The conduct of pediatric clinical trials is legally required, monitored, and encouraged in major geographic areas such as the United States and Europe. However, because pediatric patients are considered vulnerable populations, they should only be enrolled as research subjects in a clinical trial if enrolling adult subjects will not be able to answer the scientific question related to the health and welfare of children. Thus, there is an ethical obligation to build the foundation for the use of pediatric extrapolation and related innovative analytical strategies with appropriately designed pediatric and adult clinical trials to reduce the amount of, or general need for, additional information needed from children to reach conclusions. This manuscript discusses innovative applications of clinical trial designs, analytic strategies to more efficiently leverage prior information, and modeling approaches that impact the data required to determine efficacy of an investigational drug in pediatrics. The planning of pediatric trials and regulatory interactions related to required pediatric studies and the expectations for innovative analytics are also discussed.
WilsonJT. Pragmatic assessment of medicines available for young children and pregnant or breast-feeding women. In: MorselliPL, ed. Basic and Therapeutic Aspects of Perinatal Pharmacology. New York, NY: Raven Press; 1975:411–421.
2.
WilsonJT. An update on the therapeutic orphan. Pediatrics. 1999;104(suppl 3):585–590.
3.
US Congress. Pediatric Research Equity Act of 2003. Public Law. 2003;108(155):117.
4.
BehrmanREFieldMJ, eds. Ethical Conduct of Clinical Research Involving Children. Washington, DC: National Academies Press; 2004.
5.
Regulation (EC) No 1901/2006 of the European Parliament and of the Council of 12 December 2006: on medicinal products for paediatric use and amending Regulation (EEC) No 1768/92 (Vol. 1), Directive 2001/20/EC, Directive 2001/83/EC and Regulation (EC) No 726/2004. Offic J Eur Union. 2006;L378. http://ec.europa.eu/health/documents/eudralex. Accessed September 19, 2018.
6.
US Food and Drug Administration. Best Pharmaceuticals for Children Act. Public Law. 2002;107–109.
7.
US Food and Drug Administration. FDA Status Report to Congress: Best Pharmaceuticals for Children Act and Pediatric Research Equity Act. Silver Spring, MD: US Food and Drug Administration; 2016.
PenkovDTomasiPEichlerIet al.Pediatric medicine development: an overview and comparison of regulatory processes in the European Union and United States. Therapeutic Innovation & Regulatory Science. 2017;51(3):360–371.
HwangTJTomasiPABourgeoisFT. Delays in completion and results reporting of clinical trials under the Paediatric Regulation in the European Union: a cohort study. PLoS Med. 2018;15(3):e1002520.
14.
PicaNBourgeoisF. Discontinuation and nonpublication of randomized clinical trials conducted in children. Pediatrics. 2016;138:e20160223.
15.
WhartonGTMurphyMDAvantDet al.Impact of pediatric exclusivity on drug labeling and demonstrations of efficacy. Pediatrics. 2014;134(2):e512–e518.
16.
FransonTKinnettKCripeTP. Unique burdens of pediatric clinical trials in Duchenne muscular dystrophy, April 20-21, 2017, Bethesda, Maryland, USA. Therapeutic Innovation & Regulatory Science. 2019;53(1):154–163.
17.
National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research. Bethesda, MD: Superintendent of Documents, National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, 1978.
EMA. ICH E11 (R1). Addendum to ICH E11: clinical investigation of medicinal products in the pediatric population. Step 4. 2017. Accessed September 19, 2018.
TurnerRSpiegelhalterDJSmithGCSThompsonSG. Bias modelling in evidence synthesis. J R Stat Soc Ser A Stat Soc. 2009;172:21–47.
24.
Food and Drug Administration. Guidance for Industry: Drugs for Treatment of Partial Onset Seizures: Full Extrapolation of Efficacy From Adults to Pediatric Patients 4 Years of Age and Older. Washington, DC: Food and Drug Administration; 2018.
O’QuigleyJPepeMFisherL. Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics. 1990;46(1):33–48.
27.
LoebDMGarrett-MayerEHobbsRFet al.Dose-finding study of 153Sm-EDTMP in patients with poor-prognosis osteosarcoma. Cancer. 2009;115(11):2514–2522.
28.
FouladiMStewartCFBlaneySMet al.Phase I trial of lapatinib in children with refractory CNS malignancies: a Pediatric Brain Tumor Consortium study. J Clin Oncol. 2010;28:4221.
29.
BretzFPinheiroJCBransonM. Combining multiple comparisons and modeling techniques in dose-response studies. Biometrics. 2005;61(3):738–748.
30.
HumeMLewisLLNelsonRM. Meeting the goal of concurrent adolescent and adult licensure of HIV prevention and treatment strategies. J Med Ethics. 2017;43:857–860.
31.
Gamalo-Siebers M, SavicJBasuCet al.Statistical modeling for Bayesian extrapolation of adult clinical trial information in pediatric drug evaluation. Pharm Stat. 2017;16(4):232–249.
32.
VieleKBerrySNeuenschwanderBet al.Use of historical control data for assessing treatment effects in clinical trials. Pharm Stat. 2014;13(1):41–54.
33.
NeuenschwanderBCapkun-NiggliGBransonMet al.Summarizing historical information on controls in clinical trials. Clin Trials. 2010;7(1):5–18.
34.
WeberSGelmanALeeDet al.Bayesian aggregation of average data: an application in drug development. Ann Appl Stat. 2018;12(3):1583–1604.
35.
SchmidliHGsteigerSRoychoudhurySet al.Robust meta-analytic-predictive priors in clinical trials with historical control information. Biometrics. 2014;70(4):1023–1032.
36.
MoritaSThallPFMüllerP. Determining the effective sample size of a parametric prior. Biometrics. 2008;64(2):595–602.
37.
MalecDSedranskJ. Bayesian methodology for combining the results from different experiments when the specifications for pooling are uncertain. Biometrika. 1992;79(3):593–601.
38.
LinJGamalo-SiebersMTiwariR. Propensity score matched augmented controls in randomized clinical trials: a case study. Pharma Stat. 2018;17(5):629–647.
HampsonLVHeroldRPoschMet al.Bridging the gap: a review of dose investigations in paediatric investigation plans. Br J Clin Pharmacol. 2014;78(4):898–907.
42.
JohnsonSRGrantonJTTomlinsonGAet al.Effect of warfarin on survival in scleroderma-associated pulmonary arterial hypertension (SSc-PAH) and idiopathic PAH. Belief elicitation for Bayesian priors. J Rheumatol. 2011;38(3):462–469.
43.
JohnsonSRGrantonJTTomlinsonGAet al.Warfarin in systemic sclerosis-associated and idiopathic pulmonary arterial hypertension. A Bayesian approach to evaluating treatment for uncommon disease. J Rheumatol. 2012;39(2):276–285.
44.
HlavinGKoenigFMaleCet al.Evidence, eminence and extrapolation. Stat Med. 2016;35;2117–2132.
45.
Food and Drug Administration. Guidance for Industry: Adaptive Design Clinical Trials for Drugs and Biologics. Washington DC, USA: Food and Drug Administration; 2010.
46.
MandrekarSJDahlbergSESimonR. Improving clinical trial efficiency: thinking outside the box. Am Soc Clin Oncol Educ Book. 2015:e141–e147.
KovalchikSAVaradhanRFettermanBet al.A general binomial regression model to estimate standardized risk differences from binary response data. Stat Med. 2013;32(5):808–821.
49.
Gamalo-SiebersMTiwariRLaVangeL. Flexible shrinkage estimation of subgroup effects through Dirichlet process priors. J Biopharm Stat. 2016;26(6):1040–1055.
50.
ShermanREAndersonSADal PanGJet al.Real-world evidence—what is it and what can it tell us. N Engl J Med. 2016;375(23):2293–2297.
PrzepiorkaDKoCWDeisserothAet al.FDA approval: blinatumomab. Clin Cancer Res. 2015;21(18):4035-4039.
57.
MomperJDMulugetaYGreenDJet al.Adolescent dosing and labeling since the Food and Drug Administration Amendments Act of 2007. JAMA Pediatr. 2013;167(10):926–932.
