PhD position in Pharmacokinetic-Pharmacodynamic – Oncology Full-time

PhD Position In Pharmacokinetic-Pharmacodynamic – Oncology

The Department of Pharmacy at Uppsala University has an interdisciplinary environment at the center of the pharmaceutical arena. With frontline research, first-rate education and extensive collaborations we constitute a driving force in the development of our academic field. In this inspiring environment our rich diversity of research groups, several of international prominence, develop and conduct work of great scientific importance. Among our core competencies are computational modelling and simulations, PKPD, in vitro ADME models, advanced in vivo methods, biological medicines, as well as patient and societal aspects, from optimising the use of drugs in individuals to societal pharmaceutical policies. Together, we form a unique cluster of academic competencies within pharmaceutical science, playing a key role in shaping the future of pharmacy in both Sweden and globally.

A doctoral position is available within the Pharmacokinetic and Pharmacodynamic research unit at the Department of Pharmacy. The overarching aim of this PhD project is to further develop data analysis methods that enable better treatment optimisation in oncology. Despite major therapeutic advances, many crucial decisions remain marked by considerable uncertainty: how to individualise dose and dosing schedules, how to balance efficacy against toxicity over time, and how to translate evidence from clinical trials to the heterogeneous patient populations seen in everyday clinical practice. At the same time, modern cancer treatment generates increasingly rich longitudinal data: clinical biomarkers, laboratory panels, adverse events, imaging‑based endpoints, and patient‑reported outcomes (PROMs). However, these data are often analysed using methods that do not fully exploit their dynamic nature or adequately address bias.

This project will develop and apply modelling tools that integrate pharmacometric methodology with causal inference to quantify relationships between treatment exposure, biomarkers, toxicity, and clinical outcomes. Key themes will include longitudinal modelling, simulation, and “virtual patient” tools for evaluating dosing strategies while accounting for potential bias arising from treatment adjustments or irregular follow‑up intervals. Particular emphasis will be placed on distinguishing true causal effects from validity issues commonly seen in datasets from patients with cancer, such as time‑varying confounding, immortal time bias, informative censoring, and selection bias. An additional objective is to strengthen validity beyond trial data, i.e., by characterising how patients in routine clinical practice differ from trial participants and how these differences are reflected in outcomes, adverse events, and PROMs.

The work will generate implementation‑relevant results, strategies for dose optimisation and monitoring, early detection of toxicity signals using longitudinal biomarkers, and benefit–risk summaries that are interpretable for clinicians and decision‑makers. Where relevant, model outputs will also be linked to health‑economic evaluations by quantifying the consequences of different dosing and monitoring strategies. Overall, the project aims to deliver both methodological improvements and practical impact by transforming longitudinal oncology data into robust evidence for precision dosing and optimisation of treatment strategies.

The applicant should have an MSc degree in a relevant area, such as pharmaceutical sciences, medicine or engineering, with a minimum of 240 credits or alternatively a Master's in Pharmaceutical Modelling or in Drug Development, including courses in pharmacokinetics, physiology, pharmacology, modelling and programming (e.g. in R and NONMEM). Furthermore, the applicant must fulfil English Level 6 (advanced level) language requirements.

We place great emphasis on personal suitability, high motivation, and a genuine interest in research in pharmacokinetics-pharmacodynamics, pharmacometrics, dose optimisation, and oncology. Proven experience with pharmacokinetic modelling software, such as NONMEM, is essential. Experience in research in clinical trials or oncology is a merit. The applicant is expected to have excellent oral and written English skills. The applicant should also have strong collaboration skills and demonstrated ability to conduct a scientific project in a structured, methodological manner, as the project involves interaction with researchers and clinicians in the context of international collaboration.

The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date 10 August 2026 or as agreed. Placement: Uppsala.