Synthetic Data Generator
KerusCloud can be used to generate highly realistic synthetic datasets for use in a wide variety of analytics applications in the life sciences sector and beyond.
Synthetic Data
& Population Construction
& Population Construction
KerusCloud can be used to build synthetic populations and datasets for use in the clinical trial design process or for export and use in a wide variety of analytics applications.
Leverage insights from synthetic data free from sharing sensitivities and data privacy restrictions
Data privacy laws and sensitivity around data sharing have made it difficult to access and use subject-level data. Synthetic datasets provide a realistic alternative, describing the characteristics of subject-level data without revealing protected information. This allows them to be shared and used freely without raising privacy concerns to inform the development of new products, services and intellectual property.
Generate realistic synthetic data sets based on real subject-level data
KerusCloud’s Synthetic Data Generator can handle diverse and complex data collected in disparate data sources to produce realistic synthetic datasets with broad utility. Going beyond using population statistics for simulation, it can model the inter-correlation between subject-level data such as subgroups and strata, risk factors/covariates and multiple outcomes and data types.
Build special features into your data to mimic real data more closely
The exceptional modelling capabilities of KerusCloud SDG mean that special features can be incorporated into synthetic data sets such as derived variables, missing data, truncation and censoring. This allows users to generate the most realistic synthetic version of the original data.
KerusCloud SDG can be used to support many applications including:
- Market research and business intelligence
- Testing and validating software products and systems
- Building and testing algorithms
- Predictive modelling, machine learning and AI
Download Datasheets
Download Datasheets
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