Custom AI. Predictive Models.
Real Trial Impact.
Build and Customize AI & ML models to solve complex data challenges unique to your trials.
When Standard Analytics Isn't Enough
Modern trials demand more than static reports and generic models. ThoughtSphere's Clinical Science and AI Engineering capability combines platform-native AI tooling with deep clinical science expertise — giving organizations the flexibility to build and operationalize models their way.
Build Your Own Models
Develop their own proprietary AI and statistical models directly within the platform
Engage Our AI Engineers
Engage ThoughtSphere AI engineers to design and implement custom models tailored to their study and data challenges
All models are developed and executed inside the governed platform environment so data stays protected, workflows remain traceable, and customer-developed models remain customer-owned.
AI/ML Modeling Workbench: Notebook UI, Model Output Visualization, Code + Result Pane
Interactive development environment for building and testing AI models against live clinical data.
Build and Run Models Where the Data Lives
ThoughtSphere's integrated AI & ML Modeling Workbench allows teams to design, test, validate, and operationalize models directly against curated platform data — without moving data outside the controlled platform environment.
Workbench Capabilities:
- ✓ Native support for R, Python, and SAS
- ✓ Interactive notebook-based development environment
- ✓ Inline documentation and reproducible workflows
- ✓ Built-in AI/ML and statistical libraries
- ✓ Direct access to both raw and standardized data in the data lake
- ✓ External historical and RWE data upload for combined analysis
Workbench Capabilities:
- ✓ Predictive analytics
- ✓ Pattern detection in complex data
- ✓ Hypothesis testing
- ✓ Continuous monitoring models (e.g. QTLs, KRIs, etc.)
From Prototype to Production With Built-in Governance
Clinical AI models must be governed, reproducible, and production-ready. ThoughtSphere provides engineering expertise and governance platform controls that move models from experiment to execution safely.
Engineering & Governance Features:
- ✓ Code versioning and peer review workflows
- ✓ Code collaboration across global teams
- ✓ Git-based source control integration
- ✓ SDK functions for secure data access
- ✓ Model parameterization for study-specific reuse
- ✓ Publish once & reuse across studies and programs
- ✓ GxP-validated, 21 CFR Part 11 compliant environment
Code Versioning, Peer Review Workflows, Git Integration
Custom models remain traceable, reviewable, and reusable — not one-off scripts.
All models developed in ThoughtSphere are:
Versioned
Complete version control for all AI models and code
Reviewed
Peer review workflows ensure quality and compliance
Validated
ISO27001 Certified — validated, secure foundation designed for regulated clinical environments
Reusable
Build once and deploy across multiple studies and programs
Model Scheduler & Run Configuration UI
Bridge the gap between data science experimentation and real-world trial operations.
Operationalize AI. Don't Just Experiment With It.
Models built in the workbench can be integrated directly into ThoughtSphere's data processor for scheduled, automated execution — turning AI into an operational capability.
Operational Capabilities:
- ✓ Schedule model execution against refreshed data
- ✓ Run models across single or multiple studies
- ✓ Trigger downstream analytics and workflows
- ✓ Combine curated + external datasets dynamically
- ✓ Enable continuous model-driven insight generation
Bring Custom AI and Clinical Science Together
See how ThoughtSphere's Clinical Science and AI Engineering capabilities helps your teams build, validate, and operationalize AI models — directly within a governed clinical data platform.