Pre-Conference Workshops

Sunday, September 11, 2022

One day before the SCDM 2022 Annual Conference kicks off, we are excited to offer you the possibility to join Pre-Conference Workshops that will allow you to explore key CDM topics in greater depth.

The Pre-Conference Workshops are interactive 4-hour long sessions run by practitioners and leading global education organizations. These sessions will provide a hands-on learning experience that will enable you to gain new insights and explore new strategies and tools in your day-to-day work.

Participants in the Pre-Conference Workshops will earn 4.0 CEU’s/session after the successful completion of each session and post-session assessment.

Pre-registration is mandatory and an additional fee of Pre-registration is mandatory and an additional fee of $525 will apply.
 
 
 
 

workshop

AI and Machine Learning: What it is and its Impact on Data Management

Sunday, September 11
8:00 AM to 12:00 PM

SDQ-Smart Data Quality hands-on workshop will provide participants an immersive experience to work with state-of-the-art AI system in order to explain how Artificial Intelligence, Machine Learning and Rule engine work together along with human experts to reconcile Clinical Trial data.

Part 1: Workshop User guide & Registration on SDQ platform

Monday, September 5 to Friday, September 9

During Part 1 of the workshop, participants are provided access to enter their test Clinical data into a (mock) EDC system. Participants are encouraged to create realistic examples of CRF data including sample discrepancies which the SDQ AI system will then utilize to correctly predict discrepancies.

Part 2 & 3: Live Workshop & Prediction Analysis

Sunday, September 11, 8:00 AM – 12:00 PM

During Part 2, Pfizer SMEs and our partner, Saama technologies, will conduct an overview of the AI methodology for data reconciliation along with SDQ implementation best practices. Part 3 is also a live session where the participant entered data in Part 1 is used for machine predictions which are analyzed live by Subject Matter Experts.

  1. Introduction to SDQ: Smart Data Quality has 3 components: SDQ/SMC/SPD how it all works together
  2. Methodology to analyze and onboard studies
  3. Machine Learning teach cycles
  4. Prediction Analysis

Prasanna Rao

Senior Director & Global Head of AI/ML, Pfizer

Meredith Nahm Zozus

Professor, Div. Chief, Director Clinical Research Informatics, Univ. of Texas Health Science Center San Antonio

Clinical Site Immersion

Sunday, September 11
8:00 AM to 1:00 PM

Most Data Managers have never seen a clinical investigational site. Don’t be that Data Manager!

Enrich your knowledge of clinical operations and data collection by experiencing operations at a live Clinical Research Site at the University of Texas Health Science Center at San Antonio. In this half-day workshop, attendees will tour the site and gain a greater understanding of site processes from study feasibility analysis, institutional site start-up, recruitment, study conduct and data collection.

As a participant, you will see demonstrations of site-based data systems including feasibility analysis tools, the clinical data warehouse, the site Clinical Trial Management System (CTMS), and electronic data collection from the EHR. You will work and talk with site personnel including Study Coordinators, Research Administrators, Investigators and Informaticists and to see common site information systems such as the clinical data warehouse, the site CTMS, the EHR, and EHR-to-eCRF data extraction tools.

Topics and Activities

8:00 am - 8:15 am | Welcome, Workshop logistics and Coffee
Meredith Zozus & Muayad Maallah

8:15 am - 9:15 am | How a Site Considers and Approves Participation in a Study
Muayad Maallah & Mahanaz Syed

  • Study complexity and feasibility analysis worksheet.
  • Clinical Data Warehouse Query: With expert support, you will query the eligibility criteria from your favorite trial using a cohort count tool populated with de-identified data from our health system data warehouse. You will directly experience the precision and recall of your query on a cohort feasibility tool and evaluate how many queries can be fully expressed on such tools versus needing a full data warehouse query, versus those that can’t be answered using EHR data. We will explore why and introduce a common data model to facilitate consistent execution of feasibility queries and screening lists across most sites.

9:15 am - 9:45 am | Coffee Talk: Walkthrough of our site start-up process
Jason Bates

Site start-up process walkthrough and one-page diagram covering institutional approvals, budgeting, study set-up in Velos CTMS, drug storage, sample processing, and the site Trial Master File.

10:00 am - 11:30 am | Clinic Tour and Walk-through of a Mock Study Visit
Lisa Fleming (MARC), Sara E. Espinoza (Barshop), Bill Sanns (EHR-to-eCRF)

  1. Recruitment and screening options for patients and non-patients.
  2. Consent and enrollment showing use of our site CTMS
  3. Study visit walkthrough with emphasis on source documentation.
  4. Menu of common EHR functionality used to support research and the costs.
  5. Demonstration of EHR-to-eCRF data collection.

11:30 am - 12:00 pm | Fishbowl Data Discussion with the UT Health Science Center IRB
Wanda Quezada

We will cover questions like the following as well as questions from participants:

  1. What does the commercial IRB do versus the local IRB in an industry trial?
  2. What events need to be reported to a local IRB? We’ll use ours as an example.
  3. What data-related things does an IRB care about and why?
  4. What, if any, pre-screening or screening information can be collected in a study database pre-consent?
  5. What does the IRB want every Data Manager to know?

12:00 pm - 1:00 pm | Wrap-up Discussion with UTHSA IRB, Site PIs, Study Coordinators, and Informatics
Wanda Quezada, Lisa Fleming, Sara E. Espinoza, Muayad Maallah, Bill Sanns, Mahanaz Syed, Meredith Zozus

  1. What makes a trial easy or hard to operationalize at sites?
  2. What makes data collection easy or hard for study sites?
  3. What do the Study Coordinators want every Data Manager to know?
  4. Questions from the attendees?

Topics and Activities

Data Requirements for an FDA Submission

Sunday, September 11
1:00 PM to 5:00 PM

This session will provide an overview of the requirements for submitting standardized electronic data and documents to Regulatory authorities (FDA, PMDA). We will also highlight some of the tools the FDA uses to facilitate their review and their approach to reviewing the safety and efficacy portions of a submission.

Topics will include the following:

  • Regulatory History of Submitting Standardized Electronic Data
  • CDISC Overview
  • Metadata Submission Model
    • aCRF
    • Define.XML
    • Study data Reviewers Guide
  • Technical Conformance Guide
    • Study Data Standardization Plan
    • Traceability
    • Pooling of Data
    • Coding
    • Terminology
  • PMDA Submissions
  • FDA Review Tools
  • An FDA Reviewers Approach to Clinical Review of a Submission
  • Breakout sessions with exercises

Dan Crawford

Senior Director, Veeva Systems

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