Join the Clymb Clinical Team at PharmaSUG 2026!

Clymb Clinical will be attending PharmaSUG 2026, a premier conference focused on statistical programming, data science, and clinical research methodologies. The conference brings together professionals from pharma, biotech, CROs, and technology providers to share practical approaches for improving efficiency, automation, and regulatory readiness in clinical development.

Hands-On Training

Session Title: CDISC Analysis Results Standard (ARS)

Date & Time: Wednesday, June 3, 2026, 1:00 PM – 5:00 PM

Instructor: Bhavin Busa

This seminar will provide an overview of the CDISC Analysis Results Standard (ARS) and updates on the eTFL Portal, along with an introduction to the emerging CDISC Analysis Concepts framework.

Paper Presentation

1. From SAP to CSR: A Metadata-Driven TFL Workflow

Presenter : Bhavin Busa

This paper presents a metadata-driven framework that connects the full clinical reporting workflow, from Statistical Analysis Plan (SAP specification through TFL design, automated result generation, centralized review, and integration into the Clinical Study Report (CSR).

The approach demonstrates how structured analysis metadata can serve as a single source of truth, improving traceability between planned analyses, executed programs, and reported outputs while enabling automation, reproducibility, and reuse across studies.

2. Why Standards Matter More Than Code in the Age of GenAI

Presenter: Bhavin Busa

This presentation explores how CDISC Analysis Results Standard (ARS) metadata can enable reliable use of generative AI in statistical programming and clinical reporting.

By combining structured analysis metadata with predefined programming frameworks, large language models can generate TFL code rapidly while maintaining consistency, traceability, and regulatory alignment.

Visit Our Booth

If you are attending PharmaSUG 2026, stop by our booth to meet the Clymb Clinical team and learn how our solutions support metadata-driven clinical programming, CDISC standards implementation, and AI-enabled automation for statistical reporting.