DIA 2018 Global Annual Meeting

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-533-L04-P; CME 1.25; IACET 1.25; RN 1.25

The use of historical controls in clinical trials may be an alternative method to assess the efficacy of a new drug. Challenges that arise from the use of historical controls, as well as methods for overcoming those challenges, will be discussed.

Learning Objectives

Determine whether the use of a historical control is Determine whether the use of a historical control is appropriate for their clinical trial design; Discuss how to analyze endpoints and interpret results from clinical trials that use a historical control.

Chair

Sara Jimenez, PhD

Speaker

Efforts to Combine Data Across Companies
Edward Bowen

Using Historical Data to Transform Clinical Trials: Statistical Considerations
Jessica Lim, MA

Converging Lines of Evidence: Using Modern Structural Meta-analysis to Advance Multisite Knowledge Discovery - A Case Study
Andrew Wilson, PhD, MS

Component Type: Session
Level: Advanced
CE: ACPE 1.25 Application UAN: 0286-0000-18-551-L04-P; CME 1.25; IACET 1.25; RN 1.25

The use of historical data demonstrates value and efficiency in designing clinical trials, especially in nonconfirmatory trials. This session presents an overview of theoretical framework, case studies in exploratory situations, and future directions.

Learning Objectives

Describe the use of historical information on controls in rare disease and pediatric settings; Discuss the challenges and concerns in design of confirmatory trials; Analyze industry and regulatory point of view and potentially pilot solutions.

Chair

Fei Wang, PhD

Speaker

Incorporating Adult Study Data into Pediatric Clinical Trials: Is Bayesian Borrowing the Solution?
James Travis, PhD

Approaches to Medical Device Evaluation Using Real-World Evidence
Sharon-Lise Normand

Bayesian Applications for Extrapolation from Adult to Pediatric Data
Amy Xia, PhD

Component Type: Session
Level: Advanced
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-568-L04-P; CME 1.25; IACET 1.25; RN 1.25

This session will highlight some of the new drugs approved in the last few years for rare disease and the statistical approaches used. Regulatory, industry and patient perspectives will be shared and approaches proposed that are realistic based upon needs of patients and scientific rigor necessary. Additionally, for drugs approved where there were significant differences of opinion, regulatory, industry, and patient perspectives will be shared on experience of these marketed products post-approval and whether post-marketing studies supported the treatment to be efficacious and safe.

Learning Objectives

Identify approaches to design and analyze data for studies for developing new medical products for rare diseases; Describe how use of historical controls can help show therapeutic benefit in rare diseases.

Chair

Munish Mehra, PhD

Speaker

The Use of Historical Controls From Register Data in Randomized Clinical Trials in Rare Diseases
Paolo Morelli

Challenges and Strategies: Cases Studies for Pediatric Rare Disease Clinical Trials
Yeh-Fong Chen, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-585-L04-P; CME 1.25; IACET 1.25; RN 1.25

This session will present statistical methods for analyzing adverse events with a focus on time to occurrence of the first adverse event. Speakers will discuss practical implications of the analysis of AE data in clinical trials and give illustrative examples. The topic of competing risks (e.g., non-event-related death) that preclude the observation of the event of interest will be discussed and two methodologies will be proposed.

Learning Objectives

Discuss current problems and solutions for analysis of time-to-event data; Identify new insights and a novel approach for the analysis of drug safety data with the presence of competing risks; Describe extensions to efficacy endpoints.

Chair

Brenda Crowe, PhD

Speaker

The Challenges of Analyzing Drug Safety Data with Competing Risk Events and Some Thoughts
William Wang, PhD

Academic Perspective
Tim Friede

Component Type: Session
Level: Basic
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-601-L04-P; CME 1.25; IACET 1.25; RN 1.25

This session will describe some novel tools for study planning an analysis. It will include use of open-source tools such as R and Shiny to plan, organize and execute the reporting of clinical trial data. Speakers will also show examples of self-service interactive visual tools that can be used during study design period.

Learning Objectives

Describe and demonstrate a novel report analysis plan process that uses using modern R/Shiny/Markdown technology to plan, execute and report clinical trial data; Identify examples of reusable self-service tools and show that they can help improve operational efficiency and communication.

Chair

Brenda Crowe, PhD

Speaker

ShinyRAP: A Workflow for Analysis Planning, Organization, and Reporting Using Shiny
Xiao Ni, PhD

Empower Your Physicians and Enhance Communication Via Self-Service Tools
Rebeka Revis, MS

R Shiny Review Tools
Jonathon J. Vallejo, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-619-L04-P; CME 1.25; IACET 1.25; RN 1.25

Under PDUFA VI, FDA committed to developing two pilot programs. The goal of the Complex Innovative Designs (CID) pilot is to facilitate the advancement and use of complex, Bayesian, and other novel clinical trial designs and will focus on highly innovative trial designs for which analytically derived properties (e.g., Type I error) may not be feasible, and simulations are necessary to determine trial operating characteristics. The Model-Informed Drug Development (MIDD) pilot is intended to facilitate the development and application of exposure-based and biological models derived from preclinical and clinical data sources. Drug development programs where clinical data are limited such that integration across non-traditional sources may be needed as well as programs for which MIDD can assess uncertainties about dosing, duration, patient selection, and other factors will be considered for the pilot. In this session, we will discuss the importance of these two PDUFA VI pilot programs, explain the agency’s goals for these programs, and highlight the difference between these two pilot programs.
Three speakers from FDA are invited to share their expectations and visions for these programs which launch in 2018.

Learning Objectives

Discuss the importance of these two PDUFA VI pilot programs; Explain the agency’s goals for these programs: Identify the difference between these two pilot programs.

Chair

Yeh-Fong Chen, PhD

Speaker

Panelist
Laura Lee Johnson, PhD

Panelist
Issam Zineh, PharmD, MPH

Panelist
Dionne Price, PhD

Panelist
Xun Chen, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-635-L04-P; CME 1.25; IACET 1.25; RN 1.25

Drug development has been facing both opportunities and challenges. On one hand, a variety of discovery technologies have helped drive growth in the drug development pipeline. On the other hand, the biopharmaceutical industry has had to manage a challenging operating environment characterized by increasing costs, inefficient and lengthy cycle times, and high levels of risk, uncertainty, and complexity. More efficient and innovative study designs have the great potential of improving success rates and optimizing clinical trial performance and data quality.
This session will review and discuss opportunities for efficient and innovative study designs with some real world examples in the areas of effective and efficient phase 2 study design, leveraging natural history data for rare diseases drug development, and use of innovative Bayesian designs for non-inferiority studies.

Learning Objectives

Evaluate case studies in efficient and innovative study designs; Discuss challenges and opportunities in innovative designs and analyses.

Chair

Amy Xia, PhD

Speaker

Understanding the Special Importance of Phase 2 Clinical Studies
Ron Marks, PhD

Leveraging Natural History Data for Rare Diseases Drug Development: A Bayesian Perspective
Shu Han, PhD, MBA

A Bayesian Approach in the Non-Inferiority Setting
Cristiana Mayer, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-652-L04-P; CME 1.25; IACET 1.25; RN 1.25

Given the volume of data to review and the variety of analyses to perform, it should come as no surprise that clear insight is often out of reach. In this environment, the traditional means of data summary – tables and listings – are ineffective; visualization is the key to effective communication for the modern age. Ben Shneiderman stated that “the purpose of visualization is insight.” Therefore, the goal of this session is to describe innovative data visualization techniques to aid in the understanding and communication of results from applications in the life sciences.

Learning Objectives

Describe the transition from traditional methods of data analysis to visual approaches; Explain and interpret life science data using one or more data visualizations; Assess the strengths and limitations of various graphical techniques; Appraise the “data story” of numerous examples.

Chair

Richard Zink, PhD

Speaker

Understanding Our Brain’s Graphical Superpowers Leads to Amazing Data Interpretation
Susan Duke, MSc

Data-Driven Interactive Treatment Pathway Visualization
Sharon Hensley Alford, PhD, MPH

Understanding the Individual Contributions to Multivariate Outliers in Assessments of Data Quality
Richard Zink, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-672-L04-P; CME 1.25; IACET 1.25; RN 1.25

This session will provide a platform for researchers to discuss the challenges and issues they faced, share the lessons they learned, and offer possible strategies for future development programs in assessing drug's efficacy by utilizing biomarkers.

Learning Objectives

Discuss the issues and challenges facing future development programs in assessing drug's efficacy by utilizing biomarker endpoints and develop possible strategies.

Chair

Min Min, PhD

Speaker

Individualized Treatment Recommendation Through Machine Learning Algorithms
Brenda Crowe, PhD

Validation of Biomarkers as a Surrogate for Clinical Endpoints: The Global PBC Experience
Bettina Hansen, PhD, MSc

Evidentiary Considerations of Integration of Biomarkers in Drug Development
Aloka Chakravarty, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-686-L04-P; CME 1.25; IACET 1.25; RN 1.25

Regulators expect drug makers to conduct novel studies to provide treatment effectiveness results that are valid in everyday clinical practice. This session will present opportunities and challenges in pragmatic trials to generate real-world insights.

Learning Objectives

Discuss the usefulness of pragmatic clinical trials to support regulatory decision making and shortening drug approval time; Describe how pragmatic trials offer avenue to obtain real-world data to support comparative effectiveness research; Describe design and statistical considerations for pragmatic trials to produce acceptable, valid, precise, and generalizable results.

Chair

Yeh-Fong Chen, PhD

Speaker

Design and Statistical Considerations in Real-World Evidence
Jennifer Hsiang-Ling Lin, PhD

Pragmatic Clinical Trials: The Future is Now
David Thompson, PhD

Component Type: Workshop
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-695-L04-P; CME 1.25; IACET 1.25; RN 1.25

This workshop will present the evidence from the scientific literature and existing patient registry data on the degree of correlation between PROs and ClinROs, and how this correlation varies by disease, symptom presence, frequency, and severity.

Learning Objectives

Classify the degree of correlation between patient reported outcomes (PROs) and clinician reported outcomes (ClinROs), as it relates to disease/therapeutic area and measure: symptom presence, frequency and severity; Interpret the degree of correlation as expressed by various psychometric statistics.

Chair

Eric Gemmen, MA

Speaker

Facilitator
Jing Zhang

Facilitator
Xun Chen, PhD