Who is this event intended for? Statisticans working in - or interested in - gene therapy treatments. What is the benefit of attending? Attendees will have the opportunity to hear topics and case studies covered that relate to: Gene therapy, Estimands, Real world data and Trial design.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = £20+VAT
To register for the session, please click here.
Overview
Research and clinical trials for gene therapies pose many specific challenges. These can be due to comparing potentially curative treatments to a standard of care with different modes of action or even no currently available treatments. There may also be small sample sizes due to rare or ultra-rare diseases. The talks in this webinar will cover challenges related to study design, including estimands, and use of real-world data and evidence to supplement clinical trial data. Case studies of such challenges will be presented.
Speaker details
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.
Scientific Meetings
PSI Webinar: Statistical Challenges in Gene Therapy Trials
Who is this event intended for? Statisticans working in - or interested in - gene therapy treatments. What is the benefit of attending? Attendees will have the opportunity to hear topics and case studies covered that relate to: Gene therapy, Estimands, Real world data and Trial design.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = £20+VAT
To register for the session, please click here.
Overview
Research and clinical trials for gene therapies pose many specific challenges. These can be due to comparing potentially curative treatments to a standard of care with different modes of action or even no currently available treatments. There may also be small sample sizes due to rare or ultra-rare diseases. The talks in this webinar will cover challenges related to study design, including estimands, and use of real-world data and evidence to supplement clinical trial data. Case studies of such challenges will be presented.
Speaker details
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.
Training Courses
PSI Webinar: Statistical Challenges in Gene Therapy Trials
Who is this event intended for? Statisticans working in - or interested in - gene therapy treatments. What is the benefit of attending? Attendees will have the opportunity to hear topics and case studies covered that relate to: Gene therapy, Estimands, Real world data and Trial design.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = £20+VAT
To register for the session, please click here.
Overview
Research and clinical trials for gene therapies pose many specific challenges. These can be due to comparing potentially curative treatments to a standard of care with different modes of action or even no currently available treatments. There may also be small sample sizes due to rare or ultra-rare diseases. The talks in this webinar will cover challenges related to study design, including estimands, and use of real-world data and evidence to supplement clinical trial data. Case studies of such challenges will be presented.
Speaker details
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.
Journal Club
PSI Webinar: Statistical Challenges in Gene Therapy Trials
Who is this event intended for? Statisticans working in - or interested in - gene therapy treatments. What is the benefit of attending? Attendees will have the opportunity to hear topics and case studies covered that relate to: Gene therapy, Estimands, Real world data and Trial design.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = £20+VAT
To register for the session, please click here.
Overview
Research and clinical trials for gene therapies pose many specific challenges. These can be due to comparing potentially curative treatments to a standard of care with different modes of action or even no currently available treatments. There may also be small sample sizes due to rare or ultra-rare diseases. The talks in this webinar will cover challenges related to study design, including estimands, and use of real-world data and evidence to supplement clinical trial data. Case studies of such challenges will be presented.
Speaker details
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.
Webinars
PSI Webinar: Statistical Challenges in Gene Therapy Trials
Who is this event intended for? Statisticans working in - or interested in - gene therapy treatments. What is the benefit of attending? Attendees will have the opportunity to hear topics and case studies covered that relate to: Gene therapy, Estimands, Real world data and Trial design.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = £20+VAT
To register for the session, please click here.
Overview
Research and clinical trials for gene therapies pose many specific challenges. These can be due to comparing potentially curative treatments to a standard of care with different modes of action or even no currently available treatments. There may also be small sample sizes due to rare or ultra-rare diseases. The talks in this webinar will cover challenges related to study design, including estimands, and use of real-world data and evidence to supplement clinical trial data. Case studies of such challenges will be presented.
Speaker details
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.
Careers Meetings
PSI Webinar: Statistical Challenges in Gene Therapy Trials
Who is this event intended for? Statisticans working in - or interested in - gene therapy treatments. What is the benefit of attending? Attendees will have the opportunity to hear topics and case studies covered that relate to: Gene therapy, Estimands, Real world data and Trial design.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = £20+VAT
To register for the session, please click here.
Overview
Research and clinical trials for gene therapies pose many specific challenges. These can be due to comparing potentially curative treatments to a standard of care with different modes of action or even no currently available treatments. There may also be small sample sizes due to rare or ultra-rare diseases. The talks in this webinar will cover challenges related to study design, including estimands, and use of real-world data and evidence to supplement clinical trial data. Case studies of such challenges will be presented.
Speaker details
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.
Upcoming Events
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.
The event will open with an overview on drug development in women’s health from a clinician perspective. This talk is followed by talks about statistical challenges when planning IVF studies and analysing the menstrual cycles.
This webinar will provide an overview of surrogacy for licensing and reimbursement. In turn, the need of extensions of the SPIRIT and CONSORT statement will be defined and outlined, with case studies to support.
Joint PSI/EFSPI Pre-Clinical SIG Webinar: Virtual Control Groups in Toxicity Studies
Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace.
Joint PSI/EFSPI Data Science SIG Webinar: Developing Digital Measures (Digital Biomarkers) in Drug Development – insights from Mobilise D consortium
We will share a brief overview of what Mobilise D is and why it is an important step stone in the development of digital biomarkers, and how Mobilise D outputs can be relevant for you.
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 Webinar: Development of Gene Therapies: Strategic, Scientific, Regulatory and Access Considerations
This webinar will cover the history of cell/gene therapy, major regulatory advances, the role of quantitative scientists in drug development of these novel therapeutics, and discuss opportunities for innovation and product advancement.
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 Introduction to Industry Training (ITIT) Course - 2024/2025
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.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
Statisticians in the Pharmaceutical Industry Executive Office: c/o MCI UK Ltd | Unit 24/22 South | Building 4000 | Langstone Park| Langstone Road | Havant | PO9 1SA | UK