Date: Thursday 1 October 2026 Time: 10:00 - 11:30 BST | 11:00 - 12:30 CET Location: Online via Zoom
Who is this event intended for? Anyone with an interest in the statistical analysis of ctDNA data within oncology. What is the benefit of attending? Learn about ctDNA data and gain insights into different methods and metrics that are currently used to analyse ctDNA data.
Overview
As cancers grow, they can release genetic material such as DNA into the blood stream known as circulating tumour DNA (ctDNA) which can be detected by blood tests. ctDNA has emerged as a promising biomarker over the last few years across several cancer types including non-small cell lung cancer, breast and colorectal cancer. In different settings, ctDNA has been shown to predict time-to-event outcomes, disease recurrence and treatment response, detect minimal residual disease, and enable risk stratification. However, clear guidance is lacking on which ctDNA metrics are most informative and which statistical modelling frameworks are appropriate to effectively predict long-term clinical responses, support early patient stratification, adaptive decision-making as well as early efficacy assessment.
To address this gap, we, on behalf of the Biomarker Special Interest Group of the PSI, conducted a targeted literature review on statistical modelling approaches for ctDNA data to gain insights into different methods and metrics that are mainly used nowadays. In this webinar we will discuss the emerging overall themes and summarise the reviewed methods that were published between 2023 and 2025. We will also consider what data are typically required for modelling, and their potential application in answering patient-centric questions with regard to precision medicine. We aim to provide practical recommendations on which ctDNA metrics and statistical models might be best used for which clinical endpoints to further support the utility of ctDNA in clinical trials.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Holly Tovey, Principal Statistician at The Institute of Cancer Research
Holly Tovey is a principal statistician in the Clinical Trials and Statistics Unit at the Institute of Cancer Research. She completed her PhD in 2024 on the identification of biomarkers to predict response in triple negative breast cancer. Her research interests focus on the incorporation of biomarkers into clinical trials as endpoints and for patient selection/stratification.
Saskia Ständler, Head of Statistical Programming – Translational Science at Evidenze Germany GmbH
Saskia holds a PhD in Biology and started her professional career as a Statistical Programmer in April 2022 at the CRO "Evidenze Germany" in Essen (Germany). She mainly works as a SAS programmer with a focus on biomarker analysis studies and Companion Diagnostics. Besides that, she establishes her own programming team at Evidenze Germany since early 2026 and is actively involved in working groups of PSI and Phuse.
Sara Bellinvia, Principal Biomarker Statistician & Data Scientist at Evidenze Germany GmbH
Sara works at the Biomarker Statistics & Data Science Department of the CRO Evidenze Germany where she gained several years of experience in biomarker research. Her daily work revolves around the analysis of biomarker data as part of clinical trials, including exploratory analysis and generalised analysis pipelines. Sara holds a PhD in Biology and has a long-standing passion and interest for statistics and data science.
Lidia Sacchetto, Senior Biomarker Statistician at Bayer AG
Lidia is a Senior Biomarker Statistician in Clinical Statistics & Analytics at Bayer Pharmaceuticals in Berlin (Germany). She holds a PhD in Mathematics and applies innovative quantitative methods to support biomarker research and drug development. Her interests span statistical methodology, data science, biomarker strategy, and cross-functional collaboration in precision medicine.
Rebecca Freudling, Principal Data Scientist at Staburo GmbH
Rebecca is Associate Director of Biostatistics at Staburo with focus on biomarkers in clinical development. She has several years of experience in biomarker data analysis for clinical trials across multiple therapeutic areas, particularly oncology. Rebecca received her Master's degree in Biostatistics from Ludwig Maximilian University of Munich in 2017.
Scientific Meetings
PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data
Date: Thursday 1 October 2026 Time: 10:00 - 11:30 BST | 11:00 - 12:30 CET Location: Online via Zoom
Who is this event intended for? Anyone with an interest in the statistical analysis of ctDNA data within oncology. What is the benefit of attending? Learn about ctDNA data and gain insights into different methods and metrics that are currently used to analyse ctDNA data.
Overview
As cancers grow, they can release genetic material such as DNA into the blood stream known as circulating tumour DNA (ctDNA) which can be detected by blood tests. ctDNA has emerged as a promising biomarker over the last few years across several cancer types including non-small cell lung cancer, breast and colorectal cancer. In different settings, ctDNA has been shown to predict time-to-event outcomes, disease recurrence and treatment response, detect minimal residual disease, and enable risk stratification. However, clear guidance is lacking on which ctDNA metrics are most informative and which statistical modelling frameworks are appropriate to effectively predict long-term clinical responses, support early patient stratification, adaptive decision-making as well as early efficacy assessment.
To address this gap, we, on behalf of the Biomarker Special Interest Group of the PSI, conducted a targeted literature review on statistical modelling approaches for ctDNA data to gain insights into different methods and metrics that are mainly used nowadays. In this webinar we will discuss the emerging overall themes and summarise the reviewed methods that were published between 2023 and 2025. We will also consider what data are typically required for modelling, and their potential application in answering patient-centric questions with regard to precision medicine. We aim to provide practical recommendations on which ctDNA metrics and statistical models might be best used for which clinical endpoints to further support the utility of ctDNA in clinical trials.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Holly Tovey, Principal Statistician at The Institute of Cancer Research
Holly Tovey is a principal statistician in the Clinical Trials and Statistics Unit at the Institute of Cancer Research. She completed her PhD in 2024 on the identification of biomarkers to predict response in triple negative breast cancer. Her research interests focus on the incorporation of biomarkers into clinical trials as endpoints and for patient selection/stratification.
Saskia Ständler, Head of Statistical Programming – Translational Science at Evidenze Germany GmbH
Saskia holds a PhD in Biology and started her professional career as a Statistical Programmer in April 2022 at the CRO "Evidenze Germany" in Essen (Germany). She mainly works as a SAS programmer with a focus on biomarker analysis studies and Companion Diagnostics. Besides that, she establishes her own programming team at Evidenze Germany since early 2026 and is actively involved in working groups of PSI and Phuse.
Sara Bellinvia, Principal Biomarker Statistician & Data Scientist at Evidenze Germany GmbH
Sara works at the Biomarker Statistics & Data Science Department of the CRO Evidenze Germany where she gained several years of experience in biomarker research. Her daily work revolves around the analysis of biomarker data as part of clinical trials, including exploratory analysis and generalised analysis pipelines. Sara holds a PhD in Biology and has a long-standing passion and interest for statistics and data science.
Lidia Sacchetto, Senior Biomarker Statistician at Bayer AG
Lidia is a Senior Biomarker Statistician in Clinical Statistics & Analytics at Bayer Pharmaceuticals in Berlin (Germany). She holds a PhD in Mathematics and applies innovative quantitative methods to support biomarker research and drug development. Her interests span statistical methodology, data science, biomarker strategy, and cross-functional collaboration in precision medicine.
Rebecca Freudling, Principal Data Scientist at Staburo GmbH
Rebecca is Associate Director of Biostatistics at Staburo with focus on biomarkers in clinical development. She has several years of experience in biomarker data analysis for clinical trials across multiple therapeutic areas, particularly oncology. Rebecca received her Master's degree in Biostatistics from Ludwig Maximilian University of Munich in 2017.
Training Courses
PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data
Date: Thursday 1 October 2026 Time: 10:00 - 11:30 BST | 11:00 - 12:30 CET Location: Online via Zoom
Who is this event intended for? Anyone with an interest in the statistical analysis of ctDNA data within oncology. What is the benefit of attending? Learn about ctDNA data and gain insights into different methods and metrics that are currently used to analyse ctDNA data.
Overview
As cancers grow, they can release genetic material such as DNA into the blood stream known as circulating tumour DNA (ctDNA) which can be detected by blood tests. ctDNA has emerged as a promising biomarker over the last few years across several cancer types including non-small cell lung cancer, breast and colorectal cancer. In different settings, ctDNA has been shown to predict time-to-event outcomes, disease recurrence and treatment response, detect minimal residual disease, and enable risk stratification. However, clear guidance is lacking on which ctDNA metrics are most informative and which statistical modelling frameworks are appropriate to effectively predict long-term clinical responses, support early patient stratification, adaptive decision-making as well as early efficacy assessment.
To address this gap, we, on behalf of the Biomarker Special Interest Group of the PSI, conducted a targeted literature review on statistical modelling approaches for ctDNA data to gain insights into different methods and metrics that are mainly used nowadays. In this webinar we will discuss the emerging overall themes and summarise the reviewed methods that were published between 2023 and 2025. We will also consider what data are typically required for modelling, and their potential application in answering patient-centric questions with regard to precision medicine. We aim to provide practical recommendations on which ctDNA metrics and statistical models might be best used for which clinical endpoints to further support the utility of ctDNA in clinical trials.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Holly Tovey, Principal Statistician at The Institute of Cancer Research
Holly Tovey is a principal statistician in the Clinical Trials and Statistics Unit at the Institute of Cancer Research. She completed her PhD in 2024 on the identification of biomarkers to predict response in triple negative breast cancer. Her research interests focus on the incorporation of biomarkers into clinical trials as endpoints and for patient selection/stratification.
Saskia Ständler, Head of Statistical Programming – Translational Science at Evidenze Germany GmbH
Saskia holds a PhD in Biology and started her professional career as a Statistical Programmer in April 2022 at the CRO "Evidenze Germany" in Essen (Germany). She mainly works as a SAS programmer with a focus on biomarker analysis studies and Companion Diagnostics. Besides that, she establishes her own programming team at Evidenze Germany since early 2026 and is actively involved in working groups of PSI and Phuse.
Sara Bellinvia, Principal Biomarker Statistician & Data Scientist at Evidenze Germany GmbH
Sara works at the Biomarker Statistics & Data Science Department of the CRO Evidenze Germany where she gained several years of experience in biomarker research. Her daily work revolves around the analysis of biomarker data as part of clinical trials, including exploratory analysis and generalised analysis pipelines. Sara holds a PhD in Biology and has a long-standing passion and interest for statistics and data science.
Lidia Sacchetto, Senior Biomarker Statistician at Bayer AG
Lidia is a Senior Biomarker Statistician in Clinical Statistics & Analytics at Bayer Pharmaceuticals in Berlin (Germany). She holds a PhD in Mathematics and applies innovative quantitative methods to support biomarker research and drug development. Her interests span statistical methodology, data science, biomarker strategy, and cross-functional collaboration in precision medicine.
Rebecca Freudling, Principal Data Scientist at Staburo GmbH
Rebecca is Associate Director of Biostatistics at Staburo with focus on biomarkers in clinical development. She has several years of experience in biomarker data analysis for clinical trials across multiple therapeutic areas, particularly oncology. Rebecca received her Master's degree in Biostatistics from Ludwig Maximilian University of Munich in 2017.
Journal Club
PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data
Date: Thursday 1 October 2026 Time: 10:00 - 11:30 BST | 11:00 - 12:30 CET Location: Online via Zoom
Who is this event intended for? Anyone with an interest in the statistical analysis of ctDNA data within oncology. What is the benefit of attending? Learn about ctDNA data and gain insights into different methods and metrics that are currently used to analyse ctDNA data.
Overview
As cancers grow, they can release genetic material such as DNA into the blood stream known as circulating tumour DNA (ctDNA) which can be detected by blood tests. ctDNA has emerged as a promising biomarker over the last few years across several cancer types including non-small cell lung cancer, breast and colorectal cancer. In different settings, ctDNA has been shown to predict time-to-event outcomes, disease recurrence and treatment response, detect minimal residual disease, and enable risk stratification. However, clear guidance is lacking on which ctDNA metrics are most informative and which statistical modelling frameworks are appropriate to effectively predict long-term clinical responses, support early patient stratification, adaptive decision-making as well as early efficacy assessment.
To address this gap, we, on behalf of the Biomarker Special Interest Group of the PSI, conducted a targeted literature review on statistical modelling approaches for ctDNA data to gain insights into different methods and metrics that are mainly used nowadays. In this webinar we will discuss the emerging overall themes and summarise the reviewed methods that were published between 2023 and 2025. We will also consider what data are typically required for modelling, and their potential application in answering patient-centric questions with regard to precision medicine. We aim to provide practical recommendations on which ctDNA metrics and statistical models might be best used for which clinical endpoints to further support the utility of ctDNA in clinical trials.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Holly Tovey, Principal Statistician at The Institute of Cancer Research
Holly Tovey is a principal statistician in the Clinical Trials and Statistics Unit at the Institute of Cancer Research. She completed her PhD in 2024 on the identification of biomarkers to predict response in triple negative breast cancer. Her research interests focus on the incorporation of biomarkers into clinical trials as endpoints and for patient selection/stratification.
Saskia Ständler, Head of Statistical Programming – Translational Science at Evidenze Germany GmbH
Saskia holds a PhD in Biology and started her professional career as a Statistical Programmer in April 2022 at the CRO "Evidenze Germany" in Essen (Germany). She mainly works as a SAS programmer with a focus on biomarker analysis studies and Companion Diagnostics. Besides that, she establishes her own programming team at Evidenze Germany since early 2026 and is actively involved in working groups of PSI and Phuse.
Sara Bellinvia, Principal Biomarker Statistician & Data Scientist at Evidenze Germany GmbH
Sara works at the Biomarker Statistics & Data Science Department of the CRO Evidenze Germany where she gained several years of experience in biomarker research. Her daily work revolves around the analysis of biomarker data as part of clinical trials, including exploratory analysis and generalised analysis pipelines. Sara holds a PhD in Biology and has a long-standing passion and interest for statistics and data science.
Lidia Sacchetto, Senior Biomarker Statistician at Bayer AG
Lidia is a Senior Biomarker Statistician in Clinical Statistics & Analytics at Bayer Pharmaceuticals in Berlin (Germany). She holds a PhD in Mathematics and applies innovative quantitative methods to support biomarker research and drug development. Her interests span statistical methodology, data science, biomarker strategy, and cross-functional collaboration in precision medicine.
Rebecca Freudling, Principal Data Scientist at Staburo GmbH
Rebecca is Associate Director of Biostatistics at Staburo with focus on biomarkers in clinical development. She has several years of experience in biomarker data analysis for clinical trials across multiple therapeutic areas, particularly oncology. Rebecca received her Master's degree in Biostatistics from Ludwig Maximilian University of Munich in 2017.
Webinars
PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data
Date: Thursday 1 October 2026 Time: 10:00 - 11:30 BST | 11:00 - 12:30 CET Location: Online via Zoom
Who is this event intended for? Anyone with an interest in the statistical analysis of ctDNA data within oncology. What is the benefit of attending? Learn about ctDNA data and gain insights into different methods and metrics that are currently used to analyse ctDNA data.
Overview
As cancers grow, they can release genetic material such as DNA into the blood stream known as circulating tumour DNA (ctDNA) which can be detected by blood tests. ctDNA has emerged as a promising biomarker over the last few years across several cancer types including non-small cell lung cancer, breast and colorectal cancer. In different settings, ctDNA has been shown to predict time-to-event outcomes, disease recurrence and treatment response, detect minimal residual disease, and enable risk stratification. However, clear guidance is lacking on which ctDNA metrics are most informative and which statistical modelling frameworks are appropriate to effectively predict long-term clinical responses, support early patient stratification, adaptive decision-making as well as early efficacy assessment.
To address this gap, we, on behalf of the Biomarker Special Interest Group of the PSI, conducted a targeted literature review on statistical modelling approaches for ctDNA data to gain insights into different methods and metrics that are mainly used nowadays. In this webinar we will discuss the emerging overall themes and summarise the reviewed methods that were published between 2023 and 2025. We will also consider what data are typically required for modelling, and their potential application in answering patient-centric questions with regard to precision medicine. We aim to provide practical recommendations on which ctDNA metrics and statistical models might be best used for which clinical endpoints to further support the utility of ctDNA in clinical trials.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Holly Tovey, Principal Statistician at The Institute of Cancer Research
Holly Tovey is a principal statistician in the Clinical Trials and Statistics Unit at the Institute of Cancer Research. She completed her PhD in 2024 on the identification of biomarkers to predict response in triple negative breast cancer. Her research interests focus on the incorporation of biomarkers into clinical trials as endpoints and for patient selection/stratification.
Saskia Ständler, Head of Statistical Programming – Translational Science at Evidenze Germany GmbH
Saskia holds a PhD in Biology and started her professional career as a Statistical Programmer in April 2022 at the CRO "Evidenze Germany" in Essen (Germany). She mainly works as a SAS programmer with a focus on biomarker analysis studies and Companion Diagnostics. Besides that, she establishes her own programming team at Evidenze Germany since early 2026 and is actively involved in working groups of PSI and Phuse.
Sara Bellinvia, Principal Biomarker Statistician & Data Scientist at Evidenze Germany GmbH
Sara works at the Biomarker Statistics & Data Science Department of the CRO Evidenze Germany where she gained several years of experience in biomarker research. Her daily work revolves around the analysis of biomarker data as part of clinical trials, including exploratory analysis and generalised analysis pipelines. Sara holds a PhD in Biology and has a long-standing passion and interest for statistics and data science.
Lidia Sacchetto, Senior Biomarker Statistician at Bayer AG
Lidia is a Senior Biomarker Statistician in Clinical Statistics & Analytics at Bayer Pharmaceuticals in Berlin (Germany). She holds a PhD in Mathematics and applies innovative quantitative methods to support biomarker research and drug development. Her interests span statistical methodology, data science, biomarker strategy, and cross-functional collaboration in precision medicine.
Rebecca Freudling, Principal Data Scientist at Staburo GmbH
Rebecca is Associate Director of Biostatistics at Staburo with focus on biomarkers in clinical development. She has several years of experience in biomarker data analysis for clinical trials across multiple therapeutic areas, particularly oncology. Rebecca received her Master's degree in Biostatistics from Ludwig Maximilian University of Munich in 2017.
Careers Meetings
PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data
Date: Thursday 1 October 2026 Time: 10:00 - 11:30 BST | 11:00 - 12:30 CET Location: Online via Zoom
Who is this event intended for? Anyone with an interest in the statistical analysis of ctDNA data within oncology. What is the benefit of attending? Learn about ctDNA data and gain insights into different methods and metrics that are currently used to analyse ctDNA data.
Overview
As cancers grow, they can release genetic material such as DNA into the blood stream known as circulating tumour DNA (ctDNA) which can be detected by blood tests. ctDNA has emerged as a promising biomarker over the last few years across several cancer types including non-small cell lung cancer, breast and colorectal cancer. In different settings, ctDNA has been shown to predict time-to-event outcomes, disease recurrence and treatment response, detect minimal residual disease, and enable risk stratification. However, clear guidance is lacking on which ctDNA metrics are most informative and which statistical modelling frameworks are appropriate to effectively predict long-term clinical responses, support early patient stratification, adaptive decision-making as well as early efficacy assessment.
To address this gap, we, on behalf of the Biomarker Special Interest Group of the PSI, conducted a targeted literature review on statistical modelling approaches for ctDNA data to gain insights into different methods and metrics that are mainly used nowadays. In this webinar we will discuss the emerging overall themes and summarise the reviewed methods that were published between 2023 and 2025. We will also consider what data are typically required for modelling, and their potential application in answering patient-centric questions with regard to precision medicine. We aim to provide practical recommendations on which ctDNA metrics and statistical models might be best used for which clinical endpoints to further support the utility of ctDNA in clinical trials.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Holly Tovey, Principal Statistician at The Institute of Cancer Research
Holly Tovey is a principal statistician in the Clinical Trials and Statistics Unit at the Institute of Cancer Research. She completed her PhD in 2024 on the identification of biomarkers to predict response in triple negative breast cancer. Her research interests focus on the incorporation of biomarkers into clinical trials as endpoints and for patient selection/stratification.
Saskia Ständler, Head of Statistical Programming – Translational Science at Evidenze Germany GmbH
Saskia holds a PhD in Biology and started her professional career as a Statistical Programmer in April 2022 at the CRO "Evidenze Germany" in Essen (Germany). She mainly works as a SAS programmer with a focus on biomarker analysis studies and Companion Diagnostics. Besides that, she establishes her own programming team at Evidenze Germany since early 2026 and is actively involved in working groups of PSI and Phuse.
Sara Bellinvia, Principal Biomarker Statistician & Data Scientist at Evidenze Germany GmbH
Sara works at the Biomarker Statistics & Data Science Department of the CRO Evidenze Germany where she gained several years of experience in biomarker research. Her daily work revolves around the analysis of biomarker data as part of clinical trials, including exploratory analysis and generalised analysis pipelines. Sara holds a PhD in Biology and has a long-standing passion and interest for statistics and data science.
Lidia Sacchetto, Senior Biomarker Statistician at Bayer AG
Lidia is a Senior Biomarker Statistician in Clinical Statistics & Analytics at Bayer Pharmaceuticals in Berlin (Germany). She holds a PhD in Mathematics and applies innovative quantitative methods to support biomarker research and drug development. Her interests span statistical methodology, data science, biomarker strategy, and cross-functional collaboration in precision medicine.
Rebecca Freudling, Principal Data Scientist at Staburo GmbH
Rebecca is Associate Director of Biostatistics at Staburo with focus on biomarkers in clinical development. She has several years of experience in biomarker data analysis for clinical trials across multiple therapeutic areas, particularly oncology. Rebecca received her Master's degree in Biostatistics from Ludwig Maximilian University of Munich in 2017.
Upcoming Events
PSI Book Club: Change: How organisations achieve hard-to-imagine results in uncertain and volatile times
Organizations have to adapt to the transforming landscape of our industry to ensure they continue to be successful in the future. Many of us are feeling the impact of organizational change. By reading John P Kotter’s book we can understand about organizational change and learn how to thrive, rather than just survive, through change.
Change, by John P Kotter (and his team), is a summary of all that he has learned over his decades of research and leading change. His book describes why many current approaches to change are inadequate and explains why new solutions need to give people a voice and a role in a new, change-embracing organization.
Develop your understanding of organisational change and become empowered to be part of your organisation’s change, by reading Change by John P Kotter and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply knowledge from the book in-between sessions.
PSI Careers - MEDMathS: Medicine Empowered by Data, Maths and Statistics
Date: Wednesday 4th November 2026
A careers talk about medical statistics and how it plays a crucial role in developing new medicines. Learn about the field of medical statistics and how it plays a crucial role in developing groundbreaking new medicines, vaccines and healthcare products.
Joint PSI/EFSPI, PHUSE, ASA Safety Working Group Webinar Series: Scientific Evaluation of Safety Data: A Learning and Decision-Making Approach
The webinar will explore how different clinical safety questions can be translated into appropriate estimands and aligned with corresponding estimators.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
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.
Date: 18 November 2026
This is an excellent opportunity for students to find out more about the field of medical statistics, talk to people from different organisations and make contacts for the future. All students currently studying for a mathematics or statistics-related BSc, MSc or PhD are invited to attend, and we welcome interest from exhibitors too.
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.
Aligning Estimation with the Clinical Question of Interest
This webinar will focus on aligning estimation to estimands. How do different strategies for handling intercurrent events and missing data handling influence the choice of estimation method, with illustration using a case study.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
PSI Careers Coaching Series: Peer Support Initiative
This 10-month peer support programme is aimed at professionals with five or more years of experience who are seeking structured development and connection with peers at a similar career stage. Through 5 bi-monthly topics, participants will engage in coach-led presentations, small-group discussions, and regular progress reviews focused on achieving tangible outcomes.
What if your placement year meant more than observing from the sidelines? Join Novartis and spend 12 months working hands-on with real clinical trial and healthcare data, helping to advance medicines that could improve patients' lives.
Viatris is a global healthcare company uniquely positioned to bridge the traditional divide between generics and brands, combining the best of both to more holistically address healthcare needs globally.
Viatris is a global healthcare company uniquely positioned to bridge the traditional divide between generics and brands, combining the best of both to more holistically address healthcare needs globally.
