Time: 15:00 - 16:30 UK Time
Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract
Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly
Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
Research Fellow, Advanced Analytics at Eli Lilly and CompanyLooking over the fence: What does Data Science mean outside of life sciences and what can we learn?
The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
| Registration | |
| PSI Member | Free |
| Non-member | £20 (plus VAT) |
Time: 15:00 - 16:30 UK Time
Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract
Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly
Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
Research Fellow, Advanced Analytics at Eli Lilly and CompanyLooking over the fence: What does Data Science mean outside of life sciences and what can we learn?
The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
| Registration | |
| PSI Member | Free |
| Non-member | £20 (plus VAT) |
Time: 15:00 - 16:30 UK Time
Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract
Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly
Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
Research Fellow, Advanced Analytics at Eli Lilly and CompanyLooking over the fence: What does Data Science mean outside of life sciences and what can we learn?
The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
| Registration | |
| PSI Member | Free |
| Non-member | £20 (plus VAT) |
Time: 15:00 - 16:30 UK Time
Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract
Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly
Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
Research Fellow, Advanced Analytics at Eli Lilly and CompanyLooking over the fence: What does Data Science mean outside of life sciences and what can we learn?
The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
| Registration | |
| PSI Member | Free |
| Non-member | £20 (plus VAT) |
Time: 15:00 - 16:30 UK Time
Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract
Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly
Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
Research Fellow, Advanced Analytics at Eli Lilly and CompanyLooking over the fence: What does Data Science mean outside of life sciences and what can we learn?
The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
| Registration | |
| PSI Member | Free |
| Non-member | £20 (plus VAT) |
Time: 15:00 - 16:30 UK Time
Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract
Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly
Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
Research Fellow, Advanced Analytics at Eli Lilly and CompanyLooking over the fence: What does Data Science mean outside of life sciences and what can we learn?
The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
| Registration | |
| PSI Member | Free |
| Non-member | £20 (plus VAT) |
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.
Develop your non-technical skills by reading The Art of Explanation by Ros Atkins and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply skills from the book in-between sessions.
This course is aimed at biostatisticians with no or some pediatric drug development experience who are interested to further their understanding. We will give you an introduction to the pediatric drug development landscape. This will include identifying the key regulations and processes governing pediatric development, a discussion on the needs and challenges when conducting pediatric research and a focus on the ways to overcome these challenges from a statistical perspective.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
AI agents are large language models equipped with tools that can autonomously tackle challenging tasks. This talk will explore how generative AI agents can enable biomedical discovery.
The webinar is targeted at statisticians working in the pharmaceutical industry, and the objective is to 1) provide a basic understanding of IV methodology including how it relates to causal inference, and 2) present two inspirational pharma-relevant applications.
The Pre-Clinical Special Interest Group (SIG) Workshop 2025 will take place over two half-days on 7 - 8 October in Verona, Italy, bringing together experts from industry, academia, and regulatory institutions to discuss key challenges and innovations in pre-clinical research.
Four sessions will include ML foundation (including an introduction, data exploration for ML and dimensionality reduction and feature selection), Supervised learning (including support vector machines and model evaluation and interpretation), model optimization and unsupervised learning (including clustering) and advanced topics (including neural networks, deep learning and large language models).
The program will feature insightful sessions led by distinguished invited speakers, alongside a poster session showcasing the latest advancements in the field. Further details will be provided.
Date: Wednesday 5th November 2025 A careers talk about medical statistics and how it plays a crucial role in developing new medicines
Date: 19 November 2025 This event is aimed at students with an interest in the field of Medical Statistics, for example within pharmaceuticals, healthcare and/or medical research.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
As an Associate Director Biostatistics Early Development, you will be a key member of our biostatistics group, you will play a crucial role in the design, analysis, and interpretation of clinical trials for early development programs.
If you are passionate about biostatistics and real-world data, and are looking for an exciting opportunity to contribute to groundbreaking research, we encourage you to apply.
Are you passionate about making a difference in the world of healthcare? Novartis is seeking a dynamic and experienced professional to join our team in London at The Westworks.
As the Director of HTA Biostatistics & Medical Affairs, you will play a pivotal role in shaping the future of healthcare by providing strategic biostatistical leadership and expertise.
As a Senior Principal Biostatistician, you will be responsible and accountable for all statistical work, both scientific and operational, for one or more assigned clinical trials
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