Featured Speakers
- Rebecca Betensky, New York University; Opening Remarks
- Stephen Lake, Alexion (AZ Rare Disease); Opening Remarks
- Janet Maynard, FDA; Strategies to Accelerate Rare Disease Drug Development
- Shein-Chung Chow, Duke University; Innovative Thinking for Rare Disease Drug Development
- Lee-Jen Wei, Harvard University; Panel Discussant
Invited Speakers
- Marie-Abèle Bind, Massachusetts General Hospital Biostatistics Center; The use of balancing methods in ALS real-world settings and beyond
- Cong Chen, Merck & Co.; Adaptive Endpoint Selection in Rare Disease Drug Development
- Yoonjin Cho, Regenxbio; Challenges of Mucopolysaccharidosis II (MPS II) Drug Development and Path to Acceleration of The Pediatric Rare Disease Drug Development with Novel Endpoints
- Gaohong Dong, BeiGene; Use of win statistics (win ratio, win odds and net benefit) for hierarchical analysis of clinical endpoints with low event rates and surrogate endpoints
- Haoda Fu, Eli Lilly and Company; AI/ML for drug discovery
- Ixavier A. Higgins, Eli Lilly and Company; The Temporally-resolved Connectedness of Genetics, Imaging Biomarkers, and Clinical Endpoints in Alzheimer's disease
- Bo Huang, Pfizer; Endpoints Selection and Efficacy Evaluation for Clinical Development in Rare Disease
- Carina Ittrich, Boehringer Ingelheim; Evaluation of Biomarker Assessments in Conjunction with Clinical Endpoints for Early Decision Making in Rare Disease Drug Development
- Xiaodong Luo, Sanofi; Conditional and Unconditional Analyses for Bayesian Historical Data Borrowing
- Peter Mueller, University of Texas at Austin; A Bayesian Nonparametric Model to Create Synthetic Matching Populations
- Kevin Roberts, Pfizer; An Exploration of Model-Based Dose Findings Algorithms for Use in Dose-Finding Gene Therapy Trials
- Peng Sun, Biogen; A causal mediation model to evaluate the individual surrogacy of plasma neurofilament light chain (NfL) for SOD1 ALS using tofersen data
- Chenguang Wang, Regeneron; Leveraging Real-World Data and Real-World Evidence in Clinical Trial Design and Analysis for Rare Diseases
- Xin Wang, Bristol Myers Squibb; Design considerations in expanding lines of therapy for unmet medical need
- Ying Yuan, University of Texas MD Anderson Cancer Center; SAM: Self-adapting Mixture Prior to Dynamically Borrow Information from Historical Data for Rare Disease Clinical Trials
- Yaohua Zhang and Bang Wang, Vertex; Composite Endpoint in Cell/Gene Therapy Development
- Jian Zhu, Servier; An extended Bayesian divide-and-conquer analysis approach for hybrid control trials
Rebecca Betensky, New York University
Dr. Rebecca
Betensky is the President-Elect of the New England Statistical
Society (NESS). She is Professor and Chair of Biostatistics at
NYU School of Global Public Health. Her research focuses on
censored and truncated data and efficient designs for clinical
trials. Much of her current work is motivated by clinical and
observational studies in Alzheimer's disease.
Stephen Lake, Alexion (AZ Rare Disease)
Steve Lake is the
Vice President of Quantitative Sciences at Alexion, the rare
disease unit of AstraZeneca. At Alexion, he leads the
biostatistics, statistical programming, epidemiology and real
world science, medical writing, and transparency and disclosure
functions. Prior to joining Alexion, he worked at Wave Life
Sciences and Clementia Pharmaceuticals and spent 15 years at
Genzyme and Sanofi. He holds a doctorate degree in Biostatistics
from the Harvard School of Public Health.
Janet Maynard, FDA
Dr. Janet Maynard is
the Director of the Office of Rare Diseases, Pediatrics,
Urologic and Reproductive Medicine (ORPURM) within the Food and
Drug Administration’s Center for Drug Evaluation and Research
(CDER). In this role, she oversees the development, review, and
regulation of applications for drugs and biologic products
reviewed within the divisions in ORPURM: The Division of
Pediatrics and Maternal Health, the Division of Rare Diseases
and Medical Genetics, the Division of Urology, Obstetrics and
Gynecology, and the Division of Pharmacology-Toxicology for Rare
Diseases, Pediatrics, Urologic and Reproductive
Medicine/Specialty Medicine. Prior to serving as Director, she
was the Deputy Director of ORPURM.
Prior to ORPURM, Dr.
Maynard was the Director of the Office of Orphan Products
Development, and oversaw legislatively mandated designation and
grant programs intended to promote the development of products
for rare diseases including, orphan drug, rare pediatric
disease, and humanitarian use device designation programs, as
well as clinical trial, natural history study, and pediatric
device consortia grant programs. Before directing OOPD, she was
a clinical team leader in CDER’s Division of Anesthesia,
Analgesia, and Addiction Products. She originally joined FDA in
2011 as a Medical Officer in the Division of Pulmonary, Allergy,
and Rheumatology Products (DPARP), before becoming a clinical
team leader in DPARP.
Dr. Maynard received her medical
degree from Vanderbilt University and completed a residency in
internal medicine at Duke Hospital. Subsequently, she completed
a fellowship in rheumatology at Johns Hopkins Hospital. During
her fellowship, she completed a Master of Health Science at the
Johns Hopkins Bloomberg School of Public Health in the Graduate
Training Program in Clinical Investigation.
Shein-Chung Chow, Duke University
Shein-Chung Chow,
Ph.D. is currently a Professor at the Department of
Biostatistics and Bioinformatics, Duke University School of
Medicine, Durham, North Carolina. Dr. Chow was also a special
government employee (SGE) appointed by the Unite States Food and
Drug Administration (FDA) as an Oncologic Drug Advisory
Committee (ODAC) voting member and Statistical Advisor to the
FDA (2015-2017, 2019-2022). Between 2017-2019, Dr. Chow was
on-leave for FDA as an Associate Director at Office of
Biostatistics, Center for Drug Evaluation and Research (CDER),
FDA. Dr. Chow was the Editor-in-Chief of the Journal of
Biopharmaceutical Statistics (1992-2020) and is the
Editor-in-Chief of the Biostatistics Book Series at
Chapman and Hall/CRC Press of Taylor & Francis Group. He was
elected Fellow of the American Statistical Association in 1995
and an elected member of the ISI (International Statistical
Institute) in 1999. Dr. Chow is the author or co-author of over
350 methodology papers and 33 books including Design and
Analysis of Bioavailability and Bioequivalence Studies,
Biosimilars: Design and Analysis of Follow-on Biologics,
Biosimilar Product Development, Analytical Similarity Assessment
in Biosimilar Drug Development, Advanced Statistics in
Biosimilar Product Development, Advanced Statistics in
Regulatory Critical Clinical Initiatives, and most recently,
Innovative Methods for Rare Disease Drug Development.
Lee-Jen Wei, Harvard University
L.J. Wei is a
professor of Biostatistics at Harvard University. Before joining
Harvard, he was a professor at University of Wisconsin,
University of Michigan, and George Washington University. His
main research interest is in the clinical trial methodology,
especially in design, monitoring and analysis of studies. He has
developed numerous novel statistical methods which are utilized
in practice. He received the prestigious Wald Medal in 2009 from
the American Statistical Association for his contribution to
clinical trial methodology. He is a fellow of American
Statistical Associating and Institute of Mathematical
Statistics. In 2014, to honor his mentorship, Harvard School of
Public Health established a Wei-family scholarship to support
students studying biostatistics. His recent research area is
concentrated on translational statistics, the personalize
medicine under the risk-benefit paradigm via biomarkers and
revitalizing clinical trial methodology. He has more than 250
publications and served on numerous editorial and scientific
advisory boards including data monitoring for governments and
industry. L. J. Wei has extensive working experience in
regulatory science for developing and evaluating new
drugs/devices.
Marie-Abèle Bind, Massachusetts General Hospital Biostatistics Center
Marie-Abèle Bind
is an Assistant of Investigation at the Massachusetts General
Hospital (MGH) Biostatistics Center and an Assistant Professor
at the Harvard Medical School. Her research interests focus on
developing causal inference methods for quantifying the effects
of randomized and non-randomized exposures on various outcomes
and understanding the mechanisms explaining these effects. Her
current research is funded by the NIH Early Independence Award
program. She completed her joint PhD in Biostatistics and
Environmental Health at the Harvard School of Public Health,
working with Professors Joel Schwartz and Brent Coull. She then
became a Ziff postdoctoral Fellow at the Harvard University
Center for the Environment. In 2016, she was awarded an Early
Independence Award (NIH High-Risk High-Reward research grant)
and became Research Associate in the Department of Statistics.
From 2017 to 2021, she became a John Harvard Distinguished
Science Fellow.
Cong Chen, Merck & Co.
Dr. Cong Chen is
Scientific AVP in Early Development Statistics at Merck &
Co., Inc., providing fit-for-purpose decision-making strategies
and novel statistical approaches for early and early-to-late
transitional oncology programs, and supporting oncology external
collaborations, competitive intelligence, and high-profile due
diligence projects. Prior to taking the role, he led the
statistical support for the development of pembrolizumab and
played a key role in accelerating its regulatory approvals.
He is an elected Fellow of American Statistical
Association (2016), an Associate Editor of Statistics in
Biopharmaceutical Research, a member of Cancer Clinical Research
Editorial Board and a leader of the DIA Innovative Design
Working Group. He has published over 100 papers and 10 book
chapters on innovative design and analysis methods of clinical
trials, has given multiple short courses on the subject at
statistical conferences and was invited to give oral
presentations at multiple medical conferences on design
strategies for oncology drug development.
Yoonjin Cho, Regenxbio
Dr. Cho is a Sr.
Director of Biostatistics at REGENXBIO Inc. She has over 15
years of experiences in pharmaceutical and biotechnical
industries. She is currently leading projects in rare disease
and ophthalmology drug development within the company. She
previously worked at Vanda, GSK and Gilead Science. Yoonjin
received her PhD in statistics from North Carolina State
University. Her research interest includes rare disease drug
development, biomarker endpoints and the utilization of
historical data.
Gaohong Dong, BeiGene
Gaohong Dong, PhD has
20 years of experience in the pharmaceutical industry. He is a
Director of Biostatistics at BeiGene. Prior to joining BeiGene,
he worked at Novartis, then worked as a consultant under his own
entity of iStats Inc. Gaohong is very active on research. He
published statistical journal papers and book chapters on
Bayesian-Frequentist design, adaptive design, missing data
imputation, meta-analysis, and composite of prioritized multiple
outcomes. During the recent years, he has been focusing on the
win statistics (win ratio, win odds, and net benefit). Gaohong
has been serving as an Associate Editor of the Journal of
Biopharmaceutical Statistics since 2017.
Haoda Fu, Eli Lilly and Company
Dr. Haoda Fu is an
Associate Vice President and an Enterprise Lead for Machine
Learn- ing, Artificial Intelligence, and Digital Connected Care
from Eli Lilly and Company. Dr. Haoda Fu is a Fellow of ASA
(American Statistical Association), and IMS Fellow (Institute of
Mathematical Statistics). He is also an adjunct professor of
biostatistics department, Univ. of North Carolina Chapel Hill
and Indiana university school of medicine. Dr. Fu received his
Ph.D. in statistics from University of Wisconsin - Madison in
2007 and joined Lilly after that. Since he joined Lilly, he is
very active in statistics methodology research. He has more than
100 publications in the areas, such as Bayesian adaptive design,
survival analysis, recurrent event modeling, personalized
medicine, indirect and mixed treatment comparison, joint
modeling, Bayesian decision making, and rare events analysis. In
recent years, his research area focuses on machine learning and
artificial intelligence. His research has been published in
various top journals including JASA, JRSS, Biometrika,
Biometrics, ACM, IEEE, JAMA, Annals of Internal Medicine etc..
He has been teaching topics of machine learning and AI in large
industry conferences including teaching this topic in FDA
workshop. He was board of directors for statistics organizations
and program chairs, committee chairs such as ICSA, ENAR, and ASA
Biopharm session. He is a COPSS Snedecor Awards committee member
from 2022-2026, and will also serve as an associate editor for
JASA theory and method from 2023.
Ixavier A. Higgins, Eli Lilly and Company
Ixavier (Zae)
Higgins is a Senior Advisor at Eli Lilly & Company. He works
in preclinical statistics supporting Neuroscience, where he
leverages imaging, genetics, and -omics data to gain insights on
neurodegenerative diseases. Prior to Eli Lilly, Zae was a PhD
student in the Department of Biostatistics and Bioinformatics at
Emory University. His work focused on methods development for
network analysis of resting state fMRI and diffusion tensor
imaging data. He also holds a B.S. in Mathematical Economics and
an M.A. in Mathematics from Wake Forest University. In his free
time, Zae loves to be outdoors (biking or playing sports),
spending time with family, and reading.
Bo Huang, Pfizer
Dr. Bo Huang is Executive
Director, Statistics Group Head of Non-malignant Hematology at
Pfizer. Previously, he had more than 15 years of industry
experience across all stages of global clinical development of
oncology products in solid tumors and hematological
malignancies, and successfully led a number of global
submissions, including the first Pfizer submission in the FDA’s
Real-Time Oncology Review (RTOR) pilot program. He is a
recognized scientific leader in developing and applying
innovative quantitative methods, adaptive dose finding and
confirmatory designs in drug development, one of the main
drivers behind the increased use of innovative model-based and
adaptive designs at Pfizer. He designed the first protocol at
Pfizer Oncology using a Bayesian model-based adaptive design in
2010, paving the way for future use of similar innovative
adaptive designs. He has over 120 publications, including as
lead author or co-author of articles published in top-tier
journals such as NEJM, JCO, The Lancet, JAMA Oncology, Annals of
Internal Medicine, Biometrics, Statistics in Medicine etc. He
also jointly holds a US patent in cancer treatment
(US8435516B2). In addition, he received several poster and paper
awards from the American Statistical Association and the
International Biometric Society, and has been serving as Guest
Editor/Associate Editor for several scientific journals, serving
as Industry Co-Chair of the 2021 Regulatory-Industry Statistics
Workshop, serving as Chair of the Poster Award Committee for the
ASA Biopharmaceutical Section (2020-2023), elected as Program
Chair-elect 2023 for the ASA Biopharmaceutical Section, and was
an elected Board Director of the International Chinese
Statistical Association (2016-2019). He received his PhD in
Statistics from the University of Wisconsin-Madison, and is an
elected Fellow of the American Statistical Association.
Carina Ittrich, Boehringer Ingelheim
Dr. Carina Ittrich
is working as Expert Therapeutic Area and Methodology
Statistician in Inflammation at Boehringer Ingelheim Pharma GmbH
& Co KG, Germany. She has more than 15 years of experience
in pharmaceutical industry with focus on statistical aspects in
Translation Medicine and Clinical Pharmacology and special
interest in biomarker guided clinical development. Carina has a
Ph.D. in Mathematics from the University of Rostock, Germany.
Before joining Boehringer Ingelheim, she worked as PostDoc in
the Biostatistics Department at the German Cancer Research
Center in Heidelberg.
Xiaodong Luo, Sanofi
Xiaodong Luo (PhD) is
working at Sanofi as Biostatistics Team Leader focusing on
Neurology and Statistical Innovation. He has published papers on
different research topics including survival analysis, missing
data handling, multiplicity control, Bayesian hypothesis testing
and Basket trials. He is a Board member of ICSA (2021-2023) and
a member of Editorial Board for Contemporary Clinical
Trials.
Peter Mueller, University of Texas at Austin
Peter Mueller is
Professor of Statistics and Mathematics at UT Austin.He works on
Bayesian inference, with a focus on nonparametric Bayesian
methods, simulation based methods, optimal design and multiple
comparison procedures, with an interest in applications to
biostatistics and bioinformatics, including in particular
Bayesian clinical trial design. He is an elected fellow of the
ASA, the IMS, and ISBA, and served as president of ISBA, and as
chair of ASA/SBSS.
Kevin Roberts, Pfizer
Kevin Roberts is a
statistician at Pfizer in the Inflammation & Immunology
therapeutic area, with a focus on I&I rare diseases. Kevin
joined Pfizer in 2019. He has worked is rare diseases since 2018
and has worked in the drug development since 2005. Kevin earned
his Ph.D in Biostatistics from Harvard in 2003.
Peng Sun, Biogen
Dr. Peng Sun is Senior
Director of Biostatistics at Biogen. After receiving his Ph.D.
degree in statistics in 2006 from the University of Iowa, Peng
worked in the clinical pharmacology statistics group at Merck
for four years before joining GSK. At GSK, Peng was the lead
statistician for the global submission of a combination
treatment for metastatic melanoma that received accelerated
approval from the FDA. Peng currently works at Biogen as the
statistical lead in the neuromuscular area.
Bang Wang, Vertex
Dr. Bang Wang is the
Senior Biostatistician II at Vertex Pharmaceuticals, where he
supports multiple clinical trials in the early phase. Before
joining Vertex, Bang graduated from the University of Pittsburgh
with Ph.D. in Statistics. His primary research interests are
win-odds regression in clinical trials with composite endpoints,
missing values in risk prediction, and causal inference. During
his Ph.D. studies, he also interned at FDA CDER II and Moderna.
Before that, he earned his BS degrees in Statistics and
Mathematics from the University of North Carolina at Chapel
Hill.
Chenguang Wang, Regeneron
Dr. Chenguang Wang
is the Head of Statistical Innovation at Regeneron. Previously,
Dr. Wang was an Associate Professor at Johns Hopkins University.
He also worked as a Mathematical Statistician at CDRH, FDA. Dr.
Wang has extensive experience in clinical trial design and
analysis, especially in regulatory settings.
Xin Wang, Bristol Myers Squibb
Dr. Xin Wang is Senior
Director in BMS leading Cell Therapy Breyanzi Franchise
Biometrics Team. Xin received her Ph.D in Statistics from
Northwestern University, since then she has 15+ years of
experience in pharmaceutical industry.
Prior to joining
BMS in 2021, Xin was TA Lead of Rheumatology at AbbVie where she
held positions with increasing responsibilities with 5 years as
people manager. Xin has led the Rheumatology statistics team
with significant contributions to the submission and approval of
Rheumatology indications in Rinvoq and Humira. Prior to AbbVie,
Xin had worked at Pfizer and Sanofi in Inflammation, CVMED and
internal medicine.
Her research interest includes
multiple comparisons, gatekeeping procedures, dose-finding,
missing data imputations, and adaptive designs.
Ying Yuan, University of Texas MD Anderson Cancer Center
Ying Yuan is Bettyann
Asche Murray Distinguished Professor and Deputy Chair in the
Department of Biostatistics at University of Texas MD Anderson
Cancer Center. Dr. Yuan is an internationally renowned
researcher in innovative Bayesian adaptive designs. The designs
and software developed by Dr. Yuan’s lab
(www.trialdesign.org)
have been widely used in medical research institutes and
pharmaceutical companies. The BOIN design, developed by Dr.
Yuan’s team, is a groundbreaking oncology dose-finding design
that has been recognized by the FDA as a fit-for-purpose drug
development tool. Dr. Yuan was elected as the American
Statistical Association Fellow, and is the leading author of two
books, “Bayesian Designs for Phase I-II Clinical Trials” and
“Model-Assisted Bayesian Designs for Dose Finding and
Optimization,” both published by Chapman & Hall/CRC.
Yaohua Zhang, Vertex
Dr. Yaohua Zhang is
an Associate Director at Vertex Pharmaceuticals. Since joining
Vertex in 2017, Yaohua has worked on various trials from phase I
to phase III and submission work. Most recently, he is the
project lead statistician of two disease areas and is actively
engaging in strategic planning, early pipeline development and
theoretical research. Yaohua graduated with a PhD degree in
statistics from UConn in 2017 and since then has been an active
alumnus. He has been supporting NESS activities and sit on
several NESS committees. Apart from his daily busy work, he also
conducts several research topics related to practical issues
seen in the setting of pharmaceutical industry through
collaboration with colleagues.
Jian Zhu, Servier
Jian Zhu is currently a
Director of Biostatistics at Servier Pharmaceuticals. He
obtained his PhD in Biostatistics from University of Michigan,
Ann Arbor and worked at Michigan Alzheimer's Disease Center and
Takeda Pharmaceuticals prior to joining Servier. His drug
development experience includes leading global oncology programs
in hematologic malignancy and solid tumors, leading statistical
innovation working groups and serving as statistical consultant
and advisory panel member in multiple therapeutic areas. His
research interest includes adaptive designs, real world data,
non-proportional hazards, Bayesian dose finding designs and
missing data analysis. He has also published 20+ statistical
methodology papers in peer-reviewed journals and book
chapters.