Curate. Explore. Analyze.
Datacise is an innovative, cloud-based technology platform, with the ability to aggregate and mine data to provide real-time insights for our Sponsors. With this secure, scalable data science platform, Datacise allows Sponsors to immediately analyze and visualize clinical data, Real-World Data (RWD) and data from other data sources through three advanced applications: Curate, Analyze, and Explore.
All applications in the Datacise suite are fully-integrated with the ability to use together or as stand-alone applications.
Datacise CURATE is a flexible cloud application for the collection and aggregation of clinical data through a variety of data mapping or abstraction methods. This scalable platform can simplify the extract, load, transform (ETL) process and easily ingest structured and unstructured data from just about any source.
Typical Sponsor use cases for Datacise CURATE include:
- Extract and abstract structured and unstructured data via API or other methods
- Build databases, including data lakes, data warehouses, and other advanced data storage structures (i.e. network graphs)
- Utilize external ontologies, including WHO Drug, MedDRA, CDISC controlled terminology, and other custom dictionaries
- Perform data and image processing in preparation for further analysis or anonymization (DICOM images)
Typical Sponsor use cases for Datacise EXPLORE include:
- DSMB and Adjudication meetings including dashboards to augment static tables and listings
- Patient profiles to aid in ongoing safety reviews and assessments
- Dashboards for medical device and wearables data
- In-process data reviews by clinical teams or data managers to ensure data accuracyA tool used in the application of risk–based monitoring (RBM) strategies
- Safety surveillance signal detection, using social media and regulatory data sources (i.e. FAERS)
Typical Sponsor use cases for Datacise Explore include:
- Produce simulations and scenario planning
- Perform trend identification across disparate data, including a focus on subsets (cluster analyses)
- Analyze data from unstructured sources, using ML and NLP
- Ability to utilize high-performance computing as necessary for analysis
Listen to our webinar
Best Practices for Data Visualization in Pharma
Learn pharmaceutical industry best practices for developing practical data visualizations, tips on identifying and avoiding common pitfalls, interactive dashboards from initial discovery through UAT and validation strategies, and the importance of understanding the intended audience and planned use for data visualizations.
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