Event

PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data

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Date: Thursday 1 October 2026
Time: 11:00 - 12:30 BST
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

SpeakerBiography

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 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.

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