Date: Wednesday 19th March 2025
Time: 15:00-16:00 CET | 14:00 - 15:00 GMT
Location: Online via Zoom
Speakers: Dr. Liam Childs, AI working group lead - Paul Ehrlich Institute
Who is this event intended for? Statisticians, Data Scientists, Researchers, Physicians, etc. interested in quantitative decision making.
What is the benefit of attending? Information on AI driven approaches in different applications in research and pharmaceutical development.
This webinar is free to both Members of PSI and Non-Members.
To register for this event, please click here
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.
Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.
|
Speaker |
Biography |
Abstract |
|
|
Dr. Liam Childs received his Doctorate in Natural Sciences (Dr. rer. nat.) from the Max-Planck Institute for Molecular Plant Physiology, with a research focus on machine learning and bioinformatics. He has over two decades of experience in artificial intelligence, data science, and bioinformatics and is currently the AI Working Group Lead at the Paul-Ehrlich-Institut in Germany, where he is responsible for developing and implementing the institute's AI strategy. Throughout his career, Liam has held multiple academic and industry positions, including postdoctoral fellowships in bioinformatics at the German Cancer Research Center (DKFZ) and Humboldt University, Berlin, as well as a role as a Senior Software Developer at Gotthardt Healthgroup. |
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing. Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies. |
Date: Wednesday 19th March 2025
Time: 15:00-16:00 CET | 14:00 - 15:00 GMT
Location: Online via Zoom
Speakers: Dr. Liam Childs, AI working group lead - Paul Ehrlich Institute
Who is this event intended for? Statisticians, Data Scientists, Researchers, Physicians, etc. interested in quantitative decision making.
What is the benefit of attending? Information on AI driven approaches in different applications in research and pharmaceutical development.
This webinar is free to both Members of PSI and Non-Members.
To register for this event, please click here
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.
Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.
|
Speaker |
Biography |
Abstract |
|
|
Dr. Liam Childs received his Doctorate in Natural Sciences (Dr. rer. nat.) from the Max-Planck Institute for Molecular Plant Physiology, with a research focus on machine learning and bioinformatics. He has over two decades of experience in artificial intelligence, data science, and bioinformatics and is currently the AI Working Group Lead at the Paul-Ehrlich-Institut in Germany, where he is responsible for developing and implementing the institute's AI strategy. Throughout his career, Liam has held multiple academic and industry positions, including postdoctoral fellowships in bioinformatics at the German Cancer Research Center (DKFZ) and Humboldt University, Berlin, as well as a role as a Senior Software Developer at Gotthardt Healthgroup. |
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing. Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies. |
Date: Wednesday 19th March 2025
Time: 15:00-16:00 CET | 14:00 - 15:00 GMT
Location: Online via Zoom
Speakers: Dr. Liam Childs, AI working group lead - Paul Ehrlich Institute
Who is this event intended for? Statisticians, Data Scientists, Researchers, Physicians, etc. interested in quantitative decision making.
What is the benefit of attending? Information on AI driven approaches in different applications in research and pharmaceutical development.
This webinar is free to both Members of PSI and Non-Members.
To register for this event, please click here
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.
Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.
|
Speaker |
Biography |
Abstract |
|
|
Dr. Liam Childs received his Doctorate in Natural Sciences (Dr. rer. nat.) from the Max-Planck Institute for Molecular Plant Physiology, with a research focus on machine learning and bioinformatics. He has over two decades of experience in artificial intelligence, data science, and bioinformatics and is currently the AI Working Group Lead at the Paul-Ehrlich-Institut in Germany, where he is responsible for developing and implementing the institute's AI strategy. Throughout his career, Liam has held multiple academic and industry positions, including postdoctoral fellowships in bioinformatics at the German Cancer Research Center (DKFZ) and Humboldt University, Berlin, as well as a role as a Senior Software Developer at Gotthardt Healthgroup. |
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing. Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies. |
Date: Wednesday 19th March 2025
Time: 15:00-16:00 CET | 14:00 - 15:00 GMT
Location: Online via Zoom
Speakers: Dr. Liam Childs, AI working group lead - Paul Ehrlich Institute
Who is this event intended for? Statisticians, Data Scientists, Researchers, Physicians, etc. interested in quantitative decision making.
What is the benefit of attending? Information on AI driven approaches in different applications in research and pharmaceutical development.
This webinar is free to both Members of PSI and Non-Members.
To register for this event, please click here
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.
Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.
|
Speaker |
Biography |
Abstract |
|
|
Dr. Liam Childs received his Doctorate in Natural Sciences (Dr. rer. nat.) from the Max-Planck Institute for Molecular Plant Physiology, with a research focus on machine learning and bioinformatics. He has over two decades of experience in artificial intelligence, data science, and bioinformatics and is currently the AI Working Group Lead at the Paul-Ehrlich-Institut in Germany, where he is responsible for developing and implementing the institute's AI strategy. Throughout his career, Liam has held multiple academic and industry positions, including postdoctoral fellowships in bioinformatics at the German Cancer Research Center (DKFZ) and Humboldt University, Berlin, as well as a role as a Senior Software Developer at Gotthardt Healthgroup. |
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing. Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies. |
Date: Wednesday 19th March 2025
Time: 15:00-16:00 CET | 14:00 - 15:00 GMT
Location: Online via Zoom
Speakers: Dr. Liam Childs, AI working group lead - Paul Ehrlich Institute
Who is this event intended for? Statisticians, Data Scientists, Researchers, Physicians, etc. interested in quantitative decision making.
What is the benefit of attending? Information on AI driven approaches in different applications in research and pharmaceutical development.
This webinar is free to both Members of PSI and Non-Members.
To register for this event, please click here
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.
Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.
|
Speaker |
Biography |
Abstract |
|
|
Dr. Liam Childs received his Doctorate in Natural Sciences (Dr. rer. nat.) from the Max-Planck Institute for Molecular Plant Physiology, with a research focus on machine learning and bioinformatics. He has over two decades of experience in artificial intelligence, data science, and bioinformatics and is currently the AI Working Group Lead at the Paul-Ehrlich-Institut in Germany, where he is responsible for developing and implementing the institute's AI strategy. Throughout his career, Liam has held multiple academic and industry positions, including postdoctoral fellowships in bioinformatics at the German Cancer Research Center (DKFZ) and Humboldt University, Berlin, as well as a role as a Senior Software Developer at Gotthardt Healthgroup. |
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing. Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies. |
Date: Wednesday 19th March 2025
Time: 15:00-16:00 CET | 14:00 - 15:00 GMT
Location: Online via Zoom
Speakers: Dr. Liam Childs, AI working group lead - Paul Ehrlich Institute
Who is this event intended for? Statisticians, Data Scientists, Researchers, Physicians, etc. interested in quantitative decision making.
What is the benefit of attending? Information on AI driven approaches in different applications in research and pharmaceutical development.
This webinar is free to both Members of PSI and Non-Members.
To register for this event, please click here
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing.
Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies.
|
Speaker |
Biography |
Abstract |
|
|
Dr. Liam Childs received his Doctorate in Natural Sciences (Dr. rer. nat.) from the Max-Planck Institute for Molecular Plant Physiology, with a research focus on machine learning and bioinformatics. He has over two decades of experience in artificial intelligence, data science, and bioinformatics and is currently the AI Working Group Lead at the Paul-Ehrlich-Institut in Germany, where he is responsible for developing and implementing the institute's AI strategy. Throughout his career, Liam has held multiple academic and industry positions, including postdoctoral fellowships in bioinformatics at the German Cancer Research Center (DKFZ) and Humboldt University, Berlin, as well as a role as a Senior Software Developer at Gotthardt Healthgroup. |
Artificial Intelligence (AI) is increasingly integrated into the development and regulation of medicinal products, offering new opportunities in drug discovery, clinical trials, and manufacturing. AI-driven approaches, particularly machine learning and bioinformatics, facilitate target identification, optimize patient selection in clinical trials, and enhance process control in pharmaceutical manufacturing. In the context of biomedicine, AI plays a critical role in predicting drug-target interactions, modeling peptide-MHC binding for immunotherapy, and improving the precision of CRISPR-Cas9 genome editing. Despite its potential, AI applications in medicinal products present challenges, including data quality, algorithm validation, and regulatory compliance. The necessity for robust performance metrics and risk assessment frameworks is paramount to ensure the reliability and safety of AI-driven methodologies. |
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.
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.
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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