Merck Optimizes Critical Drug Development with Revolution Analytics' gsDesign Explorer
Promising New Drugs Get to Market Faster and Less Time and Money is Spent on Drugs That Don’t Work
|Customer:||Merck Research Laboratories|
|User:||Keaven Anderson, Executive Director, Late Stage Biostatistics, Merck & Co.|
|Challenge:||During the clinical trials and research process of drug development at pharmaceutical companies, statisticians need to create and compare group sequential trial designs without programming.|
|Benefits:||Interim analyses during the clinical trials and research process offer opportunities for early stopping of trials, if, for example, the new treatment is demonstrably better than the standard treatment or clearly inferior. This can have benefits in many areas, from improved patient outcomes to significant savings in money and time.|
Major pharmaceutical companies face constant hurdles in a race against time in the clinical trial drug development process. The cost to develop drugs can be exorbitant and the sooner those drugs exit the pipeline, the sooner doctors can start administering them to help save the lives of countless patients. But it takes the tireless analysis of massive amounts of mission critical data to get from point A to point B.
So, how can data analysts in this business get to where they want to go much faster? One answer is by implementation of Revolution Analytics’ gsDesign Explorer graphical user interface (GUI). At Merck & Co., Keaven Anderson, Executive Director of Late Stage Biostatistics and co-creator of this open source R project, uses this GUI to collect and analyze massive data sets to complete the clinical drug trial process in a fraction of the time, potentially saving Merck millions of dollars.
“The greatest challenge to pharmaceutical drug development is the large amount of data generated by the sequential testing of experimental therapies. Analyzing these large sets of data can significantly delay a new drug’s delivery to patients or just as easily waste resources on drugs that turn out to be inferior to already available standard treatments. GsDesign Explorer significantly reduces the time of data analysis required in sequential drug testing. Recently, we had a trial at Merck that we couldn’t have done without gsDesign Explorer. This project allows promising new drugs to get to market faster at less cost, thus enhancing their potential to improve patient outcomes and save lives.”
Executive Director Late Stage Biostatistics
GsDesign Explorer allows data analysts to instantly create, compare, and produce graphical and textual summaries of multiple group sequential clinical trial designs. Users can focus on the model parameters and their statistical and clinical implications without being burdened by technical details or programming.
This solution is based on gsDesign—a group sequential design package for the R language. Group sequential methods allow clinical trial design with interim analyses to evaluate efficacy, while controlling false positive and false negative error. Interim analyses offer opportunities for early stopping of trials if, for example, the new treatment is demonstrably better than the standard treatment or clearly inferior.
As illustrated in Anderson’s work, this can have benefits in many areas, from improved patient outcomes to significant savings in money and time.
In funding the development of the gsDesign Explorer project, Merck aimed to bring the gsDesign package up to a more commercial standard and is supporting Anderson who is pushing for the GUI’s broad adoption among statisticians in the biopharmaceutical space. Anderson’s goal—make open source R software for adaptive designs a more viable strategy. He believes such software is an essential tool for innovation.
At Merck, group sequential designs with appropriate futility analyses may save on the order of $10 million dollars for a trial. These benefits come at the minimal cost of installing and learning to use the interface, which is intuitive and well-documented user interface. The output provided by the package provides clear documentation of the rationale for a particular design.
Unlike gsDesign Explorer’s main competitor, East by Cytel, arguably the most widely used clinical trial design software in use today, this software is built on established open source software tools (R and Qt Creator) to minimize development costs and maximize ease of use and extensibility.
Also, gsDesign Explorer does things East doesn’t do. For instance, to illustrate one of gsDesign’s more powerful capabilities, since the GUI is integrated with R, it’s possible for a user to go back into the GUI and further customize it to enhance graphics.
That has been one of the goals of gsDesign Explorer since its inception. The origin of the project dates back to 2006. The objective of this project was to create a GUI for gsDesign so that statisticians could easily create and compare group sequential trial designs without programming. Simply put—the purpose of the gsDesign Explorer is to make gsDesign easier to use on a wider basis.
“We use R for adaptive designs frequently because it’s the fastest tool to explore designs that interest us. Off- the-shelf software, gives you off-the-shelf options. Those are a good first order approximation, but if you really want to nail down a design, R is going to be the fastest way to do that.”
Executive Director Late Stage Biostatistics,
About Revolution Analytics
Revolution Analytics was founded in 2007 to foster the R community, as well as support the growing needs of commercial users. Our name derives from combining the letter "R" with the word "evolution." It speaks to the ongoing development of the R language from an open-source academic research tool into commercial applications for industrial use.
Though our Revolution R products, we aim to make the power of predictive analytics accessible to every type of user & budget. We provide free and premium software and services that bring high-performance, productivity and ease-of-use to R – enabling statisticians and scientists to derive greater meaning from large sets of critical data in record time.
We also offer our full-featured production-grade software to the academic community for FREE, in order to support the continued spread of R's popularity to the next generation of analysts.
For customers such as Pfizer, Novartis, Yale Cancer Center, Bank of America and others, our flagship Revolution R Enterprise product stands for faster drug development, reduced time of data analysis, and more powerful and efficient financial models.