Date: Tuesday 27th June 2023 Time: 14:00-15:00 BST | 15:00-16:00 CET Speakers: Weiliang Qiu and Cheng Wenren
Who is this event intended for? Statisticians in the Pharmaceutical Industry. What is the benefit of attending? EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. In this talk, attendees will hear from Weiliang and Cheng who will be presenting their investigations on EC50 estimation based on multi-donor dose-response data via different approaches.
Registration
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
Overview
Weiliang Qiu1, Cheng Wenren1, Tamara Slavnic2, Els Pattyn1, Luc Essermeant1
1Non-Clinical Efficacy & Safety, Early Development & Research, Biostatistics & Programming, Sanofi
2 IT&M Stats.
Dose–response relationships are important in assessing the efficacy and potency of drugs, which can usually be characterized by a 4-parameter logistic (4-PL) model: EC50, slope, lower asymptote, and upper asymptote. EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. For multi-donor dose-response data, it is often the interest to estimate the overall EC50 and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in literature. Jiang and Kopp-Schneider (2014) systematically compared meta-analysis and nonlinear mixed-effects approaches and concluded that meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of small number of experiments, while nonlinear mixed-effects approach has issue of convergence failure probably due to overparameterization. In this talk, we investigated ways to improve nonlinear mixed-effects approach to alleviates its issue of convergence failure.
Weiliang Qiu, Els Pattyn, Cheng Wenren and Luc Essermeant are Sanofi employees and may hold shares and/or stock options in the company. Tamara Slavnic has nothing to disclose.
Speaker details
Speaker
Biography
Weiliang Qiu
Weiliang Qiu is a Non-Clinical Efficacy and Safety statistician expert leader at Sanofi and is passionate about using statistics knowledge to help improve the lives of patients. He obtained PhD degree in Statistics from the University of British Columbia in 2004 and have worked at Brigham and Women's Hospital/Harvard Medical School for 14 years since 2004.
Weiliang joined Sanofi Non-Clinical Efficacy and Safety (NCES) team in 2018 and provided statistical supports for non-clinical studies in a variety of therapeutic areas, such as translational sciences, rare and neurological diseases, immunology and inflammation, immuno-oncology, and Genome Medicine Unit. He also works with the NCES team to develop and implement innovative statistical methods to analyze the data from these studies.
Cheng Wenren
Cheng Wenren is a Principal Statistician in the Non-Clinical Efficacy & Safety (NCES) team at Sanofi. Prior to joining Sanofi in 2021, Cheng worked as a CMC Statistician at Bristol-Myers Squibb. Cheng earned his PhD in Statistics from Bowling Green State University in 2014, where his thesis focused on "Mixed model selection based on the conceptual predictive statistic".
Scientific Meetings
PSI Pre-Clinical SIG Webinar: An investigation to improve nonlinear mixed-effects approach for EC50 estimation based on multi-donor dose-response data
Date: Tuesday 27th June 2023 Time: 14:00-15:00 BST | 15:00-16:00 CET Speakers: Weiliang Qiu and Cheng Wenren
Who is this event intended for? Statisticians in the Pharmaceutical Industry. What is the benefit of attending? EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. In this talk, attendees will hear from Weiliang and Cheng who will be presenting their investigations on EC50 estimation based on multi-donor dose-response data via different approaches.
Registration
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
Overview
Weiliang Qiu1, Cheng Wenren1, Tamara Slavnic2, Els Pattyn1, Luc Essermeant1
1Non-Clinical Efficacy & Safety, Early Development & Research, Biostatistics & Programming, Sanofi
2 IT&M Stats.
Dose–response relationships are important in assessing the efficacy and potency of drugs, which can usually be characterized by a 4-parameter logistic (4-PL) model: EC50, slope, lower asymptote, and upper asymptote. EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. For multi-donor dose-response data, it is often the interest to estimate the overall EC50 and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in literature. Jiang and Kopp-Schneider (2014) systematically compared meta-analysis and nonlinear mixed-effects approaches and concluded that meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of small number of experiments, while nonlinear mixed-effects approach has issue of convergence failure probably due to overparameterization. In this talk, we investigated ways to improve nonlinear mixed-effects approach to alleviates its issue of convergence failure.
Weiliang Qiu, Els Pattyn, Cheng Wenren and Luc Essermeant are Sanofi employees and may hold shares and/or stock options in the company. Tamara Slavnic has nothing to disclose.
Speaker details
Speaker
Biography
Weiliang Qiu
Weiliang Qiu is a Non-Clinical Efficacy and Safety statistician expert leader at Sanofi and is passionate about using statistics knowledge to help improve the lives of patients. He obtained PhD degree in Statistics from the University of British Columbia in 2004 and have worked at Brigham and Women's Hospital/Harvard Medical School for 14 years since 2004.
Weiliang joined Sanofi Non-Clinical Efficacy and Safety (NCES) team in 2018 and provided statistical supports for non-clinical studies in a variety of therapeutic areas, such as translational sciences, rare and neurological diseases, immunology and inflammation, immuno-oncology, and Genome Medicine Unit. He also works with the NCES team to develop and implement innovative statistical methods to analyze the data from these studies.
Cheng Wenren
Cheng Wenren is a Principal Statistician in the Non-Clinical Efficacy & Safety (NCES) team at Sanofi. Prior to joining Sanofi in 2021, Cheng worked as a CMC Statistician at Bristol-Myers Squibb. Cheng earned his PhD in Statistics from Bowling Green State University in 2014, where his thesis focused on "Mixed model selection based on the conceptual predictive statistic".
Training Courses
PSI Pre-Clinical SIG Webinar: An investigation to improve nonlinear mixed-effects approach for EC50 estimation based on multi-donor dose-response data
Date: Tuesday 27th June 2023 Time: 14:00-15:00 BST | 15:00-16:00 CET Speakers: Weiliang Qiu and Cheng Wenren
Who is this event intended for? Statisticians in the Pharmaceutical Industry. What is the benefit of attending? EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. In this talk, attendees will hear from Weiliang and Cheng who will be presenting their investigations on EC50 estimation based on multi-donor dose-response data via different approaches.
Registration
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
Overview
Weiliang Qiu1, Cheng Wenren1, Tamara Slavnic2, Els Pattyn1, Luc Essermeant1
1Non-Clinical Efficacy & Safety, Early Development & Research, Biostatistics & Programming, Sanofi
2 IT&M Stats.
Dose–response relationships are important in assessing the efficacy and potency of drugs, which can usually be characterized by a 4-parameter logistic (4-PL) model: EC50, slope, lower asymptote, and upper asymptote. EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. For multi-donor dose-response data, it is often the interest to estimate the overall EC50 and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in literature. Jiang and Kopp-Schneider (2014) systematically compared meta-analysis and nonlinear mixed-effects approaches and concluded that meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of small number of experiments, while nonlinear mixed-effects approach has issue of convergence failure probably due to overparameterization. In this talk, we investigated ways to improve nonlinear mixed-effects approach to alleviates its issue of convergence failure.
Weiliang Qiu, Els Pattyn, Cheng Wenren and Luc Essermeant are Sanofi employees and may hold shares and/or stock options in the company. Tamara Slavnic has nothing to disclose.
Speaker details
Speaker
Biography
Weiliang Qiu
Weiliang Qiu is a Non-Clinical Efficacy and Safety statistician expert leader at Sanofi and is passionate about using statistics knowledge to help improve the lives of patients. He obtained PhD degree in Statistics from the University of British Columbia in 2004 and have worked at Brigham and Women's Hospital/Harvard Medical School for 14 years since 2004.
Weiliang joined Sanofi Non-Clinical Efficacy and Safety (NCES) team in 2018 and provided statistical supports for non-clinical studies in a variety of therapeutic areas, such as translational sciences, rare and neurological diseases, immunology and inflammation, immuno-oncology, and Genome Medicine Unit. He also works with the NCES team to develop and implement innovative statistical methods to analyze the data from these studies.
Cheng Wenren
Cheng Wenren is a Principal Statistician in the Non-Clinical Efficacy & Safety (NCES) team at Sanofi. Prior to joining Sanofi in 2021, Cheng worked as a CMC Statistician at Bristol-Myers Squibb. Cheng earned his PhD in Statistics from Bowling Green State University in 2014, where his thesis focused on "Mixed model selection based on the conceptual predictive statistic".
Journal Club
PSI Pre-Clinical SIG Webinar: An investigation to improve nonlinear mixed-effects approach for EC50 estimation based on multi-donor dose-response data
Date: Tuesday 27th June 2023 Time: 14:00-15:00 BST | 15:00-16:00 CET Speakers: Weiliang Qiu and Cheng Wenren
Who is this event intended for? Statisticians in the Pharmaceutical Industry. What is the benefit of attending? EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. In this talk, attendees will hear from Weiliang and Cheng who will be presenting their investigations on EC50 estimation based on multi-donor dose-response data via different approaches.
Registration
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
Overview
Weiliang Qiu1, Cheng Wenren1, Tamara Slavnic2, Els Pattyn1, Luc Essermeant1
1Non-Clinical Efficacy & Safety, Early Development & Research, Biostatistics & Programming, Sanofi
2 IT&M Stats.
Dose–response relationships are important in assessing the efficacy and potency of drugs, which can usually be characterized by a 4-parameter logistic (4-PL) model: EC50, slope, lower asymptote, and upper asymptote. EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. For multi-donor dose-response data, it is often the interest to estimate the overall EC50 and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in literature. Jiang and Kopp-Schneider (2014) systematically compared meta-analysis and nonlinear mixed-effects approaches and concluded that meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of small number of experiments, while nonlinear mixed-effects approach has issue of convergence failure probably due to overparameterization. In this talk, we investigated ways to improve nonlinear mixed-effects approach to alleviates its issue of convergence failure.
Weiliang Qiu, Els Pattyn, Cheng Wenren and Luc Essermeant are Sanofi employees and may hold shares and/or stock options in the company. Tamara Slavnic has nothing to disclose.
Speaker details
Speaker
Biography
Weiliang Qiu
Weiliang Qiu is a Non-Clinical Efficacy and Safety statistician expert leader at Sanofi and is passionate about using statistics knowledge to help improve the lives of patients. He obtained PhD degree in Statistics from the University of British Columbia in 2004 and have worked at Brigham and Women's Hospital/Harvard Medical School for 14 years since 2004.
Weiliang joined Sanofi Non-Clinical Efficacy and Safety (NCES) team in 2018 and provided statistical supports for non-clinical studies in a variety of therapeutic areas, such as translational sciences, rare and neurological diseases, immunology and inflammation, immuno-oncology, and Genome Medicine Unit. He also works with the NCES team to develop and implement innovative statistical methods to analyze the data from these studies.
Cheng Wenren
Cheng Wenren is a Principal Statistician in the Non-Clinical Efficacy & Safety (NCES) team at Sanofi. Prior to joining Sanofi in 2021, Cheng worked as a CMC Statistician at Bristol-Myers Squibb. Cheng earned his PhD in Statistics from Bowling Green State University in 2014, where his thesis focused on "Mixed model selection based on the conceptual predictive statistic".
Webinars
PSI Pre-Clinical SIG Webinar: An investigation to improve nonlinear mixed-effects approach for EC50 estimation based on multi-donor dose-response data
Date: Tuesday 27th June 2023 Time: 14:00-15:00 BST | 15:00-16:00 CET Speakers: Weiliang Qiu and Cheng Wenren
Who is this event intended for? Statisticians in the Pharmaceutical Industry. What is the benefit of attending? EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. In this talk, attendees will hear from Weiliang and Cheng who will be presenting their investigations on EC50 estimation based on multi-donor dose-response data via different approaches.
Registration
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
Overview
Weiliang Qiu1, Cheng Wenren1, Tamara Slavnic2, Els Pattyn1, Luc Essermeant1
1Non-Clinical Efficacy & Safety, Early Development & Research, Biostatistics & Programming, Sanofi
2 IT&M Stats.
Dose–response relationships are important in assessing the efficacy and potency of drugs, which can usually be characterized by a 4-parameter logistic (4-PL) model: EC50, slope, lower asymptote, and upper asymptote. EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. For multi-donor dose-response data, it is often the interest to estimate the overall EC50 and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in literature. Jiang and Kopp-Schneider (2014) systematically compared meta-analysis and nonlinear mixed-effects approaches and concluded that meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of small number of experiments, while nonlinear mixed-effects approach has issue of convergence failure probably due to overparameterization. In this talk, we investigated ways to improve nonlinear mixed-effects approach to alleviates its issue of convergence failure.
Weiliang Qiu, Els Pattyn, Cheng Wenren and Luc Essermeant are Sanofi employees and may hold shares and/or stock options in the company. Tamara Slavnic has nothing to disclose.
Speaker details
Speaker
Biography
Weiliang Qiu
Weiliang Qiu is a Non-Clinical Efficacy and Safety statistician expert leader at Sanofi and is passionate about using statistics knowledge to help improve the lives of patients. He obtained PhD degree in Statistics from the University of British Columbia in 2004 and have worked at Brigham and Women's Hospital/Harvard Medical School for 14 years since 2004.
Weiliang joined Sanofi Non-Clinical Efficacy and Safety (NCES) team in 2018 and provided statistical supports for non-clinical studies in a variety of therapeutic areas, such as translational sciences, rare and neurological diseases, immunology and inflammation, immuno-oncology, and Genome Medicine Unit. He also works with the NCES team to develop and implement innovative statistical methods to analyze the data from these studies.
Cheng Wenren
Cheng Wenren is a Principal Statistician in the Non-Clinical Efficacy & Safety (NCES) team at Sanofi. Prior to joining Sanofi in 2021, Cheng worked as a CMC Statistician at Bristol-Myers Squibb. Cheng earned his PhD in Statistics from Bowling Green State University in 2014, where his thesis focused on "Mixed model selection based on the conceptual predictive statistic".
Careers Meetings
PSI Pre-Clinical SIG Webinar: An investigation to improve nonlinear mixed-effects approach for EC50 estimation based on multi-donor dose-response data
Date: Tuesday 27th June 2023 Time: 14:00-15:00 BST | 15:00-16:00 CET Speakers: Weiliang Qiu and Cheng Wenren
Who is this event intended for? Statisticians in the Pharmaceutical Industry. What is the benefit of attending? EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. In this talk, attendees will hear from Weiliang and Cheng who will be presenting their investigations on EC50 estimation based on multi-donor dose-response data via different approaches.
Registration
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
Overview
Weiliang Qiu1, Cheng Wenren1, Tamara Slavnic2, Els Pattyn1, Luc Essermeant1
1Non-Clinical Efficacy & Safety, Early Development & Research, Biostatistics & Programming, Sanofi
2 IT&M Stats.
Dose–response relationships are important in assessing the efficacy and potency of drugs, which can usually be characterized by a 4-parameter logistic (4-PL) model: EC50, slope, lower asymptote, and upper asymptote. EC50, the concentration of a drug that induces a response halfway between the baseline and maximum, is a key quantity to evaluate drug potency. For multi-donor dose-response data, it is often the interest to estimate the overall EC50 and its 95% confidence interval (CI). A few multi-donor EC50 estimation methods have been proposed in literature. Jiang and Kopp-Schneider (2014) systematically compared meta-analysis and nonlinear mixed-effects approaches and concluded that meta-analysis approach is simple and robust to summarize EC50 estimates from multiple experiments, especially suited in the case of small number of experiments, while nonlinear mixed-effects approach has issue of convergence failure probably due to overparameterization. In this talk, we investigated ways to improve nonlinear mixed-effects approach to alleviates its issue of convergence failure.
Weiliang Qiu, Els Pattyn, Cheng Wenren and Luc Essermeant are Sanofi employees and may hold shares and/or stock options in the company. Tamara Slavnic has nothing to disclose.
Speaker details
Speaker
Biography
Weiliang Qiu
Weiliang Qiu is a Non-Clinical Efficacy and Safety statistician expert leader at Sanofi and is passionate about using statistics knowledge to help improve the lives of patients. He obtained PhD degree in Statistics from the University of British Columbia in 2004 and have worked at Brigham and Women's Hospital/Harvard Medical School for 14 years since 2004.
Weiliang joined Sanofi Non-Clinical Efficacy and Safety (NCES) team in 2018 and provided statistical supports for non-clinical studies in a variety of therapeutic areas, such as translational sciences, rare and neurological diseases, immunology and inflammation, immuno-oncology, and Genome Medicine Unit. He also works with the NCES team to develop and implement innovative statistical methods to analyze the data from these studies.
Cheng Wenren
Cheng Wenren is a Principal Statistician in the Non-Clinical Efficacy & Safety (NCES) team at Sanofi. Prior to joining Sanofi in 2021, Cheng worked as a CMC Statistician at Bristol-Myers Squibb. Cheng earned his PhD in Statistics from Bowling Green State University in 2014, where his thesis focused on "Mixed model selection based on the conceptual predictive statistic".
Upcoming Events
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
PSI Introduction to Industry Training (ITIT) Course - 2024/2025
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
PSI Training Course: Mixed Models and Repeated Measures
This course is presented through lectures and practical sessions using SAS code. It is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models.
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.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
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