PSI Journal Club Webinar: Subgroup and Covariate Analysis

AIMS SIG - Open-Source Lunch Bites

Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry.

PSI Mentoring 2026

Date: Ongoing 6 month cycle beginning late April/early May 2026 Are you a member of PSI looking to further your career or help develop others - why not sign up to the PSI Mentoring scheme? You can expand your network, improve your leadership skills and learn from more senior colleagues in the industry.

PSI Book Club Lunch and Learn: Communicating with Clarity and Confidence

If you have read Ros Atkins’ book The Art of Explanation or want to listen to the BBC’s ‘Communicator in Chief’, you are invited to join the PSI Book Club Lunch and Learn, to discuss the content and application with the author, Ros Atkins. Having written the book within the context of the news industry, Ros is keen to hear how we have applied the ideas as statisticians within drug development and clinical trials. There will be dedicated time during the webinar to ASK THE AUTHOR any questions – don’t miss out on this exclusive PSI Book Club event! Haven’t read the book yet? Pick up a copy today and join us. Explanation - identifying and communicating what we want to say - is described as an art, in the title of his book. However, the creativity comes from Ros’ discernment in identifying and describing a clear step-by-step process to follow and practice. Readers can learn Ros’ rules, developed and polished throughout his career as a journalist, to help communicate complex written or spoken information clearly.

PSI Training Course: Effective Leadership – the keys to growing your leadership capabilities

This course will consist of three online half-day workshops. The first will be aimed at building trust, the backbone of leadership and a key to becoming effective. This is key to building a solid foundation. The second will be on improving communication as a technical leader. This workshop will focus on communication strategies for different stakeholders and will involve tips on effective communication and how to develop the skills of active listening, coaching and what improv can teach us about good communication. The final workshop will bring these two components together to help leaders become more influential. This will also focus on how to use Steven Covey’s 7-Habits, in particular Habits 4, 5 and 6, which are called the habits of communication. The workshops will be interactive, allowing you to practice the concepts discussed. There will be plenty of time for questions and discussion. There will also be reflective time where you can think about what you are learning and how you might experiment with it.

Speaker	Biography
Björn Holzhauer	Björn holds a doctorate in mathematics from the Otto-von-Guericke University Magdeburg. He has helped develop drugs in several disease areas at Novartis for 20 years. Björn is one on the authors of a collection of case studies on applied flexible Bayesian modelling in drug development with brms. He has worked on exploring the opportunities for machine learning in clinical development.
Thomas Jemielita	Thomas Jemielita is a Principal Scientist in Oncology Statistics, BARDS. Since joining Merck in 2017, his evolving job roles have spanned across various areas, including statistical support for early to late phase studies, biomarker studies, competitive intelligence, strategic initiatives, and real-world evidence studies. He has been actively involved in statistical research and has authored/co-authored over 20 scientific publications in peer-reviewed statistical and clinical journals, along with currently being a member of the ASA BIOP RWE Scientific Working Group for Rare Diseases. His currently research interests include causal inference, machine learning, and software development. Prior to joining Merck, Thomas received his PhD in biostatistics from the University of Pennsylvania in 2017.
Chris Harbron	Chris Harbron is an Expert Statistician leading capabilities in Advanced Analytics within the Data Sciences function at Roche. Through a variety of roles within the pharmaceutical industry Chris has worked in all stages of the drug development pipeline from drug discovery to early and late development. Chris has published and presented widely both within the statistical and the broader scientific literature.

Speaker	Biography
Björn Holzhauer	Björn holds a doctorate in mathematics from the Otto-von-Guericke University Magdeburg. He has helped develop drugs in several disease areas at Novartis for 20 years. Björn is one on the authors of a collection of case studies on applied flexible Bayesian modelling in drug development with brms. He has worked on exploring the opportunities for machine learning in clinical development.
Thomas Jemielita	Thomas Jemielita is a Principal Scientist in Oncology Statistics, BARDS. Since joining Merck in 2017, his evolving job roles have spanned across various areas, including statistical support for early to late phase studies, biomarker studies, competitive intelligence, strategic initiatives, and real-world evidence studies. He has been actively involved in statistical research and has authored/co-authored over 20 scientific publications in peer-reviewed statistical and clinical journals, along with currently being a member of the ASA BIOP RWE Scientific Working Group for Rare Diseases. His currently research interests include causal inference, machine learning, and software development. Prior to joining Merck, Thomas received his PhD in biostatistics from the University of Pennsylvania in 2017.
Chris Harbron	Chris Harbron is an Expert Statistician leading capabilities in Advanced Analytics within the Data Sciences function at Roche. Through a variety of roles within the pharmaceutical industry Chris has worked in all stages of the drug development pipeline from drug discovery to early and late development. Chris has published and presented widely both within the statistical and the broader scientific literature.

Speaker	Biography
Björn Holzhauer	Björn holds a doctorate in mathematics from the Otto-von-Guericke University Magdeburg. He has helped develop drugs in several disease areas at Novartis for 20 years. Björn is one on the authors of a collection of case studies on applied flexible Bayesian modelling in drug development with brms. He has worked on exploring the opportunities for machine learning in clinical development.
Thomas Jemielita	Thomas Jemielita is a Principal Scientist in Oncology Statistics, BARDS. Since joining Merck in 2017, his evolving job roles have spanned across various areas, including statistical support for early to late phase studies, biomarker studies, competitive intelligence, strategic initiatives, and real-world evidence studies. He has been actively involved in statistical research and has authored/co-authored over 20 scientific publications in peer-reviewed statistical and clinical journals, along with currently being a member of the ASA BIOP RWE Scientific Working Group for Rare Diseases. His currently research interests include causal inference, machine learning, and software development. Prior to joining Merck, Thomas received his PhD in biostatistics from the University of Pennsylvania in 2017.
Chris Harbron	Chris Harbron is an Expert Statistician leading capabilities in Advanced Analytics within the Data Sciences function at Roche. Through a variety of roles within the pharmaceutical industry Chris has worked in all stages of the drug development pipeline from drug discovery to early and late development. Chris has published and presented widely both within the statistical and the broader scientific literature.

Speaker	Biography
Björn Holzhauer	Björn holds a doctorate in mathematics from the Otto-von-Guericke University Magdeburg. He has helped develop drugs in several disease areas at Novartis for 20 years. Björn is one on the authors of a collection of case studies on applied flexible Bayesian modelling in drug development with brms. He has worked on exploring the opportunities for machine learning in clinical development.
Thomas Jemielita	Thomas Jemielita is a Principal Scientist in Oncology Statistics, BARDS. Since joining Merck in 2017, his evolving job roles have spanned across various areas, including statistical support for early to late phase studies, biomarker studies, competitive intelligence, strategic initiatives, and real-world evidence studies. He has been actively involved in statistical research and has authored/co-authored over 20 scientific publications in peer-reviewed statistical and clinical journals, along with currently being a member of the ASA BIOP RWE Scientific Working Group for Rare Diseases. His currently research interests include causal inference, machine learning, and software development. Prior to joining Merck, Thomas received his PhD in biostatistics from the University of Pennsylvania in 2017.
Chris Harbron	Chris Harbron is an Expert Statistician leading capabilities in Advanced Analytics within the Data Sciences function at Roche. Through a variety of roles within the pharmaceutical industry Chris has worked in all stages of the drug development pipeline from drug discovery to early and late development. Chris has published and presented widely both within the statistical and the broader scientific literature.

Speaker	Biography
Björn Holzhauer	Björn holds a doctorate in mathematics from the Otto-von-Guericke University Magdeburg. He has helped develop drugs in several disease areas at Novartis for 20 years. Björn is one on the authors of a collection of case studies on applied flexible Bayesian modelling in drug development with brms. He has worked on exploring the opportunities for machine learning in clinical development.
Thomas Jemielita	Thomas Jemielita is a Principal Scientist in Oncology Statistics, BARDS. Since joining Merck in 2017, his evolving job roles have spanned across various areas, including statistical support for early to late phase studies, biomarker studies, competitive intelligence, strategic initiatives, and real-world evidence studies. He has been actively involved in statistical research and has authored/co-authored over 20 scientific publications in peer-reviewed statistical and clinical journals, along with currently being a member of the ASA BIOP RWE Scientific Working Group for Rare Diseases. His currently research interests include causal inference, machine learning, and software development. Prior to joining Merck, Thomas received his PhD in biostatistics from the University of Pennsylvania in 2017.
Chris Harbron	Chris Harbron is an Expert Statistician leading capabilities in Advanced Analytics within the Data Sciences function at Roche. Through a variety of roles within the pharmaceutical industry Chris has worked in all stages of the drug development pipeline from drug discovery to early and late development. Chris has published and presented widely both within the statistical and the broader scientific literature.

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