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Avoiding Statistical Pitfalls during Method Validation - Webinar By GlobalCompliancePanel

Date: 24-Jul-12 to 24-Jul-12
Location: Online Training / Wilmington / Delaware / United States
Category: Healthcare & Pharmaceuticals Conferences & Trade Fairs

Overview: The ICH guideline on Validation of Analytical Procedures (Q2R1) delineates the guidance and methodology for validation characteristics of an analytical procedure.

Like most guidelines, the terminology is vague enough to allow for several acceptable approaches and analysis. Appropriate statistical methods should be used and all relevant data collected during validation and formulae used for calculating validation characteristics should be submitted and discussed as appropriate. A statistical approach to validation of analytical methods can minimize the amount of testing while meeting the requirements of the guideline.

Areas Covered in the Session:
Introduction to ICH Q2R1
Statistical methods used during validation
Accuracy versus Precision
Examples and case studies

Price List:
Live : $245.00
Corporate live : $495.00
Recorded : $295.00

Phone: 800-447-9407
Fax: 302-288-6884

webinars@globalcompliancepanel.com
http://www.globalcompliancepanel.com

Visitors

Anyone responsible for, or affected by, FDA regulations on analytical method validation
Management
Research and Development
Regulatory Affairs personnel
Quality assurance/quality control personnel
Auditors and inspectors

Exhibitors

Mr. Steven Walfish is the President of Statistical Outsourcing Services, a consulting company that provides statistical analysis and training to FDA regulated industries. Prior to starting Statistical Outsourcing Services, Mr. Walfish was the Senior Manager Biostatistics, Non-clinical at Human Genome Sciences in Rockville MD. Prior to joining HGS, Mr. Walfish was a Senior Associate at PricewaterhouseCoopers specializing in the pharmaceutical industry. Mr. Walfish was Manager of Non-Clinical Statistics at Chiron Diagnostics. Mr. Walfish brings over 20 years of industrial expertise in the development and application of statistical methods for solving complex business issues including data collection, analysis and reporting.

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