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    • 08:15 - 08:50
      • Registration and refreshments

      • 08:50 - 09:00
        • Chairman's opening remarks

        • 09:00 - 09:30
          • Speaker

            Le Phoung Hua – Associate Director, Data Management System, ASTELLAS PHARMA GLOBAL DEVELOPMENT, INC

          Utilizing data visualization tools and techniques to ensure efficiency during clinical data review

          • Examining current data visualization tools available to identify how they can address data review issues quicker

          • Demonstrating how system integration models can enhance data visualization

          • Examining advantages of viewing data in various graph formats compared to original tables

          • Assessing technical solutions to visualize data (eClinical solutions) to evaluate the cost benefit of implementing these technologies

          • Analyzing different categories of clinical data review to enable quicker visualization of the data

        • 09:30 - 10:00
          • Session reserved for Clinical Ink

          • 10:00 - 10:30
            • Speaker

              Irene Pak – Associate Director, Disease Area Information Lead, BRISTOL-MYERS SQUIBB
            • Speaker

              Philip C Ross, Ph.D. – Director, Clinical and Translational Data Science, BRISTOL-MYERS SQUIBB

            Clinical Visualization and Creation of a Data Lake - Another Step in the Evolution of Clinical Development?

            • Examine the challenges arising from the need to access, integrate and conform data throughout study execution

            • Discuss the advantages of data standardization and supporting earlier access to data

            • Demonstrate the use of the data to support clinical decisions during and after study conduct

            • Give examples of the impact a Data Lake in support of Clinical Program Decision Making

          • 10:30 - 11:00
            • Morning refreshments and networking

            • 11:00 - 11:30
              • Speaker

                Karyn Cassello – Director, Clinical Data Management, NEKTAR THERAPEUTICS

              Identifying the value of Risk Based Monitoring (RBM) and the role of the data manager in facilitating RBM

              • Examining why companies are moving towards RBM and how it helps to identify critical values and standardize data collection

              • Defining the role of the clinical data manager within RBM to ensure efficient implementation

              • Uncovering current FDA guidelines to assist in identifying risks in the study

              • Highlighting the need for smooth communication between data management and CRAs to facilitate the implementation RBM

            • 11:30 - 12:00
              • Session reserved for Cytel

              • 12:00 - 12:45
                • Speaker

                  Gina Eagle – Vice President of Clinical Development, INSMED
                • Speaker

                  Robert J Boland – Associate Director of Innovation Strategy, Emerging Science & Innovation, JOHNSON & JOHNSON
                • Speaker

                  Susan Walters – Senior Site Coordinator, SANOFI

                Ensuring the right balance between increasing the speed of data delivery and continuing to produce high quality data

                • Assessing the speed clinical data can be accessed via databases

                • Identifying the importance of proper procedures, staffing and reporting when collecting and reviewing clinical data

                • Anticipating potential issues at the start of the trial, such as missing data, and putting procedures in place that will allow data management to deal with the issue quickly

                • Evaluating the option of using automation systems on the clinical database to clean data which may speed up data delivery, without compromising quality

              • 12:45 - 14:15
                • Lunch and networking

                • 14:15 - 14:45
                  • Speaker

                    Thomas Verish – Senior Director, Data Operations & Clinical Infrastructure, CSL BEHRING

                  Identifying the requirements for clinical data review to ensure due preparation for benefit of trial timeline

                  • Examining the importance of clinical data reviews in identifying and investigating adverse events

                  • Identifying the relevant data required for patient profiles reviews, such as inclusion/exclusion of certain criteria

                  • Addressing the challenges data management face with clinical reviews, such as missing data or data entry errors, to ensure patient safety

                  • Identifying the advantages of utilizing CDISC SDTM model for clinical data collection and review

                • 14:45 - 15:15
                • The Future is Connected Data

                  • Learn how and why a failure to have an overarching data strategy can cause you to lose competitive advantage

                  • Hear real life examples of the state of data in a trial by trial approach and how complex trials and mergers can create chaos even in the most strategic companies

                  • Identify clear advantages that come when you leverage cloud based solutions and advanced technologies to transform data across trials into useful information for real-time insights and decision making

                • 15:15 - 15:45
                  • Examining the advantages of utilizing Electronic Data Capture (EDC) systems within data management to allow easy access and collection of data

                    • Identifying the importance of EDC from the point of view of data management and biostatistics

                    • Advantages of utilizing EDC to a data manager and the importance of designing these programs to allow easy onsite access

                    • Deciding how to keep up to date with regular changes to EDC in order to make sure your database is upgraded and data collection is efficient

                    • Identifying specific training at the site to update them on any EDC related changes and ensure queries made on the database are addressed

                    • Looking into the role of data management in analysis programs such as SAS to improve the data review process

                  • 15:45 - 16:15
                    • Afternoon refreshments and networking

                    • 16:15 - 16:45
                    • Assessing the performance of sites and CROs to promote high quality data is consistently produced

                      • Assessing performance continually by arranging regular meetings and defining project goals at the beginning of the trial

                      • Considering which performance indicators should be implemented to ensure data quality and standardization

                      • Generating a reporting system in order to make regular checks on performance to ensure any issues are quickly dealt with

                      • Identifying potential high risk areas at the start of the trial to ensure due diligence is taken

                    • 16:45 - 17:15
                      • Developing effective relationships with CROs to ensure clinical trials timelines are upheld

                        • Defining responsibilities of both data management teams and CROs at the start of the trial to successfully manage the work load and ensure all responsibilities are assigned

                        • Ensuring effective communication between teams to manage expectations in data collection and quality throughout the trial

                        • Assessing the training and oversight required throughout the trial to ensure data standards and timelines are maintained

                        • Highlighting the advantages of high quality communication between data management team at sponsor and CRO

                      • 17:15 - 17:45
                        • Speaker

                          Wandy Romain – Specialist, Clinical Data Management, MERCK ANIMAL HEALTH

                        Recognizing technological advancements that improve data collection allowing study timelines to be met sooner

                        • Evaluating data capture systems that do real time data checks to improve data quality

                        • Evaluating models of data collection to ensure real time data access

                        • Identifying challenges with data collection models that pose technological risks with data safety

                        • Advantages of using the CDISC standard model for data collection and submission, SDTM

                      • 17:45 - 18:00
                        • Chairman’s summation and close of conference