WEBINAR | Fraud and Sloppiness Detection in Clinical Trials

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Methods, Detection, Prevention and Examples

DO YOU KNOW WHICH LAW: Data sets obeying this law have approximately 30.1% of numbers start with a 1 whereas this percentage falls to 4.6% for the numbers starting with a 9.

Agenda:
– Clinical fraud – historical overview
– What are the consequences for Bio-Pharma?
– Why does fraud happen, and how often?
– How to detect fraud and sloppiness in clinical data?
– How to combat fraud with mitigation actions?

Curious how “the power of one” and “small number bias” help detect data manipulation and tampering in clinical research?

Register for this free webinar today!

Spare yourself a fall-from-grace by so called ‘data detectives’. Implement RBQM, better sooner than later, and detect problems prior to publication. You might also like: How can RBQM spare organizations the trouble of retracting papers?

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