| Autor: |
Mitchel, Jules T., Schloss Markowitz, Judith M., Yin, Hua (Helen), Gittleman, Dean, Cho, Timothy, Kim, Yong Joong, Choi, Joonhyuk, Efros, Mitchell D., Weingard, Kerri, Tantsyura, Vadim, Carrara, Dario |
| Zdroj: |
Therapeutic Innovation and Regulatory Science; July 2012, Vol. 46 Issue: 4 p464-471, 8p |
| Abstrakt: |
In order to assess the impact of direct data entry (DDE) on the clinical trial process, a single-site, phase 2 clinical trial, under a US investigational new drug application (IND), was performed where the clinical site entered each subject’s data into an electronic data capture (EDC) system at the time of the office visit and the clinical research team implemented a risk-based monitoring (RBM) plan. For DDE, the trial used EDC for data collection and the electronic clinical trial record (eCTR) as the subject’s electronic source (eSource) record. A clinical data monitoring plan (CDMoP) defined the scope of source document verification, the frequency and scope of online data review, and the criteria for when to perform onsite monitoring. As a result of this novel approach to clinical research operations, (1) there were no protocol violations as screening errors were picked up prior to treatment; (2) because there were minimal transcription errors from paper source records to the EDC system, there was a major reduction in onsite monitoring compared to comparable studies that use paper source records; (3) EDC edit checks were able to be modified early in the course of the clinical trial; (4) compliance issues were identified in real time and corrected; (5) there was rapid transparency and detection of safety issues; and (6) the clinical site indicated that there were major cost savings overall and estimated that just in terms of data entry, it was able to save 70 hours of labor by not using paper as the original source records. It is postulated that once the pharmaceutical industry adopts DDE and RBM, there will be major increases in productivity for sponsors, clinical sites, and CROs, as well as reduced time to database lock and the statistical analyses. In addition to the productivity increases, these processes and tools will improve data integrity and quality and potentially reduce overall monitoring resources and efforts by an estimated 50% to 60%. |
| Databáze: |
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