Are we on schedule? Predictive modeling for patient recruitment in multicenter trials

Since clinical trials are experiments that study patients, they rely heavily on finding the right kind and the right number of patients. Clinical trials can be conducted only after enough patient information has been collected and treatment groups randomly assigned, so it is very important that researchers recruit enough people [...]

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Using data points to fill a graphic with color

When dealing with graphs and plots, we will very likely need to fill colors in a graph to highlight an area or distinguish it from other shapes. You may know how to shade regular shapes, but what about irregular polygons and contours? You can do can this easily to any [...]

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The QbD Column: A QbD factorial experiment

A quick review of QbD The first blog post in this series described Quality by Design (QbD) in the pharmaceutical industry as  a systematic approach for developing drug products and drug manufacturing processes. Under QbD, statistically designed experiments are used to efficiently and effectively investigate how process and product factors [...]

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The QbD Column: Overview of Quality by Design

Developing new drugs is a complex, lengthy and expensive endeavor. When the process leads to an approved drug, the result is improved patient care and great benefits for the developers. But many promising drugs never live up to expectations. The US Food and Drug Administration (FDA), observing that new drug [...]

Identifying re-enrolled subjects in clinical trials, the sequel

This past June, at the Drug Information Association (DIA) annual meeting, I had the opportunity to present and participate in a panel discussion on innovative approaches to ensure quality and compliance in clinical trials. Not surprisingly, a majority of the discussion focused on sponsor responsibilities for building quality into its [...]

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New JMP book on risk-based monitoring & fraud detection in clinical trials

Risk-based monitoring (RBM) is a hot topic in the clinical trials arena. It’s a new way of designing and operating clinical trials. Now, rather than visiting each clinical trial site and reviewing all patient records, you identify just those who present the higher risk of poor data quality, fraud and [...]

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Summarizing patient safety with standardized MedDRA queries (SMQs)

If you work or have worked within the pharmaceutical industry, then you are likely familiar with MedDRA, the Medical Dictionary for Regulatory Activities. This dictionary makes it possible for drug and device companies to perform analyses of adverse events or medical history. First, MedDRA provides a way to consistently map [...]

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7 things to love about JMP Clinical 5.0

New versions of JMP Clinical and Genomics are available starting today, so I wanted to take the opportunity to give a brief overview of some of the new features you’ll come to enjoy with the new release of JMP Clinical 5.0. Below are seven things to love! 1. Risk-Based Monitoring [...]

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Risk-based monitoring: Visualizing the risk to your clinical trials

We’ve talked about the data. We’ve defined our thresholds for risk. Now it’s time to talk about how you can visualize the safety and quality signals from your ongoing clinical trials. If you want to minimize the impact of quality issues to the data or quickly address any safety concerns [...]

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Risk-based monitoring: Defining thresholds for risk

Now that we have put together a data set containing the important metrics to monitor safety and site performance, we need to define the thresholds that constitute elevated risk. Unfortunately, there is no one-size-fits all solution to this problem. The study population (e.g., pediatric, elderly or at particular risk of safety [...]

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