• enjoy a consistent approach to identification of analytical parameters critical to analytical method performance in analytical methods using the standardized and validated Inference for QbD function library
• employ a reliable approach to identifications, visualization, documentation and verification of analytical method design space using the Inference for QbD template library
• gain valuable analytical method understanding from low-value analytical data using machine learning methods
• save time by automating repetitive QbD tasks, e.g. creating standard analyses reports and capturing them in an electronic lab notebook
• save time by rapidly prototyping, testing and deploying new data-analysis methods for QbD applications
• shorten turn-around time for delivery of custom analytical reports by enabling the scientists to perform data pipelining and documentation directly in Inference Word
• easily find and reuse prior QbD information from a global searchable database of QbD data-analysis methods for assembly into SOPs

Analytical Managers

• deploy a consistent approach to implementing QbD goals across Analytical R&D
• ensure consistent, accurate and traceable Analytical QbD records and reports
• shorten time-to-decision and improve efficiency by providing streamlined, regulatory compliant Analytical workflows
• improve Analytical R&D’s capability to share and collaborate on QbD projects
• leverage and exploit an underutilized asset: QbD information from prior Analytical projects 
• collect a broadly accessible, enterprise wide analytical R&D knowledge base for training new employees and initiating future QbD projects
• improve decision quality and reduce time-to-decision by supplying facts-based predictive modeling of analytical methods to entire R&D team
• shorten QbD training by using templates and leveraging familiarity with Microsoft Office

Adjoining Development Functions

• clearly communicate QbD project status, uncertainties and development strategy to senior stakeholders and the entire development team
• enable adjoining development functions involved in QbD project to have real-time access to relevant analytical R&D information
• support regulatory by maintaining QbD study data in a searchable 21 CFR Part 11 compliant centralized repository with full audit trails
• enable regulatory and CMC project teams to easily assemble standardized QbD results for CMC filing
• support process engineering during scale-up and validation by enabling direct access to analytical QbD information
• support IT by providing: a single platform that spans the full development organization; a standards-based architecture that is scalable to thousands of users; and a set of core applications that requires minimal training and support built on familiar Microsoft Office