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*PSI Scientific Committee Webinar: Risk-Based Monitoring 22 April 2015, 13:30 – 15:00 BST Registration is FREE!* *Attendees must register on the PSI website* * in order to obtain the dial-in details and the webinar link. Non-members can register by creating an account.* We do encourage your participation. If you have questions relating to the Risk-Based Monitoring webinar, ahead of the webinar, please email them to [log in to unmask] <[log in to unmask]>and [log in to unmask] We will do our best to discuss them at the webinar. *As drug development becomes more complex and expensive, risk based monitoring (RBM) is one area which can allow companies to target and prioritize resources around identifiable risks for patient safety as well as ensuring high quality clinical data. This webinar aims to take a practical approach to RBM. The webinar will go through the regulatory aspects of RBM, as well as considering the Statistical methodology and clinical data-management perspectives of RBM.* *Analytical Considerations for Risk-Based Monitoring* *Richard C. Zink, Ph.D. (JMP Life Sciences, SAS Institute)* Central computerized review of clinical trial data enables RBM to determine if sites should receive more extensive quality review or intervention. The availability of extensive logic and validation checks to detect outliers and implausible values early in the clinical trial not only ensures data quality, but can be used to identify instances of data fabrication and other forms of misconduct. This presentation discusses analytical considerations for RBM, including supervised and unsupervised methodologies, and the need to consider both sets of approaches in practice. Regulatory guidance and the TransCelerate position paper on RBM methodology motivate the discussion. Numerous examples are provided to illustrate concepts. The audience will learn how to • Improve data quality; Understand instances where potential misconduct may be identified; Learn the impact of data standards on RBM; Utilize graphical techniques for analysis and reporting of quality and safety anomalies. *Risking it all? Introducing Risk Based Monitoring to Cancer Research UK * *Sherraine Hurd, BSc. (Senior Clinical Data Manager, CRUK)* Risk Based Monitoring has been the hot topic for a number of years, with a big focus on the role of the CRA and what they can do in order to achieve effective monitoring and applied clinical risk. However very little is mentioned of the CDM and the role they play. This presentation addresses this need, highlighting the process of RBM implemented by Cancer Research UK and in particular, what RBM means to a CDM. At the end of the session, the participants will be able to use the CRUK case study to • Describe how RBM can have a positive impact on the CDM role; Assess and constructively challenge their own RBM processes to see where it can bring more benefits for CDMs; Describe the metrics and questionnaires used to quantitatively and qualitatively assess the success of a RBM pilot; Explain the importance of considering site staff in order to effectively implement RBM. *Data-Driven Risk-Based Monitoring of Clinical Trial Operation* *Vladimir Anisimov, Prof. PhD (Senior Strategic Biostatistics Director, Quintiles)* Predictive risk-based monitoring requires developing analytic techniques accounting for stochasticity and hierarchic structure of trial operation. Most of operational characteristics are driven by patient enrolment and various events (clinical & non-clinical). For modelling hierarchic follow-up processes on the top of enrolment a new methodology is proposed. It allows deriving closed-form solutions for many practical scenarios, so does not require Monte Carlo simulation. As distributions of many operational variables are far from normal, traditional approaches to detect outliers based on empirical mean and SD may lead to biased results. Thus, more sophisticated models should be used (e.g. Poisson mixed with gamma, Pareto). A few real case studies: • Describe applications to data-driven RBM: detecting unusual site/trial behaviour (enrolment, AE), analysis of patient’s follow-up processes and predicting future site/regions performance, associated events, etc. Registration via www.psiweb.org > events > PSI events You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.