Evolution of Clinical Data Management

Following the success of our inaugural Evolution of Data Management in Pharma conference last year, this year’s event being held in Munich will further the networking opportunities and provide delegates with a wealth of practical ideas and tools to improve their processes with handling the vast amount of data generated by clinical trials.

The challenging economic climate presents an opportunity for all manufacturers to develop more robust and cost efficient data management processes for clinical trials at a critical time for the future of the industry.

Through a series of interactive discussions and presentations by the leading manufacturers, the agenda will cover all the key topics facing data management professionals today including:

1. Utilising EDC tools to integrate data across multiple sites to reduce the risk of data loss
2. Assessing collaboration between partners during the trials process for seamless sharing of information without comprising confidentiality and data integrity
3. Understanding CDISC standards and implementation challenges to develop improved data management standards and reduce the time to market for new treatments
4. Making the right decision on cost and outcomes in data management when outsourcing and working with service providers in emerging markets
5. Staff development and change to management processes to maximise the use of resources

Improving data management strategies requires a thorough understanding of industry trends, technological developments, evolutions in regulatory frameworks and data standards. The benefits of continuous improvement in data management strategies are very clear – getting products to market through the quickest and most cost efficient way possible without risking the chances of getting regulatory approval.

Located in Munich, a central hub of the manufacturing and CRO industry, VIBpharma’s Data Management in Clinical Trials conference will provide a high-level platform to generate ideas and solutions to make the best use of data management resources and improve processes during clinical trials through to submissions for regulatory approval.