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The translation of discoveries to drugs, devices, and behavioral interventions requires well-prepared study teams. Execution of clinical trials remains suboptimal due to varied quality in design, execution, analysis, and reporting. A critical impediment is inconsistent, or even absent, competency-based training for clinical trial personnel.
In 2014, the National Center for Advancing Translational Science (NCATS) funded the project, Enhancing Clinical Research Professionals’ Training and Qualifications (ECRPTQ), aimed at addressing this deficit. The goal was to ensure all personnel are competent to execute clinical trials. A phased structure was utilized.
This paper focuses on training recommendations in Good Clinical Practice (GCP). Leveraging input from all Clinical and Translational Science Award hubs, the following was recommended to NCATS: all investigators and study coordinators executing a clinical trial should understand GCP principles and undergo training every 3 years, with the training method meeting the minimum criteria identified by the International Conference on Harmonisation GCP.
We anticipate that industry sponsors will acknowledge such training, eliminating redundant training requests. We proposed metrics to be tracked that required further study. A separate task force was composed to define recommendations for metrics to be reported to NCATS.
Training for the clinical research workforce does not sufficiently prepare workers for today’s scientific complexity; deficiencies may be ameliorated with training. The Enhancing Clinical Research Professionals’ Training and Qualifications developed competency standards for principal investigators and clinical research coordinators.
Clinical and Translational Science Awards representatives refined competency statements. Working groups developed assessments, identified training, and highlighted gaps.
Forty-eight competency statements in 8 domains were developed.
Training is primarily investigator focused with few programs for clinical research coordinators. Lack of training is felt in new technologies and data management. There are no standardized assessments of competence.
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