Ponemah is a robust, GLP validated, software platform for data acquisition and analysis. It can be used with implantable and external telemetry, traditional hardwired monitoring, and to collect endpoints such as cardiovascular/hemodynamic and respiratory. Ponemah is a multi-application platform, used in physiology, pharmacology, and toxicology laboratories. The software is modular, consisting of multiple acquisition interfaces, as well as a library of pre-programmed, validated analysis modules, providing flexible configurations and easy expansion options for evolving research emphases.
Ponemah analysis modules are trusted by researchers worldwide for consistent, reliable, and robust results. A variety of analysis modules are available to calculate physiologic parameters from many animal models, using validated algorithms developed from scientific and peer reviewed journals. Analysis modules are applied during acquisition to provide real-time results.
Ponemah Review allows researchers to view, sort, and sync calculated data with multiple graphic presentations to quickly locate outliers and confirm accurate creation of waveforms.
This module integrates ECG cycle detection method to provide robust, accurate results. Over 30 derived parameters can be calculated for every complex on a beat-to-beat basis and presented in real-time or during subsequent analysis sessions.
Ponemah offers a template-based ECG analysis module which allows selection of a templated cardiac cycle to be used for precise comparison to other cycles in the dataset for more accurate analysis. Researchers can build a library of cardiac cycles to mix and match regions of interest with multiple templates. Once libraries are built, the Batch Template Analysis function can be used to analyze multiple subject ECG channels without any user interaction.
Left Ventricular Pressure
This module specifically analyzes the left ventricular pressure from the heart. Some of the on-line derived parameters include LVEDP, HR, +/-dP/dt, Q-A interval and Tau.
This module can analyze pressure from the circulatory system and can derive, on a beat-to-beat basis, values for the cardiac cycle such as systolic and diastolic pressures, heart rate, and +/-dP/dt.
This module analyzes the blood glucose signal obtained from the HD-XG implant. The analysis calculates the common parameters that are associated with glucose after the signal has been calibrated.
Blood Pressure Respiration
This module can analyze any pressure from the circulatory system and can derive, on a beat-to-beat basis, respiration values from the cardiac cycle.
This module analyzes any volume from the circulatory system and derives real-time values relative to the cardiac cycle, such as filling and emptying rates, stroke work, and cardiac output.
This module operates in conjunction with the LVP and Cardiac Volume analysis modules to calculate a wide host of derived parameters including PRSW, ESPVR, and EDPVR.
Coronary Blood Flow
This module derives typical flow information such as Maximum and Minimum Flow, Mean, Stroke Volume and Cardiac Output. When coupled with the Left Ventricular Pressure Module, the addition of timing information from this module allows for flows and volumes to be calculated specific to the Systolic and Diastolic portions of the cardiac cycle.
Systemic Blood Flow
This module analyzes both coronary and systemic blood flow. Common derived parameters generated from the Systemic Blood Flow analysis include, but are not limited to, Max and Min Flow, Stroke Volume, and Cardiac Output.
This module calculates, on a breath-to-breath basis, values for respiratory volume, flow and a host of other calculated parameters.
Pulmonary Airflow & Airway Resistance
This module calculates, on a breath-to-breath basis, values for the respiratory cycle obtained from plethysmograph boxes or pneumotachs. Tidal volume, peak flows and PEnh are examples of the derived output that are available.
This module analyzes signals obtained from free-roaming chambers. Derived values for flow and volume measurements, as well as PEnh, are examples of measurements performed by this module.
The purpose of this module is to compute physiologically meaningful parameters from digitized EMG data.
This module is used to calculate respiratory parameters from EMG data acquired from the diaphragm. Tidal Volume, Minute Ventilation, and Respiration Rate are examples of derived outputs available in breath-to-breath or time averaged presentations.
This module identifies common parameters such as Maximum, Minimum and Plateau voltages. User defined Recovery Points as well as rates of change are also generated by this module.
Pulsatile Tissue & Gut Motility
This module calculates, on a contraction-to-contraction basis, derived values such as Maximum and Minimum values, Average (AUC) and Rate. Numerous other parameters can be generated in real time such as first and second derivatives.
Automatic Arrhythmia Detection Using Data Insights™
Data Insights™ optimizes data analysis using interactive tools which give the user multi-faceted views of data so they can remain engaged in the decision-making process and save time. As researchers can quickly locate data sections with morphology variations, they are able to adjust settings and reanalyze as needed. In addition, they can visualize signal noise to confidently eliminate artifact. When this is done manually, without considering inter-animal variability, the algorithm may exclude good, physiological data and/or mismark reported data. Data Insights can apply quality assessment-based searches to ensure the data are reported accurately and minimize the exclusion of data. By reducing the amount of manual data analysis, Data Insights™ reduces variability and increases reproducibility.
Researchers can identify complexes to use with ECG template libraries. Data Insights™ correlates physiologic interactions between waveform types allowing efficient performance of waveform marking validation.
Data Insights™ can help researchers select the most appropriate subjects by screening prior to study, developing and characterizing disease models, and creating individual subject arrhythmia signatures to discern treatment effects.
Alarms for monitoring system and animal health
With Remote Notification, researchers can set alarms in Ponemah to notify appropriate personnel, based on alarm conditions, via email or text message.
Remote Notification can also be used as an animal welfare refinement method to monitor for signals of pain, stress, and infection. Alerts can be set to notify veterinary staff when vital signs go outside specified ranges (e.g. when temperature exceeds a certain threshold).
Advanced GLP Compliance
Ponemah’s Data Security Option (DSO) allows the system to operate within FDA 21 CFR Part 11 regulations. DSO uses a Smart Card technology and electronic signatures to provide a high level of system security and data control. DSO also provides secure program login, electronic signatures, controlled user privileges, multiple user profiles, file integrity validation, and audit trail.
Data File Management
Ponemah manages all data files collected throughout the study in an underlying SQL Database Express Engine. The SQL database provides structure and control, allowing users to run studies consistently across workstations locally or world-wide.
Reporting is a customizable data organization, analysis, visualization, and reporting tool seamlessly integrated with Ponemah. Reporting generates individual derived data listings, group mean summary tables, and graphs directly into MS Word. The GLP feature locks tables and graphs so no changes can be made to the final report.
- Boulay E., Pugsley MK., Jacquemet V., Vinet A., Accardi MV., Soloviev M., Troncy E., Doyle JM., Pierson JB., Authier S. (2017). Cardiac contractility: Correction strategies applied to telemetry data from a HESI-sponsored consortium. J Pharmacol Toxicol Methods. Doi: 10.1016/j.vascn.2017.04.009.
- Lagrange J., Kossmann S., Wenzel P. (2017). Assessment of Vascular Dysfunction and Inflammation Induced by Angiotensin II in Mice. Inflammation. 1559: 439-453.