JMPer Cable
A technical blog for JMP users of all levels, full of how-to's, tips and tricks, and detailed information on JMP features
The latest release of JMP Clinical makes it the most sophisticated visualization and analysis tool for clinical trials the market. It has as much to do with our teams that build the software as it does its amazing functionality. Building on the powerful functionality of JMP Pro, JMP has delivered a solution that addresses the needs of a wide audience, including safety surveillance teams, medical monitoring teams, data quality teams, regulatory agencies, and academic institutions. There are many new features in this release that offer a more comprehensive safety profile analysis that reaches beyond what most organizations are capable of doing. Let’s take a look at the exciting things we have been up to.
Office of New Drugs Custom Medical Queries (OCMQ) and Medical Query Distribution
My colleague Rebecca Lyzinski has helped changed the way we visualize and analyze adverse events data. By engaging with industry and regulatory experts, the risk plot is familiar to safety experts with enhancements to forest plots for understanding the signals. These interactive plots were discussed at Rebecca’s presentation on her most recent work adding Office of New Drugs Custom Medical Queries in JMP Clinical 19 at a Phuse Single Day Event in TarryTown, Pennsylvania. Whether aggregating adverse event data at the term level, body system level, Standardized MedDRA Query level, Office of New Drugs Custom Medical Query level (formerly FDA Medical Queries), or creating custom medical queries in the CDISC ADaM domains, collectively these reports comprise a comprehensive solution to interact with your adverse event data. To better understand this, check out our new publication.
The new Medical Query Distribution report enhances JMP’s already impressive list of safety analyses geared toward medical queries. In particular, this report was added for cases where there aren't at least two treatment groups to compare, providing a simpler frequency and count report of the MedDRA or OCMQ levels:
Recurrences, co-occurrences, and nearby occurrences
By understanding the temporal relationships of adverse events and concomitant medications, safety scientists gain a more detailed analysis of possible treatment effects on patients in the clinical trial. My colleague Richard Zink (who needs little introduction) has been extremely busy publishing journal articles, blogs, and code for creating interactive visualizations and analysis in JMP Clinical 19. This latest release now includes an often-overlooked assessment of adverse events recurrences over time or co-occurring adverse events and concomitant medications – taking into account their overlap in time – and, finally, nearby occurrences of adverse events and concomitant medications. To dive deeper, please see Richard’s recent blogs:
Recurrence: Visualizes how adverse events repeat over time and differ between treatments.
Dynamic survival
The brand new Dynamic Survival report offers interactive summaries of time-to-event data, showing sensitivity to interim analysis timing. Paired with JMP’s ability to track snapshots of the clinical trials data, these interim analyses are now provided with a turn-key solution. Richard describes the features more fully here.
Subgroup screening
The Subgroup Screening report is a straightforward way to assess how the treatment effect (or the treatment response, in the case of single-arm studies) can vary within subgroups and which factors might contribute to this heterogeneity. To learn more, check out Richard’s blog describing this feature.
Pharmacokinetics
My colleague Meichen Dong is prolific as well. She has just published a new platform in JMP Causal Treatment’s personality and written a blog about it here and how to choose estimators here. For JMP Clinical 19, she has added features for scientists interested in pharmacokinetics (PK) analysis and a non-compartmental analysis (NCA) that uses data available from the CDISC pharmacokinetics concentrations (PC) domain.
Further, this report produces PK profiles that enable the user to view the data of each individual patient in the context of summary statistics derived across groups of patients. For more of the details, please see this blog by Richard.
Study data support enhancements
Our colleague Nora Varga not only writes the code to perform data quality and safety reports, she also assists all of us in adding the study data so that we can analyze any CDISC data provided to the system. New in JMP Clinical is support for CDISC Dataset-JSON v1.0 (JMPC 18.2) and v1.1 (JMPC 19.0), as well as enhanced support for more complex international character sets within the data, technically introduced in JMP 18.2.2.
JMP Clinical now provides support for compressed and normal JMP tables, SAS data sets, SAS transport files, and JSON files. Whether in person or JMP Discovery Summit Europe in Berlin this March or from her office in Cary, NC, Nora helps our customers by providing expert advice on JMP Clinical in general and the Adverse Event Narrative report and the many Data Quality reports in particular. Keep an eye out for her new snapshot data domain viewer in the Early Adopter program for JMP Clinical 20. It will help our customers easily understand the differences in each snapshot of the data as they load new data on a weekly or monthly basis, as shown here:
Enhanced JMP Live interactivity and integration
Another colleague of mine, John Cromer, keeps his mind sharp by writing very sophisticated code to allow our customers to streamline and automate their work in JMP Clinical. They can automate everything, from adding studies to creating reports and even saving them in JMP Live. You learn more about JMP Live, our secure collaborative hub product, here. John explains how to share visualizations here, which helps users by eliminating the need to set up anything themselves with APIs to enhance the support JMP already provides. Here is a sample of JMP’s current API enhancements:
Notice that you can automate anything in JMP, ranging from adding studies to performing a full safety analysis, so that end users don’t have to lift a finger to do so. Furthermore, John and Nora have collaborated to provide the metadata gleaned from your studies to make it available to the system in a way that is configurable through JMP’s study preferences. It has been around for a few versions, but the level of sophistication is constantly improving to meet our customers’ needs.
Enhanced validation tools for JMP Clinical
The teams at JMP are very concerned about validating our products, working with our customers to constantly improve our products. JMP Clinical 19 is the culmination of that effort. JMP’s quality statement underscores our commitment to validation; it includes the JMP Clinical Installation Qualification and JMP Operational Qualification tools, in particular the Configuration Qualification tool that John wrote.
This tool allows our customers to control user access to data and system output.
Rebecca and I, along with Distinguished Software Developer Drew Foglia, have worked hard to release our JMP Clinical Double-Programming Validation tool, now available in the JMP Marketplace.
To enhance customer’s output needs, Drew has also created a more generic output capability to generate other formatted documents from JMP and JMP Clinical. I have had the pleasure of working with Drew for over 20 years; his enthusiasm and personality are infectious and ideal for teams in the software industry. Drew has a hand in everything we do from UI design to performance enhancements to patient profiles and integrations with 3rd party technologies.
As you can see, there’s some pretty amazing work being done over here by some pretty amazing people. A recent summary of our collective effort was published in the Journal for the Society of Clinical Data Management and promoted by our colleague Wenjun Bao, detailing how our software is helping sponsors and regulatory agencies around the world get drugs approved and into the marketplace. To enable this, our teams write code in C++, JMP Scripting Language, SAS, Python, Java, and R. We have been integrating many languages and technologies for years to perform clinical trials visualization and analysis, choosing the best languages for the job. Regardless of the technologies, JMP is the hub and that connects them all, helping scientists and engineers solve complex problems.
Of course, we are all passionate about our use of JMP and we believe JMP Clinical 19 is pretty amazing. But we aren’t taking a break. Take a look at our director Russ Wolfinger’s latest JMP Assistant for JMP 18 and 19, powered by LLM’s so that JMP user’s benefit from having a virtual expert help them with their repetitive tasks and streamlining workflows. Keep a lookout for more reports coming in JMP Clinical 19.1 and JMP Clinical 20. To get a sneak peek at some of our newest features (and to offer your feedback), consider joining the Early Adopter program for JMP Clinical.
Watch this video for a demo of new features in JMP Clinical 19.