JMP Clinical software can shorten the drug development process by streamlining safety reviews of clinical trials data – using JMP and SAS® Analytics together.
JMP® Clinical Features
New features benefit clinicians:-
A new medical monitors dashboard in JMP Clinical 4 displays frequency and count information for adverse events.
Explore and Analyze :-
A simplified Starter menu helps users easily choose specific reports and analyses for dynamic visual exploration
1-click patient profiles, narratives
A patient profile dashboard allowing configuration of clinical information, notes for reviewers and printing to PDF documents.
Compare interventions across groups
Use Graph Builder's Mosaic Plot to compare adverse events, here from the vascular body system, by sex across treatment groups.
Monitor events and outcomes
A volcano plot reveals significant adverse events across treatment groups with time windows (days 1-3, 4-6 and 7-11).
Quickly identify potential harms
JMP Clinical makes it easy to identify outliers with graphs that provide a statistical view of change from baseline for any finding.
Visual discovery from the start
Tree maps like this one can show whether drug-event pairs meet signal criteria
Add a Study that contains CDISC-formatted SDTM and/or ADaM data from SAS data sets or transport files.
Create ADSL data sets and other types of ADaM data on the fly by collecting relevant slices of SDTM data.
Rename a study or its associated folders, or delete parts or all of it with Manage Study.
Check Required Variables in SDTM and ADaM folders for all variables required in JMP Clinical analytical processes to produce a table of results indicating missing variables and affected processes.
Use Basic Safety Workflow to perform a complete set of standard safety data analyses with only a few mouse clicks.
Create custom workflows with Workflow Builder.
Employ Journal Builder to create a journal file containing results of user-specified processes.
Compare Distribution of demographic variables across treatment arms via a oneway ANOVA or contingency analysis.
Generate an Exposure Summary of drug exposure duration for subjects across entire study or specified time window.
Compare Distribution of concomitant medications and substance use variables across treatment arms.
Use Incidence Screen to perform an incidence analysis of concomitant medications or substance use between two or more treatment groups to produce a volcano plot of relative risk, risk difference or odds ratio.
Create Kaplan-Meier Survival Curves and associated statistics, grouped by treatment arm.
Compare cause-of-death frequencies between treatment arms via a contingency analysis with Mortality Cause Comparison.
View Distribution of adverse events, subject disposition or medical history across treatment arms.
With AE Incidence Screen perform an incidence analysis of all adverse events or Standard MedDRA Query terms across two or more treatment groups to produce a volcano plot of relative risk, risk difference or odds ratio. Optionally perform the incidence screen using the Double FDR methodology of Mehrotra and Adewale (2011) to discover true signals by incorporating a grouping variable, such as body system, into the analysis.
Analyze incidence of adverse event resolution across treatment arms using AE Resolution Screen.
Perform AE Severity ANOVA to explore severity for each distinct adverse event that differs between time periods and/or treatment groups.
Create tabular and graphical overviews of Treatment Emergent Adverse Events for the safety population by treatment arm.
Determine time to first occurrence of an adverse event using AE Time to Event to perform log-rank and Wilcoxon tests between treatment groups.
Generate AE narratives for clinical study reports on all AEs or SAEs with option to capture all adverse events within specified time frame surrounding AE start date.
Use DS/MH Incidence Screen to perform an incidence analysis of disposition or medical history across two or more treatment groups to produce a volcano plot of relative risk.
Compare Distribution of laboratory, vital signs and ECG findings across treatment arms.
With Baseline ANOVA efficiently screen all findings measurements that differ across treatment groups over the entire study or for a defined time window.
Display Shift Plots to compare test measurements for a specified findings domain at baseline versus on-therapy values and performs a matched pairs analysis.
Display Box Plots by treatment group representing the change from baseline in measurements for each test for specified findings domain across various specified time windows or points in the study.
Visualize Time Trends for findings measurements for each subject across the timeline of the study.
Track a pair of findings measurements over time with an animated Bubble Plot and select subjects of interest to display their time profiles.
Define events using one or more findings tests to be analyzed in a Time to Event analysis.
Hy's Law Screening
Visualize peak values over the duration of a study for lab measurements pertaining to Hy's Law for detecting potential liver toxicity for all subjects across treatment arms.
Calculate number of days subject experiences elevated liver test measurements to identify individual Hy's Law cases.
Perform contingency analysis to compare the incidence and frequency of potential liver toxicity across treatment arms which may be used to evaluate the possibility of drug-induced liver injury (DILI).
Tabulate number of subjects with missing lab tests.
Generate a Study Visit Attendance Report, various Standard Safety Reports and a report of study Comments in RTF and PDF formats.
Examine patient profiles from any CDISC domain.
Drill down to view demographics, disposition, safety, findings, medical history and comments for any subject.
Profile multiple subjects simultaneously, side by side.
Create customized patient profile templates.
Create a PDF report and AE narrative from drill-down views.
Other Subject Utilities
Cluster Subjects to search for hidden patterns in interventions, events and findings within or across domains.
Create interactive Venn Diagrams with up to five variables.
Tailor data views using complex queries with Data Filter.
Apply Subject Filter to any analytical process.
Review Status Distribution of the subjects in a study.
Create Cross Domain Data suitable for clustering, pattern discovery and predictive modeling.
Pattern Discovery & Predictive Modeling
Perform interactive partial correlation analysis on clusters of events to adjust for potential confounding.
Employ dimension-reduction techniques such as principal components and multidimensional scaling to highlight major structural trends in your data.
Compare results across nine different major predictive modeling methods, with numerous options and tuning capabilities.
Customize predictor filtering during model construction.
Perform predictive modeling for survival analysis.
Assess the impact of sample size using a Learning Curve analysis.