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Clinical Research Statistics for Non-Statisticians


Statistics and statistical concepts touch every point of a clinical trial – and can help you market the trial, recruit participants, apply for an FDA application, and understand the trial outcomes – but there tends to be a lack of understanding in the clinical operations field about what these concepts are, how they apply to clinical research and trials, and why it is important to have an understanding of them. The Clinical Research Statistics for Non-Statisticians symposium will discuss these statistical methods and their applications in the context of clinical operations for those that are in operations, business, and marketing, as well as those that work with clinical scientists and want to contribute more to conversations about planning and execution. Both biostatisticians and industry experts will guide you through the two-day course, providing both theory and application.


This in-depth, two-day workshop is appropriate for those new to the field as well as experts who want to gain deeper knowledge and techniques in statistical methods for the improvement of their trial planning and implementation. It will be of great value to clin ops leaders and trial managers as well as to those on the business and marketing side of clinical research. It is targeted at Pharma, Biotech, Device, Diagnostic companies and CROs developing products and designing and managing trials.

 

Tuesday, February 23

7:15 am Registration and Morning Coffee

8:25 Opening Plenary Keynotes - View Details

9:45 Grand Opening Coffee Break in the Exhibit Hall


BASIC STATISTICAL CONCEPTS

10:45 Chairperson’s Remarks

Paula Bernstein, President, Axcent Advance Analytics

10:50 Statistics for Non-Statisticians

Chetachi_Akunna_EmeremniChetachi Akunna Emeremni, Senior Principal Biostatistician, Novartis Oncology

This module provides a brief overview of basic statistical concepts, methods and applications to clinical trial design and data analysis. This module is designed to give the non-statistician a working understanding of statistical concepts with applications and examples from real clinical trials.

 

11:30 Statistical Programming Demystified

Vincent_AmoruccioVincent Amoruccio, Director, Clinical & Statistical Programming, Alexion Pharmaceuticals

Ever wonder what your statistical programmer does? How do they write programs to apply the concepts, methods, and applications identified by the statistician to source data and create the tables, listings, and figures (TLFs) submitted to regulators? This module will demystify statistical programming for not only the non-statistician, but the non-programmer.

 

CLINICAL TRIAL DESIGN

12:00 pm The How and Why of Clinical Trial Design: By the Numbers

Fang_XieFang Xie, Ph.D., Head of Global Biostatistics, CSL Behring

The design of a clinical trial is a group effort between the statistician and the operations group, an effort made easier with a deeper understanding of statistical principles that come into play during the design phase. Discover the different types of trial design, when each are used, and how the design drives the statistics used throughout the development and execution of the trial and in the final analysis and reporting of the trial.

12:35 Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own

1:20 Coffee and Dessert in the Exhibit Hall


PROTOCOL WRITING AND HYPOTHESIS TESTING

2:00 Statistical Concepts and Their Impact on Protocol Writing

Kari_KastangoKari Kastango, Director of Biostatistics, Real-World & Late Phase Research, Quintiles

A protocol originates from a desire to answer a research question. Answering a research question involves testing a hypothesis. This session will discuss how the research question and the data elements that will be collected during the study get written into the protocol and their interdependence with statistical concepts (such as sample size, effect size, power, and randomization) that are fundamental to hypothesis testing.

2:45 On the Front Line: Site Training and Its Impact on the Statistical Aspects of a Study

Kathleen_ThrushKathleen E. Thrush, MS, RD, Section Manager, Clinical Operations, Abbott Nutrition

Clinical operations professionals such as monitors and clinical research associates (CRA) are the “feet on the ground” of a clinical study. They are typically the only ones who see the true implementation of a clinical trial and have the opportunity to impact its direction. Drop outs, protocol deviations, and poor study conduct all have costly and timely implications on a clinical study. Therefore, we need to educate these individuals about site issues that can impact the statistical aspects of a study. This presentation will discuss how clinical operations professionals can recognize issues at sites and implement strategies such as risk based monitoring and centralized data review to help course correct early on to assure that the study is delivered on time and within budget.

3:20 Interactive Discussion: From the Basics to the Protocol

Kari_KastangoKari Kastango, Director of Biostatistics, Real-World & Late Phase Research, Quintiles

Kathleen E. Thrush, MS, RD, Section Manager, Clinical Operations, Abbott Nutrition

Day 1 covered a lot of ground, from basic statistical concepts through hypothesis testing and protocol writing. Ask a statistician and operations professional to:


  • Clarify concepts, from sample size to randomization
  • Elaborate on process, including where to begin and how to generate numbers
  • Frame these concepts more concretely with real-world situations

BREAKOUT DISCUSSION GROUPS

3:55 Find Your Table and Meet Your Moderator


4:00 Interactive Breakout Discussion Groups

Concurrent breakout discussion groups are interactive, guided discussions hosted by a facilitator or set of co-facilitators to discuss some of the key issues presented earlier in the day’s sessions. Delegates will join a table of interest and become an active part of the discussion at hand. To get the most out of this interactive session and format please come prepared to share examples from your work, vet some ideas with your peers, be a part of group interrogation and problem solving, and, most importantly, participate in active idea sharing.


5:00 Welcome Reception in the Exhibit Hall

6:30 Close of Day

Wednesday, February 24

7:15 am Registration and Morning Coffee


PROTOCOL DESIGN AND OPTIMIZATION IN BIOMARKER-DRIVEN TRIALS

8:25 Chairperson’s Remarks

8:30 Statistical Designs of Master Protocols and on the Design of the SWOG Lung Master Protocol (S1400; Lung-Map)

Mary_RedmanMary Redman, Ph.D., Lead Statistician, Lung Cancer Committee Southwest Oncology Group, Lead Statistician, Lung Map Trial, Fred Hutchinson Cancer Research Center

The Master Protocol concept has been around for a long time. The idea behind a master protocol is to gain efficiencies by utilizing one protocol that can be updated as new studies or objectives arise. However, the perceived utility of master protocols has been limited until recently. Genomic characterization studies conducted over the last 10 years have revealed a number of therapeutically targetable alterations, many of which have received therapeutic validation. This has led to a transformation of our standard of care approach for these patients that are now routinely molecularly genotyped in an attempt to pair the identified mutation with the appropriate targeted therapy.

The rate of potentially drug-able target identification and associated therapies is increasing and general consensus is that now is the time for master protocols to facilitate speed in development of new therapies and to bring new drugs to patients more quickly. Master protocols are often separated into two categories: umbrella protocols which evaluate multiple drugs and targets among patients with the same disease type and basket protocols which evaluate drugs/target pairs among patients defined by their genetic alternation and across disease type (so-called histology agnostic trials). However, the underlying statistical design of such studies can be broadly categorized into confirmatory and discovery-focused design.

The specific details of the design are motivated by the objectives of the study and study population. In this talk we will discuss the basic design options and possible design features for master protocols. The SWOG Lung-MAP protocol will be used to motivate the different decision points and trade-offs between different designs.

9:10 Design and Analysis of Biomarker-Driven Clinical Trials

Robert_BigelowRobert Bigelow, Ph.D., Associate Director, CT Statistics, Duke Clinical Research Institute

Biomarkers can be useful in disease prognosis and prediction of treatment outcome, giving physicians the ability to more precisely tailor the therapeutic approach to individual patients. While a biomarker may have a plausible biological mechanism, demonstration of its prognostic and predictive accuracy poses numerous statistical challenges, including appropriate use of randomization, multiplicity, stratification and statistical interaction and use of surrogate endpoints.

This session presents design strategies in biomarker-driven studies.

9:50 Interactive Discussion: Statistical Concepts for Biomarker-Driven Trials

Topics to be discussed include but are not limited to the following:

  • Broadly speaking these designs can be classified as either confirmatory or discovery-based
  • The overall goal of the trial determines the design
  • The relative merits and trade-offs for different designs

10:10 Coffee Break in the Exhibit Hall


Clinical Trial Execution BY THE NUMBERS

11:10 Chairperson’s Remarks

Paula Bernstein, President, Axcent Advance Analytics

11:15 Study Execution Issues and Their Impact on Analysis and Interpretation of Results

Kari_KastangoKari Kastango, Director Biostatistics, Real-World & Late Phase Research, Quintiles

Execution of a clinical trial may not always go as planned. Protocol amendments, incorrect treatment allocation by the site, protocol violations and missing data due to a variety of reasons are just a few things that can arise during the conduct of the study. This session will discuss the impact these topics have on the analysis of the data and the interpretation of the results and why it is important to communicate with the clinical trial statistician during the course of the clinical trial and not wait until just before database lock.

11:35 Trial Execution by the Numbers: Understanding the Impact of Protocol Amendments, Site Issues, and Other Study Execution Issues on Trial Enrollment and Analysis


Mike_LonettoMike Lonetto, Associate Director, Senior Application Architect, Novartis

There are many risks in clinical trial execution, including changes due to protocol amendments as well as uncertainty due to site issues, patient enrollment, and retention and event rates. This session will explore applications of probability and statistics to understanding and dealing with uncertainty in clinical operation parameters. Topics include understanding uncertainty in patient accrual, and retention, and how these can impact analysis plans.

11:55 Interactive Discussion: Statistical Pain Points in Clinical Trial Execution and Analysis

Kari_KastangoKari Kastango, Director Biostatistics, Real-World & Late Phase Research, Quintiles


Mike_LonettoMike Lonetto, Associate Director, Senior Application Architect, Novartis


Ask your most burning questions of our presenters in this interactive Q&A session. Possible topics include:

  • In-depth explanation of how data is analyzed by a statistician
  • A closer look at probability and how it is calculated
  • Real-world scenarios of how a statistical and operations team successfully worked together – or lessons learned from when it did not

12:10 pm Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own

12:50 Coffee and Dessert in the Exhibit Hall

1:30 Plenary Keynotes - View Details

3:00 Refreshment Break in the Exhibit Hall (Last Chance for Viewing)

Post-Trial Data Flow

4:00 Post-Trial Information Flow: Direct and Indirect Estimation of Relative Effect to Support Reimbursement

Sarah_GoringSarah Goring, MSc, Director, Epidemiology, ICON plc.

Health technology assessment agencies recommend using meta-analysis or network meta-analysis to synthesize evidence of efficacy and safety from medicinal products across the therapeutic space. This presentation will provide an overview of this approach and will highlight considerations at the clinical trial design stage that can support a strong and statistically robust analysis and obviate challenges in downstream evidence synthesis.

4:30 Post Lock Data Flow: From CRF to the FDA

Ben_VaughnBen Vaughn, MS, RAC, Senior Statistical Scientist, Rho, Inc.

This presentation will cover the various manipulations to patient data to prepare it for analysis, tabulation, and submission to the FDA.Learn what CDASH, SDTM and ADaM mean to a study and how they fit into project timelines. Approaches to legacy data and the impact of the new electronic data submission guidance will be discussed.

5:00 Post-Trial Information Flow: Integrated Summaries of Effectiveness and Safety Data to Support Marketing Authorization

Kenneth_KouryKenneth Koury, Ph.D., Executive Director, Clinical Biostatistics, Merck Research Laboratories

This presentation will describe the integrated summaries of effectiveness and safety data, which synthesize results across the entire clinical development program using data from individual trials, and their importance in the FDA review process. These comprehensive analyses are used to support statements in the proposed product label, including describing differences across important sub-populations. Consequently, they provide the basis for obtaining the desired product label and ultimately achieving commercial success.

5:25 Interactive Discussion: What Happens Next?

Ben_VaughnBen Vaughn, MS, RAC, Senior Statistical Scientist, Rho, Inc.


Kenneth_KouryKenneth Koury, Ph.D., Executive Director, Clinical Biostatistics, Merck Research Laboratories


Sarah_GoringSarah Goring, MSc, Director, Epidemiology, ICON plc.

From an operational standpoint, running a smooth trial with as few delays and errors as possible is the main goal, but what happens after the trial wraps should be part of the initial planning stage. Ask these professionals your most pressing post-trial data questions, on topics such as:


  • Elaboration on FDA forms and processes
  • Translating data and analyses for the business and marketing professional
  • Incorporating trial data into global reimbursement submissions

5:45 Close of Symposium

Thursday, February 25

Join Thursday conference sessions at SCOPE:

 

 

Who Should Attend:
  • Clinical Operations
  • Trial Managers, Product Managers
  • Clinical Data Managers
  • Biostatistics, Statistics, Statistical Programming
  • Protocol Development, Protocol Writing, Medical Writing
  • Clinical Scientists, Clinical R&D
  • Medical Affairs, Commercial
  • Project Managers, Clinical Project Managers
  • Business Development, Sales, Marketing