Clinical SAS

  1. Home
  2. Clinical SAS

Clinical SAS

At Progue Technologies, we empower healthcare, pharmaceutical, and life sciences organizations with Clinical SAS Technology solutions that enable efficient clinical data management, analysis, and reporting. Using SAS (Statistical Analysis System), our solutions help you unlock valuable insights, ensure regulatory compliance, and drive the success of your clinical trials.

Whether you're working on clinical data from Phase I to Phase IV studies, regulatory submissions, or post-market surveillance, our Clinical SAS services are tailored to meet the highest standards of data accuracy and regulatory compliance.

Our Approach

Discover & Strategize

We begin by understanding your goals, challenges, and target audience.

Product Design

Our expert team transforms the strategy into a powerful digital solution — combining intuitive UI/UX design with clean, scalable code.

Deliver & Optimize

We rigorously test, deploy, and monitor the solution to ensure a smooth launch.

Benefits

We help you manage and streamline clinical trial data efficiently using SAS tools for data collection, validation, and storage. Our team ensures that your data is accurate, complete, and compliant with regulatory standards such as FDA, EMA, and ICH-GCP.

We assist with integrating data from multiple sources and clinical trial phases using SAS. This includes data harmonization, creating datasets for analysis, and generating required reports for stakeholders and regulatory agencies.

We specialize in preparing Statistical Analysis Plans (SAPs), TFL (Tables, Figures, and Listings), and regulatory submission datasets (e.g., ADaM, SDTM) for FDA, EMA, and other global regulatory bodies. Our solutions ensure that your submission data is accurate, compliant, and ready for review.

We provide custom SAS programming services, whether you need specialized analysis or complex algorithms tailored to your specific clinical trial needs. Our team is adept at creating efficient, reusable code for your clinical data processes.