 2003;43:133–140. doi: 10.1177/0091270002239821. [DOI] [PubMed] [Google Scholar]
  • 44.Panetta JC, Iacono LC, Adamson PC, Stewart CF. The importance of pharmacokinetic limited sampling models for childhood cancer drug development. Clin Cancer Res. 2003;9:5068–5077. [PubMed] [Google Scholar]
  • 45.Desoize B, Marechal F, Cattan A. Clinical pharmacokinetics of etoposide during 120 hours continuous infusions in solid tumours. Br J Cancer. 1990;62:840–841. doi: 10.1038/bjc.1990.390. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Kobayashi K, Ratain MJ. Pharmacodynamics and long-term toxicity of etoposide. Cancer Chemother Pharmacol. 1994;34:S64–S68. doi: 10.1007/BF00684866. [DOI] [PubMed] [Google Scholar]
  • 47.Minami H, Ratain MJ, Ando Y, Shimokata K. Pharmacodynamic modeling of prolonged administration of etoposide. Cancer Chemother Pharmacol. 1996;39:61–66. doi: 10.1007/s002800050538. [DOI] [PubMed] [Google Scholar]
  • 48.Relling MV, McLeod H, Bowman L, Santana VM. Etoposide pharmacokinetics and pharmacodynamics after acute and chronic exposure to cisplatin. Clin Pharmacol Ther. 1994;56:503–511. doi: 10.1038/clpt.1994.171. [DOI] [PubMed] [Google Scholar]
  • 49.Sonnichsen DS, Ribeiro RC, Luo X, Mathew P, Relling MV. Pharmacokinetics and pharmacodynamics of 21-day continuous oral etoposide in pediatric patients with solid tumors. Clin Pharmacol Ther. 1995;58:99–107. doi: 10.1016/0009-9236(95)90077-2. [DOI] [PubMed] [Google Scholar]
  • 50.Panetta JC, Wilkinson M, Pui CH, Relling MV. Limited and optimal sampling strategies for etoposide and etoposide catechol in children with leukemia. J Pharmacokinet Pharmacodyn. 2002;29:171–188. doi: 10.1023/A:1019755608555. [DOI] [PubMed] [Google Scholar]
  • 51.Kirstein MN, Panetta JC, Gajjar A, et al. Development of a pharmacokinetic limited sampling model for temozolomide and its active metabolite MTIC. Cancer Chemother Pharmacol. 2005;55:433–438. doi: 10.1007/s00280-004-0896-9. [DOI] [PubMed] [Google Scholar]
  • 52.D'Argenio DZ. Optimal sampling times for pharmacokinetic experiments. J Pharmacokinet Biopharm. 1981;9:739–756. doi: 10.1007/BF01070904. [DOI] [PubMed] [Google Scholar]
  • 53.D'Argenio DZ. Incorporating prior parameter uncertainty in the design of sampling schedules for pharmacokinetic parameter estimation experiments. Math Biosci. 1990;99:105–118. doi: 10.1016/0025-5564(90)90141-K. [DOI] [PubMed] [Google Scholar]
  • 54.D'Argenio DZ, Schumitzky A. ADAPT II User's Guide: Pharmacokinetic/Pharmacodynamic Systems Analysis Software. Los Angeles: Biomedical Simulations Resource; 1997. [Google Scholar]
  • 55.Steimer JL, Mallet A, Golmard JL, Boisvieux JF. Alternative approaches to estimation of population pharmacokinetic parameters: comparison with the nonlinear mixed-effect model. Drug Metab Rev. 1984;15:265–292. doi: 10.3109/03602538409015066. [DOI] [PubMed] [Google Scholar]
  • 56.Retout S, Duffull S, Mentre F. Development and implementation of the population Fischer information matrix for the evaluation of population pharmacokinetic designs. Comput Methods Programs Biomed. 2001;65:141–151. doi: 10.1016/S0169-2607(00)00117-6. [DOI] [PubMed] [Google Scholar]
  • 57.Sheiner LB, Beal SL. Some suggestions for measuring predictive performance. J Pharmacokinet Biopharm. 1981;9:503–512. doi: 10.1007/BF01060893. [DOI] [PubMed] [Google Scholar]
  • 58.Stewart CF, Iacono LC, Chintagumpala M, et al. Results of a phase II upfront window of pharmacokinetically guided topotecan in high-risk medulloblastoma and supratentorial primitive neuroectodermal tumor. J Clin Oncol. 2004;22:3357–3365. doi: 10.1200/JCO.2004.10.103. [DOI] [PubMed] [Google Scholar]
  • 59.Santana VM, Zamboni WC, Kirstein MN, et al. A pilot study of protracted topotecan dosing using a pharmacokinetically guided dosing approach in children with solid tumors. Clin Cancer Res. 2003;9:633–640. [PubMed] [Google Scholar]
  • 60.Evans WE, Relling MV, Rodman JH, Crom WR, Boyett JM, Pui CH. Conventional compared with individualized chemotherapy for childhood acute lymphoblastic leukemia. N Engl J Med. 1998;338:499–505. doi: 10.1056/NEJM199802193380803. [DOI] [PubMed] [Google Scholar]
  • 61.Wilson JT. An update on the therapeutic orphan. Pediatrics. 1999;104:585–590. [PubMed] [Google Scholar]
  • 62.Lockwood PA, Cook JA, Ewy WE, Mandema JW. The use of clinical trial simulation to support dose selection: application to development of a new treatment for chronic neuropathic pain. Pharm Res. 2003;20:1752–1759. doi: 10.1023/B:PHAM.0000003371.32474.ee. [DOI] [PubMed] [Google Scholar]
  • 63.Anderson JJ, Bolognese JA, Felson DT. Comparison of rheumatoid arthritis clinical trial outcome measures: a simulation study. Arthritis Rheum. 2003;48:3031–3038. doi: 10.1002/art.11293. [DOI] [PubMed] [Google Scholar]
  • 64.Blesch KS, Gieschke R, Tsukamoto Y, Reigner BG, Burger HU, Steimer JL. Clinical pharmacokinetic/pharmacodynamic and physiologically based pharmacokinetic modeling in new drug development: the capecitabine experience. Invest New Drugs. 2003;21:195–223. doi: 10.1023/A:1023525513696. [DOI] [PubMed] [Google Scholar]
  • 65.Thall PF, Lee SJ. Practical model-based dose-finding in phase I clinical trials: methods based on toxicity. Int J Gynecol Cancer. 2003;13:251–261. doi: 10.1046/j.1525-1438.2003.13202.x. [DOI] [PubMed] [Google Scholar]
  • 66.Hausheer FH, Kochat H, Parker AR, et al. New approaches to drug discovery and development: a mechanism-based approach to pharmaceutical research and its application to BNP7787, a novel chemoprotective agent. Cancer Chemother Pharmacol. 2003;52:1S3–1S15. doi: 10.1007/s00280-003-0653-5. [DOI] [PubMed] [Google Scholar]
  • 67.Konski A, Sherman E, Krahn M, et al. Monte Carlo simulation of a Markov model for a phase III clinical trial evaluating the addition of total androgen suppression (TAS) to radiation versus radiation alone for locally advanced prostate cancer (RTOG 86-10) Int J Radiat Oncol Biol Phys. 2003;57:S215–S216. doi: 10.1016/j.ijrobp.2005.03.010. [DOI] [PubMed] [Google Scholar]
  • 68.Jumbe N, Yao B, Rovetti R, Rossi G, Heatherington AC. Clinical trial simulation of a 200-microg fixed dose of darbepoetin alfa in chemotherapy-induced anemia. Oncology (Huntingt) 2002;16:37–44. [PubMed] [Google Scholar]
  • 69.Veyrat-Follet C, Bruno R, Olivares R, Rhodes GR, Chaikin P. Clinical trial simulation of docetaxel in patients with cancer as a tool for dosage optimization. Clin Pharmacol Ther. 2000;68:677–687. doi: 10.1067/mcp.2000.111948. [DOI] [PubMed] [Google Scholar]
  • 70.Nestorov I, Graham G, Duffull 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. 2001;18:1210–1219. doi: 10.1023/A:1010943430471. [DOI] [PubMed] [Google Scholar]
  • 71.Chabaud S, Girard P, Nony P, Boissel JP. Clinical trial simulation using therapeutic effect modeling: application to ivabradine efficacy in patients with angina pectoris. J Pharmacokinet Pharmacodyn. 2002;29:339–363. doi: 10.1023/A:1020953107162. [DOI] [PubMed] [Google Scholar]
  • 72.Holford NH, Kimko HC, Monteleone JP, Peck CC. Simulation of clinical trials. Annu Rev Pharmacol Toxicol. 2000;40:209–234. doi: 10.1146/annurev.pharmtox.40.1.209. [DOI] [PubMed] [Google Scholar]
  • 73.Ette EI, Sun H, Ludden TM. Balanced designs in longitudinal population pharmacokinetic studies. J Clin Pharmacol. 1998;38:417–423. doi: 10.1002/j.1552-4604.1998.tb04446.x. [DOI] [PubMed] [Google Scholar]
  • 74.Ette EI, Sun H, Ludden TM. Ignorability and parameter estimation in longitudinal pharmacokinetic studies. J Clin Pharmacol. 1998;38:221–226. doi: 10.1002/j.1552-4604.1998.tb04419.x. [DOI] [PubMed] [Google Scholar]
  • 75.Fernandez de Gatta MM, Tamayo M, Garcia MJ, et al. Prediction of imipramine serum levels in enuretic children by a Bayesian method: comparison with two other conventional dosing methods. Ther Drug Monit. 1989;11:637–641. doi: 10.1097/00007691-198911000-00004. [DOI] [PubMed] [Google Scholar]
  • 76.Kraus DM, Dusik CM, Rodvold KA, Campbell MM, Kecskes SA. Bayesian forecasting of gentamicin pharmacokinetics in pediatric intensive care unit patients. Pediatr Infect Dis J. 1993;12:713–718. doi: 10.1097/00006454-199309000-00002. [DOI] [PubMed] [Google Scholar]
  • 77.Desoky E, Ghazal MH, Mohamed MA, Klotz U. Disposition of intravenous theophylline in asthmatic children: Bayesian approach vs direct pharmacokinetic calculations. Jpn J Pharmacol. 1997;75:13–20. doi: 10.1254/jjp.75.13. [DOI] [PubMed] [Google Scholar]
  • 78.Lares-Asseff I, Lugo-Goytia G, Perez-Guille MG, Flores-Perez J, Juarez-Olguin H, Raquel Moreno MA. Cefuroxime Bayesian pharmacokinetics in severely ill septic children. Rev Invest Clin. 1998;50:311–316. [PubMed] [Google Scholar]
  • 79.Lares-Asseff I, Lugo-Goytia G, Perez-Guille MG, et al. Bayesian prediction of chloramphenicol blood levels in children with sepsis and malnutrition. Rev Invest Clin. 1999;51:159–165. [PubMed] [Google Scholar]
  • 80.Wrishko RE, Levine M, Khoo D, Abbott P, Hamilton D. Vancomycin pharmacokinetics and Bayesian estimation in pediatric patients. Ther Drug Monit. 2000;22:522–531. doi: 10.1097/00007691-200010000-00004. [DOI] [PubMed] [Google Scholar]
  • 81.Bressolle F, Gouby A, Martinez JM, et al. Population pharmacokinetics of amikacin in critically ill patients. Antimicrob Agents Chemother. 1996;40:1682–1689. doi: 10.1128/aac.40.7.1682. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82.Barrett JS, Gibiansky E, Hull RD, et al. Population pharmacodynamics in patients receiving tinzaparin for the prevention and treatment of deep vein thrombosis. Int J Clin Pharmacol Ther. 2001;39:431–446. [PubMed] [Google Scholar]
  • 83.Andrew MV, Mitchell DJ, Barrett JS, Hainer JW. Design aspects of dose-finding trials in pediatric patients with severe TE: Tinzaparin pediatric study [abstract].Thromb Heamostasis. 2001;86.
  • 84.Gastonguay MR, Gibiansky E, Gibiansky L, Barrett JS. Optimizing a Bayesian dose-adjustment scheme for a pediatric trial: a simulation study. In: Kimko HC, Duffull SB, editors. Simulation for Designing Clinical Trials. New York: Marcel Dekker; 2002. pp. 369–390. [Google Scholar]
  • 85.Willis C, Staatz CE, Tett SE. Bayesian forcasting and prediction of tacrolimus concentrations in pediatric liver and adult renal transplant recipients. Ther Drug Monit. 2003;25:158–166. doi: 10.1097/00007691-200304000-00004. [DOI] [PubMed] [Google Scholar]
  • 86.Wildt SN, Hoog M, Vinks AA, Giesen E, Anker JN. Population pharmacokinetics and metabolism of midazolam in pediatric intensive care patients. Crit Care Med. 2003;31:1952–1958. doi: 10.1097/01.ccm.0000084806.15352.da. [DOI] [PubMed] [Google Scholar]
  • 87.Innovation and Stagnation: Challenge and Opportunity on the Critical Path to New Medicinal Products. Rockville, MD: Food and Drug administration, Center for Drug Evaluation and Research; 2004. [Google Scholar]
  • 88.Schwartz GJ, Haycock GB, Spitzer A. Plasma creatinine and urea concentration in children: normal values for age and sex. J Pediatr. 1976;88:828–830. doi: 10.1016/S0022-3476(76)81125-0. [DOI] [PubMed] [Google Scholar]

Articles from The AAPS Journal are provided here courtesy of American Association of Pharmaceutical Scientists

RESOURCES