CluePoints Founder, Marc Buyse to Deliver Clinical Trial Data Quality Course at the ASA Biopharmaceutical Workshop

By July 18, 2016 Blog No Comments

The ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop is fast approaching and we’re thrilled to announce that CluePoints Founder, Marc Buyse will deliver a course with Paul Schuette, FDA; Richard C Zink, JMP Life Sciences, focused on methods to assess data integrity in clinical trials.

Course: SC3 Short Course 3: An Overview of Methods to Assess Data Integrity in Clinical Trials

Date: 09/28/16
Time: 08:30 AM – 12:00 PM
Location: Marriott Wardman Park, Washington DC

Course Overview

The quality of data from clinical trials has received a great deal of attention in recent years. Of central importance is the need to protect the well-being of study participants and maintain the integrity of final analysis results. However, traditional approaches to assessing data quality have come under increased scrutiny as providing little benefit for the substantial cost. Numerous regulatory guidance documents and industry position papers have described risk-based approaches to identify quality and safety issues. An emphasis on risk-based approaches forces the sponsor to take a more proactive approach to quality through a well-defined protocol and sufficient training and communication, and by highlighting those data most important to patient safety and the integrity of the final study results. Identifying problems early allows sponsors to refine procedures to address shortcomings as the trial is ongoing. The instructors of this short course will provide an overview of recent regulatory and industry guidance on data quality, and explore issues involving data standards and integration, sampling schemes for source data verification, risk-indicators and their corresponding thresholds, and analyses to enrich sponsor insight and site intervention. In addition, statistical and graphical algorithms used to identify patient- and investigator trial misconduct and other data quality issues will be presented, and corresponding multiplicity considerations will be described. To supplement concepts, this course will provide numerous practical illustrations and describe examples from the literature. The role of statisticians in assessing data quality will be discussed. 1. Regulatory Landscape (Schuette) 2. Background (Zink) a. Recent history b. TransCelerate c. Classification of risk-based approaches d. Definitions e. Data sources and data standards f. Prospective approaches to quality g. Role of the statistician and why we should care h. Sampling Approaches for Source Data Verification (Zink) 3. Supervised Methods (TransCelerate) (Zink) a. Risk indicators and thresholds b. Graphical approaches c. Advanced analyses 4. Unsupervised Methods of Statistical Monitoring (Zink) a. Patient- and site-level analyses b. Graphical approaches c. Multiplicity, power and sample size considerations 5. Unsupervised Methods Using All Data (Buyse) a. Patient-, site-, and country level analyses b. Graphical approaches c. Multiplicity and power considerations d. Scoring and prioritizing centers for audits e. Experience with these methods 6. Conclusions (Zink) a. Review cycle b. Models for centralized review 7. References

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