{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["17(4)"],"submitter":["Lennie JL"],"pubmed_abstract":["Rare disease clinical trials are constrained to small sample sizes and may lack placebo-control, leading to challenges in drug development. This paper proposes a Bayesian model-based framework for early go/no-go decision making in rare disease drug development, using Duchenne muscular dystrophy (DMD) as an example. Early go/no-go decisions were based on projections of long-term functional outcomes from a Bayesian model-based analysis of short-term trial data informed by prior knowledge based on 6MWT natural history literature data in DMD patients. Frequentist hypothesis tests were also applied as a reference analysis method. A number of combinations of hypothetical trial designs, drug effects and cohort comparison methods were assessed. The proposed Bayesian model-based framework was super"],"journal":["PloS one"],"pagination":["e0247286"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9049549"],"repository":["biostudies-literature"],"pubmed_title":["Bayesian modeling and simulation to inform rare disease drug development early decision-making: Application to Duchenne muscular dystrophy."],"pmcid":["PMC9049549"],"pubmed_authors":["Mondick JT","Gastonguay MR","Lennie JL"],"additional_accession":[]},"is_claimable":false,"name":"Bayesian modeling and simulation to inform rare disease drug development early decision-making: Application to Duchenne muscular dystrophy.","description":"Rare disease clinical trials are constrained to small sample sizes and may lack placebo-control, leading to challenges in drug development. This paper proposes a Bayesian model-based framework for early go/no-go decision making in rare disease drug development, using Duchenne muscular dystrophy (DMD) as an example. Early go/no-go decisions were based on projections of long-term functional outcomes from a Bayesian model-based analysis of short-term trial data informed by prior knowledge based on 6MWT natural history literature data in DMD patients. Frequentist hypothesis tests were also applied as a reference analysis method. A number of combinations of hypothetical trial designs, drug effects and cohort comparison methods were assessed. The proposed Bayesian model-based framework was super","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2025-04-25T22:54:39.481Z","creation":"2025-04-06T09:14:32.132Z"},"accession":"S-EPMC9049549","cross_references":{"pubmed":["35482633"],"doi":["10.1371/journal.pone.0247286"]}}