Abstract
TransCelerate has developed a risk-based monitoring methodology that transforms clinical trial monitoring from a model rooted in source data verification (SDV) to a comprehensive approach leveraging cross-functional risk assessment, technology, and adaptive on-site, off-site, and central monitoring activities to ensure data quality and subject safety. Evidence suggests that monitoring methods that concentrate on what is critical for a study and a site may produce better outcomes than do conventional SDV-driven models. This article assesses the value of SDV in clinical trial monitoring via a literature review, a retrospective analysis of data from clinical trials, and an assessment of major and critical findings from TransCelerate member company internal audits. The results support the hypothesis that generalized SDV has limited value as a quality control measure and reinforce the value of other risk-based monitoring activities.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
ICH harmonised tripartite guideline, guideline for good clinical practice E6(R1). http://www.ich.org/products/guidelines/efficacy/article/efficacy-guidelines.html. Accessed April 18, 2014.
Schuyl ML, Engel T. A review of the source document verification process in clinical trials. Drug Information Journal. 1999;33:789–797.
International Federations of Pharmaceutical Manufacturers and Associations. Clinical trials portal. http://clinical-trials.ifpma.org/clinicaltrials/en/tips/#s-link.
TransCelerate BioPharma Inc. Position paper: risk-based monitoring methodology. http://www.transceleratebiopharmainc.com/wp-content/uploads/2013/10/TransCelerate-RBM-Position-Paper-FINAL-30MAY2013.pdf. Published 2013.
Funning S, Grahnen A, Eriksson K, Kettis-Linblad A. Quality Assurance within the scope of good clinical practice (GCP): what is the cost of GCP-related activities? A survey within the Swedish Association of Pharmaceutical Industry (LIF)’s members. Qual Assur J. 2009;12:3–7.
Baigent C, Harrell FE, Buyse M, et al. Ensuring trial validity by data quality assurance and diversification of monitoring methods. Clin Trials. 2008;5:49–55.
Tantsyura V, Grimes I, Mitchel J, et al. Risk-based source data verification approaches: pros and cons. Drug Information Journal. 2010;44:745–756.
Duley L, Antman K, Arena J, et al. Specific barriers to the conduct of randomized trials. Clin Trials. 2008;5:40–48.
De S. Hybrid approaches to clinical trial monitoring: practical alternatives to 100% source data verification. Perspect Clin Res. 2011;2(3):100–104.
European Medicines Agency, Science Medicinces Health. Reflection Paper on Risk Based Quality Management in Clinical Trials. London, England: European Medicines Agency; 2013. Publication EMA/269011/2013.
Bakobaki J, Rauchenberger M, Joffe N, McCormack S, Stenning S, Meredith S. The potential for central monitoring techniques to replace on-site monitoring: findings from an international multi-centre clinical trial. Clin Trials. 2012;9:257–264.
Tudur Smith C, Stocken DD, Dunn J, et al. The value of source data verification in a cancer clinical trial. PLoS ONE. 2012;7(12):e51623.
US Department of Health and Human Services, Food and Drug Administration. Guidance for Industry: Oversight of Clinical Investigations—A Risk-Based Approach to Monitoring. Washington, DC: US Department of Health and Human Services; 2013. OMB control 0910-0733.
Neilsen E, Hyder D, Deng C. A data-driven approach to risk-based source data verification. Therapeutic Innovation & Regulatory Science. 2014;48:173–180.
Medidata Solutions. Industry metric indicates low ROI with full source document verification. http://www.appliedclinicaltrialsonline.com/appliedclinicaltrials/article/articleDetail.jsp?id=767452. Published April 2012.
Atkinson I. Accuracy of data transfer: double data entry and estimating levels of error. J Clin Nurs. 2012;21:2730–2735.
Verhulst K, Artiles-Carloni L, Beck M, et al. Source document verification in the Mucopolysaccharidosis Type I Registry. Pharmacoepidemiol Drug Saf. 2012;21:749–752.
Carraro P, Plebani M. Post-analytical errors with portable glucose meters in the hospital setting. Clin Chim Acta. 2009;404:65–67.
Grahnen A, Karlsson K, Bragazzi F. Impact of transcription errors on the outcome of a clinical trial. Clinical Pharmacology & Therapeutics. 2007;81(1):S21.
Brosteanu O, Houben P, Ihrig, et al. Risk analysis and risk adapted on-site monitoring in noncommercial clinical trials. Clin Trials. 2009;6:585–596.
Toth-Allen J. Building Quality Into Clinical Trials: An FDA Perspective. Washington, DC: US Food and Drug Administration; 2012.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Sheetz, N., Wilson, B., Benedict, J. et al. Evaluating Source Data Verification as a Quality Control Measure in Clinical Trials. Ther Innov Regul Sci 48, 671–680 (2014). https://doi.org/10.1177/2168479014554400
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1177/2168479014554400