Date: Tuesday 21st June 2022 Time: 14:00-15:00 BST | 15:00-16:00 CEST Speaker: Bernard Francq
Who is this event intended for? Statisticians and others working on assay qualification within the Pharmaceutical Industry. What is the benefit of attending? Attendees will learn about robust assay qualification methodology.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
Overview
In the pharmaceutical industry, all analytical methods must be shown to deliver unbiased and precise results. In an assay qualification or validation study, the trueness, accuracy and intermediate precision are usually assessed by comparing the measured concentrations to their nominal levels. Trueness is assessed by using confidence intervals of mean measured concentration, accuracy by prediction intervals for a future measured concentration, and the intermediate precision by the total variance.
ICH and USP guidelines alike request that all relevant sources of variability must be studied, e.g. the effect of different technicians, the day-to-day variability or the use of multiple reagent lots. Those different random effects must be modeled as crossed, nested or a combination of both.
Confidence, prediction and tolerance intervals in linear mixed models will be detailed with a focus on the interpretation of statistical results. Their relationships will be discussed together with the POOS (out-of-specification probability). Two real datasets from assay validation study during vaccine development are used to illustrate the statistical intervals and the POOS.
Speaker details
Speaker
Biography
Bernard Francq
Bernard G Francq is Lead Statistician with GSK Biologicals, driving statistical innovation for CMC projects worldwide. He holds a PhD in Statistics (UCLouvain, 2013).
His work on errors-in-variables (EIV) regressions in method comparison studies has been awarded Best MSc Thesis Biostatistics (Quételet 2008, Belgium), Best Chemometrician Prize (Chimiométrie 2009, Paris) and Best Young Researcher (Agrostat 2012, Paris). His communication skills have been recognized with the Greenfield Challenge Award (ENBIS 2012, Ljubljana). Recent work on tolerance intervals in bridging studies was awarded Best GSK Statistical Paper (2020). He lectures at UCLouvain and regularly offers trainings to statisticians in the (bio)pharmaceutical industry.
Scientific Meetings
PSI Pre-Clinical SIG Webinar: Assay Qualification by Linear Mixed Model: Confidence, Prediction & Tolerance Intervals
Date: Tuesday 21st June 2022 Time: 14:00-15:00 BST | 15:00-16:00 CEST Speaker: Bernard Francq
Who is this event intended for? Statisticians and others working on assay qualification within the Pharmaceutical Industry. What is the benefit of attending? Attendees will learn about robust assay qualification methodology.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
Overview
In the pharmaceutical industry, all analytical methods must be shown to deliver unbiased and precise results. In an assay qualification or validation study, the trueness, accuracy and intermediate precision are usually assessed by comparing the measured concentrations to their nominal levels. Trueness is assessed by using confidence intervals of mean measured concentration, accuracy by prediction intervals for a future measured concentration, and the intermediate precision by the total variance.
ICH and USP guidelines alike request that all relevant sources of variability must be studied, e.g. the effect of different technicians, the day-to-day variability or the use of multiple reagent lots. Those different random effects must be modeled as crossed, nested or a combination of both.
Confidence, prediction and tolerance intervals in linear mixed models will be detailed with a focus on the interpretation of statistical results. Their relationships will be discussed together with the POOS (out-of-specification probability). Two real datasets from assay validation study during vaccine development are used to illustrate the statistical intervals and the POOS.
Speaker details
Speaker
Biography
Bernard Francq
Bernard G Francq is Lead Statistician with GSK Biologicals, driving statistical innovation for CMC projects worldwide. He holds a PhD in Statistics (UCLouvain, 2013).
His work on errors-in-variables (EIV) regressions in method comparison studies has been awarded Best MSc Thesis Biostatistics (Quételet 2008, Belgium), Best Chemometrician Prize (Chimiométrie 2009, Paris) and Best Young Researcher (Agrostat 2012, Paris). His communication skills have been recognized with the Greenfield Challenge Award (ENBIS 2012, Ljubljana). Recent work on tolerance intervals in bridging studies was awarded Best GSK Statistical Paper (2020). He lectures at UCLouvain and regularly offers trainings to statisticians in the (bio)pharmaceutical industry.
Training Courses
PSI Pre-Clinical SIG Webinar: Assay Qualification by Linear Mixed Model: Confidence, Prediction & Tolerance Intervals
Date: Tuesday 21st June 2022 Time: 14:00-15:00 BST | 15:00-16:00 CEST Speaker: Bernard Francq
Who is this event intended for? Statisticians and others working on assay qualification within the Pharmaceutical Industry. What is the benefit of attending? Attendees will learn about robust assay qualification methodology.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
Overview
In the pharmaceutical industry, all analytical methods must be shown to deliver unbiased and precise results. In an assay qualification or validation study, the trueness, accuracy and intermediate precision are usually assessed by comparing the measured concentrations to their nominal levels. Trueness is assessed by using confidence intervals of mean measured concentration, accuracy by prediction intervals for a future measured concentration, and the intermediate precision by the total variance.
ICH and USP guidelines alike request that all relevant sources of variability must be studied, e.g. the effect of different technicians, the day-to-day variability or the use of multiple reagent lots. Those different random effects must be modeled as crossed, nested or a combination of both.
Confidence, prediction and tolerance intervals in linear mixed models will be detailed with a focus on the interpretation of statistical results. Their relationships will be discussed together with the POOS (out-of-specification probability). Two real datasets from assay validation study during vaccine development are used to illustrate the statistical intervals and the POOS.
Speaker details
Speaker
Biography
Bernard Francq
Bernard G Francq is Lead Statistician with GSK Biologicals, driving statistical innovation for CMC projects worldwide. He holds a PhD in Statistics (UCLouvain, 2013).
His work on errors-in-variables (EIV) regressions in method comparison studies has been awarded Best MSc Thesis Biostatistics (Quételet 2008, Belgium), Best Chemometrician Prize (Chimiométrie 2009, Paris) and Best Young Researcher (Agrostat 2012, Paris). His communication skills have been recognized with the Greenfield Challenge Award (ENBIS 2012, Ljubljana). Recent work on tolerance intervals in bridging studies was awarded Best GSK Statistical Paper (2020). He lectures at UCLouvain and regularly offers trainings to statisticians in the (bio)pharmaceutical industry.
Journal Club
PSI Pre-Clinical SIG Webinar: Assay Qualification by Linear Mixed Model: Confidence, Prediction & Tolerance Intervals
Date: Tuesday 21st June 2022 Time: 14:00-15:00 BST | 15:00-16:00 CEST Speaker: Bernard Francq
Who is this event intended for? Statisticians and others working on assay qualification within the Pharmaceutical Industry. What is the benefit of attending? Attendees will learn about robust assay qualification methodology.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
Overview
In the pharmaceutical industry, all analytical methods must be shown to deliver unbiased and precise results. In an assay qualification or validation study, the trueness, accuracy and intermediate precision are usually assessed by comparing the measured concentrations to their nominal levels. Trueness is assessed by using confidence intervals of mean measured concentration, accuracy by prediction intervals for a future measured concentration, and the intermediate precision by the total variance.
ICH and USP guidelines alike request that all relevant sources of variability must be studied, e.g. the effect of different technicians, the day-to-day variability or the use of multiple reagent lots. Those different random effects must be modeled as crossed, nested or a combination of both.
Confidence, prediction and tolerance intervals in linear mixed models will be detailed with a focus on the interpretation of statistical results. Their relationships will be discussed together with the POOS (out-of-specification probability). Two real datasets from assay validation study during vaccine development are used to illustrate the statistical intervals and the POOS.
Speaker details
Speaker
Biography
Bernard Francq
Bernard G Francq is Lead Statistician with GSK Biologicals, driving statistical innovation for CMC projects worldwide. He holds a PhD in Statistics (UCLouvain, 2013).
His work on errors-in-variables (EIV) regressions in method comparison studies has been awarded Best MSc Thesis Biostatistics (Quételet 2008, Belgium), Best Chemometrician Prize (Chimiométrie 2009, Paris) and Best Young Researcher (Agrostat 2012, Paris). His communication skills have been recognized with the Greenfield Challenge Award (ENBIS 2012, Ljubljana). Recent work on tolerance intervals in bridging studies was awarded Best GSK Statistical Paper (2020). He lectures at UCLouvain and regularly offers trainings to statisticians in the (bio)pharmaceutical industry.
Webinars
PSI Pre-Clinical SIG Webinar: Assay Qualification by Linear Mixed Model: Confidence, Prediction & Tolerance Intervals
Date: Tuesday 21st June 2022 Time: 14:00-15:00 BST | 15:00-16:00 CEST Speaker: Bernard Francq
Who is this event intended for? Statisticians and others working on assay qualification within the Pharmaceutical Industry. What is the benefit of attending? Attendees will learn about robust assay qualification methodology.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
Overview
In the pharmaceutical industry, all analytical methods must be shown to deliver unbiased and precise results. In an assay qualification or validation study, the trueness, accuracy and intermediate precision are usually assessed by comparing the measured concentrations to their nominal levels. Trueness is assessed by using confidence intervals of mean measured concentration, accuracy by prediction intervals for a future measured concentration, and the intermediate precision by the total variance.
ICH and USP guidelines alike request that all relevant sources of variability must be studied, e.g. the effect of different technicians, the day-to-day variability or the use of multiple reagent lots. Those different random effects must be modeled as crossed, nested or a combination of both.
Confidence, prediction and tolerance intervals in linear mixed models will be detailed with a focus on the interpretation of statistical results. Their relationships will be discussed together with the POOS (out-of-specification probability). Two real datasets from assay validation study during vaccine development are used to illustrate the statistical intervals and the POOS.
Speaker details
Speaker
Biography
Bernard Francq
Bernard G Francq is Lead Statistician with GSK Biologicals, driving statistical innovation for CMC projects worldwide. He holds a PhD in Statistics (UCLouvain, 2013).
His work on errors-in-variables (EIV) regressions in method comparison studies has been awarded Best MSc Thesis Biostatistics (Quételet 2008, Belgium), Best Chemometrician Prize (Chimiométrie 2009, Paris) and Best Young Researcher (Agrostat 2012, Paris). His communication skills have been recognized with the Greenfield Challenge Award (ENBIS 2012, Ljubljana). Recent work on tolerance intervals in bridging studies was awarded Best GSK Statistical Paper (2020). He lectures at UCLouvain and regularly offers trainings to statisticians in the (bio)pharmaceutical industry.
Careers Meetings
PSI Pre-Clinical SIG Webinar: Assay Qualification by Linear Mixed Model: Confidence, Prediction & Tolerance Intervals
Date: Tuesday 21st June 2022 Time: 14:00-15:00 BST | 15:00-16:00 CEST Speaker: Bernard Francq
Who is this event intended for? Statisticians and others working on assay qualification within the Pharmaceutical Industry. What is the benefit of attending? Attendees will learn about robust assay qualification methodology.
Registration
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
Overview
In the pharmaceutical industry, all analytical methods must be shown to deliver unbiased and precise results. In an assay qualification or validation study, the trueness, accuracy and intermediate precision are usually assessed by comparing the measured concentrations to their nominal levels. Trueness is assessed by using confidence intervals of mean measured concentration, accuracy by prediction intervals for a future measured concentration, and the intermediate precision by the total variance.
ICH and USP guidelines alike request that all relevant sources of variability must be studied, e.g. the effect of different technicians, the day-to-day variability or the use of multiple reagent lots. Those different random effects must be modeled as crossed, nested or a combination of both.
Confidence, prediction and tolerance intervals in linear mixed models will be detailed with a focus on the interpretation of statistical results. Their relationships will be discussed together with the POOS (out-of-specification probability). Two real datasets from assay validation study during vaccine development are used to illustrate the statistical intervals and the POOS.
Speaker details
Speaker
Biography
Bernard Francq
Bernard G Francq is Lead Statistician with GSK Biologicals, driving statistical innovation for CMC projects worldwide. He holds a PhD in Statistics (UCLouvain, 2013).
His work on errors-in-variables (EIV) regressions in method comparison studies has been awarded Best MSc Thesis Biostatistics (Quételet 2008, Belgium), Best Chemometrician Prize (Chimiométrie 2009, Paris) and Best Young Researcher (Agrostat 2012, Paris). His communication skills have been recognized with the Greenfield Challenge Award (ENBIS 2012, Ljubljana). Recent work on tolerance intervals in bridging studies was awarded Best GSK Statistical Paper (2020). He lectures at UCLouvain and regularly offers trainings to statisticians in the (bio)pharmaceutical industry.
Upcoming Events
PSI Book Club: Change: How organisations achieve hard-to-imagine 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.
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 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: 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.
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.
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.
Making Estimands Work - Practical Approaches with Implementation in Data Standards
This event will discuss the impact of the estimand framework on data flow and data handling for analysis datasets (ADaM). What are the considerations to produce data sets suitable for estimation of estimands and traceability of the occurrence of intercurrent events. This webinar will include tips for best practice, based on the White paper Implementation of ICH E9(R1) Estimands Framework using Data Standards.
PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data
This webinar will describe what ctDNA is and what the key challenges are for analysing it. We will then summarise and review methods that were published over the last few years for analysing ctDNA data.
This two-afternoon virtual course provides a practical introduction to adaptive clinical trials, focusing on the concepts, applications, and regulatory principles outlined in ICH E20 through real-world examples and case studies.
PSI Careers - MEDMathS: Medicine Empowered by Data, Maths and Statistics
Date: Wednesday 4th November 2026
A careers talk about medical statistics and how it plays a crucial role in developing new medicines. Learn about the field of medical statistics and how it plays a crucial role in developing groundbreaking new medicines, vaccines and healthcare products.
Date: 18 November 2026
This is an excellent opportunity for students to find out more about the field of medical statistics, talk to people from different organisations and make contacts for the future. All students currently studying for a mathematics or statistics-related BSc, MSc or PhD are invited to attend, and we welcome interest from exhibitors too.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
In this vital role you will generate evidence to meet Health Technology Assessment (HTA) requirements, while ensuring that the analyses performed meet required standards and are robust and valid.
Bristol Myers Squibb - Director, Statistical Methodology and Innovation
Lead the development of innovative statistical methods, provides expert consulting, oversees tools and software, and mentors team members while collaborating cross-functionally to address complex drug development challenges.
Phastar – Associate Director, Statistics – Real World Evidence (RWE)
As an Associate Director, Statistics (RWE) you will focus on supporting one of our key pharmaceutical clients within our FSP function. This will be a hands-on technical role, with oversight responsibilities and cross-functional exposure.
Phastar – Principal Statistician – Real World Evidence (RWE)
We are seeking an experienced Statistician to join our FSP team to support one of our fantastic and well-known global pharmaceutical clients, at Principal level.
We are seeking an experienced Statistician to join our FSP team to support one of our fantastic and well-known global pharmaceutical clients, at either Senior or Principal levels.
This position is deal for a statistician who values ownership, collaboration, and using data to enable confident development decisions and to support regulatory submissions.
