DIA 2017 Annual Meeting

Component Type: Session
Level: Intermediate
CE: CME 1.25; IACET 1.25; RN 1.25

In this session, you will hear case studies in leveraging big data/real-world data in clinical development. The case studies include an industry perspective on how one biopharmaceutical company generated significant incremental value out of the data investments the company has already made in other areas, with appropriate data governance, a leading vendor’s perspective on an end-to-end value proposition of using real world data from clinical strategy to product launch, and best practices, challenges, and opportunities of leveraging claims and EHR data from the perspective of a non-profit organization affiliated with a national health ministry.

Learning Objectives

Describe the full potential of existing datasets within the organization with appropriate data governance; Discuss opportunities and challenges with leveraging big data/ real world data for clinical trial design, optimizing planning and recruitment, mitigating against avoidable delays and costs, and segmenting for market launches.

Chair

Crystal Ancona, MS

Speaker

Big Data: Unleashing the Full Potential of Big Data to Make the Buzzword Tangible
Crystal Ancona, MS

From Trial to Launch: Closing the Innovation Loop and Designing Smarter Trials with Real World Evidence
Andrew Cassel

Big Data Utilization Experience in Clinical Trial Feasibility
Kelly Han

Component Type: Session
Level: Intermediate
CE: CME 1.25; IACET 1.25; RN 1.25

This session will describe the current state and evolution of data standards.

Learning Objectives

Discuss the status of required study data standards, as well as other data standards initiatives; Summarize FDA's efforts to develop, test, and support therapeutic area data standards; Describe FDA's participation in and status of international data standards initiatives.

Chair

Ron D. Fitzmartin, PhD, MBA

Speaker

Impact of the Binding Guidance for Standardized Study Data Internally at the FDA
Vaishali Popat, MD, MPH

CDASH v2.0: Whats New and What Does it Mean for Me?
Dawn Marie Kaminski

CDISC Standards for Regulatory Submissions
Lauren Becnel

Metadata Driven Data Operations: What is it and How Can it Transform Traditional Clinical Data Management/Analysis/Reporting
Michael Goedde

Component Type: Session
Level: Intermediate
CE: CME 1.00; IACET 1.00; RN 1.00

In 2018, EU General Data Privacy Requirements (GDPR) will extend scope of EU data protection law to all foreign companies processing data of EU residents. For pharma companies, CROs, and others involved in the clinical development process, violations of the new regulation can result in fines up to $10 million Euros or 2% of the organization's worldwide revenue. The US and the EU have entered into a vexed relationship regarding data protection and privacy, Privacy Shield. The panel will discuss current privacy regulations in the US and how the GDPR relates to US privacy initiatives, including HIPAA and ONC regulations and proposed legislation in the US Congress.

Learning Objectives

Discuss EU GDPR; Describe the US government privacy and data protection requirements; Discuss issues related to these two frameworks for protecting PII.

Chair

Peter S. Alterman, PhD

Speaker

The €10 Million Penalty: Are You Ready for EU's New PII Regulation?
Peter S. Alterman, PhD

Data Protections, Data Directives, and Clinical Trial Data: How Can I Collect and Use My Global Clinical Trial Data?
Jonathan Andrus, MS

Emerging Technologies Coupled With the Ever Increasing Globalization of Data and Information Demand New Ways to Discuss and Protect Personal Information
Debra N. Diener, JD, MA

Component Type: Session
Level: Intermediate
CE: CME 1.25; IACET 1.25; RN 1.25

This session will cover scalable and expandable big data infrastructures; cloud, outsourcing, and remote monitoring.

Learning Objectives

Discuss how big data and new technology can be used to enhance patient experience, manage outcomes, and enhance research.

Chair

David Kiger

Speaker

Obtaining Better Outcomes with Unstructured/Structured Data; How to Improve Clinical, Regulatory, and Commercial Convergence
David Kiger

Generating Meaningful Clinical Evidence from Electronic Health Record Data: Oncology as a Case Study
Amy Abernethy, MD, PhD

Shouldn’t Patient Registries Be Attractive to Patients? Implementing Thoughtful Technology for Richer Data
Mildred Menos, MA

Component Type: Session

In the not too distant future, we as an industry will execute, manage and monitor clinical trials the same way we execute, manage and monitor banking transactions online, quickly and without the need to maintain paper records. However, as we bring new and innovative technology solutions to the market, we must assess and address the concerns of all of the stakeholders within the clinical trial enterprise. We need to assure patients, clinical research sites, pharmaceutical and device companies, as well as regulators, that there will be improved efficiencies, improved data quality and integrity, improved patient safety, reduced fraud and an overall better experience during the clinical trial process. Topics to be addressed include clinical site acceptance, regulatory concerns, software validation, risk assessments, change management within companies, and a comprehensive assessments of the risks and rewards.

Chair

Jules T Mitchel, PhD, MBA

Component Type: Session
Level: Intermediate
CE: CME 1.00; IACET 1.00; RN 1.00

This session will focus on the status of health informatics at the FDA. Topics will include data standards for health care and clinical research, as well as use of EDC and EHRs in clinical research.

Learning Objectives

Explain the Health IT activities at the FDA; Discuss the use of Health IT systems in clinical research; Discuss the results of one of the FDA-led initiatives focusing on the use of EHRs and other types of eSource in clinical investigations.

Chair

Mitra Rocca, MSc

Speaker

Health Information Technology at FDA
Mitra Rocca, MSc

Structured Sourcing of Clinical Data from EHRs
Adam L Asare, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-17-511-L04-P; CME 1.25; IACET 1.25; RN 1.25

Using big data to identify correlations and determinants of disease or to predict response to therapy.

Learning Objectives

Describe challenges and opportunities of using big data to achieve more precise modeling of complex diseases.

Chair

Arpit Dave, MS

Speaker

Conundrum of Analytics in R&D: How to Drive Science by Leveraging Data
Arpit Dave, MS

The Path from Big Data to Precision Medicine: Leveraging Population Analytics to Prevent, Intercept, and Cure Complex Disease
Bevan Emma Huang, PhD

Connected Health Ecosystem: Practice Application of Precision Medicine
Michael Mentesana, MA

Component Type: Session
Level: Intermediate
CE: CME 1.25; IACET 1.25; RN 1.25

This session will discuss data quality in the light of risk-based methodologies: data fit for purpose, appropriate risk treatment, and quality by design.

Learning Objectives

Discuss if and how the approach to data quality has evolved with the adoption of risk-based methodologies.

Chair

Teresa Ancukiewicz, MA

Speaker

A Quality by Design Approach to Data Quality
Erik Doffagne, MS

Going Beyond Data Collection to Ensure Data Quality
Kenneth Stoltzfus

Model Data Management Plan
Scott Brand, PhD

Component Type: Session
Level: Basic
CE: CME 1.00; IACET 1.00; RN 1.00

This session will discuss how research is done using tools remotely to minimize patient visits and allow much broader accessibility to clinical research as well as additional types of information being generated - wearables and apps.

Learning Objectives

Discuss the support structure necessary for combining traditional clinical research with emerging technologies.

Chair

Jonathan Solomon Helfgott, MS

Speaker

Getting Down to the Nitty-Gritty: Addressing the Specific Challenges of Electronic Data and Mobile Devices in Clinical Trials
Jennifer Goldsack, MBA

How Will Wearables and Biosensors Transform Clinical Trials?
Scott Weidley

My Fitbit Heart Rate Data is Clinical Trial Grade, Right?
Keith W. Wenzel

Component Type: Session
Level: Intermediate
CE: CME 1.25; IACET 1.25; RN 1.25

This session will cover rare data, postmarketing, leveraging RWE, data sharing, open access, identifying cohorts for clinical trials, interoperability, differing standards, and submission considerations.

Learning Objectives

Identify the potential of combining various types of studies and requirements to make it a success

Chair

Michael J Pencina, PhD

Speaker

Supporting Open Access to Clinical Trials Data for Researchers: Challenges and Learnings
Michael J Pencina, PhD

Synthetic Control Arms: A Scientific Alternative to Historical Controls
Michael R. Elashoff, PhD

Panelist
Abel Kho

Component Type: Session
Level: Intermediate
CE: CME 1.25; IACET 1.25; RN 1.25

Includes predictive analytics, what do we do with it, cleaning it.

Learning Objectives

Identify how to use big data analytics to develop new insights from patient data.

Chair

David Olaleye

Speaker

Big Data Analytics to Historical Cancer Research Data: Project Data Sphere Oncology Data-Sharing Experiment
David Olaleye

Indication Expansion and Drug Positioning: Opportunities for Translational Sciences
Lun Yang, PhD

Project Data Sphere: Building a Data Sharing Platform and Research Community to Advance Cancer Treatment
Dave Handelsman

Component Type: Session
Level: Intermediate
CE: CME 1.25; IACET 1.25; RN 1.25

Real-life challenges and lessons learned. Impact on traditional roles, new opportunities, cross-functional collaboration, identifying data trends and issues.

Learning Objectives

Define key challenges in RBM implementation; Describe how processes and roles need to change in the organization to support the RBM; Demonstrate how results from analytics can be turned into actionable items to mitigate risks.

Chair

Mary Arnould, BSN, MSN

Speaker

Five Years of Global Risk-Based Monitoring Implementation: Where We’ve Been and Where We’re Going - Best Practices and Lessons Learned
Mary Arnould, BSN, MSN

Risk-Based Monitoring Centralized Monitoring: What's Needed to be Effective?
Stephen Young, MSc

The Evolving Area of Central Monitoring: What is it? What Data is Being Reviewed? Who is Responsible?
Keith Dorricott