Managing Clinical Trials Utilizing Electronic Data Capture (EDC2)
July 15 – August 11, 2019
The course will address study conduct utilizing Electronic Data Captures (EDC) systems, whether managed directly by a sponsor, with an EDC vendor, or through a Contract Research Organization (CRO). Concepts related to the EDC system, the EDC study application, user roles, responsibilities and training as well as regulatory requirements for change management will be addressed. A sample protocol will provide application of learning to real world situations.
Over four weeks, the course will address general principles, best practice and issues that will allow a Data Manager to work collaboratively and communicate effectively with appropriate team members during study conduct. Topics will include user management, training compliance and regulatory considerations for working in an electronic environment. Participants will gain an understanding of necessary Software Development Life Cycle (SDLC) documentation for EDC system updates, as well as mid-study updates for the EDC study application. Considerations for ‘faster to lock” will be introduced to take advantage of EDC process.
WHAT YOU’LL LEARN
Participants completing the training should be able to accomplish the following objectives:
- Define EDC workflow, change management, and documentation unique to EDC
- Describe best practice for proactively validating data to achieve faster DB Lock
- Author test scripts needed for Validation and change control
- Compare criteria for EDC system management verses EDC study management
This course addresses competencies tested in the CCDM® exam under the EDC domain.
WHO SHOULD ATTEND
CDMs and others involved in study conduct that will be or are currently responsible for conducting clinical trials utilizing EDC. Participants should be experienced data managers who have in-depth knowledge of the majority of data management and related processes. The course will focus on the foundational components of managing clinical trials utilizing EDC. Once enrolled, participants will need a computer with access to the Internet and the ability to print out course materials. Recommended time commitment is 8-10 hours per week to complete each module (1 module = 1 week)
MEET THE INSTRUCTOR
Farida Dabouz, PhD. CCRP, is the president of FB2D Clinical Research Consulting Inc., a consulting company.
Over the course of her multi-faceted 23 year career, she has worked in international pharmaceutical companies, CROs as well as academic international oncology group, in Europe and Canada. She has experience in the field of biostatistics, data management and medical writing as well as process improvement (quality assurance), applied in a vast array of therapeutics areas from Phase II to Phase IV, and observational studies.
Dr. Dabouz has a strong experience in training investigators, study coordinators, nurses, project managers, CRAs, administrative assistants, QA and data managers, IT, as well as statisticians covering all data aspects, mainly demystifying statistics in clinical trials.
Dr Dabouz has a PhD in statistics and certified SOCRA. This certification allows being closer to clinical sites and working with investigators’ teams in improving data quality/integrity at the source.
Farida is the instructor for the SCDM On-line courses and webinars:
– Mysteries of Randomization as interpreted through a Statistical Analysis Plan
– Data Quality in Clinical research
– Influence of the Statistical Analysis Plan (SAP) and Randomization on Data Collection
– Managing Clinical Trials Utilizing EDC
Refund Policy: Participants will receive a full refund if notice is provided in writing via post or email one week prior to the course start date. If cancellation occurs by the end of week one of the course, students will be allowed to apply 50% of the course fee to the next offering of the same course. No refunds will be offered after that time.
Participants are eligible to receive CEUs upon successful completion of the course.
SCDM is authorized by IACET to offer 4.0 CEUs for this program.