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Corinna Maier
MSc Mathematics in Bioscience / Universität Potsdam

PharMetrX Research+ Student
PhD student year: 2017

Home University: Universität Potsdam
Supervisor: Prof. Wilhelm Huisinga
Co-Supervisor: Prof. Charlotte Kloft
Mentoring I-Partner: AbbVie

PhD Project

Mathematical approaches for data assimilation in the context of systems pharmacology (working title)

Scientific interests

Novel digital healthcare devices, allowing e.g. for therapeutic drug monitoring, call for the application of sequential methods to predict the therapy outcome for a specific patient.
Ideally, knowledge from population analyses of clinical studies should be combined with patient specific data and prior knowledge about the system.

Weather forecasting methods comprise various sequential methods, so called sequential data assimilation methods, that update model-based predictions as new data becomes available and allow for improved risk and uncertainty assessment, e.g. the probability of precipitation.

The aim of my PhD project is to develop and apply data assimilation methods in the field of systems pharmacology. As the general problem statement in systems pharmacology is non-Gaussian and non-linear, particle methods are the most suitable sequential data assimilation methods. The most basic particle filter is, however, for most applications ineffective and therefore, depending on the problem, many different add-on techniques exist to improve the performance. Hence, the methodological part of my PhD project focuses on different particle filter algorithms and their adaptations to applications in systems pharmacology.

The application-oriented part of my PhD project deals with quantifying the risk of neutropenia and individually scheduling the treatment cycles in chemotherapy. Particle methods allow to update, and thus, individualise, model-based predictions as patient neutrophil data streams in. These patient-specific forecasts allow for a quantification of the patient’s future status, including its uncertainty. Eventually, reliable forecasts of neutropenia will improve the time management in clinics and support oncologists in decision-making.


Please see the list of all publications and PhD theses.


  • Since 02/2017: PhD candidate at the Graduate Research Training Program PharMetrX: Pharmacometrics & Computational Disease Modelling at the University of Potsdam and Freie Universität Berlin

  • 11/2015 – 05/2016: Master Thesis at Helmholtz Center Munich, Germany

  • 08/2015 - 09/2015: Internship at Bayer Technology Services, Bayer AG Leverkusen, Germany

  • 04/2015 – 07/2015: Research assistant at the Speciality Division for Systems Biotechnology, Technical University Munich, Germany

  • 08/2014 – 12/2014: Graduate Studies in Mathematical Biology at University of Alberta, Canada

  • 10/2013 – 09/2016: Master of Science in Mathematics in Bioscience at Technical University Munich, Germany

  • 10/2010 – 09/2013: Bachelor of Science in Integrated Life Science (biology, biomathematics and biophysics) at

  • Friedrich-Alexander University Nürnberg-Erlangen, Germany