SCE - Statistical Computing Environment
Manage tasks, track work, & enforce process for programmers
Sycamore Statistical Computing Environment (Sycamore SCE), is the only state-of-the art modern polyglot and GxP, 21 CFR Part 11 & EU Annex 11 compliant computing environment that automates the highly complex, collaborative processes in present day clinical trials biostatistics programming and data sciences
Sycamore SCE has the largest number of successful proven production deployments (10 of the top 20 Pharmaceutical companies) and with several thousand active global users. Sycamore SCE employs version control, audit trails, dynamic traceability for analysis using any programming language SAS, R, Python WinNonlin, NONMEM, impact analysis, role-based security, workflow and tasks to create an environment for clinical reporting and analysis.
Ensures that the lineage, integrity and provenance of data are always available and reproducible
Ensures that the lineage, integrity and provenance of data are always available and reproducible
Provides the same traceability, reproducibility for analysis LLMs, GenAI and Agentic applications
Sycamore SCE can work with different programming languages such as R, Python, the SAS language, Julia and multiple ML/AI algorithms. Sycamore SCE is agnostic to programming editors and can work with multiple web based and desktop editors such as Posit (RStudio), UltraEdit, Notepad++, VS Code, PyCharm and SAS language editors including using command line.
Unique Benefits:
Coordinate tasks, track work and enforce processes within the system
Dynamic traceability and lineage across programs, data and outputs with version control
Program in-app or from MS Windows desktop with versioning, DIFF tools, & role-based permissions
Easily define and manage role-based access, blinding, sequestering, and partner access
Reliably audit access, changes and usage across all functions
