PSI Webinar: Statistical Challenges in Gene Therapy Trials

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

Topic: R Package Basics. 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, “R Package Basics,” will introduce the fundamentals of working with R packages—covering how to install, load, and manage them effectively to support data analysis and reproducible research. The session will provide a solid starting point, clarify common misconceptions, and offer valuable resources for continued learning.

PSI Mentoring 2026

Date: Ongoing 6 month cycle beginning late April/early May 2026 Are you a member of PSI looking to further your career or help develop others - why not sign up to the PSI Mentoring scheme? You can expand your network, improve your leadership skills and learn from more senior colleagues in the industry.

PSI Book Club Lunch and Learn: Communicating with Clarity and Confidence

If you have read Ros Atkins’ book The Art of Explanation or want to listen to the BBC’s ‘Communicator in Chief’, you are invited to join the PSI Book Club Lunch and Learn, to discuss the content and application with the author, Ros Atkins. Having written the book within the context of the news industry, Ros is keen to hear how we have applied the ideas as statisticians within drug development and clinical trials. There will be dedicated time during the webinar to ASK THE AUTHOR any questions – don’t miss out on this exclusive PSI Book Club event! Haven’t read the book yet? Pick up a copy today and join us. Explanation - identifying and communicating what we want to say - is described as an art, in the title of his book. However, the creativity comes from Ros’ discernment in identifying and describing a clear step-by-step process to follow and practice. Readers can learn Ros’ rules, developed and polished throughout his career as a journalist, to help communicate complex written or spoken information clearly.

PSI Training Course: Effective Leadership – the keys to growing your leadership capabilities

This course will consist of three online half-day workshops. The first will be aimed at building trust, the backbone of leadership and a key to becoming effective. This is key to building a solid foundation. The second will be on improving communication as a technical leader. This workshop will focus on communication strategies for different stakeholders and will involve tips on effective communication and how to develop the skills of active listening, coaching and what improv can teach us about good communication. The final workshop will bring these two components together to help leaders become more influential. This will also focus on how to use Steven Covey’s 7-Habits, in particular Habits 4, 5 and 6, which are called the habits of communication. The workshops will be interactive, allowing you to practice the concepts discussed. There will be plenty of time for questions and discussion. There will also be reflective time where you can think about what you are learning and how you might experiment with it.

Speaker	Biography	Abstract
Gerald Downey (Bluebird Bio)	Gerry has over 20 years experience in biostatistics and began his statistical career as an industrial placement student with GlaxoWellcome in 1998, before moving from the UK to the United States to work in academic funded clinical research in HIV. Prior to joining bluebird bio in 2021, Gerry worked in gene therapy at Orchard Therapeutics and Amgen, most recently supporting the regulatory approval and reimbursement of gene therapy products including Libmeldy (@ Orchard) and Imlygic (@ Amgen). In his current role at at bluebird bio, Gerry oversees biostatistics activities for real world evidence and reimbursement dossiers for bbb gene therapy programs.	Gene Therapy, Real-World Data and Real-World Evidence There is a growing interest in whether real-world data (RWD) and real-world evidence (RWE) can be used to supplement evidence from gene therapy clinical studies to support decision making. Statistical issues surrounding gene therapy and specifically rare diseases in the RWD/RWE setting will be discussed.
Shihua Wen (Novartis)	Dr. Shihua Wen is currently a director of biostatistics in Novartis Pharmaceuticals Corp. (US). He joined Novartis in 2016 and started to work in gene therapy area since last year. Dr. Wen has rich experience in late phase clinical development across multiple therapeutic areas. At Novartis, he serves as the statistical lead for global clinical development programs in neurology area and successfully supported multiple regulatory submissions for health authorities’ approval. Prior to Novartis, he worked in Abbott Laboratory / AbbVie Inc. as a biostatistician as well with increasing responsibility. Dr. Wen received his doctoral degree in statistics at University of Maryland, Collage Park, in 2007. His research interests are drug development, benefit-risk assessment, innovative trial design, data fusion, etc.	Estimands in gene therapy trials According to the ICH E9 (R1) guidance, an estimand is a description of the treatment effect associated with a clinical trial objective. Since its final approval and release in 2019, estimand discussion is almost unavoidable in clinical trials design under the regulatory environment. This presentation will look into the estimand used in gene therapy trials, describe the current practice and discuss some potential further improvements.
Chenxuan Zang (Duke University)	Chenxuan is a 2nd-year Master student, studying Biostatistics and Bioinformatics at Duke University School of Medicine. Her research interests include: clinical trial methodology, real-world data/real-world evidence, composite index, statistical genetics.	Statistical Considerations for Gene Therapy in Rare Diseases Clinical Trials For rare disease drug development, one of the challenges is that there are only limited subject available for clinical trials. It is quite difficult to obtain substantial evidence to support effectiveness and safety for approval of a rare disease drug product. However, FDA indicated that the Agency does not have the intention to create a statutory standard for rare disease drug development. In this case, innovative thinking and approach for obtaining substantial evidence need to be applied. Some innovative thinking includes: (1) a probability monitoring procedure for sample size requirement, (2) demonstrating not-ineffectiveness, (3) borrowing real-world data (RWD), (4) using complex innovative design to shorten the process of drug development. In addition, a case study of Luxturna, the first approved gene therapy for a rare disease is discussed.

Speaker	Biography	Abstract
Gerald Downey (Bluebird Bio)	Gerry has over 20 years experience in biostatistics and began his statistical career as an industrial placement student with GlaxoWellcome in 1998, before moving from the UK to the United States to work in academic funded clinical research in HIV. Prior to joining bluebird bio in 2021, Gerry worked in gene therapy at Orchard Therapeutics and Amgen, most recently supporting the regulatory approval and reimbursement of gene therapy products including Libmeldy (@ Orchard) and Imlygic (@ Amgen). In his current role at at bluebird bio, Gerry oversees biostatistics activities for real world evidence and reimbursement dossiers for bbb gene therapy programs.	Gene Therapy, Real-World Data and Real-World Evidence There is a growing interest in whether real-world data (RWD) and real-world evidence (RWE) can be used to supplement evidence from gene therapy clinical studies to support decision making. Statistical issues surrounding gene therapy and specifically rare diseases in the RWD/RWE setting will be discussed.
Shihua Wen (Novartis)	Dr. Shihua Wen is currently a director of biostatistics in Novartis Pharmaceuticals Corp. (US). He joined Novartis in 2016 and started to work in gene therapy area since last year. Dr. Wen has rich experience in late phase clinical development across multiple therapeutic areas. At Novartis, he serves as the statistical lead for global clinical development programs in neurology area and successfully supported multiple regulatory submissions for health authorities’ approval. Prior to Novartis, he worked in Abbott Laboratory / AbbVie Inc. as a biostatistician as well with increasing responsibility. Dr. Wen received his doctoral degree in statistics at University of Maryland, Collage Park, in 2007. His research interests are drug development, benefit-risk assessment, innovative trial design, data fusion, etc.	Estimands in gene therapy trials According to the ICH E9 (R1) guidance, an estimand is a description of the treatment effect associated with a clinical trial objective. Since its final approval and release in 2019, estimand discussion is almost unavoidable in clinical trials design under the regulatory environment. This presentation will look into the estimand used in gene therapy trials, describe the current practice and discuss some potential further improvements.
Chenxuan Zang (Duke University)	Chenxuan is a 2nd-year Master student, studying Biostatistics and Bioinformatics at Duke University School of Medicine. Her research interests include: clinical trial methodology, real-world data/real-world evidence, composite index, statistical genetics.	Statistical Considerations for Gene Therapy in Rare Diseases Clinical Trials For rare disease drug development, one of the challenges is that there are only limited subject available for clinical trials. It is quite difficult to obtain substantial evidence to support effectiveness and safety for approval of a rare disease drug product. However, FDA indicated that the Agency does not have the intention to create a statutory standard for rare disease drug development. In this case, innovative thinking and approach for obtaining substantial evidence need to be applied. Some innovative thinking includes: (1) a probability monitoring procedure for sample size requirement, (2) demonstrating not-ineffectiveness, (3) borrowing real-world data (RWD), (4) using complex innovative design to shorten the process of drug development. In addition, a case study of Luxturna, the first approved gene therapy for a rare disease is discussed.

Speaker	Biography	Abstract
Gerald Downey (Bluebird Bio)	Gerry has over 20 years experience in biostatistics and began his statistical career as an industrial placement student with GlaxoWellcome in 1998, before moving from the UK to the United States to work in academic funded clinical research in HIV. Prior to joining bluebird bio in 2021, Gerry worked in gene therapy at Orchard Therapeutics and Amgen, most recently supporting the regulatory approval and reimbursement of gene therapy products including Libmeldy (@ Orchard) and Imlygic (@ Amgen). In his current role at at bluebird bio, Gerry oversees biostatistics activities for real world evidence and reimbursement dossiers for bbb gene therapy programs.	Gene Therapy, Real-World Data and Real-World Evidence There is a growing interest in whether real-world data (RWD) and real-world evidence (RWE) can be used to supplement evidence from gene therapy clinical studies to support decision making. Statistical issues surrounding gene therapy and specifically rare diseases in the RWD/RWE setting will be discussed.
Shihua Wen (Novartis)	Dr. Shihua Wen is currently a director of biostatistics in Novartis Pharmaceuticals Corp. (US). He joined Novartis in 2016 and started to work in gene therapy area since last year. Dr. Wen has rich experience in late phase clinical development across multiple therapeutic areas. At Novartis, he serves as the statistical lead for global clinical development programs in neurology area and successfully supported multiple regulatory submissions for health authorities’ approval. Prior to Novartis, he worked in Abbott Laboratory / AbbVie Inc. as a biostatistician as well with increasing responsibility. Dr. Wen received his doctoral degree in statistics at University of Maryland, Collage Park, in 2007. His research interests are drug development, benefit-risk assessment, innovative trial design, data fusion, etc.	Estimands in gene therapy trials According to the ICH E9 (R1) guidance, an estimand is a description of the treatment effect associated with a clinical trial objective. Since its final approval and release in 2019, estimand discussion is almost unavoidable in clinical trials design under the regulatory environment. This presentation will look into the estimand used in gene therapy trials, describe the current practice and discuss some potential further improvements.
Chenxuan Zang (Duke University)	Chenxuan is a 2nd-year Master student, studying Biostatistics and Bioinformatics at Duke University School of Medicine. Her research interests include: clinical trial methodology, real-world data/real-world evidence, composite index, statistical genetics.	Statistical Considerations for Gene Therapy in Rare Diseases Clinical Trials For rare disease drug development, one of the challenges is that there are only limited subject available for clinical trials. It is quite difficult to obtain substantial evidence to support effectiveness and safety for approval of a rare disease drug product. However, FDA indicated that the Agency does not have the intention to create a statutory standard for rare disease drug development. In this case, innovative thinking and approach for obtaining substantial evidence need to be applied. Some innovative thinking includes: (1) a probability monitoring procedure for sample size requirement, (2) demonstrating not-ineffectiveness, (3) borrowing real-world data (RWD), (4) using complex innovative design to shorten the process of drug development. In addition, a case study of Luxturna, the first approved gene therapy for a rare disease is discussed.

Speaker	Biography	Abstract
Gerald Downey (Bluebird Bio)	Gerry has over 20 years experience in biostatistics and began his statistical career as an industrial placement student with GlaxoWellcome in 1998, before moving from the UK to the United States to work in academic funded clinical research in HIV. Prior to joining bluebird bio in 2021, Gerry worked in gene therapy at Orchard Therapeutics and Amgen, most recently supporting the regulatory approval and reimbursement of gene therapy products including Libmeldy (@ Orchard) and Imlygic (@ Amgen). In his current role at at bluebird bio, Gerry oversees biostatistics activities for real world evidence and reimbursement dossiers for bbb gene therapy programs.	Gene Therapy, Real-World Data and Real-World Evidence There is a growing interest in whether real-world data (RWD) and real-world evidence (RWE) can be used to supplement evidence from gene therapy clinical studies to support decision making. Statistical issues surrounding gene therapy and specifically rare diseases in the RWD/RWE setting will be discussed.
Shihua Wen (Novartis)	Dr. Shihua Wen is currently a director of biostatistics in Novartis Pharmaceuticals Corp. (US). He joined Novartis in 2016 and started to work in gene therapy area since last year. Dr. Wen has rich experience in late phase clinical development across multiple therapeutic areas. At Novartis, he serves as the statistical lead for global clinical development programs in neurology area and successfully supported multiple regulatory submissions for health authorities’ approval. Prior to Novartis, he worked in Abbott Laboratory / AbbVie Inc. as a biostatistician as well with increasing responsibility. Dr. Wen received his doctoral degree in statistics at University of Maryland, Collage Park, in 2007. His research interests are drug development, benefit-risk assessment, innovative trial design, data fusion, etc.	Estimands in gene therapy trials According to the ICH E9 (R1) guidance, an estimand is a description of the treatment effect associated with a clinical trial objective. Since its final approval and release in 2019, estimand discussion is almost unavoidable in clinical trials design under the regulatory environment. This presentation will look into the estimand used in gene therapy trials, describe the current practice and discuss some potential further improvements.
Chenxuan Zang (Duke University)	Chenxuan is a 2nd-year Master student, studying Biostatistics and Bioinformatics at Duke University School of Medicine. Her research interests include: clinical trial methodology, real-world data/real-world evidence, composite index, statistical genetics.	Statistical Considerations for Gene Therapy in Rare Diseases Clinical Trials For rare disease drug development, one of the challenges is that there are only limited subject available for clinical trials. It is quite difficult to obtain substantial evidence to support effectiveness and safety for approval of a rare disease drug product. However, FDA indicated that the Agency does not have the intention to create a statutory standard for rare disease drug development. In this case, innovative thinking and approach for obtaining substantial evidence need to be applied. Some innovative thinking includes: (1) a probability monitoring procedure for sample size requirement, (2) demonstrating not-ineffectiveness, (3) borrowing real-world data (RWD), (4) using complex innovative design to shorten the process of drug development. In addition, a case study of Luxturna, the first approved gene therapy for a rare disease is discussed.

Speaker	Biography	Abstract
Gerald Downey (Bluebird Bio)	Gerry has over 20 years experience in biostatistics and began his statistical career as an industrial placement student with GlaxoWellcome in 1998, before moving from the UK to the United States to work in academic funded clinical research in HIV. Prior to joining bluebird bio in 2021, Gerry worked in gene therapy at Orchard Therapeutics and Amgen, most recently supporting the regulatory approval and reimbursement of gene therapy products including Libmeldy (@ Orchard) and Imlygic (@ Amgen). In his current role at at bluebird bio, Gerry oversees biostatistics activities for real world evidence and reimbursement dossiers for bbb gene therapy programs.	Gene Therapy, Real-World Data and Real-World Evidence There is a growing interest in whether real-world data (RWD) and real-world evidence (RWE) can be used to supplement evidence from gene therapy clinical studies to support decision making. Statistical issues surrounding gene therapy and specifically rare diseases in the RWD/RWE setting will be discussed.
Shihua Wen (Novartis)	Dr. Shihua Wen is currently a director of biostatistics in Novartis Pharmaceuticals Corp. (US). He joined Novartis in 2016 and started to work in gene therapy area since last year. Dr. Wen has rich experience in late phase clinical development across multiple therapeutic areas. At Novartis, he serves as the statistical lead for global clinical development programs in neurology area and successfully supported multiple regulatory submissions for health authorities’ approval. Prior to Novartis, he worked in Abbott Laboratory / AbbVie Inc. as a biostatistician as well with increasing responsibility. Dr. Wen received his doctoral degree in statistics at University of Maryland, Collage Park, in 2007. His research interests are drug development, benefit-risk assessment, innovative trial design, data fusion, etc.	Estimands in gene therapy trials According to the ICH E9 (R1) guidance, an estimand is a description of the treatment effect associated with a clinical trial objective. Since its final approval and release in 2019, estimand discussion is almost unavoidable in clinical trials design under the regulatory environment. This presentation will look into the estimand used in gene therapy trials, describe the current practice and discuss some potential further improvements.
Chenxuan Zang (Duke University)	Chenxuan is a 2nd-year Master student, studying Biostatistics and Bioinformatics at Duke University School of Medicine. Her research interests include: clinical trial methodology, real-world data/real-world evidence, composite index, statistical genetics.	Statistical Considerations for Gene Therapy in Rare Diseases Clinical Trials For rare disease drug development, one of the challenges is that there are only limited subject available for clinical trials. It is quite difficult to obtain substantial evidence to support effectiveness and safety for approval of a rare disease drug product. However, FDA indicated that the Agency does not have the intention to create a statutory standard for rare disease drug development. In this case, innovative thinking and approach for obtaining substantial evidence need to be applied. Some innovative thinking includes: (1) a probability monitoring procedure for sample size requirement, (2) demonstrating not-ineffectiveness, (3) borrowing real-world data (RWD), (4) using complex innovative design to shorten the process of drug development. In addition, a case study of Luxturna, the first approved gene therapy for a rare disease is discussed.

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