ABSTRACT
BackgroundPediatric clinical trials commonly experience recruitment challenges including limited number of patients and investigators, inclusion/exclusion criteria that further reduce the patient pool, and a competitive research landscape created by pediatric regulatory commitments. To overcome these challenges, innovative approaches are needed.MethodsThis article explores the use of Bayesian statistics to improve pediatric trial feasibility, using pediatric Type-2 diabetes as an example. Data for six therapies approved for adults were used to perform simulations to determine the impact on pediatric trial size.ResultsWhen the number of adult patients contributing to the simulation was assumed to be the same as the number of patients to be enrolled in the pediatric trial, the pediatric trial size was reduced by 75-78% when compared with a frequentist statistical approach, but was associated with a 34-45% false-positive rate. In subsequent simulations, greater control was exerted over the false-positive rate by decreasing the contribution of the adult data. A 30-33% reduction in trial size was achieved when false-positives were held to less than 10%.ConclusionReducing the trial size through the use of Bayesian statistics would facilitate completion of pediatric trials, enabling drugs to be labeled appropriately for children.
Subject(s)
Biomedical Research/statistics & numerical data , Clinical Trials as Topic/statistics & numerical data , Models, Statistical , Patient Selection , Pediatrics/statistics & numerical data , Sample Size , Adolescent , Age Factors , Bayes Theorem , Biomarkers/blood , Biomedical Research/methods , Blood Glucose/drug effects , Blood Glucose/metabolism , Child , Clinical Trials as Topic/methods , Computer Simulation , Data Interpretation, Statistical , Diabetes Mellitus, Type 2/blood , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/epidemiology , Drug Labeling , Feasibility Studies , Female , Humans , Hypoglycemic Agents/therapeutic use , Male , Patient Safety , Pediatrics/methods , Treatment Outcome , Young AdultABSTRACT
The dopamine transporter (DAT) modulates dopamine neurotransmission and is a primary target for psychostimulant influences on locomotion and reward. Selective DAT expression by dopaminergic neurons has led to use of cocaine analog DAT radioligands to assess rates of progression of dopamine neuronal degeneration in Parkinson's disease. We have documented that DAT is a phosphoprotein that is regulated by phosphorylation through pathways that include protein kinase C cascades. We now extend this work using drugs selective for phosphatidylinositol 3-kinase (PI3K), protein kinase C, MEK1/2, p38 kinase, and Ca2+/calmodulin kinase II. We compare the drug effects on wild type DAT to the effects on 20 DAT mutants and a DAT deletion. PI3K and MEK1/2 modulators exert strong effects on DAT expression patterns and dopamine uptake Vmax. PKC principally modulates Vmax. Neither p38 nor Ca2+/calmodulin kinase II agents exert significant influences on wild type DAT. Several mutants and a DAT with an N-terminal deletion display alterations that interact with the effects of kinase modulators, especially S7A for PKC effects; T62A, S581A, and T612A for PI3K effects; and S12A and T595A mutants for MEK1/2 effects. 32P-Labeling studies confirm several of these effects of kinase pathway modulators on DAT phosphorylation. DAT expression and activities can be regulated by kinase cascades that require phosphoacceptor sites most concentrated in its N terminus. These results have a number of implications for DAT regulation and mandate caution in using DAT radioligand binding to infer changes in dopaminergic neuronal integrity after treatments that alter activities of these kinase pathways.
