Dr. Ming-Hui Chen is
currently Professor and Head of the Department of Statistics at the
University of Connecticut (UConn). He was elected to Fellow of
International Society for Bayesian Analysis in 2016, Fellow of the
Institute of Mathematical Statistics in 2007, Fellow of American
Statistical Association in 2005. He has published over 395 statistics
and biostatistics methodological and medical research papers in
mainstream statistics, biostatistics, and medical journals. He has also
published five books including two advanced graduate-level books on
Bayesian survival analysis and Monte Carlo methods in Bayesian
computation. He has supervised or been supervising 28 PhD students. He
served as President of the International Chinese Statistical Association
(ICSA) in 2013, Program Chair and Publication Officer of SBSS of the
American Statistical Association (ASA) and the ASA Committee on
Nomination for 2016-2017 to nominate candidates for ASA President/Vice
President. Currently, he serves as President of the New England
Statistical Society (nestat.org), Chair of Eastern Asia Chapter of ISBA in
2018 (https://isba-eastasia.github.io/), Co Editor-in-Chief
of Statistics and Its Interface, and an Associate Editor of JASA, JCGS,
and LIDA.
Jeff Palmer has been a
statistics group head leading early clinical development in rare
diseases at Pfizer for the past 5 years. Prior to Pfizer he had worked
for over ten years with various other pharma and consulting companies
supporting mainly rare diseases, oncology, and neurology. Jeff received
his MS in statistics from the University of Chicago and conducted his
doctoral research in statistics at Carnegie Mellon University.
Dan Meyer is Head of
Statistics for the Rare Disease Therapeutic category for Pfizer Global
Product Development. He held previous group head roles at Pfizer for
infectious disease, cardiovascular & metabolic disease, and
nonclinical statistics. Dan received his PhD in Statistics from the
University of Wisconsin. He is a Fellow of the American Statistical
Association.
Dr. Kun Chen is an Associate
Professor in the Department of Statistics, University of Connecticut
(UConn), and a Research Fellow at the Center for Population Health,
UConn Health Center. Chen’s research mainly focuses on multivariate
statistical learning, dimension reduction, high-dimensional statistics,
and healthcare analytics with large-scale heterogeneous data. He has
extensive interdisciplinary research experience in a variety of fields
including insurance, ecology, biology, agriculture, medical imaging, and
public health. Chen's research projects have received funding from the
National Institutes of Health (NIH), the Simons Foundation, and the
National Science Foundation (NSF). Recently Chen is funded by NSF for
developing integrative multivariate methods and heterogeneous response
regression, and he is a co-PI in an NIH-funded data-driven suicide
prevention study which leverages integrated big data from disparate
sources scattered in healthcare system. Chen was a Co-Editor of the 2015
ICSA Symposium Proceeding Book, and serves as an Associate Editor of
Sankhya: The Indian Journal of Statistics since 2016. He has received
Recognition for Teaching Excellence at UConn for multiple times.
Chen received his B.Econ. in Finance and Dual B.S. in Computer Science & Technology from the University of Science and Technology of China in 2003, his M.S. in Statistics from the University of Alaska Fairbanks in 2007, and his PhD in Statistics from the University of Iowa in 2011. Before joining UConn, he was on the faculty of Kansas State University from 2011 to 2013.
Charlie Cao is Statistics Head
for Late Clinical Development at Biogen. He has over 25 years of working
experiences in pharmaceutical and biotech companies, worked on various
therapeutic areas such as CNS, Cardiovascular and Diabetes, Pain,
Obesity, Respiratory, GI and Rare Disease. He worked at Takeda and
Abbott/Abbvie after he received his PhD from Duke University. He is a
strong advocator for innovative methods of clinical trial design and
analysis.
Dr. Roee Gutman is an
Associate Professor in the Department of Biostatistics at Brown
University. His areas of expertise are causal inference, file linkage,
missing data, Bayesian analysis and their application to data sources in
health services research. He has vast experience in designing and
analyzing large pragmatic randomized trials and secondary datasets from
various sources (e.g. Medicare claims data, VA health data). He has been
involved in many comparative effectiveness studies where he contributed
in terms of the statistical theory and its implementation. Dr. Gutman is
the lead statistician on multiple NIH and VA grants, and he has received
two PCORI methods award.
Mike Hale, Ph.D., is Vice
President and Chief Statistical Scientist for Takeda, following leading
Biostatistics and Programming at Shire. Mike has worked in biotech since
the mid-1980’s in both clinical and non-clinical applications, at Amgen,
GSK, Roche, and Monsanto. In the early 1990’s he proposed and developed
the current paradigm of clinical trial simulation using models relating
dosing, pharmacokinetics, and clinical response including stochastic
components. He has served as a member of the clinical pharmacology
subteam of the FDA Pharmaceutical Sciences Advisory Committee. Recent
research interests include rare disease drug development, precision
medicine (particularly evaluation of selection biomarkers, cut-point
determination, and companion diagnostic co-development), big data,
wearable technology, data transparency, and patient engagement. Mike has
given invited talks on several topics in many countries, including an
invited talk for an FDA Advisory Committee. Mike has organized several
conferences and conference sessions, and has been effective in
collaborating with professionals in other biopharmaceutical companies
and regulatory agencies. He is the chair of QSPI, Quantitative Sciences
in the Pharmaceutical Industry, a committee of the Society for Clinical
Trials. Mike received a PhD in mathematical statistics from Iowa State
University.
Dr. Yang Song is currently
Senior Director, Biostatistics Therapeutic Area Head for General
Medicines (including gene therapies), Pain and Neurology, at Vertex
Pharmaceuticals Inc., leading his statistical team on multiple rare
disease pipeline development projects. Prior to joining Vertex, he was
with Merck for nearly 10 years, rotated through its PA, Beijing, and NJ
global sites, with increasing responsibilities for global drug
development across multiple therapeutic areas. He also worked with
Johnson & Johnson for oncology drug development early in his career.
His research interests include rare disease clinical trial methodology,
real world evidence, data integration, optimal clinical development
strategy, statistical issues in oncology clinical trials, biomarker
endpoints, and subgroup analyses. He is a member of the ASA
Biopharmaceutical Scientific Working Group on Real World Evidence. Yang
received his Ph.D. in Statistics from the University of Wisconsin -
Madison.
Dr. Rui (Sammi) Tang is a
leading expert of biostatistics/bioinformatics in the
biotech/pharmaceutical industry and she is currently the Head of
Biostatistics, Programming and Medical Writing Department at Servier
Pharmaceuticals US. Prior to join Servier she was the Biostatistics
Therapeutic Area head of Oncology, Transplants, Ophthalmology and
prematurity neonates programs at Shire pharmaceutical. Prior to that she
was at Vertex pharmaceutical leading Oncology and Hematology pipelines.
Before that she also has worked at Amgen for about 8 years, Mayo
clinical biostatistics and Merck shortly. Previously she served as the
biostatistics lead of Companion Diagnostics and the Global Statistics
Lead for multiple oncology clinical programs from early phase to late
phase at Amgen. Sammi has great experience in CDRH, CBER, CDER, health
Canada, EMA and Asian regulatory agencies interactions. Sammi’s research
interests are primarily in the area of adaptive clinical trial design
and biomarker subgroup related statistical issues in precision medicine.
She has authored more than 30 articles in peer-reviewed scientific
journals on methodology, study design, data analysis and reporting and
is a co-inventor of several patents. Besides her daily work, she
actively promotes data science through many of her volunteer activities:
Sammi is co-founder of DahShu which is a 501(c)(3) non-profit
organization, founded to promote research and education in data sciences
with almost 5000 members internationally. She serves in the SCT (Society
of Clinical Trials) scientific program committee and development
committee since 2013 to help organize the annual international
conference. She is leading teams in the DIA (Drug Information
Association) Adaptive design working group of oncology drug development
and small population working group for rare disease statistical
methodology development. She is also an active member in ASA (American
Statistics Association) and ICSA (International Chinese Statistics
Association) to serve the biostatistics and data science professional
community.
Sammi graduated from the University of Michigan Technology University with a PhD in statistics Genetics.
Dr. John Zhong is the Vice
President of Biometrics at REGENXBIO, a leading AAV gene therapy
company. Before joining REGENXBIO, John was a Biostatistics Group Head
at Biogen, leading his teams to provide statistical strategy and support
to all phases of clinical development for Immunology and Rare Diseases
as well Early Development for all assets. He also led the Innovative
Analytics group and played a critical role in the use of innovative
clinical trial designs, statistical methods and analytical approaches in
Biogen’s research and drug development. Prior to Biogen, John was a
Senior Director of Biostatistics at Human Genome Sciences, accountable
for statistical strategy and support to all phases of clinical
development in autoimmune disease and infectious disease areas. John has
20 years of industry experience and played pivotal roles in multiple
successful drug development programs, bringing efficacious treatments to
patients with serious unmet needs. In the industry, John actively
promoted statistical innovation in drug development and brought
industry’s voice to regulatory innovation. John was an invited expert
panelist at the FDA Public Meeting on "Promoting the Use of Complex
Innovative Designs in Clinical Trials". He made a positive impact on the
design of FDA’s Complex Innovative Designs Pilot program. Currently,
John is a Rapporteur at the ICH, leading the E20 Expert Working Group to
develop an international regulatory guideline on Adaptive Clinical
Trials. John received his PhD in Mathematical Statistics from the
University of Maryland at College Park. He has coauthored over 50
manuscripts in peer reviewed medical and statistical journals and more
than 100 presentations.