Indegene Clinical Programming provides operational and data reporting, about clinical trials being conducted for and by the sponsor, to internal sponsor study teams and external partners supporting trial functions (monitoring, safety, etc).
Clinical Programming supports the following deliverables:
CRF Listings – line listings from individual CRFs for multiple subjects
Clinical Data Review – line listings from multiple CRFs for multiple subjects
Data Transfers – moving clinical trial datasets or data files between sponsor and vendors
Metrics – performance of site quality reports showing performance over time
Profiles – patient or safety profiles summarizing patient condition, disease progression, or trial participation
Trackers – trial completion measures such as task/work logs, page review status, query review status, and reconciliation reports
Queries – reports showing subjects/visits that fail conditional logic checks
Indegene Statistical Programming supports the creation of deliverables that meet one or more of the following criteria:
Deliverables provided to regulatory body or agency
Deliverables that include end point analysis
Deliverables for publication or conference
Analysis requested by senior management
Deliverables that include summary of derived data
Deliverables used for strategy and research decisions
Deliverables supporting commercial organization
Clinical trials require statistical information in order to set performance benchmarks, keep a tab on finances, and measure quality. Metrics are reports that provide such information in the form of graphs and summarize data.
Metrics reports are used to create a balanced view (or scorecard) that monitors the trial performance, customer satisfaction, organizational growth, and performance. Metrics also flag poor internal performance or industry-relative performance.
At Indegene, our experts provide better accessibility of data for KPI Metrics, patient profile, clinical data review, listings, and safety analysis. The reporting solutions that we offer are Spot Fire, SAS, Business Objects, J-review, Crystal Reports, SSIS/Informatica, and BOXI Reports.
Clinical trials have complex computational needs. The right programming approach to deal with such needs involves a robust technology-based trial ecosystem. Strategically designed and programmed technology solutions are the key to successful clinical programming.
Indegene provides the healthcare, biotechnology and pharmaceuticals sectors, clinical research organizations, and regulatory authorities effective technology solutions that aide study timelines and data quality.
Country regulations require that clinical trial data be archived and made available till years after completion of the trial. This calls for a good archiving program.
Indegene uses the CDISC Operational Data Model (ODM) format for archiving. This is a standard for clinical trial data in XML. In future, companies and regulators might want to use ODM trial data in a usable way. An ODM viewer and then an ODM Navigator allow the users to extract subsets, to understand trends, and to look at data on a site-by-site basis.
Indegene’s EDC system makes sure that meta-data is also archived during the trial. Meta-data includes information about the eCRFs, the questions, and the validation logic, giving a clear idea of how data was collected and handled during the study.
Raw data generated by a trial is transferred from a source server to a data warehouse on the target server. This process is called External Data Loading. The data is then prepared for downstream use. All this is part of the data integration process called Extract, Transform, Load (ETL) that allows raw data to be loaded directly into the target and then transformed there. It is particularly useful for processing large data sets required for statistical analysis, business intelligence (BI), and big data analytics.
At Indegene, we work with a number of methods using BASE SAS®, SAS/STAT®, and SAS/ACCESS® to build models for External Data Loading. These programs are run on a platform that allows rebuilding data models in a short time.