2022

Below is the information for the 2022 Boston Pharmaceutical Symposium. 

Data and time: Friday, Oct 7, 2022. 8:15am - 4:15pm EDT

Location: Pfizer Inc.1 Portland Street Cambridge, MA 02139

About this event

The Boston Chapter of the American Statistical Association (BCASA) invites you all to attend the 2022 Boston Pharmaceutical Symposium on October 7, 2022 at Pfizer, Building 2, Kendall Sq, Cambridge MA. This year's event is co-sponsored by the ASA Biopharmaceutical Section and includes a special discounted rate for all ASA Biopharmaceutical Section members! 

As an annual event, the Boston Pharmaceutical Symposium provides a unique venue for sharing statistical applications and research in the biotech-pharma industry, and building connections among all colleagues of the Greater Boston area engaged in the industry statistical practice. We welcome the participation from industry statisticians, academia researchers, as well as university students and any professionals who are interested in pharmaceutical statistical topics.

The 2022 Boston Pharmaceutical Symposium will be a full-day event, featuring a series of invited talks, a poster session, and networking opportunities.

Our speakers

Sandeep M. Menon, PhD, Chief Scientific Officer of AI and Digital Science and SVP, Head of Early Clinical Development at Pfizer

Junjing “Jane” Lin, PhD, Associate Director at Takeda

Peter Henstock, PhD, Senior Director, Biostatistics at Pfizer

Amy Pace, ScD, Vice President, Biostatistics at Parexel

Susan Mayo, PhD, Senior Mathematical Statistician at FDA

Ying Yuan, PhD, Bettyann Asche Murray Distinguished Professor, Department of Biostatistics, University of Texas MD Anderson Cancer Center

Shelby Huang, PhD, Director in Alexion Pharmaceuticals

Ting Wang, PhD, Principal Biostatistician at Biogen

Lorenzo Trippa, PhD, Associate Professor of Biostatistics and Computational Biology, Harvard University and Dana-Farber Cancer Institute

Scientific Committee
Kristin Baltrusaitis, Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health (chair)
Alyssa Biller, Cytel
Wenting Cheng, Biogen
Geoffrey Grove, Cytel
Hrishi Kulkarni, Alexion
Xihao Li, Harvard T.H. Chan School of Public Health
Jianchang Lin, Takeda
Charles Liu, Gilead
Jameson Luks, Cytel
Gautier Paux, Sanofi
Veena Somayaji, Pfizer (host)
Sammi Tang, Servier
Zhaoyang Teng, Servier
Christie Watters, Novartis
Weidong Zhang, Sana Biotechnology



2022 Boston Pharmaceutical Symposium Agenda

8:15 - 8:45am: Registration
8:45 - 8:55am: Welcome address

  • Geoffrey Grove 

8:55 - 9:30am: Keynote

  • Introduction: Veena Somayaji 
  • Sandeep Menon: Achieving End to End Success in the Clinic: Precision Medicine and Role of Quantitative Decision-making

9:30 - 10:30am: Session 1: Novel statistical methods in drug development 

  • Moderator: Jianchang Lin
  • Junjing “Jane” Lin: Statistical Methods of Indirect Comparison with Real-World Data for Survival Endpoint under Non-proportional Hazards 

presentation_slides_Jane_Lin

  • Peter Henstock: Leveraging natural language processing to mine public data sets for scientific, research, and legal insights

presentation_slides_Peter_Henstock

10:30 - 11am: Break 

11 - 12pm: Session 2: Estimands in practice

  • Moderator: Hrishi Kulkarni
  • Amy Pace: Grasping at Estimands 

         presentation_slides_Amy_Pace

  • Susan Mayo: Estimands Implementation: An FDA Reviewer’s Perspective 

             presentation_slides_Susan_Mayo

12 - 1pm: Lunch

1 - 2pm: Session 3: Lightning Talks

  • Moderator: Gautier Paux
  • Timer: Xihao Li 

2 - 2:30pm: Break/ Poster Session

2:30 - 4pm: Session 4: Innovative Bayesian methods in clinical trial design

  • Moderator: Zhaoyang Tang
  • Ying Yuan: A Bayesian Platform Trial Design to Simultaneously Evaluate Multiple Drugs in Multiple Indications with Mixed Endpoints

             presentation_slides_Ying_Yuan

  • Shelby Huang, Ting Wang: Partial Extrapolation in Pediatric Trial Development Using Bayesian Statistics

          presentation_slides_Shelby_Huang_Ting_Wang

  • Lorenzo Trippa: The Design of Hybrid Controlled Trials that Leverage External Data and Randomization

4 - 4:15pm: Closing Remarks

  • Wenting Cheng

 Bio

Keynote: Achieving End to End Success in the Clinic: Precision Medicine and Role of Quantitative Decision-making

Sandeep M. Menon, PhD, Senior Vice President and the Head of Early Clinical Development at Pfizer

Sandeep Menon is the Chief Scientific Officer of AI and Digital Science and SVP, Head of Early Clinical Development at Pfizer Inc., and holds Adjunct faculty positions at Boston University School of Public Health, Tufts University School of Medicine and the Indian Institute of Management. At Pfizer, he is in the Worldwide Research, Development and Medical Leadership Team and leads a multi-functional global team which includes experts in Clinical Sciences, Biostatistics and Bioinformatics, Clinical Pharmacology, Quantitative Systems Pharmacology, Precision Medicine including labs, Digital Medicine which includes Pfizer Research and Innovation (PfIRE) lab, Translational Imaging and Early Scientific Planning and Operations. His responsibilities span into multiple therapeutic areas including Inflammation and Immunology, Oncology, Rare Disease, Anti-Infectives and Cardiovascular and Metabolism. He also leads Digital Medicine PfIRe (Pfizer Innovation and Research) lab with a remit to leverage state of the art technology to enable dynamic and remote monitoring of human behaviors to develop meaningful novel quantitative digital endpoints. During his years at Pfizer Sandeep has held leadership positions of increasing responsibility, from Discovery through Pivotal Studies. Prior to joining Pfizer, he held late-phase leadership roles at Biogen Idec and Aptiv Solutions (now ICON). Before joining the industry, he practiced family medicine in Mumbai and was Resident Medical Officer.

Sandeep is an elected fellow of the American Statistical Association (ASA), awarded the Young Scientist Award by the International Indian Statistical Association, received the Statistical Excellence Award in Pharmaceutical Industry by Royal Statistical Society, UK and recently received the Distinguished Alumni Award from Boston University School of Public Health. He received his medical degree from Bangalore (Karnataka) University, India, and later completed his Masters in Epidemiology and Biostatistics and Ph.D. in Biostatistics at Boston University and research Assistantship at Harvard Clinical Research Institute. He is on the advisory board for the M.S. program at Boston University.  Sandeep served as an associate editor of the ASA journal Statistics in Biopharmaceutical Research and served as an invited committee member of the prestigious Samuel S. Wilks Memorial Award offered by ASA. He has published more than 50 scientific original publications and book chapters and co-authored /co-edited 7 books. He has received several awards for academic, teaching and research excellence.

Bios for Session 1: Innovative Bayesian methods in clinical trial design

Junjing “Jane” Lin, PhD, Associate Director at Takeda

Dr. Jane Lin is an associate director from Takeda. In this capacity, she has been the lead statistician for several early to late-phase oncology trials with rare subpopulations, and provides internal consultation on the topics of external data borrowing and real-world evidence, and has numerous publications in these areas. She is an associate editor of the Journal of Biopharmaceutical Statistics and was a guest editor for the special issue on RWE. She previously worked at AbbVie and obtained doctoral degree in Statistics and Applied Probability from the University of California, Santa Barbara in 2015.

Peter Henstock, PhD, Senior Manager in the Business Technology group at Pfizer

Peter Henstock is the Machine Learning & AI Lead at Pfizer and based in greater Boston.  His work has focused at the intersection of AI, visualization, statistics and software engineering applied mostly to drug discovery but more recently to clinical trials.  Peter holds a PhD in Artificial Intelligence from Purdue University along with 6 Master’s degrees.  He was recognized as being among the top 12 leaders in AI and Pharma globally by the Deep Knowledge Analytics group.  He also currently teaches graduate AI, and Software Engineering courses at Harvard.

Bios for Session 2: Estimands in practice

Amy Pace, ScD, Vice President, Biostatistics at Parexel

Dr. Amy Pace serves as a statistical consultant within the Statistical Center for Innovation at Parexel. She brings over 19 years of experience from within the biotech-pharma industry supporting all phases of drug development, including global regulatory interactions and submissions. She provides statistical leadership for clinical development programs, advising on optimal study designs, protocols, statistical analysis plans, clinical study reports, regulatory submission materials, reimbursement dossiers, and publications. Amy is passionate about mentoring statisticians to support their development.

 

Susan Mayo, PhD, Senior Mathematical Statistician at FDA

After many years as an industry statistician, Susan is a Senior Mathematical Statistician reviewer in CDER since 2018, assigned to pulmonary, allergy and critical care indications.  Susan’s interests in estimands, safety and benefit-risk assessment and graphics have a common thread and focus, addressing the question of scientific interest: How to make clear and precise decisions aligned with the clinical goals of the program by using structured thinking and framing during drug development and reporting, for the benefit of public health.

Bios for Session 4: Innovative Bayesian methods in clinical trial design

Ying Yuan, PhD, Bettyann Asche Murray Distinguished Professor, Department of Biostatistics, University of Texas MD Anderson Cancer Center

Ying Yuan, PhD, is a Bettyann Asche Murray Distinguished Professor and Deputy Chair in the Department of Biostatistics at the University of Texas MD Anderson Cancer Center. Dr. Yuan has published over 100 statistical methodology papers on innovative Bayesian adaptive designs, including early phase trials, seamless trials, biomarker-guided trials, and basket and platform trials. 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 lab is the first oncology dose-finding design designated as a fit-for-purpose drug development tool by FDA. Dr. Yuan was elected as the American Statistical Association Fellow, and wrote book “Bayesian Designs for Phase I-II Clinical Trials” published by Chapman & Hall/CRC.

 

Shelby Huang, PhD, Director at Alexion Pharmaceuticals and Ting Wang, PhD, Principal Biostatistician at Biogen

Shelby Huang is a Director in Alexion Pharmaceuticals. In her over 11 years in the pharmaceutical industry, she has worked in all phases of clinical trials and multiple therapeutic areas such as immunology, neuroscience, rare diseases and infectious diseases. Her areas of interests include integrated clinical development strategy, innovative trial design and Bayesian statistics. She formerly worked in Biogen and led a working group in pediatric studies. She holds a Ph.D. degree in Biostatistics from University of Michigan.

Ting Wang is a principal biostatistician in Biogen. He graduated from University of North Carolina at Chapel Hill with a Ph.D. degree in Biostatistics in 2020 and then joined Biogen Biostatistics. He has worked on the design and analysis of several late phase clinical trials in multiple sclerosis and immunology. His research interests include design and analysis of innovative clinical trials, precision medicine and Bayesian inference.

 

Lorenzo Trippa, PhD, Associate Professor of Biostatistics and Computational Biology, Harvard University and Dana-Farber Cancer Institute

Lorenzo Trippa is Associate Professor of Biostatistics at Harvard and Dana-Farber Cancer Institute.

 Acknowledgements: We thank our colleagues at Pfizer for hosting this event. support from Cytel and the ASA Biopharmaceutical Section is also gratefully acknowledged.