PharmaSUG 2025

1st June 2025 to 4th June 2025

San Diego, CA

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Join the Clymb Team at PharmaSUG 2025!

Our team will be attending PharmaSUG 2025, a premier conference dedicated to statistical programming, data analytics, and clinical research methodologies. With the theme “Bridge to the Future!”, this year’s event will feature 2.5 days of live presentations, hands-on training, e-posters, and panel discussions, bringing together experts from pharma, biotech, and CROs to explore the evolving landscape of data science and regulatory analytics.

1. Paper Presentation

Title: Towards an Integrated Submission-Ready Data Pipeline: Unifying Compliance, Automation, and Open-Source Innovation

Presenters: Shivani Gupta and Bhavin Busa

Explore how a unified, automated workflow can streamline regulatory submissions by integrating CDISC compliance checks, regulatory guidance, metadata submission, and eCTD validation. This session discusses leveraging open-source initiatives and automated validation to enhance submission efficiency, reduce manual effort, and ensure regulatory alignment.

2. Paper Presentation

Title: Harnessing AI & CDISC ARS for Effortless Statistical Reporting & CSR Writing

Presenters: Bhavin Busa and Navin Dedhia

Discover how Gen-AI and CDISC Analysis Results Standard (ARS) are revolutionizing Clinical Study Report (CSR) writing. Learn how an AI-driven model, fine-tuned on ARS and Analysis Results Data (ARD), automates statistical reporting, generates narrative summaries, and streamlines efficiency for medical writers, clinicians, and biostatisticians.

3. Paper Presentation

Title: Hands-on Training: eTFL Portal & TFL Designer Community

Presenter: Bhavin Busa

Join this hands-on session to explore the eTFL Portal, a CDISC-hosted resource for implementing Analysis Results Standard (ARS) and Analysis Results Data (ARD). Learn how to leverage standardized templates and metadata to automate TFL development, enhance workflow efficiency, and align with evolving CDISC standards.

Event snapshots

Accelerate Clinical Trials with Data-driven Insights