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. |
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
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.
The book club’s usual focus is to read and discuss professional development books. In this short format event you can more easily develop you career without the commitment of reading the whole book - simply listen to the 1-hour long podcast before joining the interactive session on 21 May.
This webinar is organised by the RWD SIG and the Historical Data SIG. We will review recent methods, applications, and tools of integrating subject-level-data from clinical trial with external data using Bayesian methods and/or causal inference methods.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This will be a 45 minute webinar which will explain the topic presented in the published paper, ‘Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance’. There will be 15 minutes for a panel Q&A with some of the authors following the presentation.
This 1-hour webinar will be an opportunity to hear about the methodology and first results of the iRISE consortium. iRISE is working towards a better understanding of reproducibility and the interventions that work to improve it. At the end of the presentation there will also be the opportunity to ask questions.
This one-day event focuses on the comprehensive management of transitioning to R/Open-Source, addressing the challenges and providing actionable insights. Attendees will participate in sessions covering essential topics such as training best practices, creating strategic plans, making the case to senior management, and managing both statistical and programming aspects of the transition.
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.
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.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This is an exciting, new opportunity for an experienced Statistician looking to take the next step in their career. Offered as a remote or hybrid position aligned with our site in Harrogate, North Yorkshire.
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