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Checklists. Some people hate them; some people love them. There have been whole books written about them. Some checklist fans say they live by their checklists. Cynics may see checklists as long, tedious, ineffective, bothersome, or just plain wrong. And, well, that’s sometimes true.
So what makes a good and effective checklist?
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I can actually say that I have been working in the Clinical Trials industry since the last century. I started as a database programmer, part of data management in a large (now huge) CRO. In those days we used paper CRFs, entered by hand into a database platform that was built and maintained inhouse. We had our own naming conventions for variables and could pretty much build whatever we wanted and group the data however it made sense to us. Prior to deliverables, we printed out the entire database so data managers could review it. All the files were burned to floppy discs and we’d pop them in the mail to the sponsor. With the amount of data we collect, and the requirement to do more, faster, can you even imagine doing that now?
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The objective of phase 1 dose-finding studies is to determine the maximum tolerated dose (MTD), defined as the highest dose at which a pre-specified proportion of subjects experience a dose limiting toxicity (DLT). Ideally, the trial design would not only be easy to implement but also efficient and ethical. In recent years, several statistical models for adaptive trial designs have emerged.
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The thinking on monitoring of clinical studies has been changing over the past several years, so now is a good time to reassess the place of SDV and SDR in the operation of clinical trials.
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Related, Not Related, Likely, Possibly Related, Unlikely Related, Certain, Definitely, Unassessable, Unknown, Probably Related…if you recognize these terms, then there is a reasonable possibility you are familiar with what the Drug Safety and Pharmacovigilance world refers to as the causality assessment.