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JMP Clinical software from SAS simplifies data discovery, analysis and reporting in clinical trials, bringing greater efficiency and accuracy to clinical and nonclinical studies.
Through a purpose-built, streamlined user interface, JMP Clinical significantly reduces medical monitoring time and enhances capabilities for detecting risks at clinical trials sites. Simplified access to clinical and statistical reports and flexible sharing options allow cross-functional teams to collaborate more efficiently than ever before.
JMP Clinical lets you streamline the management of all ongoing trials and past research by configuring clients to provide personalized, need-based access to reports. This allows all parties engaged in the review of preclinical and clinical trials -- regulatory agencies, academic institutions, pharmaceutical and biotechnology companies and more -- to use the same state-of-the art tools.
Risk-based monitoring functionality, one of many central statistical monitoring tools in JMP Clinical, limits costly on-site reviews while safeguarding the well-being of study participants. These features tie in seamlessly with fraud detection, data monitoring and statistical analysis capabilities to reduce trial failure.
Out-of-the-box capabilities in JMP Clinical make it easy for data monitors, medical writers, biostatisticians and data managers to see and explore trends and outliers, and then communicate their discoveries.
Risk-based monitoring tools in JMP Clinical promote the paradigm shift toward more efficient clinical trial review, reducing costly on-site source data verification while preserving data integrity and the safety of study participants.
Using standard CDISC data formats, JMP Clinical allows centralized data monitoring teams to evaluate risk efficiently with reliable statistics and intuitive visualization. Risk metrics derived from recommendations by TransCelerate BioPharma, a consortium of pharmaceutical and biotech companies, provide a foundation for assessment. Simple customization makes it easy to add or modify metrics based on the nature of trial sites and study populations.
Site-level tables deliver color-coded risk levels at a glance, allowing easy identification of any sites requiring immediate attention. Geospatial maps show site- and country-level clinical trials risk, providing additional insight into potential clinical trial problems such as environmental conditions or training programs.
Data snapshot comparison features track all changes over time, allowing clinicians, statisticians and data managers to focus on new or modified data. Data monitors can easily compare performance before and after site interventions.
Risk-based monitoring capabilities integrate seamlessly with JMP Clinical features such as Patient Profiles and Adverse Event Narratives, making it easy for monitoring personnel to look more closely at sites with identified risks.
The success of any clinical trial depends on the accuracy and integrity of the study process and the data produced from the trial. Detecting inadvertent errors and fraudulent data is paramount at every step.
Classic monitoring strategies rely on on-site visits and source data verification, which are expensive and of limited value. JMP Clinical offers unique tools for summarizing clinical trials data in a way that makes it easy to identify unintentional or intentional errors in data about individual subjects or clinical sites.
With JMP Clinical, you don’t need to be a statistician or a programmer to detect fraud or data quality problems. Using CDISC data, JMP Clinical conducts statistical analyses and presents results visually. Its interactive paradigm makes it easy to share and explore your findings. Data integrity capabilities in the software help you identify and address issues at both the site and patient level, and include methods to:
During clinical trials, JMP Clinical organizes the review process, working behind the scenes to automate the analytics and reporting so reviewers have more time to interpret and understand the results. Its visual paradigm speeds discovery, revealing trends and outliers that spreadsheets tend to hide.
Data monitors can evaluate data from ongoing, blinded trials for safety issues with the click of a button, creating summary dashboards of adverse events, concomitant medications, labs and vital signs with the ability to drill down to customized patient profiles and patient narratives. Monitors share these reports in PDF or RTF format with medical writers, who tailor the final study reports. At any point, biostatisticians can evaluate statistically significant differences due to age group, sex, race or site using sophisticated pattern discovery or predictive modeling analyses.
By using standard CDISC data – the format for clinical analysis and reporting preferred by the FDA – as well as standard reviewer guidances and standard visualizations, the software streamlines the exploration, review and submission of clinical trials data to the FDA.
Designed in collaboration with data monitors, summary dashboards in JMP Clinical enable clinicians to evaluate data from ongoing, blinded trials for safety issues with the click of a button, creating interactive reports of adverse events, concomitant medications, labs and vital signs with the ability to drill down to customized patient profiles and patient narratives.
By combining the most sophisticated statistical algorithms with innovative visualizations, JMP Clinical allows biostatisticians to dig deep into clinical events, findings and interventions from a clinical trial.
Bayesian hierarchical models, unique in JMP Clinical, find rare adverse events that might put a clinical trial at great risk. These models complement our incidence screens analyses based on more commonly used frequentist methods.
Industry-leading predictive modeling capabilities in JMP Clinical offer a broad and robust array of methods as well as options for predictor filtering, predictor lock-in, and cross-validation. The software guides statistical reviewers through comprehensive exploratory analyses of separate and paired data types and permits the combination of multiple predictor types to build, test and cross-validate biomarker signatures with a choice of hold-out methods.
Pattern discovery capabilities in the software include clustering techniques and correlation methods that identify individuals or subgroups of patients who are at risk of serious safety issues that could stop the trial.
JMP Clinical makes it easy to pose questions about your data and find statistically responsible answers quickly. The integration of graphics with comprehensive statistics makes it easy to see trends, patterns, and outliers.
Automated patient profiles and patient narratives reduce the time and complexity of creating output for review and submission both internally as well as to the FDA and other regulatory agencies. Along with summary dashboards of events, findings and interventions, these features enable medical officers to quickly generate hypotheses about particular groups or subgroups within the study population.
The Review Builder app loads data and reports into a simple user interface, eliminating frustration and wasted time for medical officers who need access to the data but don’t want to learn a new system. With a single click, clinicians can gain access to patient profiles and narratives.
JMP Clinical lets medical officers instantly generate patient profiles for an individual or group of subjects simply by selecting subjects, and it displays clinical results visually, making it easier for nonstatisticians to understand. Patient profiles are customizable, displaying data from any combination of the core safety domains. Once the reports are tailored, users can save the view as a template or can print the report in PDF or RTF, making for straightforward communication of findings among review groups.
JMP Clinical can compose a configurable patient narrative for each subject who experienced a serious adverse event during the clinical trial. Reviewers and medical writers enjoy the speed of this programmed process, using the write-ups as a starting point for the final patient narratives compiled in the Clinical Study Report (CSR) required by the FDA.
The Exposure Summary process identifies differences in dose and duration of exposure across treatment groups, providing context for all downstream analyses. JMP Clinical includes options to choose the number of dosing groups and the duration of the time window. Incidence screens of concomitant medications and substance use allow clinicians to identify drug-drug interactions. Following FDA Reviewer Guidance principles and ICHE3 guidelines, with a focus on adverse events, JMP Clinical enables analysis of distributions, event rates and estimations of risk over time for blinded and unblinded data. Clinicians can easily select subgroups with Distribution dashboards that summarize by age, sex, race, treatment group and site.
With JMP Clinical, you can determine the onset of an adverse event and its outcomes with time-to-event analyses and resolution screening, respectively. Various time-to-event analyses, such as Time To Discontinuation, are available with the click of a button. JMP Clinical facilitates time windowing in most analyses, and the AE Resolution Screen lets you monitor adverse event outcomes during a specified time window.
Incidence screens, the principal safety analyses for adverse event identification, perform a Cochran-Mantel-Haenszel test, yielding volcano plots of multiplicity-adjusted p-values by risk difference, relative risk or odds-ratio. The bubble size indicates the total incidence of an event that occurs for both treatments combined. Select adverse events (bubbles) of interest to determine the frequency of co-occurrence in the study population using a Venn diagram.
JMP Clinical supports the MedDRA hierarchy, allowing examination of any term level, including Standardized MedDRA Queries, to help you discern adverse event patterns across treatment groups. The software also lets you compare the incidence of any of these term levels across the duration of the trial.
Determining treatment compliance and establishing baseline values for lab measurements is important for all clinical reviewers. Often these data provide the means to determine both efficacy and safety evaluations. JMP Clinical equips medical reviewers with analyses for both measures of central tendency and outlier detection so that they can quickly identify potentially harmful symptoms that develop during the clinical trial.
Nearly all of the visualizations recommended in the FDA Reviewer Guidance are available in JMP Clinical without any programming, including distribution displays, box plots, shift plots, time trends, scatterplots as well as change from baseline. In addition, our volcano plots offer a simplified but uniquely comprehensive view of relative risk data that shows changes over time.
JMP Clinical evaluates liver toxicity, a primary safety focus of clinical trials, by identifying subjects who meet the Hy’s Law criteria described in the Drug Induced Liver Injury Guidance document set by the FDA. An industry-standard scatterplot matrix displays Hy’s Law along with a mosaic plot to confirm the number of days subjects experienced elevated liver test measurements. Finally, a tabular report in the dashboard display shows the number of subjects who missed the laboratory tests necessary for Hy’s Law determination.
JMP Clinical provides tailored dashboards to support statistical summarization techniques that let epidemiologists and statisticians review post-market study data. Spontaneously reported adverse events are collected by regulatory agencies, pharmaceutical companies and device manufacturers to monitor the safety of a product once it reaches the market. This data is generally obtained from physicians, patients or from medical literature.
Because there is no measure of total exposure, spontaneously reported adverse events present a unique challenge. To identify potential safety signals, the rate at which a particular event of interest co-occurs with a given drug is compared to the rate this event occurs without the drug in the event database. JMP Clinical includes four industry-standard techniques for disproportionality analysis:
Configure JMP Clinical on a Citrix XenApp 6.0 Fundamentals Server.
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