Overview

JMP® Clinical is a comprehensive software solution designed to enhance the analysis and monitoring of clinical trial data. It empowers medical monitors, data scientists, and clinical operations teams to interactively explore trends, detect anomalies, and ensure the safety and efficacy of clinical trials. By automating complex processes such as patient narratives and risk-based monitoring, JMP Clinical streamlines workflows, reduces the potential for errors, and accelerates decision-making.

Features and Capabilities

• Patient Narratives: Automatically generate configurable narratives for subjects experiencing adverse events, including serious cases and study discontinuations.
• Patient Profiles: Instantly create customizable profiles to effectively communicate findings among review teams.
• Data Visualization and Analysis: Utilize interactive visualizations to uncover trends and outliers, facilitating rapid discovery and pattern detection.
• Data Monitoring: Efficiently assess trial data for safety concerns and generate interactive adverse event reports with a single click.
• Data Integrity: Identify anomalies at both site and patient levels, addressing issues stemming from fraud, data quality, or protocol deviations.
• Data Management: Visually detect data modifications and isolate entry errors, ensuring downstream data accuracy.
• Risk-Based Monitoring: Minimize costly on-site data verification by preserving data integrity and participant safety through targeted monitoring.
• Tumor Response Analysis: Identify efficacy signals in solid tumor trials using specialized visualizations like survival, swimmer, waterfall, and spider plots.
• DSUR/PSUR Reporting: Automate the generation of required report components, saving time and effort in assembling tables and listings.
• Medical Query Reports: Detect diseases arising from treatments using standardized or customized medical queries, including FDA algorithms.
• Interventions: Monitor patient treatment exposures, identify drug interactions, and analyze distributions and risk factors.
• Events: Determine adverse event onset and outcomes, and discern patterns across treatment groups.
• Findings: Evaluate efficacy and safety swiftly, identifying potentially harmful symptoms, including liver toxicity.
• Biometrics and Biostatistics: Delve into clinical trial events, findings, and interventions using advanced statistical algorithms.