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1 min read

How machine learning and artificial intelligence can drive clinical innovation

As the global pandemic has created a greater need for remote monitoring, the adoption of machine learning and artificial intelligence (AI) into clinical trials can help to generate new efficiencies to enhancing patient safety and trial outcomes, while not replacing the need for clinical trial monitors or other research personnel. This Byline explores the links

4 min read

COVID-19: A Wakeup Call for Clinical Trial Monitoring

Clinical trials have two key goals: to prove the safety and efficacy of new therapeutics. Their success rests on the accurate collection, monitoring, and analysis of data. While today’s data collection is increasingly electronic, monitoring itself still largely occurs onsite, with monitors verifying source data by physically comparing the electronic data capture with the data

4 min read

What’s Needed: An Alternative Approach To Clinical Trial Management

Risk-Based Monitoring. Risk-Based Execution. Risk-Based Quality Management. The monitoring and management of clinical trials are called many things—yet, they are, in fact, different. FDA Director of the Office of Scientific Investigations, David Burrow, notes that “Risk-based quality management is not just risk-based monitoring.” RBQM is a more substantial undertaking, requiring quality, reliability, and interpretability. It

1 min read

Alternative Monitoring: Clinical Trial Management In The Era Of COVID-19

Effective Trial Continuity In the Face of a Pandemic While social distancing and isolation are paramount, clinical trials must adapt to remain viable. However, many clinical trial sponsors still have questions about how to effectively gather collective insights and apply them to improve their clinical trials. The result is a call for risk-based quality management

2 min read

Sharp Thinking A New Angle on Clinical Trial Management Systems

New technologies are inevitably heralded as making life simpler: streamlining tasks, eliminating steps, managing things so you don’t have to manage them. Yet the practical application of a new technology often seems to make things more complex. Clinical trial management is a case in point. Contract Research Organizations (CROs) and sponsors are juggling increased data

8 min read

Using AI & Machine Learning to Better Understand Data and Manage Risk

Against a backdrop of stricter regulatory standards and increased emphasis on trial oversight and patient safety, the clinical development landscape is more competitive than ever. Clinical trials have also increased in complexity, driven in large part by the shift toward biomarker-guided drug development and value-based outcomes. With about 7,000 medicines in development globally, nearly three-quarters

7 min read

Making Risk-Based Monitoring Technology a Friend: Considerations for Practical Execution of an RBM Strategy

Introduction Infused into virtually everything we touch, technology can feel like both a blessing and a curse. While some technologies are easy to use right out of the box, others require set-up in order to be useful. At times, that set-up and even the eventual use of the technology can feel daunting and frustrating. However,

1 min read

What the FDA Says

These documents are either from or about the FDA and its concerns about clinical trials. What’s more important is that the concerns addressed within these articles can all be addressed with the capabilities of the Remarque Systems Platform. Speech Transforming FDAs Approach to Digital Health FDA Draft RBM monitoring FDA Seeks More Efficent Clinical Research