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Join SAS at PHUSE US Connect 2022

Accelerating Analytic Innovation in Clinical Development

May 1 - 4  |  Atlanta

Data and analytics create innovation in clinical development, from improving access and patient-centricity to applying real-world insight.

Join SAS at PHUSE US Connect and explore important themes like bias in machine learning and real-world data use cases for clinical development, as well as tips and tricks for getting the most from SAS®.

SAS Analytics transforms data into life-changing insight.

Our most anticipated presentation

Exploring RWE in pharma: A hands-on workshop with a trial feasibility use case

Life sciences organizations are compelled to create more patient-centric protocols to reduce operational risk and development costs, while increasing the likelihood of regulatory approval and accelerating new treatments to patients. A comprehensive real-world evidence (RWE) strategy helps pharmaceutical companies stay competitive and get better, safer therapies to market faster.

To maximize the probability of success for clinical trials, clinical researchers must refine patient eligibility criteria using real-world data (RWD). This increases the likelihood of patient retention while decreasing protocol amendments. When RWD is used in clinical trials as a synthetic study arm, data robustness needs to be assessed for hypothesis generation and regulatory acceptability.


In this workshop, we'll cover applications of RWD in pharma and focus the hands-on portion on trial feasibility. In the interactive, theoretical part we will handle:

  • The accessibility and management of RWD.
  • The robustness of RWD.
  • Acceptability of using RWD in clinical trials.
  • The advantages and pitfalls in eligibility testing of clinical trials

We’ll use a SAS® Viya® demo environment for the hands-on part. The environment uses SAS Health: Cohort Builder, Viya Visual Interfaces and Coding Interfaces (SAS Studio, R and Python) on Microsoft Azure. We’ll show how OHDSI models and analytical packages can be integrated in the approach.

Workshop participants will have the opportunity to explore target patient populations, test hypothesis and conduct sensitivity analysis to understand the impact with different combinations of eligibility criteria and hypotheses.

Please register beforehand. We have a maximum of 40 participants for the hands-on portion. Other participants will be offered an alternative program.

Additional presentations include:

  • Bias in Machine Learning: Your Responsibilities as a Programmer
  • CAS-L Coding in SAS
  • Ensuring Distributed Data Custody on Cloud Platforms
  • Integration of SAS Life Science Analytics Framework and VEEVA Using REST APIs
  • Leveraging OHDSI Methods Library and SAS Viya for Clinical Decision Making Using Real-World Data

Learn how SAS and bioMérieux create better health outcomes with analytics

Scientist viewing sample through microscope during

Strengthening the fight against antimicrobial resistance via data visualization

Meet our SAS experts

Jim Box
Principal Data Scientist, Life Sciences

Pritesh Desai
Principal Industry Consultant, Life Sciences

Samiul Haque
Systems Engineer, HLS

Robert Collins
Principal Industry Consultant