DIA Global Center: Washington, DC, USA | Basel, Switzerland | Beijing, China Horsham, PA, USA | Mumbai, India | Tokyo, Japan

800 Enterprise Road Suite 200 Horsham, PA 19044 USA

KEYNOTE SPEAKERS:

Frank F. Weichold, MD, PhDDirectorOffice of Critical Path and Regulatory Science InitiativesOffice of the Chief Scientist and Office of the CommissionerFDA

Benjamin HeywoodPresident and Co-founderPatientsLikeMe Inc.

OVERVIEW:

Now in its ninth year, the DIA/FDA Statistic Forum fosters open discussion of timely topics of mutual theoretical and practical interest to statisticians and clinical trialists who develop new drugs and biologics. This unique forum continues the dialogue on issues including FDA guidance development and regulatory science initiatives.

You will have the opportunity to focus on statistical opportunities and challenges associated with data standards and innovative approaches to the design, monitoring, analysis and reporting of clinical trials and assessments of safety and effectiveness in the pre- and post-market settings.

WHAT YOU WILL LEARN:

• Key topics relevant to the evaluation of therapeutic products

• Input from key thought leaders from regulatory agencies, industry, and academia

• Regulatory and statistical solutions associated with innovative approaches to the design and analysis of clinical trials data

• Examine your role in these changes and improvements to help develop appropriate, scientific/regulatory consensus.

At the conclusion of this forum, participants should be able to:

• Recognize innovative statistical solutions to issues associated with the evidence and regulatory review of medical products

• Describe the application of statistical methodologies including the thinking to the development of new medical products

• Assess the impact of regulations and guidance on statistical practice

• Discuss ideas for improving the communication between industry Statisticians and Reviewers

As of April 16, 2015

PROGRAM CO-CHAIRS:

Ram C. Tiwari, PhDAssociate DirectorOffice of BiostatisticsOffice of Translational ScienceCDER, FDA

Joan Buenconsejo, PhDStatistics Team Leader Inflammation, Neuroscience, Respiratory TA, Biometrics and Information SciencesAstraZenecaChair, North American DIA Statistics Community

STEERING COMMITTEE:

Frank Bretz, PhDGlobal Head of Statistical MethodologyNovartis Pharma AG, Switzerland

Brenda Crowe, PhDSenior Research AdvisorGlobal Statistical SciencesEli Lilly and Company

Jeff Maca, PhDSenior DirectorCenter for Statistics in Drug Development InnovationQuintiles

Laura Meyerson, PhDVice PresidentBiometrics, Data Management and Medical Writing (BDMW)Biogen Idec, Inc.

Walter W. Offen, PhDGlobal Head of Statistical InnovationData and Statistical SciencesAbbVie

Estelle Russek-Cohen, PhDDivision DirectorDivision of BiostatisticsCBER, FDA

Jerald S. Schindler, DrPHVice PresidentBiostatistics and Research Decision SciencesMerck Research LaboratoriesChair, Global DIA Statistics Community

Stephen E. Wilson, DrPH, CAPT, USPHSDirectorDivision of Biometrics IIIOffice of Biostatistics, OTSCDER, FDA

Peiling Yang, PhDTeam LeadDivision of Biometrics I, Office of BiostatisticsOffice of Translational ScienceCDER, FDA

SPECIAL ADVISOR:

Lisa M. LaVange, PhDDirectorOffice of Biostatistics, Office of Translational ScienceCDER, FDA

DIA/FDA Statistics Forum 2015Tutorials: April 19 | Forum: April 20-22

Bethesda North Marriott Hotel and Conference Center North Bethesda, MD

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CONTINUING EDUCATION

DIA has been accredited as an Authorized Provider by the International Association for Continuing Education and Training (IACET).

As an IACET Authorized Provider, DIA offers CEUs for its programs that qualify under the ANSI/IACET Standard. DIA is authorized by IACET to offer up to 2.5 CEUs for this program. Participants must attend the entire program < tutorials, meeting, if applicable> in order to be able to receive an IACET statement of credit. No partial credit will be awarded.

If you would like to receive a statement of credit, you must attend the tutorial(s), if applicable, and/or meeting, sign in each day at the DIA registration desk, and complete the online credit request process through My Transcript. To access My Transcript, please go to www.DIAGlobal.org, select “Login to My DIA” and you will be prompted for your user ID and password. Select “My Transcript” (left side bar) and “Credit Request” to process your credit request. Participants will be able to download a statement of credit upon successful submission of the credit request. My Transcript will be available for credit requests on Wednesday, May 6, 2015.

It is DIA’s policy that anyone in a position to control the content of a continuing education activity must disclose to the program audience (1) any real or apparent conflict(s) of interest related to the content of their presentation and/or the educational activity, and (2) discussions of unlabeled or unapproved uses of drugs or medical devices. Faculty disclosures will be included in the course materials.

CONTINUING EDUCATION CREDIT ALLOCATION

TUTORIALS:

• Statisticians as Leaders: IACET .3 CEUs • Propensity Score Methodology Application to Observational Comparative Studies in Regulatory Settings: IACET .3 CEUs• Subgroup Analysis in Clinical Trials: IACET .3 CEUs• Dose Finding in Drug Development: Methods and Implementation: IACET .3 CEUs

MEETING:

DIA/FDA Statistics 2015 Forum: IACET 1.9 CEUs

Unless otherwise disclosed, the statements made by speakers represent their own opinions and not necessarily those of the organization they represent, or that of DIA. Speakers, agenda, and CE information are subject to change without notice. Recording of any DIA educational material in any type of media, is prohibited without prior written consent from DIA.

View DIA’s Grievance Policy, at www.DIAGlobal.org/CE.

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DIA’S CERTIFICATE PROGRAM This program is part of DIA’s Certificate Program and is awarded the following:

• Clinical Research Certificate Program: 12 Elective Units

• Clinical Safety and Pharmacovigilance Certificate Program: 4 Elective Units

• Regulatory Affairs Certificate Program: 12 Elective Units

For more information go to www.DIAGlobal.org/certificateprograms

TO ACCESS PRESENTATIONS:• Visit DIAGlobal.org

• Login to My DIA

• Enter your User ID and Password

• View ‘My Presentation Downloads’

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SUNDAY, APRIL 19

9:00am-12:00pm TUTORIALS

Tutorial #1: Statisticians as Leaders

INSTRUCTORS:

Lisa M. LaVange, PhDDirectorOffice of Biostatistics, Office of Translational ScienceCDER, FDA

Jerald S. Schindler, DrPHVice PresidentBiostatistics and Research Decision SciencesMerck Research LaboratoriesChair, Global DIA Statistics Community

Over the past few years, the rapid increase of data from many sources and the near real time availability of these data have created a need for those knowledgeable in quantitative sciences and information technology. This, in turn, has created an increased urgency for those with quantitative and statistical skills to guide their organizations in the efficient use of statistical methods for drug development. The result is a new and evolving opportunity for statisticians to be out front and provide leadership for their organizations.

This half-day tutorial will provide a perspective on the development of leadership skills and the changing roles of statisticians in drug development. Through a combination of presentations, discussion, and personal recollections, the instructors will provide a framework for discussion of the leadership opportunity and present potential techniques that can be put into practice. The tutorial is aimed at all statisticians working in drug development. Leadership will be broadly defined as creating a vision, setting a course, and influencing colleagues in other disciplines as well as direct line management.

LEARNING OBJECTIVES:

At the conclusion of this tutorial, participants should be able to:

• Describe specific leadership opportunities for statisticians involved in drug development

• Discuss successful strategies for implementing leadership behavior and influencing others

• Discuss both successful and unsuccessful leadership experiences including providing a framework for each individual to evaluate their own opportunities for leadership

TARGET AUDIENCE:

• All statisticians involved in drug development. The tutorial is aimed at those early in their careers and also at those who have established careers. The intention of the course is to provide a thought-provoking experience that will help each individual consider expanding beyond their current role into a leadership position.

Tutorial #2: Propensity Score Methodology Application to Observational Comparative Studies in Regulatory Settings

INSTRUCTORS:

Lilly Yue, PhDDeputy DirectorDivision of Biostatistics CDRH, FDA

Diqiong (Joan) Xie, PhDMathematical StatisticianDivision of Biometrics VIIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Well-controlled and conducted randomized clinical trials (RCT) are viewed as the gold standard in the safety and effectiveness evaluation of medical products, including drugs, biological products and medical devices. Observational (non-randomized) comparative studies also play an important role in medical product evaluation, due to ethical or practical reasons, in both pre-market and post-market regulatory settings. However, various biases could be introduced at every stage and into every aspect of the observational study, and adversely impact the interpretation of the study results. Among existing statistical techniques for addressing some of the challenging issues, propensity score methodology is one increasingly used in regulatory settings, due to its unique future of separating “study design” and “outcome analysis”.

This tutorial will introduce the causal inference framework and propensity score methods (e.g. matching, stratification, and weighting), and highlight the principle and importance of prospective design of observational comparative studies to increase the integrity and the interpretability of outcome analysis results. Practical issues encountered in the application of the methodology in the regulatory settings will be presented, including but not limited to: study design process in regulatory submissions, specification of treatment effects of interest in treatment comparisons (average treatment effect (ATE) or average treatment effect on the treated (ATT), covariate identification and inclusion, control group selection/formation (a concurrent control, historical control or a control group extracted from national/international registry), sample size and power consideration. Some differences for implementing propensity score methodology will be delineated for studies with different purposes, for regulatory submissions or general comparative effectiveness research. For example, exclusion of treated patients with an investigational product should be discouraged in studies aimed at pre-market regulatory submissions. These topics will be illustrated with examples based on regulatory review experience.

LEARNING OBJECTIVES:

TBD

TARGET AUDIENCE:

TBD

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1:30-4:30pm TUTORIALS

Tutorial #3: Subgroup Analysis in Clinical Trials

INSTRUCTORS:

Alex Dmitrienko, PhDExecutive DirectorCenter for Statistics in Drug DevelopmentQuintiles Inc.

Ilya Lipkovich, PhD Senior DirectorCenter for Statistics in Drug Development, InnovationQuintiles Inc.

This half-day tutorial focuses on a broad class of statistical problems arising in subgroup analysis. The first part of the course deals with exploratory subgroup analysis, i.e., subgroup search/identification methods that can be applied in late-phase clinical trials. The discussion of exploratory subgroup analysis begins with an overview of recent approaches to subgroup identification in the context of personalized medicine. These approaches fall in the four subtypes: global modeling of the outcome function, direct modeling of treatment contrast, identifying optimal treatment regimes, and direct subgroup search. The overview will be followed by a detailed review of the SIDES method (Subgroup Identification based on Differential Effect Search) introduced in Lipkovich et al. (2011), Lipkovich and Dmitrienko (2014, 2015). SIDES is based on recursive partitioning and can be used in prospective and retrospective subgroup analysis. Key elements of SIDES will be discussed, including generation of multiple promising subgroups based on different splitting criteria, choice of optimal values of complexity parameters via cross-validation, evaluation of variable importance and using variable importance indices for pre-screening covariates, and addressing Type I error rate inflation using a resampling-based method.

The second part focuses on the issues related to confirmatory subgroup analysis, i.e., analysis of pre-specified subgroups in the context of confirmatory Phase III clinical trials. This will include a summary of general principles of confirmatory subgroup analysis (interpretation of findings in several patient populations based on the influence and interaction conditions) introduced in Millen at el. (2012, 2014) and Dmitrienko, Millen and Lipkovich (2015). In addition, a review and comparison of multiplicity adjustment methods used in confirmatory subgroup analysis will be provided, including non-parametric and parametric procedures (Dmitrienko et al., 2009; Dmitrienko, D’Agostino and Huque, 2013).

Multiple case studies will be used to illustrate the principles and statistical methods introduced in this course, including design and analysis of Phase III trials with target subgroups and biomarker discovery in Phase III development programs. Software tools for implementing the subgroup analysis methods in clinical trials will be presented, including the SIDES package developed by the authors.

LEARNING OBJECTIVES:

At the conclusion of this tutorial, participants should be able to:

• Define statistical methods for analyzing subgroup effects in exploratory and confirmatory settings and describe their properties

• Identify the factors to consider in selecting appropriate statistical methods in exploratory and confirmatory subgroup analysis

• Discuss relevant regulatory considerations that affect the choice of subgroup analysis methods

• Apply the statistical methods discussed in the course using statistical software (Excel and R)

TARGET AUDIENCE:

The tutorial is designed mainly for statisticians working in the pharmaceutical or biotechnology industries as well as contract research organizations. It is equally beneficial to statisticians working in institutions that deliver health care and government branches that conduct health-care related research. The attendees are required to have basic knowledge of clinical trials.

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Tutorial #4: Dose Finding in Drug Development: Methods and Implementation

INSTRUCTORS:

Frank Bretz, PhDGlobal Head of Statistical MethodologyNovartis Pharma AG, Switzerland

Jose C. Pinheiro, PhDSenior DirectorQuantitative Decision StrategiesJanssen Research & Development, LLC

Björn Bornkamp, PhD, MScExpert Statistical Methodologist - Integrated Information SciencesNovartis Pharma AG, Switzerland

This tutorial will discuss and propose methods to address key statistical issues leading to the problems currently observed in dose finding studies. A review of basic multiple comparisons and modeling methods will be included, as traditionally used in these studies. A unified strategy for designing and analyzing dose finding studies, denoted MCP-Mod, combining multiple comparisons and modeling, will be the focus of the course. MCP-Mod received a positive CHMP qualification opinion in January 2014, as an efficient statistical methodology for model-based design and analysis of phase II dose finding studies under model uncertainty. It will be discussed in detail, including a step-by-step description of its practical implementation. An extension of MCP-Mod will be described for count data, time-to-event endpoints as well as situations involving generalized non-linear models, linear and non-linear mixed effects models, and Cox proportional hazards models. A short reference will be made to another extension of the comprehensive multiple comparisons and modeling framework to confirmatory testing in dose-response studies using MCP-Mod. Case studies based on real clinical trials, together with concrete examples of code in R based on the DoseFinding package available on CRAN, will be used to illustrate the practical use of the methodology.

LEARNING OBJECTIVES:

At the conclusion of this tutorial, participants should be able to:

• Discuss goals and characteristics of dose-finding trials including why traditional methods tend to lead to poor dose selection and dose-response estimation

• Identify alternative approaches based on multiple comparisons and modeling for target dose selection and dose-response estimation

• Describe key concepts of the MCP-Mod methodology including how to implement it in practice for designing and analyzing dose finding trials

• State the capabilities of the Dose Finding R package and how to use its functions to implement the MCP-Mod methodology

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6

MONDAY, APRIL 20

7:30-8:30am REGISTRATION AND CONTINENTAL BREAKFAST

8:30-8:45am WELCOME AND OPENING REMARKS

Barbara Lopez-Kunz Ram C. Tiwari, PhD Joan Buenconsejo, PhDDIA Global Chief Executive Associate Director Statistics Team Leader Office of Biostatistics Inflammation, Neuroscience, Respiratory TA, Biometrics and Information Sciences Office of Translational Science AstraZeneca CDER, FDA Chair, North American DIA Statistics Community

8:45–9:15am FDA PRESENTATION

Lisa M. LaVange, PhDDirectorOffice of Biostatistics, Office of Translational ScienceCDER, FDA

9:15-10:30am KEYNOTE ADDRESS

Frank F. Weichold, MD, PhDDirectorOffice of Critical Path and Regulatory Science InitiativesOffice of the Chief Scientist and Office of the CommissionerFDA

Benjamin HeywoodPresident and Co-founderPatientsLikeMe Inc.

10:30-11:00am REFRESHMENT BREAK

11:00am-12:30pm SESSION 1

Statistical Issues in Biosimilar Analytical Assessment

As some biologics are reaching the end of their patent, a sponsor may pursue “similar” biological products for marketing approval. The sponsor needs to demonstrate that the test products are biosimilar to the reference products in a three-stage process. Analytical assessment, as the first stage, becomes extremely important. Due to the limited sample size (number of lots) and numerous, some quite complex, quality attributes, the statistical “similarity” comparison is difficult, with multiple issues arising.

The objective of this session is for statisticians from regulatory agencies, academia and industry to share their knowledge and experience, and to cultivate skills and paths leading to successful development of biosimilar products. The session will consist of 3 oral presentations followed by a panel discussion led by organizers and speakers.

SESSION CO-CHAIRS:

Stella Grosser, PhD Acting DirectorDivision of Biometrics VIIIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Eric M. Chi, PhD Executive DirectorAmgen

SPEAKERS:

Yi Tsong, PhDDirectorDivision of Biometrics VIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Rick BurdickAmgen Inc

Shein-Chung Chow, PhDProfessorDepartment of Biostatistics and BioinformaticsDuke University School of Medicine Duke University

12:30-1:30pm LUNCHEON

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1:30-3:00pm SESSION 2

Observational Studies and Beyond

This session will highlight various roles observational studies play in regulatory decision making. Speakers will discuss pre-study steps to assess studies for feasibility of quality research, the role of active surveillance systems such as the Sentinel Initiative, and unmeasured confounding, which is a major statistical issue in observational studies.

SESSION CO-CHAIRS:

Aloka Chakravarty, PhDDirectorDivision of Biometrics VIIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Brenda Crowe, PhDSenior Research AdvisorGlobal Statistical SciencesEli Lilly and Company

SPEAKERS:

Unmeasured Confounding Sensitivity AnalysesJames D. Stamey, PhDDirectorStatistical Science Graduate StudiesProfessor of Statistical ScienceBaylor University

OMOP LearningsJennifer Clark Nelson, PhDGroup Health Research InstituteSenior Investigator and Director of Biostatistics

Robert Ball, MD, MPHDeputy DirectorOffice of Surveillance and EpidemiologyCDER, FDA

3:00-3:30pm REFRESHMENT BREAK

3:30-5:00pm SESSION 3

Estimands and Sensitivity Analyses

Defining the primary objective of a clinical trial in the presence of non-compliance or non-adherence to the assigned treatment is crucial for the choice of design, the statistical analysis and the interpretation of the results. This raises the need for a structured framework to specify the primary estimand (i.e. “what is to be estimated”). The missing data report released in 2010 by the National Academy of Science, “Prevention and Treatment of Missing Data in Clinical Trials”, recommends explicit specification of a casual estimand in the protocol of a confirmatory trial. This is also reflected by the decision of ICH to amend its E9 guidance in the coming years to discuss estimands and their role in clinical trials. In this session we will discuss a clear definition of estimands and how the choice of an estimand is linked to important considerations around trial design, conduct and analysis.

SESSION CO-CHAIRS:

Feng Li Staff FellowDivision of Biometrics IIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Frank Bretz, PhDGlobal Head of Statistical MethodologyNovartis Pharma AG, Switzerland

SPEAKERS:

Framework for Estimands:

Mouna Akacha, PhDStatistical MethodologistNovartis Pharma AG, Switzerland

Case Study:

Bradley McEvoyMathematical StatisticianCDER, FDA

PANELISTS:

Thomas J. Permutt, PhDDirectorDivision of Biometrics IIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Bradley McEvoyMathematical StatisticianCDER, FDA

Chrissie FletcherExecutive DirectorBiostatisticsAmgen, Inc.

Mouna Akacha, PhDStatistical MethodologistNovartis Pharma AG, Switzerland

Stephen J. RubergDistinguished Research FellowEli Lilly and Company

Daniel O. ScharfsteinAssociate Professor of BiostatisticsJohns Hopkins University

5:00pm DAY ADJOURNED

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TUESDAY, APRIL 21

7:30-8:30am REGISTRATION AND CONTINENTAL BREAKFAST

8:30-10:00am SESSION 4

Why Statisticians Need to Understand Health Technology Assessments

The added clinical value, and in some countries the economic value, of a new intervention is systematically evaluated to determine whether it should be included in health benefit plans or disease management programs and be reimbursed by health care providers. Health technology assessment (HTA) can help determine if a new technology is clinically effective, and where appropriate cost effective, relative to current interventions used in routine clinical practice. Consideration of HTA activities are integral to the drug development process for new interventions, and early awareness of activities required to support HTAs can impact clinical study designs, and improve and enhance the evidence generated during the clinical development program. This session gives an overview of HTAs, particularly in terms of statistical issues and challenges statisticians will need to address.

SESSION CHAIR:

Estelle Russek-Cohen, PhDDirectorDivision of BiostatisticsCBER, FDA

SPEAKERS:

Shelby Derene Reed, MDProfessor in Medicine Duke University School of Medicine

Chrissie Fletcher Executive DirectorBiostatistics Amgen, Inc.

Elise Berliner, PhD Director Technology Assessment Program Agency for Healthcare Research and Quality (AHRQ)

PANEL:

Claire Telford, Bsc, Msc, PhD Director Health Economics & Payer Analytics AstraZeneca

Ellis Unger, MD Director Office of Drug Evaluation I, Office of New Drugs CDER, FDA

10:00-10:30am REFRESHMENT BREAK

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9

10:30am-12:00pm SESSION 5

Modeling and Simulation in Drug Development: How Do Statisticians Participate and Impact on It?

This session will discuss and illustrate the potential roles and contributions of statisticians in Modeling and Simulation (M&S) activities at various stages of clinical development programs. It will include two short case study presentations: one on the use of M&S for bridging dose regimens in a successful NDA submission and the other focusing on M&S to assist the design of a dose finding trial, followed by a panel discussion.

SESSION CO-CHAIRS:

Peiling Yang, PhDStatistics Team LeadDivision of Biometrics IOffice of Biostatistics, Office of Translational ScienceCDER, FDA

Cristiana Mayer, PhDScientific DirectorStatistical ModelingModel-Based Drug DevelopmentJanssen Research and Development, LLC

SPEAKERS:

Model-based Bridging of Dose Regimens to Avoid Additional Studies and Accelerate Approval: A Case Study in Type 2 Diabetes

José C. Pinheiro, PhDSenior DirectorModel Based Drug DevelopmentJanssen Research and Development, LLC

Program Level Modeling and Simulation of Phase 2 to Registration – Overview and Case Studies

William R. PruckaSenior Research ScientistEli Lilly and Company

PANEL DISCUSSION:

Björn Bornkamp, PhD, MScExpert Statistical Methodologist - Integrated Information SciencesNovartis Pharma AGSwitzerland

H. M. James Hung, PhDDirectorDivision of Biometrics IOffice of Biostatistics, Office of Translational Science CDER, FDA

Dionne Price, PhDDirectorDivision of Biometrics IVOffice of Biostatistics, Office of Translational ScienceCDER, FDA

José C. Pinheiro, PhDSenior DirectorModel Based Drug DevelopmentJanssen Research and Development, LLC

William R. PruckaSenior Research ScientistEli Lilly and Company

12:00-1:30pm LUNCHEON AND ROUNDTABLE DISCUSSIONS

SESSION LIAISON:

Jeff Maca, PhDSenior DirectorCenter for Statistics in Drug Development InnovationQuintiles

SESSION CHAIRS:

Eugenio Andraca-Carrera, PhD Mathematical StatisticianDivision of Biometrics VIIOffice of Biostatistics, Office of Translational ScienceCDER, FDA

Judy Li, PhD Mathematical StatisticianDivision of BiostatisticsCBER, FDA

Cristiana Mayer, PhDScientific DirectorStatistical ModelingModel-Based Drug DevelopmentJanssen Research and Development, LLC

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1:30-3:00pm SESSION 6 – SUBGROUP ANALYSIS

Subgroup analyses are an important component of confirmatory clinical trials for assessing consistency and heterogeneity. Various stakeholders have an interest in learning if treatments have different effects in different groups of subjects. EMA is in the process of revising a guideline on subgroup analysis and FDA is in the process of publishing a white paper on the topic. This session will include presentations on the two documents and include a panel discussion regarding the application of subgroup analysis in the various regulatory settings.

SESSION CO-CHAIRS:

Kathleen S. Fritsch, PhDMathematical StatisticianDivision of Biometrics IIIOffice of Biostatistics, Office of Translational ScienceCDER, FDA

Joachim Vollmar, MS Executive ConsultantInternational Clinical Development Consultants LLC

SPEAKERS:

Professor Armin Koch, DrSc HeadInstitute of BiometryHannover Medical School, Germany

Mohamed Alosh, PhDTeam LeaderOffice of Biostatistics, OTSCDER, FDA

PANELISTS:

Frank Bretz, PhDGlobal Head of Statistical MethodologyNovartis Pharma AG, Switzerland

Estelle Russek-Cohen, PhD Division DirectorDivision of BiostatisticsCBER, FDA

Alex Dmitrienko, PhDExecutive DirectorCenter for Statistics in Drug DevelopmentQuintiles Inc.

3:00-3:30pm REFRESHMENT BREAK

| Develop | Innovate | Advance

Find out more or register at DIAGlobal.org/DIA2015

It’s a Meeting of the Minds

51ST Annual MeetingJune 14–18 | Walter E. Washington Convention Center

Washington, DC

DIA 20154 Days.20 Tracks.

245+EducationalO�erings.

450+Exhibitors.

7,000+Attendees.

Featured Program Offerings from the Statistical Science and Quantitative Thinking Track:

Tutorial #40: Analysis of Safety Data from Clinical Trials

Innovative Designs for Cardiovascular Outcome Safety Trials in Type 2 Diabetes

Benefit-Risk Assessment of Medicines: Three Perspectives on Current Methodologies and the Statistician’s Role in Implementation

The Impact of Adaptive and Bayesian Approaches to Improving the Efficiency of Clinical Trial Design and Analysis

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3:30-5:00pm SESSION 7

Quantitative Measures for Benefit-Risk Assessment

The term Benefit to Risk has long been used in the drug development process, but not much work has been done in attempting to quantify this concept at either the population or patient level. Numerous activities in the US and Europe have been spawned to look at this, and some regulators have been strong proponents of such a quantitative approach. The advantage of such an approach is that it supplies a balanced and objective framework to weigh benefits and risks of medical products, while the drawbacks may include the clarity of the interpretation of the findings. The level of rigor needed to “quantify” these concepts remains a topic of debate, but what is eminently clear is the need to communicate the methods and findings to a broad audience of diverse backgrounds. This session will discuss the merits and examples of simple ways to communicate the concepts at the population and patient level.

SESSION CO-CHAIRS:

Ram C. Tiwari, PhDAssociate DirectorOffice of Biostatistics, Office of Translational ScienceCDER, FDA

Frank W. Rockhold, PhDSenior Vice PresidentGlobal Clinical Safety and PharmacovigilanceGlaxoSmithKline

SPEAKERS:

Quantitative Structured Benefit-Risk: The Current, the New and the Future

Ian Hirsch, PhD Senior Statistics Team LeaderInflammation Neuroscience, Respiratory TA, Biometrics and Information SciencesAstraZeneca

Bayesian Approaches to Quantitative Benefit-Risk Assessment: A Perspective for Better Decision Making

Yueqin Zhao, PhD Mathematical StatisticianDivision of Biometrics VII Office of Biostatistics, Office of Translational ScienceCDER, FDA

Benefit-Risk Approaches for Hypothetical Risk

Marilyn A. Metcalf, PhD Senior DirectorBenefit-Risk EvaluationGlaxoSmithKline

PANELISTS:

Telba Irony, PhD ChiefBiostatisticsGeneral Surgical Devices BranchCDRH, FDA

Christy Chuang-Stein, PhDVice PresidentHead of Statistical Research and Consulting CenterPfizer Inc.

Yueqin Zhao, PhDMathematical StatisticianDivision of Biometrics VII Office of Biostatistics, Office of Translational ScienceCDER, FDA

Ian Hirsch, PhDSenior Statistics Team LeaderInflammation Neuroscience, Respiratory TA, Biometrics and Information SciencesAstraZeneca

Marilyn A. Metcalf, PhDSenior DirectorBenefit-Risk EvaluationGlaxoSmithKline

5:00-7:00pm NETWORKING RECEPTION AND POSTER SESSION

SESSION LIAISON:

Stephen E. Wilson, DrPH, CAPT, USPHSDirectorDivision of Biometrics IIIOffice of Biostatistics, OTS, CDER, FDA

William Wang, PhDExecutive DirectorClinical Safety and Risk Management StatisticsBiostatistics and Research Decision Sciences (BARDS)Merck Research LaboratoriesMerck & Co Inc

Barry Schwab, PhD Vice PresidentClinical BiostatisticsJanssen Research and Development, LLC

Xiaoyu “Cassie” Dong Mathematical StatisticianDivision of Biometrics VICDER, FDA

TOPICS:

• Statistical Issues in Biosimilar Analytical Assessment

• Adaptive Design and Bayesian Design

• Observational Studies

• Statistical Issues Related to Health Technology Assessment

• Utilities of Modeling and Simulation in Drug Development and Evaluation

• Subgroup Analysis

• Quantitative Measures for Benefit-Risk Assessment

• Estimands and Sensitivity Analyses

12

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WEDNESDAY, APRIL 22

7:30-8:30am REGISTRATION AND CONTINENTAL BREAKFAST

8:30-10:00am SESSION 8

Partnering with Patients in Clinical Trials: Follow-up from the 2014 SCT/FDA QSPI Workshop

In December, 2014, the Society for Clinical Trials and the FDA co-sponsored a workshop on the theme of Innovations in the Science and Practice of Clinical Trials. A multidisciplinary group of presenters and attendees discussed wide-ranging topics including small clinical trials for rare diseases, large trials for rare events, streamlining trial operations, wearable technology and other methodological innovations, and leveraging information from diverse data sources. The topic that seemed to engage the audience the most was the discussion of patient partnerships in clinical trials; increasingly patients may be more active contributors in the objectives, design, and conduct of trials, well beyond a traditional test subject role. Two speakers will provide examples of patient partnerships, and then a panel will discuss next steps to increase patient engagement in the clinical trial enterprise, and how statisticians can help and learn from patients.

SESSION CO-CHAIRS:

John Scott, PhDDeputy DirectorDivision of Biostatistics, OBECBER, FDA

Mike Hale, PhD Consultant

SPEAKERS:

Veronica L. TodaroDirector of National Programs; Co-chair, CTTI Patient Leadership Council Parkinson’s Disease Foundation

Martin Ho, MS, PhDTeam LeaderNeurologic and Dental BiostatisticsCDRH, FDA

Telba Irony, PhDChief BiostatisticsGeneral Surgical Devices BranchCDRH, FDA

PANELISTS:

Bennett Levitan, PhDDirectorDepartment of EpidemiologyJanssen Research & Development

Aloka Chakravarty, PhDDirectorDivision of Biometrics VIIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Sara Eggers, PhDOperations Research AnalystOffice of Program and Strategic AnalysisCDER, FDA

10:00-10:15am REFRESHMENT BREAK

10:15-10:30am

Introduction and Remarks from the New Deputy Commissioner of the FDA

Lisa LaVange, PhDDirectorOffice of Biostatistics, Office of Translational SciencesCDERFDA

Robert Califf, PhDDeputy Commissioner for Medical Products and TobaccoFDA

13

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10:30am-12:00pm SESSION 9

Cardiovascular Outcome Trial for Safety – Alternative Approaches to Ruling Out Cardiovascular Risk

The 2008 FDA Guidance, Diabetes Mellitus – Evaluating Cardiovascular Risk in New Antidiabetic Therapies to Treat Type 2 Diabetes established that an excess amount of CV risk be ruled out in two stages. The objective of the first stage is to rule out a relative 80% increase in risk and the second stage objective is to rule out a 30% relative increase in CV risk. In consideration of this two-stage approach various strategies have been proposed, all of which require the use of a cardiovascular outcome trial (CVOT) at some point in the development of a new antidiabetic therapy. The session will review the background of the two-stage approach and discuss some novel approaches to address these objectives.

SESSION CO-CHAIRS:

Mat Soukup, PhD Statistics Team LeaderDivision of Biometrics VIIOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Jerald S. Schindler, DrPH Vice PresidentBiostatistics and Research Decision SciencesMerck Research LaboratoriesChair, Global DIA Statistics Community

SPEAKERS:

Jean-Marc Guettier, MDDirectorDivision of Metabolism and Endocrinology Products (DMEP)CDER, FDA

Joseph G. Ibrahim, PhDAlumni Distinguished Professor of BiostatisticsUniversity of North Carolina School of Public HealthDirector, Biostatistics CoreLineberger Comprehensive Cancer Center

L.J. Wei, PhDProfessor of BiostatisticsHarvard University

DISCUSSANT:

Christy Chuang-Stein, PhDVice PresidentHead of Statistical Research and Consulting CenterPfizer Inc.

12:00-1:00pm LUNCHEON

1:00-2:30pm SESSION 10

Adaptive Design and Bayesian Working Group Feedback

Over the past few years, the DIA has established several multi-disciplinary Scientific Working Groups (SWGs) which bring together representatives from Industry, Government and Academia to address a specific unresolved research problem related to drug development. Two of the most active SWGs are the Adaptive Designs SWG and the Bayesian SWG. This session will highlight recent developments from these ongoing activities. In particular, the speakers will outline how these developments can accelerate the drug development process.

SESSION CO-CHAIRS:

Lei Nie, PhD Statistics Team LeadDivision of Biometrics VOffice of Biostatistics, Office of Translational SciencesCDER, FDA

Zoran AntonijevicSenior DirectorCytel Consulting

SPEAKERS:

Zoran AntonijevicSenior DirectorCytel Consulting

David Ohlssen, PhDSenior Expert MethodologistNovartis Pharmaceuticals Corporation

Panelists:

Estelle Russek-Cohen, PhDDivision DirectorDivision of BiostatisticsCBER, FDA

David Ohlssen, PhDSenior Expert MethodologistNovartis Pharmaceuticals Corporation

Zoran AntonijevicSenior DirectorCytel Consulting

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2:30-3:00pm REFRESHMENT BREAK

3:00-4:30pm SESSION 11

FDA and Industry Town Hall

This session will be an open-microphone and broad Q&A session. Panelists will address questions posed by attendees in one of several manners: via e-mail to Stephanie.Ritter@diahome.org before or during the meeting, writing questions on 3x5 cards available at the registration desk, or by asking them live at the session. Topics may focus on the sessions held at this meeting, but can also branch out into other areas of regulatory statistics.

SESSION CO-CHAIRS:

Lisa M. LaVange, PhDDirectorOffice of BiostatisticsOffice of Translational ScienceCDER, FDA

Walter W. Offen, PhD Global Head of Statistical InnovationData and Statistical SciencesAbbVie

PANELISTS:

Walter W. Offen, PhD Global Head of Statistical InnovationData and Statistical SciencesAbbVie

Jerald S. Schindler, DrPHVice PresidentBiostatistics and Research Decision SciencesMerck Research LaboratoriesChair, Global DIA Statistics Community

European Subgroup Guidance

Professor Armin Koch, DrSc HeadInstitute of BiometryHannover Medical SchoolGermany

Chrissie Fletcher, MSCExecutive DirectorBiostatisticsAmgen, Inc.

Névine ZariffaVice President and HeadBiometrics and Information SciencesAstraZeneca

Rajeshwari Sridhara, PhDDirector, Division of Biometrics VOffice of Biostatistics, Office of Translational SciencesCDER, FDA

John Scott, PhD Deputy DirectorDivision of BiostatisticsCBER, FDA

Stephen E. Wilson, DrPH, CAPT, USPHSDirectorDivision of Biometrics IIIOffice of Biostatistics, OTS, CDER, FDA

4:30pm CONFERENCE ADJURNED