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 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.
PSI Introduction to Industry Training (ITIT) Course - 2026/2027
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This webinar brings together three bitesize complementary sessions to help PSI contributors create conference presentations and posters that communicate clearly and inclusively. Participants will explore how to refine their message, prepare materials effectively, and adopt practical habits that support confident, accessible delivery. A focused, supportive session designed to elevate every contribution.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “Graphics Basics,” will introduce the fundamentals of producing graphics using the ggplot2 package.
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.
Join our Health Technology Assessment (HTA) European Special Interest Group (ESIG) for a webinar on the strategic role of statisticians in the Joint Clinical Assessment (JCA). The introduction of the JCA marks a new era for evidence generation and market access in Europe. As HTA requirements become more harmonized and methodologically demanding, the role of statisticians has evolved far beyond data analysis. Today, statistical expertise is central to shaping clinical development strategies, designing robust comparative evidence, and ensuring that submissions withstand the scrutiny of EU-level assessors. In this webinar, we explore how statisticians contribute strategically to successful JCA outcomes.
Statisticians in the Age of AI: On Route to Strategic Partnership
A 90-minute webinar featuring two case studies from Bayer and Roche demonstrating how statisticians successfully integrated into AI programs, followed by interactive discussion on strategies for elevating statistical expertise in the AI era.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
GSK - Statistics Director - Vaccines and Infectious Disease
We are seeking an experienced and visionary Statistics Director to join our Team and lead strategic statistical innovation across GSK’s Vaccines and Infectious Disease portfolio.
As a Senior Biostatistician I at ICON, you will play a pivotal role in designing and analyzing clinical trials, interpreting complex medical data, and contributing to the advancement of innovative treatments and therapies.
As a Statistical Scientist at ICON, you will play a pivotal role in designing and analyzing clinical trials, interpreting complex medical data, and contributing to the advancement of innovative treatments and therapies.
We have an exciting opportunity for an Associate Director, Biostatistics to join a passionate team within Advanced Quantitative Sciences – Full Development.
: We have an exciting opportunity for an Associate Director (AD), Statistical Programming, to join a passionate team within Advanced Quantitative Sciences- Development.
Novartis - Senior Principal Statistical Programmer
We have an exciting opportunity for a Senior Principal Statistical Programmer, to join a passionate team within Advanced Quantitative Sciences – Development.
Pierre Fabre - Clinical Development Safety Statistics Expert M/F
We are seeking a highly skilled and proactive Clinical Development Safety Statistics Expert to join our Biometry Department and the Biometry Leadership Team based in Toulouse (31, Oncopole) or Boulogne (92).
Pierre Fabre - Lead Statistician – Real World Evidence -CDI- M/F
Pierre Fabre Laboratories are hiring a highly skilled and experienced Lead Statistician – Real World Evidence (RWE) to join the Biometry Department, part of the Data Science & Biometry Department, based in Toulouse (Oncopôle) or Boulogne.
Pierre Fabre - Lead Statistician- Clinical Trials M/F
We are seeking a highly skilled and experienced Lead Statistician in Clinical Trials to join our Biometry Department based in Toulouse (31, Oncopole) or Boulogne (92).
We are looking for Senior Statistical Programmers in the UK to join Veramed, where you'll deliver high-impact programming solutions in an FSP-style capacity, while advancing your career in a supportive, growth-driven environment.
