JMP for Life Sciences: Modern Clinical Monitoring and Quality by Design
Featuring Andrew Lawton, Geoffrey Mann and Ron Kenett
In the pharmaceutical industry there is no guidance which states that you must use data-driven analytics, yet this is the only effective way to meet the requirements imposed by regulatory agencies. The JMP family of products provide many capabilities that help you to leverage data better, and this seminar focuses on two distinct but related areas of application.
Andrew Lawton, CEO of Risk Based Approach Ltd, will examine and interpret forthcoming regulations and guidance changes and the use of big data and analytics. The addendum to ICH E.6 (GCP) brings us QMS, RBA, quality tolerance limits and quality reporting. Similarly, whilst the WHO draft guidance (Sept 2015) contains requirements on queries that allude to training, they can only really be addressed by using analytics.
Geoffrey Mann, JMP Product Manager at SAS, will discuss how to modernize your on-site clinical trial monitoring by using the latest methods in risk-based monitoring, central statistical monitoring and clinical oversight monitoring. Using these methods will improve and align your monitoring process with recent guidance documents created by the FDA and EMA.
He will focus on:
- Risk-based monitoring that aligns to risk indicators, thresholds and actions set forth by the TransCelerate methodology documents.
- Central statistical monitoring methods.
- Data quality and fraud detection methods to identify outlying patients and sites in a clinical trial.
Ron Kenett, Chairman of the KPA Group, insights through analytics, will provide an overview of the data-driven aspects of Quality by Design (QbD) and the associated FDA guidance. Using three examples, he will show how the informed application of statistically designed experiments, one of the cornerstones of QbD, can dramatically increase your clinical, product and process understanding for the same use of resources.
The potential benefits of these cutting-edge methodologies are:
- Saving up to 30 percent of the costs of running trials.
- Identifying the causes of data quality issues faster.
- Reducing the frequency of interactions with regulatory agencies.
- Uncovering issues unidentifiable without central statistical monitoring methods.
- Managing pipeline risk with increased understanding.
- Accelerated new product introductions through knowledge re-use.
- Higher manufacturing yields.
As the pharmaceutical industry transitions into a more metrics based future, there has never been a better time to invest in realizing the enormous benefits of using data-driven analytics.
|The Impact of Regulatory Guidance on Analytics|
|Modern Techniques in Clinical Trial Monitoring|
|Using QbD to Increase Clinical, Product and Process Understanding|
|Conclusions and closing remarks|