This week, Clinical Trials Arena will be shining a spotlight on data management as part of May’s ‘Data Week’. Running throughout the week of May 23rd, 2016, CTA will post articles uncovering the most pressing issues facing industry today.
Be on hand to gain expert views as Marcin Makowski (AstraZeneca) delves into the complex nature of centralized monitoring, while consumer expert, Avi Greengart (Current Analysis), explains how the use of wearables to obtain data could pose industry an ethical dilemma.
Later today, however, be sure to check out Mahnu Davar’s article (Arnold & Porter LLP), as he examines three compliance risks in data management activities that sponsors should consider.
But before we get things underway, catch up on some of CTA’s most recent data-themed stories below…
What does the future hold for the Clinical Data Manager?
Over the years, Clinical Data Management (CDM) has come a long way having its ups and downs, for a while being viewed as a commodity that could easily be outsourced or off-shored … Fifteen years ago, it was absolutely OK for a CDM to be on top of the patient data and not worry about the status of individual fields, outstanding queries and un-coded items. These days, however, many other functions have a vested interest in accessing the clinical trial data on an ongoing basis and have information available on how ‘clean’ the data are. To finish this compelling article, read Johann Proeve’s article here…
Welcome IRT to your Clinical Trials
Clinical Trial results are driven by the billions of data generated and the need to find smart solutions and processes to improve patient management, data registration, logistics and compliance is unavoidable. One of the key success factors of a trial is to ensure patients are randomly allocated to treatment groups (to avoid statistical bias) and comply to study treatment as defined in study protocol. All of this should in most cases be achieved while keeping the study blind…
Exploring Quality by Design as the Paradigm for Future Clinical Trials
Most clinical trials operate in a decidedly non-Quality by Design manner. When protocols are designed and studies are conducted, there is no systematic approach to determining how likely the end result is to be successful. Using further deduction, there is therefore no substantive understanding via quantification of how each component of a study will lead to timely, error-free completion in a repeatable and predictable manner.