Flexible access to clean, high-quality data and effective risk management are more vital than ever to the success of clinical drug trials. With the mile-a-minute pace of clinical research, though, there’s little time for hours and hours of training on complicated, siloed systems that only get you halfway to your goals.
In previous posts, we showed you how the Remarque Quality Management System (QMS) provides peace of mind at the patient level (Medical Monitor) and site level (Central Monitor), harnessing advanced data visualizations, customizable workflows, and machine learning capabilities to give you the insights you need to make confident decisions. In our final post in the series, we’ll focus on the Statistical Monitor Module and how it provides a one-stop monitoring solution for the study as a whole.
Transform Data Into Information
We begin with the raw data. Remarque’s risk-based monitoring platform is system-agnostic, collecting data from all the electronic data capture (EDC) systems used across your trial: electronic medical records to mHealth wearables, central lab systems to issue management systems.
But data alone doesn’t mean anything. Remarque’s proprietary algorithms quickly identify trends, risks, and anomalies; the system then allows you to drill down to data-point-specific detail, giving you crystal clear insight into not only what is happening, but why — critical real-time information on which to base crucial conclusions and determine next steps.
Easily Detect Patterns and Anomalies
The Remarque System’s analytics provide immediate, intuitive access to a wide range of study metrics. Sponsors and CROs can choose from multiple view options, including univariate, multivariate, funnel plot, repeated measures, and Benford analysis.
For instance, you might choose a single data point, such as abdominal pain at visit one, then compare it with abdominal pain at all visits to see if there has been any global change. Drilling deeper, you can compare two variables, to determine whether there is a correlation between abdominal pain and diastolic blood pressure — then further hone in on any outliers to understand the implications — both to the patient and to the study.
With two clicks of the mouse, the sponsor compares abdominal pain in visit 1 with abdominal pain across all visits in this univariate view.
In a multivariate view, the sponsor compares abdominal pain with diastolic blood pressure across all intervals study-wide, immediately identifying those patients who are outliers. You can then drill down to the individual site or patient with a single click for more information.
Customize the Display to Suit Your Needs
You can further customize the data’s display to suit your needs when evaluating risk. Whether you want a pie chart, histogram, grid, line, or box to display your data, you can change the display with a few clicks of the mouse. This allows you not only quick access to data but also enables you to easily identify any trends in your data that may be actionable. You’ll see risks sooner with the Remarque Systems QMS, helping you avoid serious problems and costly fines.
The option to further customize insights by adding specific panels, such as this pie chart display of the number of closed queries, creates an at-a-glance dashboard of key metrics.
Use the Power of Machine Learning to Your Advantage
The system’s built-in statistical models allow quick identification of key study integrity risks, such as outliers, noise, and digit preference. Its nimble, interactive visualizations make it simple to spot those trends, without complex, time-consuming data manipulation and analysis. Further, the user interface is powered by machine learning algorithms that train the machine learning model as you shift from an unsupervised model to a semi-supervised model.
Minimize Risk With No Additional Effort
When your future rides on a single molecule, you cannot afford to ignore risk — and new regulations further the imperative for risk-based monitoring. You need to manage your trial risk in real time, not only mitigating threats and protecting your investment, but saving time, money, and — most importantly — patient lives.
The solution lies in access both to the highest quality data possible and to the insights that data can deliver. Harnessing the power of machine learning and the ease of the Remarque Statistical Monitor Module can help you see beyond the top line data, to understand results in real time — and take immediate action. That means faster, more relevant data that can help you see what you need to see, when you need to see it.
Interested in Remarque Systems QMS? Schedule a demo today to see how it can minimize your clinical trial risk and enhance your outcomes.