From Dialogue to Action: Women at CluePoints on Driving Gender Equality Forward
At the current rate of progress, it will take until 2070 to reach equal representation for women in STEM1 and 2158 to achieve full gender parity.2 These shocking statistics highlight the need to take swift and decisive steps to achieve gender equality. But what do those steps look like, and how can we help speed […]
Meet MSR: Why Data Accuracy Matters in Clinical Trials
Accurate data is the backbone of successful clinical trials. Every piece of patient data, from electronic health records (EHRs) to lab results, holds critical value for decision-making processes, influencing not only trial outcomes but also patient safety. Traditional, manual methods of medical and safety reviews often struggle to keep data fresh, consolidated, and error-free, and […]
The Bold Future of RBQM for CROs
In a world where complacency is the enemy of progress, Contract Research Organizations (CROs) stand at a crossroads. Traditional approaches have their merits, but they’re no match for the transformative power of risk-based quality management (RBQM). It’s time to be bold, challenge the status quo, and redefine the future of CROs. CROs are uniquely positioned […]
Meet SPOT: Transforming Site Monitoring Practices with Adaptive Intelligence
Clinical trial site monitoring is one of the most expensive components of clinical trials; on-site clinical research monitoring alone accounts for around 25 to 30% of the total trial expenses.1 A substantial portion of the clinical trial timeline involves inefficient Source Data Verification (SDV) and Source Data Review (SDR) activities, which can also consume a […]
A New Era of Automation: Improving Efficiency & Outcomes with Intelligent Medical Coding
A New Era of Automation In clinical trials, patient data such as adverse events and concomitant medications must be coded against standardized medical dictionaries like MedDRA and WHODrug. This process, known as medical coding in clinical trials, ensures that data is categorized consistently across sites and studies, enabling accurate analysis, regulatory submission, and cross-trial comparisons. […]
Centralized Monitoring in Clinical Trials: Everything You Should Know
What Is Centralized Monitoring? Centralized monitoring is a key component of Risk-Based Quality Management (RBQM) that enables proactive detection of quality-related risks, both pre-identified and unanticipated, during clinical trials. Central Statistical Monitoring (CSM) is a subset of central monitoring that specifically uses advanced statistical and analytical methods to identify unusual patterns in the trial data. […]
Centralized Monitoring In Clinical Trials: Everything You Should Know
What Is Centralized Monitoring? Centralized monitoring is a component of risk-based quality management (RBQM) that aims to detect emerging quality-related risks (either pre-identified or unanticipated risks) proactively during the conduct of a clinical trial. There are three main elements of centralized monitoring: Statistical Data Monitoring (SDM) serves as an unsupervised method for quality oversight in […]
What Is Trending In Data Management And AI?
With the advent of AI promising to transform the way we process and interpret data, there has never been a more exciting time to be working in clinical data management. The buzz around technologies like machine and deep learning (ML/DL) has been palpable throughout 2023, and was particularly at hot topic at this year’s Society […]
A Year In Review: 2023 As A Watershed Moment In The Evolution Of Clinical Data Management
From risk-based quality management’s (RBQM) inclusion in ICH E6 (R3) to the roll-out of numerous AI-driven solutions, 2023 has been a year of huge advance for clinical data management – and could mark a tipping point in the adoption of Research 2.0. Here, Andy Cooper, CEO at CluePoints highlights the milestones and breakthroughs of the […]
Enhancing RBQM With Artificial Intelligence: Your Questions Answered
Traditional clinical trial data management is often manual, cumbersome, and vulnerable to human error, slowing progress and compromising quality. Streamlining these processes isn’t just a nice-to-have; it’s a game-changer. Risk-Based Quality Management (RBQM) has already raised the bar by accelerating studies and enhancing oversight. But there’s even greater potential on the horizon: artificial intelligence (AI). […]
