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A 2-day certification course covering trial design, project management, self audit and developing GCP problem solving skills.
Faculty of Pharmaceutical Medicine (Royal Colleges of Physicians of the United Kingdom) has awarded 13.5 CPD credits to this course.
This is a stand-alone course ideal for those who have experience in the clinical trial process and wish to develop their skills. The course involves a large amount of group work.
Using learning by involvement techniques, participants will......
How much do you know about GCP?
Interactive Q&A to refresh your GCP knowledge
What’s new and coming up
A brief heads up on the latest developments in EU and USA
Data protection in clinical research
Overview of how the data protection directive affects clinical trials: processing and transfer of data
Electronic records and documents workshop
Group exercise to consider questions relating to e-source data based on the EMA Reflection Paper and e-TMF basics
Emergence of Good Clinical Laboratory Practice (GCLP)
Group exercise on GCLP requirements
GCP problem solving using root cause analysis, CAPA and SMART approaches
– including the identification and management of breaches of GCP and study protocol
Case studies: common breaches of GCP and protocol – determining root cause, SMART corrective and preventative action plans and testing CAPA effectiveness.
Risk based approaches to implementation of regulation and trial monitoring
An overview of the key guidance followed by an exercise on the pro’s and con’s of risk based monitoring
Investigator oversight of clinical trials
Good and poor practices relating to the oversight of trials and delegation of responsibilities
Critical review of the consent process
Your chance to critique a consent process and assess its compliance with GCP. Discussion to consider the impact of the consent process on the recruitment and retention of trial subjects.
The monitoring and audit of critical clinical trial documents
Group exercise to evaluate the quality and content of some key clinical trial documents, including the detection of fraud in trial data followed by discussion