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Source Data Verification (SDV) has been reported to account for up to 25% of the budget in Clinical Trials (CT) and cost-benefit of SDV has been questioned. Guidelines for Risk-Based Monitoring (RBM) were published in 2013 by agencies and in 2016, ICH-GCP-E6-(R2) added a requirement for risk-based approaches. This report will perform a comparison of the impact of RBM versus Classic Monitoring (CM) on data quality (defined as accuracy of data reporting from source data to final trial data) and expected impact on costs of CTs.

There is a need for antidiabetic agents successfully targeting insulin sensitivity and treating obesity control at the same time. The aim of this first-in-human study was (a) to evaluate safety and tolerability, (b) to evaluate pharmacokinetics and (c) to assess indications of receptor engagement of single ascending doses of KBP-042, a dual amylin and calcitonin receptor agonist (DACRA) that has shown promising preclinical data, with superior activity in terms of typical amylin-induced responses including reduction of food intake, weight loss and gluco-regulatory capacities.

The aim of this project was to perform an empirical evaluation of the impact of on site source data verification (SDV) on the data quality in a clinical trial database to guide an informed decision on selection of the monitoring approach. We used data from three randomized phase III trials monitored with a combination of complete SDV or partial SDV. After database lock, individual subject data were extracted from the clinical database and subjected to post hoc complete SDV. Error rates were calculated with focus on the degree of on study monitoring and relevance and analyzed for potential impact on end points.