Date: Tuesday 12th April 2022
Time: 14:00-15:00 BST | 15:00-16:00 CEST
Speaker: Tim Holland-Letz
Who is this event intended for? Statisticians in Pharma.
What is the benefit of attending? The chance to learn about new study designs.
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
In practical dose response trials, especially in a cell culture context, experimental designs to establish functional relationships between dose and effect of a substance are generally chosen based on simple rules of thumb. These designs are generally reasonably effective, but not optimal.
In this webinar we give an overview over the statistical optimal design approach in this context. We show how optimal designs can be constructed, covering mainly all-purpose designs (D-optimality) but also more specific designs (c-optimality). We introduce a graphical representation. Next, we show how these concepts can be extended to trials aiming to estimate the interaction between two different substances given simultaneously.
Finally, we present an R-Shiny application which allows construction of optimal designs in most of these contexts with a minimum of theoretical knowledge.
|
Speaker |
Biography |
|
Tim Holland-Letz |
Tim Holland-Letz studied Statistics at the Technical University of Dortmund. In 2010, he completed his PhD in the same subject in cooperation with the Department of Mathematics of the Ruhr-University Bochum, focusing on the topic of optimal experimental design. At the same time he was employed at the Department of Medical Informatics and Biometry also at the Ruhr-University, working mainly on clinical studies and general applied statistics in medical research. In 2011, he moved to the Biostatistics Division within the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg. From this moment on, he has concentrated more on preclinical studies, with a special focus on optimal experimental designs and dose-response analysis. However, he still works on more or less all kinds of statistical problems arising in research and preclinical studies. In 2019 he completed his Habilitation in Medical Biostatistics at the University of Heidelberg. |
Date: Tuesday 12th April 2022
Time: 14:00-15:00 BST | 15:00-16:00 CEST
Speaker: Tim Holland-Letz
Who is this event intended for? Statisticians in Pharma.
What is the benefit of attending? The chance to learn about new study designs.
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
In practical dose response trials, especially in a cell culture context, experimental designs to establish functional relationships between dose and effect of a substance are generally chosen based on simple rules of thumb. These designs are generally reasonably effective, but not optimal.
In this webinar we give an overview over the statistical optimal design approach in this context. We show how optimal designs can be constructed, covering mainly all-purpose designs (D-optimality) but also more specific designs (c-optimality). We introduce a graphical representation. Next, we show how these concepts can be extended to trials aiming to estimate the interaction between two different substances given simultaneously.
Finally, we present an R-Shiny application which allows construction of optimal designs in most of these contexts with a minimum of theoretical knowledge.
|
Speaker |
Biography |
|
Tim Holland-Letz |
Tim Holland-Letz studied Statistics at the Technical University of Dortmund. In 2010, he completed his PhD in the same subject in cooperation with the Department of Mathematics of the Ruhr-University Bochum, focusing on the topic of optimal experimental design. At the same time he was employed at the Department of Medical Informatics and Biometry also at the Ruhr-University, working mainly on clinical studies and general applied statistics in medical research. In 2011, he moved to the Biostatistics Division within the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg. From this moment on, he has concentrated more on preclinical studies, with a special focus on optimal experimental designs and dose-response analysis. However, he still works on more or less all kinds of statistical problems arising in research and preclinical studies. In 2019 he completed his Habilitation in Medical Biostatistics at the University of Heidelberg. |
Date: Tuesday 12th April 2022
Time: 14:00-15:00 BST | 15:00-16:00 CEST
Speaker: Tim Holland-Letz
Who is this event intended for? Statisticians in Pharma.
What is the benefit of attending? The chance to learn about new study designs.
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
In practical dose response trials, especially in a cell culture context, experimental designs to establish functional relationships between dose and effect of a substance are generally chosen based on simple rules of thumb. These designs are generally reasonably effective, but not optimal.
In this webinar we give an overview over the statistical optimal design approach in this context. We show how optimal designs can be constructed, covering mainly all-purpose designs (D-optimality) but also more specific designs (c-optimality). We introduce a graphical representation. Next, we show how these concepts can be extended to trials aiming to estimate the interaction between two different substances given simultaneously.
Finally, we present an R-Shiny application which allows construction of optimal designs in most of these contexts with a minimum of theoretical knowledge.
|
Speaker |
Biography |
|
Tim Holland-Letz |
Tim Holland-Letz studied Statistics at the Technical University of Dortmund. In 2010, he completed his PhD in the same subject in cooperation with the Department of Mathematics of the Ruhr-University Bochum, focusing on the topic of optimal experimental design. At the same time he was employed at the Department of Medical Informatics and Biometry also at the Ruhr-University, working mainly on clinical studies and general applied statistics in medical research. In 2011, he moved to the Biostatistics Division within the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg. From this moment on, he has concentrated more on preclinical studies, with a special focus on optimal experimental designs and dose-response analysis. However, he still works on more or less all kinds of statistical problems arising in research and preclinical studies. In 2019 he completed his Habilitation in Medical Biostatistics at the University of Heidelberg. |
Date: Tuesday 12th April 2022
Time: 14:00-15:00 BST | 15:00-16:00 CEST
Speaker: Tim Holland-Letz
Who is this event intended for? Statisticians in Pharma.
What is the benefit of attending? The chance to learn about new study designs.
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
In practical dose response trials, especially in a cell culture context, experimental designs to establish functional relationships between dose and effect of a substance are generally chosen based on simple rules of thumb. These designs are generally reasonably effective, but not optimal.
In this webinar we give an overview over the statistical optimal design approach in this context. We show how optimal designs can be constructed, covering mainly all-purpose designs (D-optimality) but also more specific designs (c-optimality). We introduce a graphical representation. Next, we show how these concepts can be extended to trials aiming to estimate the interaction between two different substances given simultaneously.
Finally, we present an R-Shiny application which allows construction of optimal designs in most of these contexts with a minimum of theoretical knowledge.
|
Speaker |
Biography |
|
Tim Holland-Letz |
Tim Holland-Letz studied Statistics at the Technical University of Dortmund. In 2010, he completed his PhD in the same subject in cooperation with the Department of Mathematics of the Ruhr-University Bochum, focusing on the topic of optimal experimental design. At the same time he was employed at the Department of Medical Informatics and Biometry also at the Ruhr-University, working mainly on clinical studies and general applied statistics in medical research. In 2011, he moved to the Biostatistics Division within the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg. From this moment on, he has concentrated more on preclinical studies, with a special focus on optimal experimental designs and dose-response analysis. However, he still works on more or less all kinds of statistical problems arising in research and preclinical studies. In 2019 he completed his Habilitation in Medical Biostatistics at the University of Heidelberg. |
Date: Tuesday 12th April 2022
Time: 14:00-15:00 BST | 15:00-16:00 CEST
Speaker: Tim Holland-Letz
Who is this event intended for? Statisticians in Pharma.
What is the benefit of attending? The chance to learn about new study designs.
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
In practical dose response trials, especially in a cell culture context, experimental designs to establish functional relationships between dose and effect of a substance are generally chosen based on simple rules of thumb. These designs are generally reasonably effective, but not optimal.
In this webinar we give an overview over the statistical optimal design approach in this context. We show how optimal designs can be constructed, covering mainly all-purpose designs (D-optimality) but also more specific designs (c-optimality). We introduce a graphical representation. Next, we show how these concepts can be extended to trials aiming to estimate the interaction between two different substances given simultaneously.
Finally, we present an R-Shiny application which allows construction of optimal designs in most of these contexts with a minimum of theoretical knowledge.
|
Speaker |
Biography |
|
Tim Holland-Letz |
Tim Holland-Letz studied Statistics at the Technical University of Dortmund. In 2010, he completed his PhD in the same subject in cooperation with the Department of Mathematics of the Ruhr-University Bochum, focusing on the topic of optimal experimental design. At the same time he was employed at the Department of Medical Informatics and Biometry also at the Ruhr-University, working mainly on clinical studies and general applied statistics in medical research. In 2011, he moved to the Biostatistics Division within the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg. From this moment on, he has concentrated more on preclinical studies, with a special focus on optimal experimental designs and dose-response analysis. However, he still works on more or less all kinds of statistical problems arising in research and preclinical studies. In 2019 he completed his Habilitation in Medical Biostatistics at the University of Heidelberg. |
Date: Tuesday 12th April 2022
Time: 14:00-15:00 BST | 15:00-16:00 CEST
Speaker: Tim Holland-Letz
Who is this event intended for? Statisticians in Pharma.
What is the benefit of attending? The chance to learn about new study designs.
You can now register for this event. Registration fees are as follows:
- Members of PSI = Free of charge
- Non-Members of PSI = Free of charge
To register for the session, please click here.
In practical dose response trials, especially in a cell culture context, experimental designs to establish functional relationships between dose and effect of a substance are generally chosen based on simple rules of thumb. These designs are generally reasonably effective, but not optimal.
In this webinar we give an overview over the statistical optimal design approach in this context. We show how optimal designs can be constructed, covering mainly all-purpose designs (D-optimality) but also more specific designs (c-optimality). We introduce a graphical representation. Next, we show how these concepts can be extended to trials aiming to estimate the interaction between two different substances given simultaneously.
Finally, we present an R-Shiny application which allows construction of optimal designs in most of these contexts with a minimum of theoretical knowledge.
|
Speaker |
Biography |
|
Tim Holland-Letz |
Tim Holland-Letz studied Statistics at the Technical University of Dortmund. In 2010, he completed his PhD in the same subject in cooperation with the Department of Mathematics of the Ruhr-University Bochum, focusing on the topic of optimal experimental design. At the same time he was employed at the Department of Medical Informatics and Biometry also at the Ruhr-University, working mainly on clinical studies and general applied statistics in medical research. In 2011, he moved to the Biostatistics Division within the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg. From this moment on, he has concentrated more on preclinical studies, with a special focus on optimal experimental designs and dose-response analysis. However, he still works on more or less all kinds of statistical problems arising in research and preclinical studies. In 2019 he completed his Habilitation in Medical Biostatistics at the University of Heidelberg. |
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.
Our monthly webinar will allow attendees to gain practical knowledge and skills in Open-Source coding and tools, with a focus on applications in the pharmaceutical industry. The sessions will provide starting points in a number of areas, correct any common misconceptions and provide valuable resources for further learning.
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.
Date: Tuesday 9th September 2025 Join us to hear Sofia Weigle and Weng-Kee Wong present their recent work.
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.
An exciting opportunity has arisen for a permanent Senior Medical Statistician & Statistical Programmer to join the UKCRC fully registered Derby Clinical Trials Support Unit (Derby CTSU).
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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