Date: Tuesday 14th March 2023
Time: 14:00-14:45 GMT | 15:00-15:45 CET
Speaker: Els Pattyn (Sanofi)
Who is this event intended for? Any statisticians working in the Pharmaceutical industry.
What is the benefit of attending? Attendees will have the opportunity to see an example of JMP development for regulatory compliant calculation of immunogenicity cut-point.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
"Immunogenicity represents a significant hurdle for the development of all biotherapeutics and biosimilars as it can affect both efficacy and safety of the treatment. Over the last decade industry and regulators succeeded in standardizing a tiered screening/confirmatory/titer testing approach for anti-drug antibodies (ADAs). Unlike assays to determine the concentration of biopharmaceuticals, ADA assays are semi-quantitative in nature, and therefore requiring error prone and complex statistical approaches for positivity cut-points at each tier of the testing paradigm.
To get around these hurdles, a solution has been created within Sanofi by the development of a fully-automated and validated script using the JMP statistical software. This script follows a pre-determined decision tree based on the latest recommendations from industry guidance, white papers and scientific best-practice. It is designed for both binding and neutralizing antibody methods used to support non-clinical and clinical studies in regulated environments (GLP/GcLP). The user-friendly interface allows application by any bioanalytical scientist without requiring deep statistical knowledge.
The script allows end-users to easily select the appropriate decision trees applicable for the specific needs of a given type of assay or study. The application accepts Excel files to upload assay response data and then makes outcome-dependent decisions based on best-practices for the chosen method and context. For example, the script will select the most appropriate normalization/transformation, apply adapted effects included in the mixed-effects model based on the study-design, optionally calculate analyst-specific cut-points in case of significant analyst-specific differences and adapt down-stream analysis in cases where no second-tier confirmatory data is available.
The validated version of this purpose-built statistical tool, named ImmunoStat Simple, allows immunogenicity cut-points to be calculated quickly and efficiently in a standardized way across multiple sites in a global organization, and the automated reporting is suitable for regulatory submissions. The successful implementation of this automated JMP script demonstrates how digital tools and automation can improve the efficiency and capabilities of modern bioanalytical laboratories."
|
Speaker |
Biography |
|
|
Els Pattyn is educated as a bio-engineer. After obtaining her PhD, she additional worked 8 years as a post-doctoral researcher at the University of Ghent in the immunology research, whereafter she took the role of scientist NANOBODY® characterization at Ablynx. After obtaining a master in statistical data analysis, she switched to Ablynx’ statistics team. By the acquisition of Ablynx by Sanofi in 2018, Els joined Sanofi’s Non Clinical Efficacy and Safety Statistics team, where she provides statistical support for mainly projects in immunology research, with focus on dose response modelling, design of experiments and immunogenicity assessment. |
Date: Tuesday 14th March 2023
Time: 14:00-14:45 GMT | 15:00-15:45 CET
Speaker: Els Pattyn (Sanofi)
Who is this event intended for? Any statisticians working in the Pharmaceutical industry.
What is the benefit of attending? Attendees will have the opportunity to see an example of JMP development for regulatory compliant calculation of immunogenicity cut-point.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
"Immunogenicity represents a significant hurdle for the development of all biotherapeutics and biosimilars as it can affect both efficacy and safety of the treatment. Over the last decade industry and regulators succeeded in standardizing a tiered screening/confirmatory/titer testing approach for anti-drug antibodies (ADAs). Unlike assays to determine the concentration of biopharmaceuticals, ADA assays are semi-quantitative in nature, and therefore requiring error prone and complex statistical approaches for positivity cut-points at each tier of the testing paradigm.
To get around these hurdles, a solution has been created within Sanofi by the development of a fully-automated and validated script using the JMP statistical software. This script follows a pre-determined decision tree based on the latest recommendations from industry guidance, white papers and scientific best-practice. It is designed for both binding and neutralizing antibody methods used to support non-clinical and clinical studies in regulated environments (GLP/GcLP). The user-friendly interface allows application by any bioanalytical scientist without requiring deep statistical knowledge.
The script allows end-users to easily select the appropriate decision trees applicable for the specific needs of a given type of assay or study. The application accepts Excel files to upload assay response data and then makes outcome-dependent decisions based on best-practices for the chosen method and context. For example, the script will select the most appropriate normalization/transformation, apply adapted effects included in the mixed-effects model based on the study-design, optionally calculate analyst-specific cut-points in case of significant analyst-specific differences and adapt down-stream analysis in cases where no second-tier confirmatory data is available.
The validated version of this purpose-built statistical tool, named ImmunoStat Simple, allows immunogenicity cut-points to be calculated quickly and efficiently in a standardized way across multiple sites in a global organization, and the automated reporting is suitable for regulatory submissions. The successful implementation of this automated JMP script demonstrates how digital tools and automation can improve the efficiency and capabilities of modern bioanalytical laboratories."
|
Speaker |
Biography |
|
|
Els Pattyn is educated as a bio-engineer. After obtaining her PhD, she additional worked 8 years as a post-doctoral researcher at the University of Ghent in the immunology research, whereafter she took the role of scientist NANOBODY® characterization at Ablynx. After obtaining a master in statistical data analysis, she switched to Ablynx’ statistics team. By the acquisition of Ablynx by Sanofi in 2018, Els joined Sanofi’s Non Clinical Efficacy and Safety Statistics team, where she provides statistical support for mainly projects in immunology research, with focus on dose response modelling, design of experiments and immunogenicity assessment. |
Date: Tuesday 14th March 2023
Time: 14:00-14:45 GMT | 15:00-15:45 CET
Speaker: Els Pattyn (Sanofi)
Who is this event intended for? Any statisticians working in the Pharmaceutical industry.
What is the benefit of attending? Attendees will have the opportunity to see an example of JMP development for regulatory compliant calculation of immunogenicity cut-point.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
"Immunogenicity represents a significant hurdle for the development of all biotherapeutics and biosimilars as it can affect both efficacy and safety of the treatment. Over the last decade industry and regulators succeeded in standardizing a tiered screening/confirmatory/titer testing approach for anti-drug antibodies (ADAs). Unlike assays to determine the concentration of biopharmaceuticals, ADA assays are semi-quantitative in nature, and therefore requiring error prone and complex statistical approaches for positivity cut-points at each tier of the testing paradigm.
To get around these hurdles, a solution has been created within Sanofi by the development of a fully-automated and validated script using the JMP statistical software. This script follows a pre-determined decision tree based on the latest recommendations from industry guidance, white papers and scientific best-practice. It is designed for both binding and neutralizing antibody methods used to support non-clinical and clinical studies in regulated environments (GLP/GcLP). The user-friendly interface allows application by any bioanalytical scientist without requiring deep statistical knowledge.
The script allows end-users to easily select the appropriate decision trees applicable for the specific needs of a given type of assay or study. The application accepts Excel files to upload assay response data and then makes outcome-dependent decisions based on best-practices for the chosen method and context. For example, the script will select the most appropriate normalization/transformation, apply adapted effects included in the mixed-effects model based on the study-design, optionally calculate analyst-specific cut-points in case of significant analyst-specific differences and adapt down-stream analysis in cases where no second-tier confirmatory data is available.
The validated version of this purpose-built statistical tool, named ImmunoStat Simple, allows immunogenicity cut-points to be calculated quickly and efficiently in a standardized way across multiple sites in a global organization, and the automated reporting is suitable for regulatory submissions. The successful implementation of this automated JMP script demonstrates how digital tools and automation can improve the efficiency and capabilities of modern bioanalytical laboratories."
|
Speaker |
Biography |
|
|
Els Pattyn is educated as a bio-engineer. After obtaining her PhD, she additional worked 8 years as a post-doctoral researcher at the University of Ghent in the immunology research, whereafter she took the role of scientist NANOBODY® characterization at Ablynx. After obtaining a master in statistical data analysis, she switched to Ablynx’ statistics team. By the acquisition of Ablynx by Sanofi in 2018, Els joined Sanofi’s Non Clinical Efficacy and Safety Statistics team, where she provides statistical support for mainly projects in immunology research, with focus on dose response modelling, design of experiments and immunogenicity assessment. |
Date: Tuesday 14th March 2023
Time: 14:00-14:45 GMT | 15:00-15:45 CET
Speaker: Els Pattyn (Sanofi)
Who is this event intended for? Any statisticians working in the Pharmaceutical industry.
What is the benefit of attending? Attendees will have the opportunity to see an example of JMP development for regulatory compliant calculation of immunogenicity cut-point.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
"Immunogenicity represents a significant hurdle for the development of all biotherapeutics and biosimilars as it can affect both efficacy and safety of the treatment. Over the last decade industry and regulators succeeded in standardizing a tiered screening/confirmatory/titer testing approach for anti-drug antibodies (ADAs). Unlike assays to determine the concentration of biopharmaceuticals, ADA assays are semi-quantitative in nature, and therefore requiring error prone and complex statistical approaches for positivity cut-points at each tier of the testing paradigm.
To get around these hurdles, a solution has been created within Sanofi by the development of a fully-automated and validated script using the JMP statistical software. This script follows a pre-determined decision tree based on the latest recommendations from industry guidance, white papers and scientific best-practice. It is designed for both binding and neutralizing antibody methods used to support non-clinical and clinical studies in regulated environments (GLP/GcLP). The user-friendly interface allows application by any bioanalytical scientist without requiring deep statistical knowledge.
The script allows end-users to easily select the appropriate decision trees applicable for the specific needs of a given type of assay or study. The application accepts Excel files to upload assay response data and then makes outcome-dependent decisions based on best-practices for the chosen method and context. For example, the script will select the most appropriate normalization/transformation, apply adapted effects included in the mixed-effects model based on the study-design, optionally calculate analyst-specific cut-points in case of significant analyst-specific differences and adapt down-stream analysis in cases where no second-tier confirmatory data is available.
The validated version of this purpose-built statistical tool, named ImmunoStat Simple, allows immunogenicity cut-points to be calculated quickly and efficiently in a standardized way across multiple sites in a global organization, and the automated reporting is suitable for regulatory submissions. The successful implementation of this automated JMP script demonstrates how digital tools and automation can improve the efficiency and capabilities of modern bioanalytical laboratories."
|
Speaker |
Biography |
|
|
Els Pattyn is educated as a bio-engineer. After obtaining her PhD, she additional worked 8 years as a post-doctoral researcher at the University of Ghent in the immunology research, whereafter she took the role of scientist NANOBODY® characterization at Ablynx. After obtaining a master in statistical data analysis, she switched to Ablynx’ statistics team. By the acquisition of Ablynx by Sanofi in 2018, Els joined Sanofi’s Non Clinical Efficacy and Safety Statistics team, where she provides statistical support for mainly projects in immunology research, with focus on dose response modelling, design of experiments and immunogenicity assessment. |
Date: Tuesday 14th March 2023
Time: 14:00-14:45 GMT | 15:00-15:45 CET
Speaker: Els Pattyn (Sanofi)
Who is this event intended for? Any statisticians working in the Pharmaceutical industry.
What is the benefit of attending? Attendees will have the opportunity to see an example of JMP development for regulatory compliant calculation of immunogenicity cut-point.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
"Immunogenicity represents a significant hurdle for the development of all biotherapeutics and biosimilars as it can affect both efficacy and safety of the treatment. Over the last decade industry and regulators succeeded in standardizing a tiered screening/confirmatory/titer testing approach for anti-drug antibodies (ADAs). Unlike assays to determine the concentration of biopharmaceuticals, ADA assays are semi-quantitative in nature, and therefore requiring error prone and complex statistical approaches for positivity cut-points at each tier of the testing paradigm.
To get around these hurdles, a solution has been created within Sanofi by the development of a fully-automated and validated script using the JMP statistical software. This script follows a pre-determined decision tree based on the latest recommendations from industry guidance, white papers and scientific best-practice. It is designed for both binding and neutralizing antibody methods used to support non-clinical and clinical studies in regulated environments (GLP/GcLP). The user-friendly interface allows application by any bioanalytical scientist without requiring deep statistical knowledge.
The script allows end-users to easily select the appropriate decision trees applicable for the specific needs of a given type of assay or study. The application accepts Excel files to upload assay response data and then makes outcome-dependent decisions based on best-practices for the chosen method and context. For example, the script will select the most appropriate normalization/transformation, apply adapted effects included in the mixed-effects model based on the study-design, optionally calculate analyst-specific cut-points in case of significant analyst-specific differences and adapt down-stream analysis in cases where no second-tier confirmatory data is available.
The validated version of this purpose-built statistical tool, named ImmunoStat Simple, allows immunogenicity cut-points to be calculated quickly and efficiently in a standardized way across multiple sites in a global organization, and the automated reporting is suitable for regulatory submissions. The successful implementation of this automated JMP script demonstrates how digital tools and automation can improve the efficiency and capabilities of modern bioanalytical laboratories."
|
Speaker |
Biography |
|
|
Els Pattyn is educated as a bio-engineer. After obtaining her PhD, she additional worked 8 years as a post-doctoral researcher at the University of Ghent in the immunology research, whereafter she took the role of scientist NANOBODY® characterization at Ablynx. After obtaining a master in statistical data analysis, she switched to Ablynx’ statistics team. By the acquisition of Ablynx by Sanofi in 2018, Els joined Sanofi’s Non Clinical Efficacy and Safety Statistics team, where she provides statistical support for mainly projects in immunology research, with focus on dose response modelling, design of experiments and immunogenicity assessment. |
Date: Tuesday 14th March 2023
Time: 14:00-14:45 GMT | 15:00-15:45 CET
Speaker: Els Pattyn (Sanofi)
Who is this event intended for? Any statisticians working in the Pharmaceutical industry.
What is the benefit of attending? Attendees will have the opportunity to see an example of JMP development for regulatory compliant calculation of immunogenicity cut-point.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
"Immunogenicity represents a significant hurdle for the development of all biotherapeutics and biosimilars as it can affect both efficacy and safety of the treatment. Over the last decade industry and regulators succeeded in standardizing a tiered screening/confirmatory/titer testing approach for anti-drug antibodies (ADAs). Unlike assays to determine the concentration of biopharmaceuticals, ADA assays are semi-quantitative in nature, and therefore requiring error prone and complex statistical approaches for positivity cut-points at each tier of the testing paradigm.
To get around these hurdles, a solution has been created within Sanofi by the development of a fully-automated and validated script using the JMP statistical software. This script follows a pre-determined decision tree based on the latest recommendations from industry guidance, white papers and scientific best-practice. It is designed for both binding and neutralizing antibody methods used to support non-clinical and clinical studies in regulated environments (GLP/GcLP). The user-friendly interface allows application by any bioanalytical scientist without requiring deep statistical knowledge.
The script allows end-users to easily select the appropriate decision trees applicable for the specific needs of a given type of assay or study. The application accepts Excel files to upload assay response data and then makes outcome-dependent decisions based on best-practices for the chosen method and context. For example, the script will select the most appropriate normalization/transformation, apply adapted effects included in the mixed-effects model based on the study-design, optionally calculate analyst-specific cut-points in case of significant analyst-specific differences and adapt down-stream analysis in cases where no second-tier confirmatory data is available.
The validated version of this purpose-built statistical tool, named ImmunoStat Simple, allows immunogenicity cut-points to be calculated quickly and efficiently in a standardized way across multiple sites in a global organization, and the automated reporting is suitable for regulatory submissions. The successful implementation of this automated JMP script demonstrates how digital tools and automation can improve the efficiency and capabilities of modern bioanalytical laboratories."
|
Speaker |
Biography |
|
|
Els Pattyn is educated as a bio-engineer. After obtaining her PhD, she additional worked 8 years as a post-doctoral researcher at the University of Ghent in the immunology research, whereafter she took the role of scientist NANOBODY® characterization at Ablynx. After obtaining a master in statistical data analysis, she switched to Ablynx’ statistics team. By the acquisition of Ablynx by Sanofi in 2018, Els joined Sanofi’s Non Clinical Efficacy and Safety Statistics team, where she provides statistical support for mainly projects in immunology research, with focus on dose response modelling, design of experiments and immunogenicity assessment. |
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.
Develop your non-technical skills by reading The Art of Explanation by Ros Atkins and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply skills from the book in-between sessions.
Date: Tuesday 9th September 2025 Join us to hear Sofia Weigle and Weng-Kee Wong present their recent work.
This course is aimed at biostatisticians with no or some pediatric drug development experience who are interested to further their understanding. We will give you an introduction to the pediatric drug development landscape. This will include identifying the key regulations and processes governing pediatric development, a discussion on the needs and challenges when conducting pediatric research and a focus on the ways to overcome these challenges from a statistical perspective.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
AI agents are large language models equipped with tools that can autonomously tackle challenging tasks. This talk will explore how generative AI agents can enable biomedical discovery.
The webinar is targeted at statisticians working in the pharmaceutical industry, and the objective is to 1) provide a basic understanding of IV methodology including how it relates to causal inference, and 2) present two inspirational pharma-relevant applications.
The Pre-Clinical Special Interest Group (SIG) Workshop 2025 will take place over two half-days on 7 - 8 October in Verona, Italy, bringing together experts from industry, academia, and regulatory institutions to discuss key challenges and innovations in pre-clinical research.
Four sessions will include ML foundation (including an introduction, data exploration for ML and dimensionality reduction and feature selection), Supervised learning (including support vector machines and model evaluation and interpretation), model optimization and unsupervised learning (including clustering) and advanced topics (including neural networks, deep learning and large language models).
The program will feature insightful sessions led by distinguished invited speakers, alongside a poster session showcasing the latest advancements in the field. Further details will be provided.
Date: Wednesday 5th November 2025 A careers talk about medical statistics and how it plays a crucial role in developing new medicines
Date: 19 November 2025 This event is aimed at students with an interest in the field of Medical Statistics, for example within pharmaceuticals, healthcare and/or medical research.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
As an Associate Director Biostatistics Early Development, you will be a key member of our biostatistics group, you will play a crucial role in the design, analysis, and interpretation of clinical trials for early development programs.
If you are passionate about biostatistics and real-world data, and are looking for an exciting opportunity to contribute to groundbreaking research, we encourage you to apply.
Are you passionate about making a difference in the world of healthcare? Novartis is seeking a dynamic and experienced professional to join our team in London at The Westworks.
As the Director of HTA Biostatistics & Medical Affairs, you will play a pivotal role in shaping the future of healthcare by providing strategic biostatistical leadership and expertise.
As a Senior Principal Biostatistician, you will be responsible and accountable for all statistical work, both scientific and operational, for one or more assigned clinical trials
About cookies on this site
We use cookies to collect and analyse information on site performance and usage, to provide social media features and to enhance and customise content and advertisements.
About cookies on this site
Cookies used on the site are categorized and below you can read about each category and allow or deny some or all of them. When categories than have been previously allowed are disabled, all cookies assigned to that category will be removed from your browser. Additionally you can see a list of cookies assigned to each category and detailed information in the cookie declaration.
Necessary cookies
Some cookies are required to provide core functionality. The website won't function properly without these cookies and they are enabled by default and cannot be disabled.
CookieHub is a Consent Management Platform (CMP) which allows users to control storage and processing of personal information.
Cloudflare is a global network designed to make everything you connect to the Internet secure, private, fast, and reliable.
Amazon Web Services offers a broad set of global cloud-based products including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security, and enterprise applications.
Microsoft Azure is a cloud computing platform offering a wide range of services, including virtual machines, databases, and AI tools.
Preferences
Preference cookies enables the web site to remember information to customize how the web site looks or behaves for each user. This may include storing selected currency, region, language or color theme.
Analytical cookies
Analytical cookies help us improve our website by collecting and reporting information on its usage.
Google Analytics is a web analytics service offered by Google that tracks and reports website traffic.
Vimeo, Inc. is an American video hosting, sharing, services provider, and broadcaster. Vimeo focuses on the delivery of high-definition video across a range of devices.
Cookies used on the site are categorized and below you can read about each category and allow or deny some or all of them. When categories than have been previously allowed are disabled, all cookies assigned to that category will be removed from your browser. Additionally you can see a list of cookies assigned to each category and detailed information in the cookie declaration.
Necessary cookies
Some cookies are required to provide core functionality. The website won't function properly without these cookies and they are enabled by default and cannot be disabled.
| Name | Hostname | Vendor | Expiry |
|---|---|---|---|
| ARRAffinity | .psiweb.org | Session | |
This cookie is set by websites run on the Windows Azure cloud platform. It is used for load balancing to make sure the visitor page requests are routed to the same server in any browsing session. | |||
| ARRAffinitySameSite | .psiweb.org | Session | |
Used to distribute traffic to the website on several servers in order to optimize response times. | |||
| __cf_bm | .vimeo.com | Cloudflare, Inc. | 1 hour |
The __cf_bm cookie supports Cloudflare Bot Management by managing incoming traffic that matches criteria associated with bots. The cookie does not collect any personal data, and any information collected is subject to one-way encryption. | |||
| _cfuvid | .vimeo.com | Session | |
Used by Cloudflare WAF to distinguish individual users who share the same IP address and apply rate limits | |||
| __cf_bm | .glueup.com | Cloudflare, Inc. | 1 hour |
The __cf_bm cookie supports Cloudflare Bot Management by managing incoming traffic that matches criteria associated with bots. The cookie does not collect any personal data, and any information collected is subject to one-way encryption. | |||
| AWSALBTGCORS | psi.glueup.com | 7 days | |
AWS Classic Load Balancer Cookie: Load Balancing Cookie: Used to map the session to the instance. Same value as AWSELB. | |||
| PHPSESSID | psi.glueup.com | Session | |
Cookie generated by applications based on the PHP language. This is a general purpose identifier used to maintain user session variables. It is normally a random generated number, how it is used can be specific to the site, but a good example is maintaining a logged-in status for a user between pages. | |||
| History.store | Session | ||
| cookiehub | .psiweb.org | CookieHub | 365 days |
Used by CookieHub to store information about whether visitors have given or declined the use of cookie categories used on the site. | |||
Preferences
Preference cookies enables the web site to remember information to customize how the web site looks or behaves for each user. This may include storing selected currency, region, language or color theme.
| Name | Hostname | Vendor | Expiry |
|---|---|---|---|
| vuid | .vimeo.com | 400 days | |
These cookies are used by the Vimeo video player on websites. | |||
| AWSALBCORS | psi.glueup.com | 7 days | |
Amazon Web Services cookie. This cookie enables us to allocate server traffic to make the user experience as smooth as possible. A so-called load balancer is used to determine which server currently has the best availability. The information generated cannot identify you as an individual. | |||
Analytical cookies
Analytical cookies help us improve our website by collecting and reporting information on its usage.
| Name | Hostname | Vendor | Expiry |
|---|---|---|---|
| _ga_ | .psiweb.org | 400 days | |
Contains a unique identifier used by Google Analytics 4 to determine that two distinct hits belong to the same user across browsing sessions. | |||
| _ga | .psiweb.org | 400 days | |
Contains a unique identifier used by Google Analytics to determine that two distinct hits belong to the same user across browsing sessions. | |||
