Data Integrity and Integrating Automation

  Рет қаралды 186

Voices In Validation

Voices In Validation

Күн бұрын

This week, Karen Ginsbury shares her ideas on data integrity lapses, and how automating now can save your business in the future. Karen looks at how the pharmaceutical industry and even society misunderstand what integration truly is. Karen shares her thoughts on how the industry can advance forward despite self-inflicted obstacles.
About Our Guest:
Karen Ginsbury is a pharmaceutical consultant who brings hands-on experience in designing and implementing environmental control programs within multinational pharmaceutical companies. She started her career in the industry by taking EM samples on the factory floor and brings her own unique perspective to her lively and instructive presentations. Ms. Ginsbury has over twenty years of industry-based experience in quality assurance and compliance and has published a book on compliance auditing for pharmaceutical manufacturers. Ms. Ginsbury is a past holder of IVT’s Presentation of the Year and Web Seminar Presenter of the Year and regularly lectures around the world on pharmaceutical topics.
Voices in Validation brings you the best in validation and compliance topics. Voices in Validation is brought to you by IVT Network, your expert source for life science regulatory knowledge. For more information on IVT Network, check out their website at ivtnetwork.com.
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Пікірлер
@chemahdi
@chemahdi 2 жыл бұрын
Very nice presentation ... Speaker is very passionate to the topic Thnx "Voices in Validation"
@davidbruun-petersen8191
@davidbruun-petersen8191 2 жыл бұрын
How are you going to justify not validating "big data algorithms", regardless of what data (primary og supportive) they are analyzing, if the direct output of those algorithms are used for making decision affecting product quality or patient safety? The need for validation depends on intended use. Some kind of validation of those algorithms has to be done surely. "Self-validating" is not a concept in itself nor exact science, but relies on the person/system behind producing the algorithm. Arguing that Tesla is not performing process validation is not an valid argument.
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