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 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.

In lieu of an in-person event, the Fifth Boston Pharmaceutical Symposium included a series of five free webinars hosted on Fridays throughout the summer and fall of 2021. Below is the event information.

Fifth Boston Pharmaceutical Symposium

Virtual Seminar Series by the Boston Chapter of the ASA

The Boston Chapter of the American Statistical Association (BCASA) invites you all to attend the Fifth Boston Pharmaceutical Symposium. In lieu of an in-person event, the Fifth Boston Pharmaceutical Symposium will include a series of five free webinars hosted on Fridays throughout the summer and fall of 2021.

Webinar Schedule

July 23rd, 10am - 11:30am: Use of Real World Data/Real World Evidence in Clinical Development (Presentation on BCASA Youtube channel: July 23 2021 webinar), Qing Li, Senior Manager, Takeda

September 3rd, 9am - 10am: Adaptive Designs for Optimal Dose Determination in I-O and Cell Therapy, Rachel Liu, Associate Director, Takeda

September 17th, 11am - 12pm. Design Considerations in a COVID-19 Platform Trial - Experience from the ACTIV-2 Trial (Presentation on BCASA Youtube channel: Sept 17 2021 webinar), Michael Hughes, Director, Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health

October 22nd, 12pm - 1pm: Bayesian Methods for Historical Data Borrowing (Presentation on BCASA Youtube Channel: Oct 22 2021 webinar), Sammi Tang, Global head of Biometrics, Oncology, Servier, and Chenkun Wang, Associate Director of Biostatistics, Vertex

October 29, 10am - 11am: Novel Design and Implementation of Interim and Final Analyses in the Sham-Controlled Double Blind Randomized Phase III Studies in Spinal Muscular Atrophy (Presentation on BCASA Youtube Channel: Oct 29 2021 webinar), Peng Sun, Senior Director, Biostatistics, Biogen

Bio and Abstract

Use of Real World Data/Real World Evidence in Clinical Development

Speaker: Qing Li, Senior Manager, Takeda


In recent years, the rapid increase in the volume, variety, and accessibility of digitized RWD and RWE has presented unprecedented opportunities for the use of RWD and RWE throughout the drug product lifecycle. We believe RWD and RWE will be leading the statistical innovation in healthcare industry and regulatory decision making for the next decades. In clinical development, RWD and RWE have the potential to improve the planning and execution of clinical trials and create a virtual control arm for a single arm for accelerated approval and label expansion. From the product lifecycle perspective, effective insights gleaned from RWE bring about informative relative benefits of drugs, comparative effectiveness, price optimization, and new indications.  Aiming to present a wide range of RWE applications throughout the lifecycle of drug product development, we have written a book "Real-World Evidence in Drug Development and Evaluation" which was published in February 2021. At the 2021 Boston Pharma Symposium, we are excited to share with researchers Chapter 4 – External Control Using RWE and Historical Data in Clinical Development. This seminar will discuss the recent case studies that adopted RWD and RWE in the clinical development and evaluation from the following perspectives:

  • Utilize synthetic control to support single arm study
  • Utilize natural history study for rare disease development
  • Utilize RWD/historical data for label expansion
  • Practical considerations of using RWD/historical data in the clinical development

Speaker Bio:

Dr. Qing Li is a senior manager in the statistics and quantitative science department at Takeda Pharmaceutical Company. His responsibilities include statistical methodology development and consultation for real-world-evidence and advanced adaptive design from proof-of-concept to late phase studies across multiple therapeutic areas including oncology, gastroenterology, rare disease, and vaccine. His research interests include propensity score methods, RWE, adaptive designs, Immuno-Oncology design and surrogate endpoints. He also serves as stat lead for several studies and programs for lymphoma and multiple myeloma diseases. He obtained his MS and PhD degree in biostatistics from the University of Iowa. 

Adaptive Designs for Optimal Dose Determination in I-O and Cell Therapy

Speaker: Rachel Liu, Associate Director, Takeda


Immuno-oncology (I-O) and cell therapy, the frontier of cancer treatment, is a rapidly developing area that brings new opportunities to patients. It is critical to identify optimal dose and patient populations in early phase of trials thus improving the probability of success in pivotal trials. Given the complex mechanism interacting with immune system and patient heterogeneity, the conventional oncology dose finding design may not serve the purpose. For example, it is questionable to believe the monotone relationship between dose level and safety/efficacy, which will likely result in inappropriate dose selection using designs with monotone assumption. Additionally, considering the immune system pathway, designs ignoring the heterogeneity of the patient populations may provide misleading dose decisions, which could be either unsafe or lead to selection mistakes for targeted population.

This seminar will provide a review and discussion of innovative designs for optimal dose determination in I-O and Cell Therapy from the following perspectives

  • Dose finding focusing on DLT
  • Dose finding considering late onset toxicity
  • Dose finding in basket trials with borrowing scheme
  • Optimal dose identification design incorporating both safety and efficacy endpoints

Speaker Bio:

Dr. Rachael Liu is an Associate Director in the statistics and quantitative science department at Takeda Pharmaceutical Company. Her research interests include dose finding design, adaptive designs, master protocol, machine learning and RWE. She has also served as statistical leader for multiple early and late phase oncology and cell therapy programs. Rachael is passionate about bringing innovation to clinical development.

Design Considerations in a COVID-19 Platform Trial -- Experience from the ACTIV-2 Trial

Speaker: Michael Hughes, Director, Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health


ACTIV-2 is a major international platform trial led by the NIH-funded AIDS Clinical Trials  Group.  It was designed in response to the COVID-19 pandemic and has evaluated several candidate agents for the treatment of non-hospitalized people with symptomatic COVID-19, with the aim of reducing hospitalizations and deaths.  The design incorporates novel design features including the sharing of placebo control groups, potentially with different placebos for each candidate agent, and a seamless transition from phase 2 to phase 3 evaluation.  I will discuss the design and implementation of this complex trial.

Speaker Bio:

Dr. Hughes is Professor of Biostatistics at Harvard TH Chan School of Public Health and Director of the School's Center for Biostatistics in AIDS Research.  His research focuses on study design and analysis issues in infectious diseases clinical trials and ancillary pathogenesis and drug mechanism studies, particularly related to HIV, tuberculosis, viral hepatitis, influenza and now COVID-19. He is Principal Investigator of the Statistical and Data Management Center for the NIH-funded AIDS Clinical Trials Group, the largest international HIV therapeutic clinical trials network.  He also is Statistical Editor for the Journal of Infectious Diseases, a Fellow of the American Statistical Association, and the Bradford-Hill Lecturer for the Royal Statistical Society in 2019. 

Methods and Case Studies Review by DIA NEED Methods and Case Studies Review by DIA NEED

Speakers: Sammi Tang, Global head of Biometrics, Oncology, Servier, Rong Liu, Senior Director of Biostatistics, BMS, and Chenkun Wang, Associate Director of Biostatistics, Vertex


In life-threatening/rare diseases, randomized controlled trial often runs into feasibility and even ethical issue. Single-arm interventional trial with historical control (HC) as the comparator, highlighted in the recent FDA Real World Evidence (RWE) framework, provides an alternative approach to assess the effectiveness of the investigative therapy in these challenging scenarios. A roadmap of using HC in clinical trials by DIA NEED team will be introduced and then followed by the discussions on statistical methodologies commonly used with HC. In the end, a few selected NDA/BLA filing cases, where HC was used as the comparator in the pivotal trials, will be presented, providing some practical guidance on incorporating historical data from the stage of trial design to the stage of data analysis. Our main findings and recommendation are published at Orphanet Journal of Rare Diseases in 2020.


Novel Design and Implementation of Interim and Final Analyses in the Sham-Controlled Double Blind Randomized Phase III Studies in Spinal Muscular Atrophy

Speaker: Peng Sun, Senior Director, Biostatistics, Biogen


In December 2016, Spinraza became the first approved drug for the treatment of Spinal Muscular Atrophy (SMA), a rare and debilitating neuromuscular disorder. There are two pivotal Phase 3 studies in the Spinraza program: ENDEAR and CHERSIH. Both studies were stopped early due to efficacy. In this talk, we will discuss various statistical challenges in the successful planning and execution of the interim analyses for both studies. Topics will include novel endpoint development, multiplicity adjustment in the group sequential setting, implementation of the multiple imputation (MI) approach, and analysis of functional endpoint truncated by death, among others.

Speaker Bio:

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 joined Biogen in 2015 and he severed as the lead statistician for the global submission of Spinraza, the first approved drug for the treatment of spinal muscular atrophy (SMA). Peng is currently the statistics lead for the neuromuscular franchise at Biogen.