4 Key Components to Achieving Compliance with ICH E6 R2

By September 29, 2017 Blog No Comments

Nithiya Ananthakrishnan, Founder and CEO of Algorics, kicked off the webinar with 4 key components to achieving compliance with (1) regulatory guidelines that impact risk management and monitoring; (2) the challenges faced in individual phases; (3) Data aggregation and interoperability for efficiency; and (4) the advantages of having integrated workflow.  

The attendees were surveyed in advance and many were fairly new to ICH E6.  Nithiya summarized the last 2 decades in data capture and the significant changes in technology and processes.

The Webinar focused first on the regulatory guidelines that impact risk management and monitoring.  Nithiya stressed that a risk-based approach to quality management as a must-have in clinical trials.  

risk Image

Risk Planning is critical in identifying things that can go wrong in during the clinical trial. Risk identification and evaluation (5.0.2, 5.0.3, 5.0.4, 5.0.5) focused on cross-functional IQRMP, prioritization of risks, and creating indicators and data points. It’s important to use a non-biased consistent scoring system to identify the impact, probability and detectability of risks.  The Risk Assessment and Categorization Tool (RACT) has been used as a cross functional collaborative exercise but has some disadvantages like lack of version control and audit trail, lack of point-of-entry data validation and overall user errors. Risk communication helps to facilitate risk review and continual improvement during clinical trial execution.

Risk review (5.0.6) helps ascertain whether implemented quality management activities remain effective and relevant, taking into account emerging knowledge and experience.  This helps you to improve the focus of onsite monitoring; proactively identify issues; delay or advance a monitoring visit; continuously monitor vs. periodic checkup; and 100% data driven review approach than sample of data.

Risk reporting (5.0.7) allows for the sponsor to describe the quality management approach implemented in the trial and summarize important deviations from the predefined quality tolerance limits and remedial actions taken in the clinical study report. This includes data, insights, and actions, but to derive meaningful data, we need data direct from the source, in context, and on a timely basis.

Then our discussion of interoperability  and integration began – getting the data for risk analysis. It’s critical to get the data in real time directly from the source in context.  Key challenges that exist are the fact that needed data is highly fragmented.  On average, this needed data resides in 20-30 disparate eClinical point solutions, often with overlapping features and reports.  Most tools excel in one or at most two areas of facilitating data aggregation and reporting but not all.

The velocity in data requires the use of real-time aggregation to pull data in from multiple sources. Intelligence built in to the way data is collected beyond recalculating columns but incorporating clinical business rules.  This is standardization and harmonization of data that is critical to decision making. When automation allows data to flow from one point to the next in EDC, CTMS, Safety and other third-party systems with a validation trail, then there is consistency and then you are in compliance.  Using the sophistication of new analytical tools, we need to address data management in a holistic way and use smart tools to become efficient and compliant.  To view our case study, click here.




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