Literature DB >> 20688782

Importance of protocols for simulation studies in clinical drug development.

Mike K Smith1, Andrea Marshall.   

Abstract

Clinical trial simulation studies can be used to assess the impact of many aspects of trial design, conduct, analysis and decision making on trial performance metrics. Simulation studies can play a vital role in improving the efficiency of the drug development process within the pharmaceutical industry, but only if they are well designed and conducted. It is imperative therefore that a protocol or simulation plan is developed, documenting how the simulation study is to be conducted, analysed and reported. This article emphasises the specific considerations necessary for designing good quality simulation studies. These include defining data generation processes, data analytic methods, decision criteria and also determining the presentation of results for all intended audiences. With clinical trial simulations becoming a vital part of the drug development process, the protocol for clinical trial simulations may in future become part of the regulatory peer review process. More rigour in the planning and execution of simulation studies will ensure that the design, analysis and decision-making process for the subsequent clinical trial is based on credible evidence that can be independently verified.

Mesh:

Year:  2010        PMID: 20688782     DOI: 10.1177/0962280210378949

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  7 in total

Review 1.  A systematic review of the quality of reporting of simulation studies about methods for the analysis of complex longitudinal patient-reported outcomes data.

Authors:  Aynslie M Hinds; Tolulope T Sajobi; Véronique Sebille; Richard Sawatzky; Lisa M Lix
Journal:  Qual Life Res       Date:  2018-04-20       Impact factor: 4.147

2.  INTEREST: INteractive Tool for Exploring REsults from Simulation sTudies.

Authors:  Alessandro Gasparini; Tim P Morris; Michael J Crowther
Journal:  J Data Sci Stat Vis       Date:  2021-12-31

3.  Using simulation studies to evaluate statistical methods.

Authors:  Tim P Morris; Ian R White; Michael J Crowther
Journal:  Stat Med       Date:  2019-01-16       Impact factor: 2.497

4.  How to design a dose-finding study using the continual reassessment method.

Authors:  Graham M Wheeler; Adrian P Mander; Alun Bedding; Kristian Brock; Victoria Cornelius; Andrew P Grieve; Thomas Jaki; Sharon B Love; Lang'o Odondi; Christopher J Weir; Christina Yap; Simon J Bond
Journal:  BMC Med Res Methodol       Date:  2019-01-18       Impact factor: 4.615

5.  Efficient and flexible simulation-based sample size determination for clinical trials with multiple design parameters.

Authors:  Duncan T Wilson; Richard Hooper; Julia Brown; Amanda J Farrin; Rebecca Ea Walwyn
Journal:  Stat Methods Med Res       Date:  2020-12-02       Impact factor: 3.021

6.  The cross-over of statistical thinking and practices: A pandemic catalyst.

Authors:  Andrew D Garrett
Journal:  Pharm Stat       Date:  2022-07       Impact factor: 1.234

7.  Sample size and classification error for Bayesian change-point models with unlabelled sub-groups and incomplete follow-up.

Authors:  Simon R White; Graciela Muniz-Terrera; Fiona E Matthews
Journal:  Stat Methods Med Res       Date:  2016-08-08       Impact factor: 3.021

  7 in total

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