Past PSI Events

Conferences

PSI Scientific Committee Webinar: Rare Diseases: Regulatory and Study Design Considerations

 

U.S. regulatory considerations and case studies for rare diseases
In this talk, I will present an overview of the U.S. Food and Drug Administration’s policies and practices for encouraging development of products for rare diseases and of evaluating clinical evidence for the safety and effectiveness of such products. I’ll discuss study designs that may be particularly appropriate for rare disease product development, and address some of their statistical implications. Finally, I’ll present case studies of products that were approved for rare diseases using unusual or innovative study designs and/or regulatory pathways.
John Scott   John Scott is Deputy Director of the Division of Biostatistics in the FDA's Center for Biologics Evaluation and Research, where he has also served as a statistical reviewer for blood products and for cellular, tissue and gene therapies. Prior to joining the FDA in 2008, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital, Harvard Medical School. He has authored or co-authored numerous articles in areas including Bayesian and adaptive clinical trial design and analysis, drug and vaccine safety, data and text mining, and benefit-risk assessment. He holds a Ph.D. in Biostatistics from the University of Pittsburgh and an M.A. in Mathematics from Washington University in St. Louis, and is an associate editor of the journal, Pharmaceutical Statistics.


Bayesian methods for the design and interpretation of clinical trials in rare diseases
For studies in rare diseases, the sample size needed to meet a conventional frequentist power requirement can be daunting, even if patients are to be recruited over several years. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose Bayesian approaches for the conduct of rare disease trials comparing an experimental treatment with a control when the primary endpoint is binary or normally distributed. We describe processes which can be used to systematically elicit from clinicians opinions on treatment efficacy in order to establish Bayesian priors for unknown model parameters. The proposed approaches are illustrated by describing applications to two Bayesian randomised controlled trials, namely a study in childhood polyarteritis nodosa and a study in chronic recurrent multifocal osteomyelitis. Once prior distributions have been established, consideration of the extent to which opinion can be changed, even by the best feasible design, can help to determine whether a small trial is worthwhile.
 
 Lisa Hampson  Lisa Hampson is a Lecturer in Statistics at Lancaster University. Her research interests are in clinical trials, including group sequential tests and Bayesian methods for trials in rare diseases and dose-escalation. Her recent research has focused on developing methods for clinical trials of new medicines for children. She holds a PhD in Statistics from the University of Bath. 

To access the recording, please visit the Video-on-Demand Library.

Scientific Meetings

PSI Scientific Committee Webinar: Rare Diseases: Regulatory and Study Design Considerations

 

U.S. regulatory considerations and case studies for rare diseases
In this talk, I will present an overview of the U.S. Food and Drug Administration’s policies and practices for encouraging development of products for rare diseases and of evaluating clinical evidence for the safety and effectiveness of such products. I’ll discuss study designs that may be particularly appropriate for rare disease product development, and address some of their statistical implications. Finally, I’ll present case studies of products that were approved for rare diseases using unusual or innovative study designs and/or regulatory pathways.
John Scott   John Scott is Deputy Director of the Division of Biostatistics in the FDA's Center for Biologics Evaluation and Research, where he has also served as a statistical reviewer for blood products and for cellular, tissue and gene therapies. Prior to joining the FDA in 2008, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital, Harvard Medical School. He has authored or co-authored numerous articles in areas including Bayesian and adaptive clinical trial design and analysis, drug and vaccine safety, data and text mining, and benefit-risk assessment. He holds a Ph.D. in Biostatistics from the University of Pittsburgh and an M.A. in Mathematics from Washington University in St. Louis, and is an associate editor of the journal, Pharmaceutical Statistics.


Bayesian methods for the design and interpretation of clinical trials in rare diseases
For studies in rare diseases, the sample size needed to meet a conventional frequentist power requirement can be daunting, even if patients are to be recruited over several years. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose Bayesian approaches for the conduct of rare disease trials comparing an experimental treatment with a control when the primary endpoint is binary or normally distributed. We describe processes which can be used to systematically elicit from clinicians opinions on treatment efficacy in order to establish Bayesian priors for unknown model parameters. The proposed approaches are illustrated by describing applications to two Bayesian randomised controlled trials, namely a study in childhood polyarteritis nodosa and a study in chronic recurrent multifocal osteomyelitis. Once prior distributions have been established, consideration of the extent to which opinion can be changed, even by the best feasible design, can help to determine whether a small trial is worthwhile.
 
 Lisa Hampson  Lisa Hampson is a Lecturer in Statistics at Lancaster University. Her research interests are in clinical trials, including group sequential tests and Bayesian methods for trials in rare diseases and dose-escalation. Her recent research has focused on developing methods for clinical trials of new medicines for children. She holds a PhD in Statistics from the University of Bath. 

To access the recording, please visit the Video-on-Demand Library.

Training Courses

PSI Scientific Committee Webinar: Rare Diseases: Regulatory and Study Design Considerations

 

U.S. regulatory considerations and case studies for rare diseases
In this talk, I will present an overview of the U.S. Food and Drug Administration’s policies and practices for encouraging development of products for rare diseases and of evaluating clinical evidence for the safety and effectiveness of such products. I’ll discuss study designs that may be particularly appropriate for rare disease product development, and address some of their statistical implications. Finally, I’ll present case studies of products that were approved for rare diseases using unusual or innovative study designs and/or regulatory pathways.
John Scott   John Scott is Deputy Director of the Division of Biostatistics in the FDA's Center for Biologics Evaluation and Research, where he has also served as a statistical reviewer for blood products and for cellular, tissue and gene therapies. Prior to joining the FDA in 2008, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital, Harvard Medical School. He has authored or co-authored numerous articles in areas including Bayesian and adaptive clinical trial design and analysis, drug and vaccine safety, data and text mining, and benefit-risk assessment. He holds a Ph.D. in Biostatistics from the University of Pittsburgh and an M.A. in Mathematics from Washington University in St. Louis, and is an associate editor of the journal, Pharmaceutical Statistics.


Bayesian methods for the design and interpretation of clinical trials in rare diseases
For studies in rare diseases, the sample size needed to meet a conventional frequentist power requirement can be daunting, even if patients are to be recruited over several years. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose Bayesian approaches for the conduct of rare disease trials comparing an experimental treatment with a control when the primary endpoint is binary or normally distributed. We describe processes which can be used to systematically elicit from clinicians opinions on treatment efficacy in order to establish Bayesian priors for unknown model parameters. The proposed approaches are illustrated by describing applications to two Bayesian randomised controlled trials, namely a study in childhood polyarteritis nodosa and a study in chronic recurrent multifocal osteomyelitis. Once prior distributions have been established, consideration of the extent to which opinion can be changed, even by the best feasible design, can help to determine whether a small trial is worthwhile.
 
 Lisa Hampson  Lisa Hampson is a Lecturer in Statistics at Lancaster University. Her research interests are in clinical trials, including group sequential tests and Bayesian methods for trials in rare diseases and dose-escalation. Her recent research has focused on developing methods for clinical trials of new medicines for children. She holds a PhD in Statistics from the University of Bath. 

To access the recording, please visit the Video-on-Demand Library.

Journal Club

PSI Scientific Committee Webinar: Rare Diseases: Regulatory and Study Design Considerations

 

U.S. regulatory considerations and case studies for rare diseases
In this talk, I will present an overview of the U.S. Food and Drug Administration’s policies and practices for encouraging development of products for rare diseases and of evaluating clinical evidence for the safety and effectiveness of such products. I’ll discuss study designs that may be particularly appropriate for rare disease product development, and address some of their statistical implications. Finally, I’ll present case studies of products that were approved for rare diseases using unusual or innovative study designs and/or regulatory pathways.
John Scott   John Scott is Deputy Director of the Division of Biostatistics in the FDA's Center for Biologics Evaluation and Research, where he has also served as a statistical reviewer for blood products and for cellular, tissue and gene therapies. Prior to joining the FDA in 2008, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital, Harvard Medical School. He has authored or co-authored numerous articles in areas including Bayesian and adaptive clinical trial design and analysis, drug and vaccine safety, data and text mining, and benefit-risk assessment. He holds a Ph.D. in Biostatistics from the University of Pittsburgh and an M.A. in Mathematics from Washington University in St. Louis, and is an associate editor of the journal, Pharmaceutical Statistics.


Bayesian methods for the design and interpretation of clinical trials in rare diseases
For studies in rare diseases, the sample size needed to meet a conventional frequentist power requirement can be daunting, even if patients are to be recruited over several years. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose Bayesian approaches for the conduct of rare disease trials comparing an experimental treatment with a control when the primary endpoint is binary or normally distributed. We describe processes which can be used to systematically elicit from clinicians opinions on treatment efficacy in order to establish Bayesian priors for unknown model parameters. The proposed approaches are illustrated by describing applications to two Bayesian randomised controlled trials, namely a study in childhood polyarteritis nodosa and a study in chronic recurrent multifocal osteomyelitis. Once prior distributions have been established, consideration of the extent to which opinion can be changed, even by the best feasible design, can help to determine whether a small trial is worthwhile.
 
 Lisa Hampson  Lisa Hampson is a Lecturer in Statistics at Lancaster University. Her research interests are in clinical trials, including group sequential tests and Bayesian methods for trials in rare diseases and dose-escalation. Her recent research has focused on developing methods for clinical trials of new medicines for children. She holds a PhD in Statistics from the University of Bath. 

To access the recording, please visit the Video-on-Demand Library.

Webinars

PSI Scientific Committee Webinar: Rare Diseases: Regulatory and Study Design Considerations

 

U.S. regulatory considerations and case studies for rare diseases
In this talk, I will present an overview of the U.S. Food and Drug Administration’s policies and practices for encouraging development of products for rare diseases and of evaluating clinical evidence for the safety and effectiveness of such products. I’ll discuss study designs that may be particularly appropriate for rare disease product development, and address some of their statistical implications. Finally, I’ll present case studies of products that were approved for rare diseases using unusual or innovative study designs and/or regulatory pathways.
John Scott   John Scott is Deputy Director of the Division of Biostatistics in the FDA's Center for Biologics Evaluation and Research, where he has also served as a statistical reviewer for blood products and for cellular, tissue and gene therapies. Prior to joining the FDA in 2008, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital, Harvard Medical School. He has authored or co-authored numerous articles in areas including Bayesian and adaptive clinical trial design and analysis, drug and vaccine safety, data and text mining, and benefit-risk assessment. He holds a Ph.D. in Biostatistics from the University of Pittsburgh and an M.A. in Mathematics from Washington University in St. Louis, and is an associate editor of the journal, Pharmaceutical Statistics.


Bayesian methods for the design and interpretation of clinical trials in rare diseases
For studies in rare diseases, the sample size needed to meet a conventional frequentist power requirement can be daunting, even if patients are to be recruited over several years. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose Bayesian approaches for the conduct of rare disease trials comparing an experimental treatment with a control when the primary endpoint is binary or normally distributed. We describe processes which can be used to systematically elicit from clinicians opinions on treatment efficacy in order to establish Bayesian priors for unknown model parameters. The proposed approaches are illustrated by describing applications to two Bayesian randomised controlled trials, namely a study in childhood polyarteritis nodosa and a study in chronic recurrent multifocal osteomyelitis. Once prior distributions have been established, consideration of the extent to which opinion can be changed, even by the best feasible design, can help to determine whether a small trial is worthwhile.
 
 Lisa Hampson  Lisa Hampson is a Lecturer in Statistics at Lancaster University. Her research interests are in clinical trials, including group sequential tests and Bayesian methods for trials in rare diseases and dose-escalation. Her recent research has focused on developing methods for clinical trials of new medicines for children. She holds a PhD in Statistics from the University of Bath. 

To access the recording, please visit the Video-on-Demand Library.

Careers Meetings

PSI Scientific Committee Webinar: Rare Diseases: Regulatory and Study Design Considerations

 

U.S. regulatory considerations and case studies for rare diseases
In this talk, I will present an overview of the U.S. Food and Drug Administration’s policies and practices for encouraging development of products for rare diseases and of evaluating clinical evidence for the safety and effectiveness of such products. I’ll discuss study designs that may be particularly appropriate for rare disease product development, and address some of their statistical implications. Finally, I’ll present case studies of products that were approved for rare diseases using unusual or innovative study designs and/or regulatory pathways.
John Scott   John Scott is Deputy Director of the Division of Biostatistics in the FDA's Center for Biologics Evaluation and Research, where he has also served as a statistical reviewer for blood products and for cellular, tissue and gene therapies. Prior to joining the FDA in 2008, he worked in psychiatric clinical trials at the University of Pittsburgh Medical Center and did neuroimaging research with the Neurostatistics Laboratory at McClean Hospital, Harvard Medical School. He has authored or co-authored numerous articles in areas including Bayesian and adaptive clinical trial design and analysis, drug and vaccine safety, data and text mining, and benefit-risk assessment. He holds a Ph.D. in Biostatistics from the University of Pittsburgh and an M.A. in Mathematics from Washington University in St. Louis, and is an associate editor of the journal, Pharmaceutical Statistics.


Bayesian methods for the design and interpretation of clinical trials in rare diseases
For studies in rare diseases, the sample size needed to meet a conventional frequentist power requirement can be daunting, even if patients are to be recruited over several years. Rather, the expectation of any such trial has to be limited to the generation of an improved understanding of treatment options. We propose Bayesian approaches for the conduct of rare disease trials comparing an experimental treatment with a control when the primary endpoint is binary or normally distributed. We describe processes which can be used to systematically elicit from clinicians opinions on treatment efficacy in order to establish Bayesian priors for unknown model parameters. The proposed approaches are illustrated by describing applications to two Bayesian randomised controlled trials, namely a study in childhood polyarteritis nodosa and a study in chronic recurrent multifocal osteomyelitis. Once prior distributions have been established, consideration of the extent to which opinion can be changed, even by the best feasible design, can help to determine whether a small trial is worthwhile.
 
 Lisa Hampson  Lisa Hampson is a Lecturer in Statistics at Lancaster University. Her research interests are in clinical trials, including group sequential tests and Bayesian methods for trials in rare diseases and dose-escalation. Her recent research has focused on developing methods for clinical trials of new medicines for children. She holds a PhD in Statistics from the University of Bath. 

To access the recording, please visit the Video-on-Demand Library.

Upcoming Events

PSI Introduction to Industry Training (ITIT) Course - 2026/2027

An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.

Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars

Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.

AIMS SIG - Open-Source Lunch Bites

Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “Graphics Basics,” will introduce the fundamentals of producing graphics using the ggplot2 package.

PSI Career Young Virtual Event (Q2 2026)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

PSI Book Club: The AI Con – Joint with ASA Book Club

The Guardian described the authors of this book as refreshingly sarcastic! What is sold to us as AI, they announce, is just "a bill of goods": "A few major well-placed players are poised to accumulate significant wealth by extracting value from other people's creative work, personal data, or labour, and replacing quality services with artificial facsimiles."

Causal Inference SIG and EFSPI Methods Leaders: Modern Covariate Adjustment in Clinical Trials

This webinar will discuss modern approaches to covariate adjustment in clinical trials. We begin with the motivation and key principles underlying the FDA guidance, then revisit established methodologies in light of these regulatory considerations. Building on this foundation, we explore extensions to more advanced applications in clinical trial analysis. The webinar concludes with an outlook on future developments and a panel discussion.

PSI Book Club: Another Door Opens – Book Club Special Event

This is a Book Club Special Event in response to the changes in our industry and as a supportive move to create community and connection for those navigating redundancy and uncertainty. Read the book in advance of the book club session then join the zoom call to discuss ideas. There will be breakout groups to connect with others, exchange experiences of how the book has helped, and offer support.

PSI Book Club: Change: How organisations achieve hard-to-image results in uncertain and volatile times

Organizations have to adapt to the transforming landscape of our industry to ensure they continue to be successful in the future. Many of us are feeling the impact of organizational change. By reading John P Kotter’s book we can understand about organizational change and learn how to thrive, rather than just survive, through change. Change, by John P Kotter (and his team), is a summary of all that he has learned over his decades of research and leading change. His book describes why many current approaches to change are inadequate and explains why new solutions need to give people a voice and a role in a new, change-embracing organization. Develop your understanding of organisational change and become empowered to be part of your organisation’s change, by reading Change by John P Kotter and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply knowledge from the book in-between sessions.

PSI Career Young Virtual Event (Q3 2026)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

PSI Training Course: Propensity Scores: Practical Application in Non-randomised Studies

The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.

PSI Career Young Virtual Event (Q4 2026)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

Latest Jobs

Bayer - Lead Statistician

A Lead Statistician builds and leads teams of statisticians and representatives from other functions and ensures the use of appropriate and efficient statistical analysis methods during development of Bayer products

Leeds Clinical Trials Research Unit - Undergraduate Internships

The Internship is open to undergraduate students in the penultimate year of their undergraduate degree at a UK university, in a mathematical, statistical, or quantitative related field.

Metronomia Clinical Research GmbH - Principal Statistician

Join a motivated and friendly team and help shape Metronomia as a Principal Statistician

Veramed - Senior Statistician

As a Senior Statistician, you will provide high-quality statistical support to one of our key-FSP clients. At Senior level you may also take on a supervisory role (e.g. line management and/or project management), depending on your experience and interest.