Dr Francq will discuss the need for analytical methods to deliver unbiased and precise results and talk in detail on confidence, prediction and tolerance intervals work in linear mixed models and the interpretation of statistical results.
This will be followed by Q&A.
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
Dr Francq will discuss the need for analytical methods to deliver unbiased and precise results and talk in detail on confidence, prediction and tolerance intervals work in linear mixed models and the interpretation of statistical results.
This will be followed by Q&A.
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
Dr Francq will discuss the need for analytical methods to deliver unbiased and precise results and talk in detail on confidence, prediction and tolerance intervals work in linear mixed models and the interpretation of statistical results.
This will be followed by Q&A.
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
Dr Francq will discuss the need for analytical methods to deliver unbiased and precise results and talk in detail on confidence, prediction and tolerance intervals work in linear mixed models and the interpretation of statistical results.
This will be followed by Q&A.
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
Dr Francq will discuss the need for analytical methods to deliver unbiased and precise results and talk in detail on confidence, prediction and tolerance intervals work in linear mixed models and the interpretation of statistical results.
This will be followed by Q&A.
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
Dr Francq will discuss the need for analytical methods to deliver unbiased and precise results and talk in detail on confidence, prediction and tolerance intervals work in linear mixed models and the interpretation of statistical results.
This will be followed by Q&A.
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 VisSIG Wonderful Wednesday Webinar Series (2023)
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.
An informal event starting with a short talk and then going into breakout rooms to connect with others from the industry. Aimed at those who have recently joined the industry looking to expand their network.
This role is for a senior functional team member supporting Biostatistics activities on assigned Clinical Development, Enterprise Data & Analytics, and QDS projects.