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Jennifer L. Proper; Haitao Chu; Purvi Prajapati; Michael D. Sonksen; Thomas A. Murray – Research Synthesis Methods, 2024
Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…
Descriptors: Network Analysis, Meta Analysis, Prediction, Drug Therapy
Weber, Sebastian; Gelman, Andrew; Lee, Daniel; Betancourt, Michael; Vehtari, Aki; Racine-Poon, Amy – Grantee Submission, 2018
Throughout the different phases of a drug development program, randomized trials are used to establish the tolerability, safety and efficacy of a candidate drug. At each stage one aims to optimize the design of future studies by extrapolation from the available evidence at the time. This includes collected trial data and relevant external data.…
Descriptors: Bayesian Statistics, Data Analysis, Drug Therapy, Pharmacology
Günhan, Burak Kürsad; Röver, Christian; Friede, Tim – Research Synthesis Methods, 2020
Meta-analyses of clinical trials targeting rare events face particular challenges when the data lack adequate numbers of events for all treatment arms. Especially when the number of studies is low, standard random-effects meta-analysis methods can lead to serious distortions because of such data sparsity. To overcome this, we suggest the use of…
Descriptors: Meta Analysis, Medical Research, Drug Therapy, Bayesian Statistics
Friede, Tim; Röver, Christian; Wandel, Simon; Neuenschwander, Beat – Research Synthesis Methods, 2017
Meta-analyses in orphan diseases and small populations generally face particular problems, including small numbers of studies, small study sizes and heterogeneity of results. However, the heterogeneity is difficult to estimate if only very few studies are included. Motivated by a systematic review in immunosuppression following liver…
Descriptors: Meta Analysis, Diseases, Medical Research, Research Problems

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