PSI Webinar(s): Causal inference in Clinical Trials
Over the course of two sessions, a panel of 8 esteemed speakers will give an introduction to the topic, followed by a presentation of case studies & interactive panel discussion.
This event will offer a practical introduction to modern methods of data visualisation.
Date: Friday 17th & Friday 24th September 2021 (Please note: this event is split into 2 parts)
Time: 13:00-17:00 BST both days
Speakers:
Part 1: Susan Mayo (FDA), Jeremy Wildfire (Gilead), Sheila Dickinson (Novartis), Matthias Trampisch (Boehringer Ingelheim), Charlotta Fruechtenicht (Roche), Patrick Schlömer (Bayer).
Part 2: Alexander Schacht (Veramed), Charlotta Fruechtenicht (Roche), James Black (Roche), Jeremy Wildfire (Gilead), Madhurima Majumder (Bayer)
Who is this event intended for? Anyone interested in data visualisation in the pharmaceutical industry.
What is the benefit of attending? Gain new insights into data visualisations and learn about the regulatory perspective. With no technical or coding knowledge assumed, a variety of practical workshop exercises will bring to life many of the concepts learned in part one. Topics include graphic design, and interactive data visualisation tools.
Part 1
Member rate = £20+VAT
Non-Member rate = £115*+VAT
*Please note: Non-Member rates include membership for the rest of the 2021 calendar year.
Part 2
Member & Non-Member rate = £60+VAT
PLEASE NOTE: Registration for Part 1 is compulsory in order to register for Part 2; in so doing, your registration for Part 2 only will be submitted for approval. As there are a limited amount of places available for Part 2, we advise booking early to avoid disappointment!
To register for Part 1 (17/09/21), please click here.
To register for Part 2 (24/09/21), please click here.
Part 1
Data visualisation has been used to gain insights into medical data for over 150 years. More modern methods include interactive and animated data visualisation tools, and the development of open source code using agile methods.
This online event will provide a practical introduction to modern methods of data visualisation, including presentations from some well-known and influential speakers in part 1 and practical hands-on workshop exercises in part 2.
To view the agenda for Part 1, please click here.
Part 2
This workshop will provide a practical introduction to modern methods of data visualisation through practical hands-on workshop exercises.
This includes interactive and animated data visualisation tools, and the development of open source code.
To view the agenda for Part 2, please click here.
Speaker | Biography | Abstract |
|
Susan is a senior mathematical statistician at the Food and Drug Administration, Center for Drug Evaluation’s Office of Biostatistics, with a demonstrated interest and impact in areas that help to make sound regulatory and drug development decisions: graphical design, drug safety and benefit-risk assessment, and the estimand framework. She has been with FDA for over 3 years, and previously worked as an industry statistician and internal company consultant in biotech and big pharma for a few more than that.
|
Making Impactful Graphs: Looking through the eyes of your audience
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
Building Open Source Tools for Safety Monitoring: Advancing Research Through Community Collaboration The Interactive Safety Graphics group seeks to modernize clinical trial safety monitoring by building tools for data exploration and reporting in a highly collaborative open source environment. At present, our team includes clinical and technical representatives from the pharmaceutical industry, academia, and the FDA, and additional contributors are always welcome |
|
Sheila Dickinson is a Global Benefit-Risk Lead, working in the Quantitative Safety and Epidemiology group at Novartis. Her responsibilities include promoting and facilitating the use of a structured benefit-risk approach by Novartis project teams. Sheila is also working on the topic of patient preference studies and is on the management board of the IMI PREFER project, which is working on developing guidelines about when and how to perform patient preference studies to support medical product decision-making. Sheila holds a degree in mathematics from Imperial College, London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine. After joining Novartis in 1997, she worked as a statistician supporting projects in the various disease areas including both diabetes and malaria, before moving to the Quantitative Safety team in 2013. |
Points to bear in mind for visual displays of benefit-risk data
|
|
Matthias works as a Safety Statistician in independent Safety Analysis Team (iSAT) at Boehringer Ingelheim. iSAT is specialized on analyzing ongoing trial data in an unblinded fashion supporting interim analysis, ad-hoc unblinding requests, or Data Monitoring Committees (DMCs).
|
Dynamic data visualization for Benefit/Risk Assessment DURING trial conduct - Insights based on DMC output for monitoring a trial in patients hospitalized with COVID-19 This talk presents learnings from a recent Boehringer Ingelheim trial targeting to prevent Adult Respiratory Distress Syndrom (ARDS) in hospitalized COVID-19 patients. It focuses on a specific output created for the Data Monitoring Committees (DMC) which combined most of the pre-defined efficacy and safety endpoints in an interactive heat-plot. Sample data and code to generate the plot will be provided |
|
Patrick received his PhD in Statistics from the University of Bremen, Germany, in 2014 for his work on group sequential and adaptive designs for three-arm non-inferiority trials. Since then he has been working at Bayer as a clinical statistician in the cardio-renal area with increasing responsibilities. Currently he acts as the Compound Statistician for a novel treatment for chronic kidney disease in type 2 diabetes that recently received FDA approval. His methodological interests include group sequential and adaptive designs, multiple comparison procedures and recurrent events. In the past years he has been working on the application for an EMA “Qualification opinion of clinically interpretable treatment effect measures based on recurrent event endpoints that allow for efficient statistical analyses”. Besides this he has been actively involved in the development of the Data Insight Generation (D.I.G) concept at Bayer, which was recently piloted in a large Phase III trial to gain deeper insights into the study data by means of intelligent visualizations.
|
Data Insight Generation (D.I.G) – A concept to foster interactive and interdisciplinary data investigations using intelligent visualizations
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines.
|
Learnings from implementing good graphical principles in a ready-to-use R package
|
Speaker | Biography | Abstract |
|
I studied mathematics and received my PhD in biostatistics on non-parametric statistics from the University of Göttingen in Germany. I authored more than 70 scientific manuscripts in peer-reviewed journals and regularly speak at international conferences – both statistical ones like PSI and medical ones like EADV. During my career at university and within the pharma industry, I have collected more than 20 years of experience. My career focused mostly on phase III and IV (RCT, observational studies, HTA submission, commercialization work) with some regulatory work as well as some experience in the early phases of clinical development. I’m interested in a broad range of methodological areas but specifically on making better decisions based on data. As such, I was the chair of the EFSPI/SPI SIG on benefit-risk for some time. PSI provided my with many more opportunities, which I’m happy to work on. At work, I supervise of a small but mighty team of statisticians in a large pharma company. The virtual work environment requires me to adjust my communication style and focus on my ability to deliver results effectively. I’m a happy husband and father of 3 wonderful kids, who I love to spend time with. In the rest of my time, I love running and listening to podcasts. |
Data Visualisation Paper and Pen Exercise
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines. |
How to implement effective visualisations in R using visR
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
ASA Safety Monitoring Tool Exercise |
|
Madhurima Majumder is a Senior Manager of Statistics and Data Insights at Bayer US LLC. Since joining Bayer in 2017, Madhurima has supported cardiovascular and thrombosis studies. She is also a member of various cross-industry working initiatives like the Drug Information Association’s (DIA) Clinically Meaningful Change Group, The Forum for Collaborative Research, etc. Her research interest focuses not only in statistical methodology but also in developing user-friendly data visualization tools for clinical trial results. She holds a PhD in Statistics from the University of Rochester, New York. |
Elaborator App
|
Alexander Schacht (Veramed) |
|
Improving a “bad” graph
|
This event will offer a practical introduction to modern methods of data visualisation.
Date: Friday 17th & Friday 24th September 2021 (Please note: this event is split into 2 parts)
Time: 13:00-17:00 BST both days
Speakers:
Part 1: Susan Mayo (FDA), Jeremy Wildfire (Gilead), Sheila Dickinson (Novartis), Matthias Trampisch (Boehringer Ingelheim), Charlotta Fruechtenicht (Roche), Patrick Schlömer (Bayer).
Part 2: Alexander Schacht (Veramed), Charlotta Fruechtenicht (Roche), James Black (Roche), Jeremy Wildfire (Gilead), Madhurima Majumder (Bayer)
Who is this event intended for? Anyone interested in data visualisation in the pharmaceutical industry.
What is the benefit of attending? Gain new insights into data visualisations and learn about the regulatory perspective. With no technical or coding knowledge assumed, a variety of practical workshop exercises will bring to life many of the concepts learned in part one. Topics include graphic design, and interactive data visualisation tools.
Part 1
Member rate = £20+VAT
Non-Member rate = £115*+VAT
*Please note: Non-Member rates include membership for the rest of the 2021 calendar year.
Part 2
Member & Non-Member rate = £60+VAT
PLEASE NOTE: Registration for Part 1 is compulsory in order to register for Part 2; in so doing, your registration for Part 2 only will be submitted for approval. As there are a limited amount of places available for Part 2, we advise booking early to avoid disappointment!
To register for Part 1 (17/09/21), please click here.
To register for Part 2 (24/09/21), please click here.
Part 1
Data visualisation has been used to gain insights into medical data for over 150 years. More modern methods include interactive and animated data visualisation tools, and the development of open source code using agile methods.
This online event will provide a practical introduction to modern methods of data visualisation, including presentations from some well-known and influential speakers in part 1 and practical hands-on workshop exercises in part 2.
To view the agenda for Part 1, please click here.
Part 2
This workshop will provide a practical introduction to modern methods of data visualisation through practical hands-on workshop exercises.
This includes interactive and animated data visualisation tools, and the development of open source code.
To view the agenda for Part 2, please click here.
Speaker | Biography | Abstract |
|
Susan is a senior mathematical statistician at the Food and Drug Administration, Center for Drug Evaluation’s Office of Biostatistics, with a demonstrated interest and impact in areas that help to make sound regulatory and drug development decisions: graphical design, drug safety and benefit-risk assessment, and the estimand framework. She has been with FDA for over 3 years, and previously worked as an industry statistician and internal company consultant in biotech and big pharma for a few more than that.
|
Making Impactful Graphs: Looking through the eyes of your audience
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
Building Open Source Tools for Safety Monitoring: Advancing Research Through Community Collaboration The Interactive Safety Graphics group seeks to modernize clinical trial safety monitoring by building tools for data exploration and reporting in a highly collaborative open source environment. At present, our team includes clinical and technical representatives from the pharmaceutical industry, academia, and the FDA, and additional contributors are always welcome |
|
Sheila Dickinson is a Global Benefit-Risk Lead, working in the Quantitative Safety and Epidemiology group at Novartis. Her responsibilities include promoting and facilitating the use of a structured benefit-risk approach by Novartis project teams. Sheila is also working on the topic of patient preference studies and is on the management board of the IMI PREFER project, which is working on developing guidelines about when and how to perform patient preference studies to support medical product decision-making. Sheila holds a degree in mathematics from Imperial College, London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine. After joining Novartis in 1997, she worked as a statistician supporting projects in the various disease areas including both diabetes and malaria, before moving to the Quantitative Safety team in 2013. |
Points to bear in mind for visual displays of benefit-risk data
|
|
Matthias works as a Safety Statistician in independent Safety Analysis Team (iSAT) at Boehringer Ingelheim. iSAT is specialized on analyzing ongoing trial data in an unblinded fashion supporting interim analysis, ad-hoc unblinding requests, or Data Monitoring Committees (DMCs).
|
Dynamic data visualization for Benefit/Risk Assessment DURING trial conduct - Insights based on DMC output for monitoring a trial in patients hospitalized with COVID-19 This talk presents learnings from a recent Boehringer Ingelheim trial targeting to prevent Adult Respiratory Distress Syndrom (ARDS) in hospitalized COVID-19 patients. It focuses on a specific output created for the Data Monitoring Committees (DMC) which combined most of the pre-defined efficacy and safety endpoints in an interactive heat-plot. Sample data and code to generate the plot will be provided |
|
Patrick received his PhD in Statistics from the University of Bremen, Germany, in 2014 for his work on group sequential and adaptive designs for three-arm non-inferiority trials. Since then he has been working at Bayer as a clinical statistician in the cardio-renal area with increasing responsibilities. Currently he acts as the Compound Statistician for a novel treatment for chronic kidney disease in type 2 diabetes that recently received FDA approval. His methodological interests include group sequential and adaptive designs, multiple comparison procedures and recurrent events. In the past years he has been working on the application for an EMA “Qualification opinion of clinically interpretable treatment effect measures based on recurrent event endpoints that allow for efficient statistical analyses”. Besides this he has been actively involved in the development of the Data Insight Generation (D.I.G) concept at Bayer, which was recently piloted in a large Phase III trial to gain deeper insights into the study data by means of intelligent visualizations.
|
Data Insight Generation (D.I.G) – A concept to foster interactive and interdisciplinary data investigations using intelligent visualizations
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines.
|
Learnings from implementing good graphical principles in a ready-to-use R package
|
Speaker | Biography | Abstract |
|
I studied mathematics and received my PhD in biostatistics on non-parametric statistics from the University of Göttingen in Germany. I authored more than 70 scientific manuscripts in peer-reviewed journals and regularly speak at international conferences – both statistical ones like PSI and medical ones like EADV. During my career at university and within the pharma industry, I have collected more than 20 years of experience. My career focused mostly on phase III and IV (RCT, observational studies, HTA submission, commercialization work) with some regulatory work as well as some experience in the early phases of clinical development. I’m interested in a broad range of methodological areas but specifically on making better decisions based on data. As such, I was the chair of the EFSPI/SPI SIG on benefit-risk for some time. PSI provided my with many more opportunities, which I’m happy to work on. At work, I supervise of a small but mighty team of statisticians in a large pharma company. The virtual work environment requires me to adjust my communication style and focus on my ability to deliver results effectively. I’m a happy husband and father of 3 wonderful kids, who I love to spend time with. In the rest of my time, I love running and listening to podcasts. |
Data Visualisation Paper and Pen Exercise
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines. |
How to implement effective visualisations in R using visR
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
ASA Safety Monitoring Tool Exercise |
|
Madhurima Majumder is a Senior Manager of Statistics and Data Insights at Bayer US LLC. Since joining Bayer in 2017, Madhurima has supported cardiovascular and thrombosis studies. She is also a member of various cross-industry working initiatives like the Drug Information Association’s (DIA) Clinically Meaningful Change Group, The Forum for Collaborative Research, etc. Her research interest focuses not only in statistical methodology but also in developing user-friendly data visualization tools for clinical trial results. She holds a PhD in Statistics from the University of Rochester, New York. |
Elaborator App
|
Alexander Schacht (Veramed) |
|
Improving a “bad” graph
|
This event will offer a practical introduction to modern methods of data visualisation.
Date: Friday 17th & Friday 24th September 2021 (Please note: this event is split into 2 parts)
Time: 13:00-17:00 BST both days
Speakers:
Part 1: Susan Mayo (FDA), Jeremy Wildfire (Gilead), Sheila Dickinson (Novartis), Matthias Trampisch (Boehringer Ingelheim), Charlotta Fruechtenicht (Roche), Patrick Schlömer (Bayer).
Part 2: Alexander Schacht (Veramed), Charlotta Fruechtenicht (Roche), James Black (Roche), Jeremy Wildfire (Gilead), Madhurima Majumder (Bayer)
Who is this event intended for? Anyone interested in data visualisation in the pharmaceutical industry.
What is the benefit of attending? Gain new insights into data visualisations and learn about the regulatory perspective. With no technical or coding knowledge assumed, a variety of practical workshop exercises will bring to life many of the concepts learned in part one. Topics include graphic design, and interactive data visualisation tools.
Part 1
Member rate = £20+VAT
Non-Member rate = £115*+VAT
*Please note: Non-Member rates include membership for the rest of the 2021 calendar year.
Part 2
Member & Non-Member rate = £60+VAT
PLEASE NOTE: Registration for Part 1 is compulsory in order to register for Part 2; in so doing, your registration for Part 2 only will be submitted for approval. As there are a limited amount of places available for Part 2, we advise booking early to avoid disappointment!
To register for Part 1 (17/09/21), please click here.
To register for Part 2 (24/09/21), please click here.
Part 1
Data visualisation has been used to gain insights into medical data for over 150 years. More modern methods include interactive and animated data visualisation tools, and the development of open source code using agile methods.
This online event will provide a practical introduction to modern methods of data visualisation, including presentations from some well-known and influential speakers in part 1 and practical hands-on workshop exercises in part 2.
To view the agenda for Part 1, please click here.
Part 2
This workshop will provide a practical introduction to modern methods of data visualisation through practical hands-on workshop exercises.
This includes interactive and animated data visualisation tools, and the development of open source code.
To view the agenda for Part 2, please click here.
Speaker | Biography | Abstract |
|
Susan is a senior mathematical statistician at the Food and Drug Administration, Center for Drug Evaluation’s Office of Biostatistics, with a demonstrated interest and impact in areas that help to make sound regulatory and drug development decisions: graphical design, drug safety and benefit-risk assessment, and the estimand framework. She has been with FDA for over 3 years, and previously worked as an industry statistician and internal company consultant in biotech and big pharma for a few more than that.
|
Making Impactful Graphs: Looking through the eyes of your audience
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
Building Open Source Tools for Safety Monitoring: Advancing Research Through Community Collaboration The Interactive Safety Graphics group seeks to modernize clinical trial safety monitoring by building tools for data exploration and reporting in a highly collaborative open source environment. At present, our team includes clinical and technical representatives from the pharmaceutical industry, academia, and the FDA, and additional contributors are always welcome |
|
Sheila Dickinson is a Global Benefit-Risk Lead, working in the Quantitative Safety and Epidemiology group at Novartis. Her responsibilities include promoting and facilitating the use of a structured benefit-risk approach by Novartis project teams. Sheila is also working on the topic of patient preference studies and is on the management board of the IMI PREFER project, which is working on developing guidelines about when and how to perform patient preference studies to support medical product decision-making. Sheila holds a degree in mathematics from Imperial College, London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine. After joining Novartis in 1997, she worked as a statistician supporting projects in the various disease areas including both diabetes and malaria, before moving to the Quantitative Safety team in 2013. |
Points to bear in mind for visual displays of benefit-risk data
|
|
Matthias works as a Safety Statistician in independent Safety Analysis Team (iSAT) at Boehringer Ingelheim. iSAT is specialized on analyzing ongoing trial data in an unblinded fashion supporting interim analysis, ad-hoc unblinding requests, or Data Monitoring Committees (DMCs).
|
Dynamic data visualization for Benefit/Risk Assessment DURING trial conduct - Insights based on DMC output for monitoring a trial in patients hospitalized with COVID-19 This talk presents learnings from a recent Boehringer Ingelheim trial targeting to prevent Adult Respiratory Distress Syndrom (ARDS) in hospitalized COVID-19 patients. It focuses on a specific output created for the Data Monitoring Committees (DMC) which combined most of the pre-defined efficacy and safety endpoints in an interactive heat-plot. Sample data and code to generate the plot will be provided |
|
Patrick received his PhD in Statistics from the University of Bremen, Germany, in 2014 for his work on group sequential and adaptive designs for three-arm non-inferiority trials. Since then he has been working at Bayer as a clinical statistician in the cardio-renal area with increasing responsibilities. Currently he acts as the Compound Statistician for a novel treatment for chronic kidney disease in type 2 diabetes that recently received FDA approval. His methodological interests include group sequential and adaptive designs, multiple comparison procedures and recurrent events. In the past years he has been working on the application for an EMA “Qualification opinion of clinically interpretable treatment effect measures based on recurrent event endpoints that allow for efficient statistical analyses”. Besides this he has been actively involved in the development of the Data Insight Generation (D.I.G) concept at Bayer, which was recently piloted in a large Phase III trial to gain deeper insights into the study data by means of intelligent visualizations.
|
Data Insight Generation (D.I.G) – A concept to foster interactive and interdisciplinary data investigations using intelligent visualizations
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines.
|
Learnings from implementing good graphical principles in a ready-to-use R package
|
Speaker | Biography | Abstract |
|
I studied mathematics and received my PhD in biostatistics on non-parametric statistics from the University of Göttingen in Germany. I authored more than 70 scientific manuscripts in peer-reviewed journals and regularly speak at international conferences – both statistical ones like PSI and medical ones like EADV. During my career at university and within the pharma industry, I have collected more than 20 years of experience. My career focused mostly on phase III and IV (RCT, observational studies, HTA submission, commercialization work) with some regulatory work as well as some experience in the early phases of clinical development. I’m interested in a broad range of methodological areas but specifically on making better decisions based on data. As such, I was the chair of the EFSPI/SPI SIG on benefit-risk for some time. PSI provided my with many more opportunities, which I’m happy to work on. At work, I supervise of a small but mighty team of statisticians in a large pharma company. The virtual work environment requires me to adjust my communication style and focus on my ability to deliver results effectively. I’m a happy husband and father of 3 wonderful kids, who I love to spend time with. In the rest of my time, I love running and listening to podcasts. |
Data Visualisation Paper and Pen Exercise
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines. |
How to implement effective visualisations in R using visR
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
ASA Safety Monitoring Tool Exercise |
|
Madhurima Majumder is a Senior Manager of Statistics and Data Insights at Bayer US LLC. Since joining Bayer in 2017, Madhurima has supported cardiovascular and thrombosis studies. She is also a member of various cross-industry working initiatives like the Drug Information Association’s (DIA) Clinically Meaningful Change Group, The Forum for Collaborative Research, etc. Her research interest focuses not only in statistical methodology but also in developing user-friendly data visualization tools for clinical trial results. She holds a PhD in Statistics from the University of Rochester, New York. |
Elaborator App
|
Alexander Schacht (Veramed) |
|
Improving a “bad” graph
|
This event will offer a practical introduction to modern methods of data visualisation.
Date: Friday 17th & Friday 24th September 2021 (Please note: this event is split into 2 parts)
Time: 13:00-17:00 BST both days
Speakers:
Part 1: Susan Mayo (FDA), Jeremy Wildfire (Gilead), Sheila Dickinson (Novartis), Matthias Trampisch (Boehringer Ingelheim), Charlotta Fruechtenicht (Roche), Patrick Schlömer (Bayer).
Part 2: Alexander Schacht (Veramed), Charlotta Fruechtenicht (Roche), James Black (Roche), Jeremy Wildfire (Gilead), Madhurima Majumder (Bayer)
Who is this event intended for? Anyone interested in data visualisation in the pharmaceutical industry.
What is the benefit of attending? Gain new insights into data visualisations and learn about the regulatory perspective. With no technical or coding knowledge assumed, a variety of practical workshop exercises will bring to life many of the concepts learned in part one. Topics include graphic design, and interactive data visualisation tools.
Part 1
Member rate = £20+VAT
Non-Member rate = £115*+VAT
*Please note: Non-Member rates include membership for the rest of the 2021 calendar year.
Part 2
Member & Non-Member rate = £60+VAT
PLEASE NOTE: Registration for Part 1 is compulsory in order to register for Part 2; in so doing, your registration for Part 2 only will be submitted for approval. As there are a limited amount of places available for Part 2, we advise booking early to avoid disappointment!
To register for Part 1 (17/09/21), please click here.
To register for Part 2 (24/09/21), please click here.
Part 1
Data visualisation has been used to gain insights into medical data for over 150 years. More modern methods include interactive and animated data visualisation tools, and the development of open source code using agile methods.
This online event will provide a practical introduction to modern methods of data visualisation, including presentations from some well-known and influential speakers in part 1 and practical hands-on workshop exercises in part 2.
To view the agenda for Part 1, please click here.
Part 2
This workshop will provide a practical introduction to modern methods of data visualisation through practical hands-on workshop exercises.
This includes interactive and animated data visualisation tools, and the development of open source code.
To view the agenda for Part 2, please click here.
Speaker | Biography | Abstract |
|
Susan is a senior mathematical statistician at the Food and Drug Administration, Center for Drug Evaluation’s Office of Biostatistics, with a demonstrated interest and impact in areas that help to make sound regulatory and drug development decisions: graphical design, drug safety and benefit-risk assessment, and the estimand framework. She has been with FDA for over 3 years, and previously worked as an industry statistician and internal company consultant in biotech and big pharma for a few more than that.
|
Making Impactful Graphs: Looking through the eyes of your audience
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
Building Open Source Tools for Safety Monitoring: Advancing Research Through Community Collaboration The Interactive Safety Graphics group seeks to modernize clinical trial safety monitoring by building tools for data exploration and reporting in a highly collaborative open source environment. At present, our team includes clinical and technical representatives from the pharmaceutical industry, academia, and the FDA, and additional contributors are always welcome |
|
Sheila Dickinson is a Global Benefit-Risk Lead, working in the Quantitative Safety and Epidemiology group at Novartis. Her responsibilities include promoting and facilitating the use of a structured benefit-risk approach by Novartis project teams. Sheila is also working on the topic of patient preference studies and is on the management board of the IMI PREFER project, which is working on developing guidelines about when and how to perform patient preference studies to support medical product decision-making. Sheila holds a degree in mathematics from Imperial College, London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine. After joining Novartis in 1997, she worked as a statistician supporting projects in the various disease areas including both diabetes and malaria, before moving to the Quantitative Safety team in 2013. |
Points to bear in mind for visual displays of benefit-risk data
|
|
Matthias works as a Safety Statistician in independent Safety Analysis Team (iSAT) at Boehringer Ingelheim. iSAT is specialized on analyzing ongoing trial data in an unblinded fashion supporting interim analysis, ad-hoc unblinding requests, or Data Monitoring Committees (DMCs).
|
Dynamic data visualization for Benefit/Risk Assessment DURING trial conduct - Insights based on DMC output for monitoring a trial in patients hospitalized with COVID-19 This talk presents learnings from a recent Boehringer Ingelheim trial targeting to prevent Adult Respiratory Distress Syndrom (ARDS) in hospitalized COVID-19 patients. It focuses on a specific output created for the Data Monitoring Committees (DMC) which combined most of the pre-defined efficacy and safety endpoints in an interactive heat-plot. Sample data and code to generate the plot will be provided |
|
Patrick received his PhD in Statistics from the University of Bremen, Germany, in 2014 for his work on group sequential and adaptive designs for three-arm non-inferiority trials. Since then he has been working at Bayer as a clinical statistician in the cardio-renal area with increasing responsibilities. Currently he acts as the Compound Statistician for a novel treatment for chronic kidney disease in type 2 diabetes that recently received FDA approval. His methodological interests include group sequential and adaptive designs, multiple comparison procedures and recurrent events. In the past years he has been working on the application for an EMA “Qualification opinion of clinically interpretable treatment effect measures based on recurrent event endpoints that allow for efficient statistical analyses”. Besides this he has been actively involved in the development of the Data Insight Generation (D.I.G) concept at Bayer, which was recently piloted in a large Phase III trial to gain deeper insights into the study data by means of intelligent visualizations.
|
Data Insight Generation (D.I.G) – A concept to foster interactive and interdisciplinary data investigations using intelligent visualizations
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Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines.
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Learnings from implementing good graphical principles in a ready-to-use R package
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Speaker | Biography | Abstract |
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I studied mathematics and received my PhD in biostatistics on non-parametric statistics from the University of Göttingen in Germany. I authored more than 70 scientific manuscripts in peer-reviewed journals and regularly speak at international conferences – both statistical ones like PSI and medical ones like EADV. During my career at university and within the pharma industry, I have collected more than 20 years of experience. My career focused mostly on phase III and IV (RCT, observational studies, HTA submission, commercialization work) with some regulatory work as well as some experience in the early phases of clinical development. I’m interested in a broad range of methodological areas but specifically on making better decisions based on data. As such, I was the chair of the EFSPI/SPI SIG on benefit-risk for some time. PSI provided my with many more opportunities, which I’m happy to work on. At work, I supervise of a small but mighty team of statisticians in a large pharma company. The virtual work environment requires me to adjust my communication style and focus on my ability to deliver results effectively. I’m a happy husband and father of 3 wonderful kids, who I love to spend time with. In the rest of my time, I love running and listening to podcasts. |
Data Visualisation Paper and Pen Exercise
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Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines. |
How to implement effective visualisations in R using visR
|
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Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
ASA Safety Monitoring Tool Exercise |
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Madhurima Majumder is a Senior Manager of Statistics and Data Insights at Bayer US LLC. Since joining Bayer in 2017, Madhurima has supported cardiovascular and thrombosis studies. She is also a member of various cross-industry working initiatives like the Drug Information Association’s (DIA) Clinically Meaningful Change Group, The Forum for Collaborative Research, etc. Her research interest focuses not only in statistical methodology but also in developing user-friendly data visualization tools for clinical trial results. She holds a PhD in Statistics from the University of Rochester, New York. |
Elaborator App
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Alexander Schacht (Veramed) |
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Improving a “bad” graph
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This event will offer a practical introduction to modern methods of data visualisation.
Date: Friday 17th & Friday 24th September 2021 (Please note: this event is split into 2 parts)
Time: 13:00-17:00 BST both days
Speakers:
Part 1: Susan Mayo (FDA), Jeremy Wildfire (Gilead), Sheila Dickinson (Novartis), Matthias Trampisch (Boehringer Ingelheim), Charlotta Fruechtenicht (Roche), Patrick Schlömer (Bayer).
Part 2: Alexander Schacht (Veramed), Charlotta Fruechtenicht (Roche), James Black (Roche), Jeremy Wildfire (Gilead), Madhurima Majumder (Bayer)
Who is this event intended for? Anyone interested in data visualisation in the pharmaceutical industry.
What is the benefit of attending? Gain new insights into data visualisations and learn about the regulatory perspective. With no technical or coding knowledge assumed, a variety of practical workshop exercises will bring to life many of the concepts learned in part one. Topics include graphic design, and interactive data visualisation tools.
Part 1
Member rate = £20+VAT
Non-Member rate = £115*+VAT
*Please note: Non-Member rates include membership for the rest of the 2021 calendar year.
Part 2
Member & Non-Member rate = £60+VAT
PLEASE NOTE: Registration for Part 1 is compulsory in order to register for Part 2; in so doing, your registration for Part 2 only will be submitted for approval. As there are a limited amount of places available for Part 2, we advise booking early to avoid disappointment!
To register for Part 1 (17/09/21), please click here.
To register for Part 2 (24/09/21), please click here.
Part 1
Data visualisation has been used to gain insights into medical data for over 150 years. More modern methods include interactive and animated data visualisation tools, and the development of open source code using agile methods.
This online event will provide a practical introduction to modern methods of data visualisation, including presentations from some well-known and influential speakers in part 1 and practical hands-on workshop exercises in part 2.
To view the agenda for Part 1, please click here.
Part 2
This workshop will provide a practical introduction to modern methods of data visualisation through practical hands-on workshop exercises.
This includes interactive and animated data visualisation tools, and the development of open source code.
To view the agenda for Part 2, please click here.
Speaker | Biography | Abstract |
|
Susan is a senior mathematical statistician at the Food and Drug Administration, Center for Drug Evaluation’s Office of Biostatistics, with a demonstrated interest and impact in areas that help to make sound regulatory and drug development decisions: graphical design, drug safety and benefit-risk assessment, and the estimand framework. She has been with FDA for over 3 years, and previously worked as an industry statistician and internal company consultant in biotech and big pharma for a few more than that.
|
Making Impactful Graphs: Looking through the eyes of your audience
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
Building Open Source Tools for Safety Monitoring: Advancing Research Through Community Collaboration The Interactive Safety Graphics group seeks to modernize clinical trial safety monitoring by building tools for data exploration and reporting in a highly collaborative open source environment. At present, our team includes clinical and technical representatives from the pharmaceutical industry, academia, and the FDA, and additional contributors are always welcome |
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Sheila Dickinson is a Global Benefit-Risk Lead, working in the Quantitative Safety and Epidemiology group at Novartis. Her responsibilities include promoting and facilitating the use of a structured benefit-risk approach by Novartis project teams. Sheila is also working on the topic of patient preference studies and is on the management board of the IMI PREFER project, which is working on developing guidelines about when and how to perform patient preference studies to support medical product decision-making. Sheila holds a degree in mathematics from Imperial College, London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine. After joining Novartis in 1997, she worked as a statistician supporting projects in the various disease areas including both diabetes and malaria, before moving to the Quantitative Safety team in 2013. |
Points to bear in mind for visual displays of benefit-risk data
|
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Matthias works as a Safety Statistician in independent Safety Analysis Team (iSAT) at Boehringer Ingelheim. iSAT is specialized on analyzing ongoing trial data in an unblinded fashion supporting interim analysis, ad-hoc unblinding requests, or Data Monitoring Committees (DMCs).
|
Dynamic data visualization for Benefit/Risk Assessment DURING trial conduct - Insights based on DMC output for monitoring a trial in patients hospitalized with COVID-19 This talk presents learnings from a recent Boehringer Ingelheim trial targeting to prevent Adult Respiratory Distress Syndrom (ARDS) in hospitalized COVID-19 patients. It focuses on a specific output created for the Data Monitoring Committees (DMC) which combined most of the pre-defined efficacy and safety endpoints in an interactive heat-plot. Sample data and code to generate the plot will be provided |
|
Patrick received his PhD in Statistics from the University of Bremen, Germany, in 2014 for his work on group sequential and adaptive designs for three-arm non-inferiority trials. Since then he has been working at Bayer as a clinical statistician in the cardio-renal area with increasing responsibilities. Currently he acts as the Compound Statistician for a novel treatment for chronic kidney disease in type 2 diabetes that recently received FDA approval. His methodological interests include group sequential and adaptive designs, multiple comparison procedures and recurrent events. In the past years he has been working on the application for an EMA “Qualification opinion of clinically interpretable treatment effect measures based on recurrent event endpoints that allow for efficient statistical analyses”. Besides this he has been actively involved in the development of the Data Insight Generation (D.I.G) concept at Bayer, which was recently piloted in a large Phase III trial to gain deeper insights into the study data by means of intelligent visualizations.
|
Data Insight Generation (D.I.G) – A concept to foster interactive and interdisciplinary data investigations using intelligent visualizations
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines.
|
Learnings from implementing good graphical principles in a ready-to-use R package
|
Speaker | Biography | Abstract |
|
I studied mathematics and received my PhD in biostatistics on non-parametric statistics from the University of Göttingen in Germany. I authored more than 70 scientific manuscripts in peer-reviewed journals and regularly speak at international conferences – both statistical ones like PSI and medical ones like EADV. During my career at university and within the pharma industry, I have collected more than 20 years of experience. My career focused mostly on phase III and IV (RCT, observational studies, HTA submission, commercialization work) with some regulatory work as well as some experience in the early phases of clinical development. I’m interested in a broad range of methodological areas but specifically on making better decisions based on data. As such, I was the chair of the EFSPI/SPI SIG on benefit-risk for some time. PSI provided my with many more opportunities, which I’m happy to work on. At work, I supervise of a small but mighty team of statisticians in a large pharma company. The virtual work environment requires me to adjust my communication style and focus on my ability to deliver results effectively. I’m a happy husband and father of 3 wonderful kids, who I love to spend time with. In the rest of my time, I love running and listening to podcasts. |
Data Visualisation Paper and Pen Exercise
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines. |
How to implement effective visualisations in R using visR
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
ASA Safety Monitoring Tool Exercise |
|
Madhurima Majumder is a Senior Manager of Statistics and Data Insights at Bayer US LLC. Since joining Bayer in 2017, Madhurima has supported cardiovascular and thrombosis studies. She is also a member of various cross-industry working initiatives like the Drug Information Association’s (DIA) Clinically Meaningful Change Group, The Forum for Collaborative Research, etc. Her research interest focuses not only in statistical methodology but also in developing user-friendly data visualization tools for clinical trial results. She holds a PhD in Statistics from the University of Rochester, New York. |
Elaborator App
|
Alexander Schacht (Veramed) |
|
Improving a “bad” graph
|
This event will offer a practical introduction to modern methods of data visualisation.
Date: Friday 17th & Friday 24th September 2021 (Please note: this event is split into 2 parts)
Time: 13:00-17:00 BST both days
Speakers:
Part 1: Susan Mayo (FDA), Jeremy Wildfire (Gilead), Sheila Dickinson (Novartis), Matthias Trampisch (Boehringer Ingelheim), Charlotta Fruechtenicht (Roche), Patrick Schlömer (Bayer).
Part 2: Alexander Schacht (Veramed), Charlotta Fruechtenicht (Roche), James Black (Roche), Jeremy Wildfire (Gilead), Madhurima Majumder (Bayer)
Who is this event intended for? Anyone interested in data visualisation in the pharmaceutical industry.
What is the benefit of attending? Gain new insights into data visualisations and learn about the regulatory perspective. With no technical or coding knowledge assumed, a variety of practical workshop exercises will bring to life many of the concepts learned in part one. Topics include graphic design, and interactive data visualisation tools.
Part 1
Member rate = £20+VAT
Non-Member rate = £115*+VAT
*Please note: Non-Member rates include membership for the rest of the 2021 calendar year.
Part 2
Member & Non-Member rate = £60+VAT
PLEASE NOTE: Registration for Part 1 is compulsory in order to register for Part 2; in so doing, your registration for Part 2 only will be submitted for approval. As there are a limited amount of places available for Part 2, we advise booking early to avoid disappointment!
To register for Part 1 (17/09/21), please click here.
To register for Part 2 (24/09/21), please click here.
Part 1
Data visualisation has been used to gain insights into medical data for over 150 years. More modern methods include interactive and animated data visualisation tools, and the development of open source code using agile methods.
This online event will provide a practical introduction to modern methods of data visualisation, including presentations from some well-known and influential speakers in part 1 and practical hands-on workshop exercises in part 2.
To view the agenda for Part 1, please click here.
Part 2
This workshop will provide a practical introduction to modern methods of data visualisation through practical hands-on workshop exercises.
This includes interactive and animated data visualisation tools, and the development of open source code.
To view the agenda for Part 2, please click here.
Speaker | Biography | Abstract |
|
Susan is a senior mathematical statistician at the Food and Drug Administration, Center for Drug Evaluation’s Office of Biostatistics, with a demonstrated interest and impact in areas that help to make sound regulatory and drug development decisions: graphical design, drug safety and benefit-risk assessment, and the estimand framework. She has been with FDA for over 3 years, and previously worked as an industry statistician and internal company consultant in biotech and big pharma for a few more than that.
|
Making Impactful Graphs: Looking through the eyes of your audience
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
Building Open Source Tools for Safety Monitoring: Advancing Research Through Community Collaboration The Interactive Safety Graphics group seeks to modernize clinical trial safety monitoring by building tools for data exploration and reporting in a highly collaborative open source environment. At present, our team includes clinical and technical representatives from the pharmaceutical industry, academia, and the FDA, and additional contributors are always welcome |
|
Sheila Dickinson is a Global Benefit-Risk Lead, working in the Quantitative Safety and Epidemiology group at Novartis. Her responsibilities include promoting and facilitating the use of a structured benefit-risk approach by Novartis project teams. Sheila is also working on the topic of patient preference studies and is on the management board of the IMI PREFER project, which is working on developing guidelines about when and how to perform patient preference studies to support medical product decision-making. Sheila holds a degree in mathematics from Imperial College, London and an MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine. After joining Novartis in 1997, she worked as a statistician supporting projects in the various disease areas including both diabetes and malaria, before moving to the Quantitative Safety team in 2013. |
Points to bear in mind for visual displays of benefit-risk data
|
|
Matthias works as a Safety Statistician in independent Safety Analysis Team (iSAT) at Boehringer Ingelheim. iSAT is specialized on analyzing ongoing trial data in an unblinded fashion supporting interim analysis, ad-hoc unblinding requests, or Data Monitoring Committees (DMCs).
|
Dynamic data visualization for Benefit/Risk Assessment DURING trial conduct - Insights based on DMC output for monitoring a trial in patients hospitalized with COVID-19 This talk presents learnings from a recent Boehringer Ingelheim trial targeting to prevent Adult Respiratory Distress Syndrom (ARDS) in hospitalized COVID-19 patients. It focuses on a specific output created for the Data Monitoring Committees (DMC) which combined most of the pre-defined efficacy and safety endpoints in an interactive heat-plot. Sample data and code to generate the plot will be provided |
|
Patrick received his PhD in Statistics from the University of Bremen, Germany, in 2014 for his work on group sequential and adaptive designs for three-arm non-inferiority trials. Since then he has been working at Bayer as a clinical statistician in the cardio-renal area with increasing responsibilities. Currently he acts as the Compound Statistician for a novel treatment for chronic kidney disease in type 2 diabetes that recently received FDA approval. His methodological interests include group sequential and adaptive designs, multiple comparison procedures and recurrent events. In the past years he has been working on the application for an EMA “Qualification opinion of clinically interpretable treatment effect measures based on recurrent event endpoints that allow for efficient statistical analyses”. Besides this he has been actively involved in the development of the Data Insight Generation (D.I.G) concept at Bayer, which was recently piloted in a large Phase III trial to gain deeper insights into the study data by means of intelligent visualizations.
|
Data Insight Generation (D.I.G) – A concept to foster interactive and interdisciplinary data investigations using intelligent visualizations
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines.
|
Learnings from implementing good graphical principles in a ready-to-use R package
|
Speaker | Biography | Abstract |
|
I studied mathematics and received my PhD in biostatistics on non-parametric statistics from the University of Göttingen in Germany. I authored more than 70 scientific manuscripts in peer-reviewed journals and regularly speak at international conferences – both statistical ones like PSI and medical ones like EADV. During my career at university and within the pharma industry, I have collected more than 20 years of experience. My career focused mostly on phase III and IV (RCT, observational studies, HTA submission, commercialization work) with some regulatory work as well as some experience in the early phases of clinical development. I’m interested in a broad range of methodological areas but specifically on making better decisions based on data. As such, I was the chair of the EFSPI/SPI SIG on benefit-risk for some time. PSI provided my with many more opportunities, which I’m happy to work on. At work, I supervise of a small but mighty team of statisticians in a large pharma company. The virtual work environment requires me to adjust my communication style and focus on my ability to deliver results effectively. I’m a happy husband and father of 3 wonderful kids, who I love to spend time with. In the rest of my time, I love running and listening to podcasts. |
Data Visualisation Paper and Pen Exercise
|
|
Charlotta is a computational biologist by training and works as a senior data scientist in the Data, Analytics & Imaging team in the Pharma Development Personalized Healthcare department at Roche. Her interests lie in using fit-for-purpose analytics (including graphical design) to untap the wealth of multimodal data coming from healthcare care systems in the real world to support the development of new medicines. |
How to implement effective visualisations in R using visR
|
|
Jeremy Wildfire is a Director of Biostatistics on the Advance Analytics team at Gilead. Jeremy has worked in clinical trial research for 15 years, first as a biostatistician on NIH funded asthma and allergy studies and more recently on cross-functional data science teams focused on creating open source tools that seek to improve the clinical trial analysis pipeline. |
ASA Safety Monitoring Tool Exercise |
|
Madhurima Majumder is a Senior Manager of Statistics and Data Insights at Bayer US LLC. Since joining Bayer in 2017, Madhurima has supported cardiovascular and thrombosis studies. She is also a member of various cross-industry working initiatives like the Drug Information Association’s (DIA) Clinically Meaningful Change Group, The Forum for Collaborative Research, etc. Her research interest focuses not only in statistical methodology but also in developing user-friendly data visualization tools for clinical trial results. She holds a PhD in Statistics from the University of Rochester, New York. |
Elaborator App
|
Alexander Schacht (Veramed) |
|
Improving a “bad” graph
|