How to Detect Lack of Data Integrity

Speaker

Instructor: Ron Snee
Product ID: 706369
Training Level: Basic

Location
  • Duration: 90 Min
This webinar provides some practical and useful answers to the question: “How to Detect Lack of Data Integrity?” Humans, equipment or both can be the source of lack of data integrity. This session discusses both types of data integrity sources and introduces the assessment of “data pedigree” as a concept that puts focus on the types of data integrity issues and analytical and statistical methods for detecting data problems. Pharma and biotech case studies are used throughout the presentation to illustrate how the various approaches fit together.
RECORDED TRAINING
Last Recorded Date: Mar-2020

 

$299.00
1 Person Unlimited viewing for 6 month info Recorded Link and Ref. material will be available in My CO Section
(For multiple locations contact Customer Care)

$399.00
Downloadable file is for usage in one location only. info Downloadable link along with the materials will be emailed within 2 business days
(For multiple locations contact Customer Care)

 

 

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Read Frequently Asked Questions

Why Should You Attend:

In this webinar, you will learn:

  • What is data integrity; what does it look like
  • Types and sources of data integrity issues as seen in case studies
  • Procedures for assessing data pedigree, integrity and quality
  • Computer, analytical and statistical methods for evaluating data integrity and quality
  • Limitations of observational data
  • Guiding principles, tips and traps for the effective data integrity assessment

Data are central to the development, manufacture and marketing of pharmaceuticals of all types. The renewed interest in data integrity raises questions regarding what is data integrity and how to assess it. Lack of data integrity comes in two forms: purposeful manipulation of the data to deceive and the inadvertent problems that occur in the production and analysis of data. Humans, equipment or both can be the source of the problem.

Areas Covered in the Webinar:

  • What is data integrity; what does it look like
  • Case studies illustrating types and sources of data integrity issues
  • Procedures for assessing data pedigree, integrity and quality
  • Data Pedigree – A New Tool for Assessing the Level of Data Integrity
  • Computer, analytical and statistical methods for evaluating data integrity and quality
  • Limitations of observational data
  • Guiding principles, tips and traps for the effective data integrity assessment

Who Will Benefit:

  • Department Managers
  • Quality Assurance Personnel
  • Quality Engineers
  • Process and Manufacturing Engineers
  • Research and Development Scientists
  • Biologists and Microbiologists
  • Chemists and Chemical Engineers
  • Those who desire to learn how to detect lack of data integrity

From Pharma and Biotech companies

Free Materials:

  • Copies of slides of presentation
Instructor Profile:
Ron Snee

Ron Snee
Founder and President, Snee Associates

Ron Snee is Founder and President of Snee Associates, a firm dedicated to the successful implementation of process and organizational improvement initiatives. He provides guidance to senior executives in their pursuit of improved business performance using Quality by Design, Lean Six Sigma and other improvement approaches that produce bottom line results. Prior to his consulting career he spent 24 years at the DuPont Company in a variety of assignments including pharmaceuticals.

While at DuPont he got involved in developing mixture and formulation systems which lead to the creation of several seminal advances for the effective design and analysis of mixture experiments. Snee has worked in the field for more than 40 years. His accumulated learnings have resulted in the recent book Strategies for Formulations Development – A Step-by-Step approach using JMP software, published by SAS Books, Cary, NC He has been developing and applying QbD methodologies for more than 30 years. His recent application and research on QbD has produced more than ten articles on use of QbD in Pharma and Biotech. He has also coauthored 3 books on the methods and tools of QbD and speaks regularly at conferences and meetings on the subject. He teaches QbD and related methodologies as an Adjunct Professor at Temple University School of Pharmacy and Rutgers University Pharmaceutical Engineering program.

Ron received his BA from Washington and Jefferson College and MS and PhD degrees from Rutgers University. He is an academician in the International Academy for Quality and Fellow of the American Society of Quality, American Statistical Association, and American Association for the Advancement of Science. He is an Honorary Member of ASQ and has been awarded ASQ’s Shewhart, Grant and Distinguished service Medals, and ASA’s Deming Lecture, W. J. Dixon Consulting and Gerry Hahn Quality and Productivity Achievement Awards. He is a frequent speaker and has published 7 books and more than 330 papers in the fields of performance improvement, quality, management, and statistics. He is a past recipient of the Institute of Validation Technology Speaker of the Year Award.

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Registrants may cancel up to two working days prior to the course start date and will receive a letter of credit to be used towards a future course up to one year from date of issuance. ComplianceOnline would process/provide refund if the Live Webinar has been cancelled. The attendee could choose between the recorded version of the webinar or refund for any cancelled webinar. Refunds will not be given to participants who do not show up for the webinar. On-Demand Recordings can be requested in exchange. Webinar may be cancelled due to lack of enrolment or unavoidable factors. Registrants will be notified 24hours in advance if a cancellation occurs. Substitutions can happen any time. On-Demand Recording purchases will not be refunded as it is available for immediate streaming. However if you are not able to view the webinar or you have any concern about the content of the webinar please contact us at below email or by call mentioning your feedback for resolution of the matter. We respect feedback/opinions of our customers which enables us to improve our products and services. To contact us please email [email protected] call +1-888-717-2436 (Toll Free).

 

 

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