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JMP® Clinical
Clinical data analysis software for ensuring trial safety and efficacy
Role-based workflows, reusable templates and automated reporting tools make it easy for all key participants in the trial review process to explore trends and outliers. Detect hidden data, safety and efficacy issues via capabilities such as RECIST-based oncology visualizations, medical monitoring, data integrity validation and statistical analyses. Publish results to a secure web environment where colleagues can view your findings.
Have a minute? See JMP Clinical in action.
Clinical data scientists and medical monitors
Summary dashboards in JMP Clinical enable medical reviewers to evaluate safety and efficacy issues with the click of a button. Create interactive reports of adverse events, concomitant medications, labs and vital signs, and drill down to customized patient profiles and patient narratives.
Medical writers
Producing adverse event narratives for clinical study reports (CSRs) can be a painstaking, time-consuming process with significant consequences for inaccuracies or delays. With JMP Clinical, medical writers can automate patient profiles and patient narratives and reduce the time and complexity of creating output for review and submission to regulatory agencies.
Clinical operations
The goal of clinical operations is to mitigate data quality risks that could hinder a regulatory submission or drug approval. Risk-based monitoring tools in JMP Clinical help you identify data anomalies at the vendor, monitor, site and country level, and determine the factors responsible for lapses in safety or data quality.
Drug safety specialists
Pharmacovigilance responsibilities often include submitting Development Safety Update Reports (DSUR) and Periodic Safety Update Reports (PSUR) to the FDA to better track ongoing safety issues. JMP Clinical automates the gathering of required report components and facilitates the integration of this information with patient profiles and narratives.
The Core Capabilities of JMP Clinical®
Patient Narratives
Automatically compose a configurable patient narrative for each subject who experienced an adverse event (AE), including reporting for deaths, serious AEs, AEs of special interest and AEs resulting in study discontinuation.
Patient Profiles
Instantly generate customizable patient profiles and easily communicate findings among review groups.
Data Visualization and Analysis
Reveal trends and outliers and accelerate discovery via interactive visualization and sophisticated pattern detection.
Data Monitoring
Assess trial data for safety issues with the click of a button and create interactive reports of adverse events.
Data Integrity
Discover data anomalies at the site and patient level, whether due to fraud, data quality or protocol errors.
Data Management
Visually identify modifications to data and isolate data entry and EDC errors for downstream users of the data.
Risk-Based Monitoring
Reduce costly on-site source data verification while preserving data integrity and the safety of study participants.
Tumor Response Analysis
Quickly identify efficacy signals in solid tumor clinical trials using visualizations tailored to RECIST criteria, including survival plots, swimmer plots, waterfall plots and spider plots.
DSUR/PSUR
Save time and effort in assembling the components for these required reports through the automated generation of relevant tables and listings in .rtf and/or .pdf formats.
Medical Query Reports
Identify diseases or complexes that may arise due to ongoing treatments using standardized or customized medical queries.
Interventions
Track patient exposure to treatment, identify drug interactions, and analyze distributions, event rates and risk.
Events
Determine the onset of an adverse event and its outcomes, and discern event patterns across treatment groups.
Findings
Quickly evaluate efficacy and safety, and identify potentially harmful symptoms, including liver toxicity.
Biometrics and Biostatistics
Dig deep into clinical trial events, findings and interventions using sophisticated statistical algorithms.