SAS Life Science Analytics Framework

SAS Life Science Analytics Framework is a cloud-native statistical computing environment designed for clinical research organisations. It provides a single, open platform for transforming, analysing and reporting on clinical trials data, supporting pharmaceutical companies, biotech firms and contract research organisations in bringing new therapies to market more efficiently.

The framework integrates embedded analytic tools, support for data standards, and optional analytic applications within one environment. It is intended for a broad range of stakeholders including clinical operations, preclinical operations, medical affairs teams, programmers and regulatory submission specialists.

Core Capabilities

• Provides a single, cloud-native solution for clinical analysis and regulatory submission, covering validation, regulatory compliance, versioning, audit trails and documentation support.
• Supports programming in SAS, R and Python, allowing users to consume R data frames within the solution and broadening the available pool of programming talent.
• Integrates analytic applications — including those already developed internally or sourced from SAS — to address a variety of business needs.
• Allows direct data pull from existing electronic data capture (EDC) systems for quicker data access and potential cost savings.
• Includes a centralized clinical data repository and shared workspace accessible to all authorised global team members within a single platform.
• Supports CDISC standards governance through a model-driven approach and enhanced study metadata management, driving efficiency from study setup through to submission.
• Covers end-to-end management of clinical data from operational data systems such as eCRF, electronic health records, sensors and wearables, omics data and biomarker data, through standardisation, analysis, reporting and post-approval meta-analysis.

Data Management and Quality

• Provides a central hub for all incoming data with automated data quality analysis.
• Includes impact analysis for every job and full mapping of data source, data manipulations and final data destination.
• Offers advanced search functionality to improve discoverability and productivity.
• Reduces time spent on operational data management, allowing more time for data exploration, quality monitoring and advanced analytics.

Workflow and Process Automation

• Workflow capabilities support project management oversight and process enablement across clinical research activities.
• Supports multiple simultaneous analyses with different team members, access rights and context-specific privileges.
• Allows task assignment and progress tracking for each analysis activity and deliverable, at the level of a single study or an entire portfolio.
• Supports workflow deployment on a per-deliverable basis, whether a table, listing or figure.
• Automates clinical process activities through process orchestration capabilities including scheduled job initiation and completion notification.
• Supports new, decentralised and hybrid trial models, including automation, decision support and activity tracking.

Regulatory and Statistical Rigour

• Combines regulatory compliance and control features with development and execution of SAS programs to reduce risk.
• Implements and manages data standards and controlled terminology.
• Supports current and future regulatory integrations and submission requirements.
• SAS is widely accepted as a standard for statistical capabilities used to determine the safety and efficacy of medicines in clinical research.

Collaboration and Stakeholder Access

• Supports global collaboration among internal team members, consultants, contractors and development partners.
• Puts analytics tools in the hands of knowledge workers across preclinical operations, clinical operations and medical affairs.
• All authorised users work within the same centralised platform, reducing fragmentation across teams.

SAS Life Science Analytics Framework is available as a cloud-native solution and can be deployed via SAS Managed Cloud Services. Related offerings include SAS for Transforming Clinical Trial Analysis and Submission (powered by Azure), SAS Clinical Enrollment Simulation and Software as a Service options. The platform is positioned to support both traditional and emerging decentralised clinical trial designs.