ArticlePharmaceutical research2012
Adaptive optimal design for bridging studies with an application to population pharmacokinetic studies.
Article in Pharmaceutical research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Pharmacometrics meets statistics-A synergy for modern drug development.CPT: pharmacometrics & systems pharmacology · 2021Article
- Comparison of Various Phase I Combination Therapy Designs in Oncology for Evaluation of Early Tumor Shrinkage Using Simulations.CPT: pharmacometrics & systems pharmacology · 2020Article
- Model-Based Adaptive Optimal Design (MBAOD) Improves Combination Dose Finding Designs: an Example in Oncology.The AAPS journal · 2018Article
- Single-dose pharmacokinetic study comparing the pharmacokinetics of recombinant human chorionic gonadotropin in healthy Japanese and Caucasian women and recombinant human chorionic gonadotropin and urinary human chorionic gonadotropin in healthy Japanese women.Reproductive medicine and biology · 2018Article
- Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.Journal of pharmacokinetics and pharmacodynamics · 2017Article
- The effect of using a robust optimality criterion in model based adaptive optimization.Journal of pharmacokinetics and pharmacodynamics · 2017Article
- Use of Modeling and Simulation in the Design and Conduct of Pediatric Clinical Trials and the Optimization of Individualized Dosing Regimens.CPT: pharmacometrics & systems pharmacology · 2015Article
- Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology.Pharmaceutical research · 2015Article
- Application of Adaptive DP-optimality to Design a Pilot Study for a Clotting Time Test for Enoxaparin.Pharmaceutical research · 2015Article
- Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice.British journal of clinical pharmacology · 2014Article
- Prediction of shrinkage of individual parameters using the bayesian information matrix in non-linear mixed effect models with evaluation in pharmacokinetics.Pharmaceutical research · 2013Article
- Optimizing drug development of anti-cancer drugs in children using modelling and simulation.British journal of clinical pharmacology · 2013Review
- Current Use and Developments Needed for Optimal Design in Pharmacometrics: A Study Performed Among DDMoRe's European Federation of Pharmaceutical Industries and Associations Members.CPT: pharmacometrics & systems pharmacology · 2013Article
- Optimal sampling times for a drug and its metabolite using SIMCYP(®) simulations as prior information.Clinical pharmacokinetics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo develop and evaluate methods for conducting adaptive population pharmacokinetic bridging studies.
methodsAn adaptive D-optimal design based on optimization of the population Fisher information matrix was used to determine the best sampling schedule for a target-population. Recruitment of the target-population was divided into batches and patients are assumed to enroll by batch. A prior-population model was used to determine the optimal sampling schedule for the first batch and to stabilise the data analysis in the interim iteration. Simulation studies were performed under two scenarios (1) the prior- and target-populations have similar pharmacokinetic profiles and (2) the pharmacokinetic profiles diverge significantly. A design criterion to determine early full enrollment was also proposed.
resultsThe target-population estimates obtained using the proposed method were compared to estimates obtained if the target-population was studied with a design optimized based on the prior-population model. The proposed method is shown to be not inferior in scenario (1) and superior in scenario (2). The criterion to determine early full enrollment was proven to be effective.
conclusionsAn adaptive optimal design method together with an early full enrollment criterion were evaluated and resulted in more accurate estimates for the target-population in bridging studies.
Indexed as
Identifiers
22350799What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.