
OrganoFeed: Feedback-enhanced organoid maturation towards higher reproducibility for in-vitro drug testing
Project period
January 2025 – December 2026
Objective
With the OrganoFeed project, we aim to leverage our joint expertise regarding microfluidic engineering & integration, and predictive algorithms development, to help address a core problem in biomedical research: reproducibility. Specifically, we aim to greatly reduce the variability of organoid cultures, which otherwise hold great promise for improving both fundamental research and drug development, by shifting the paradigm from a homogenous chemical environment to individualized, data-driven feedback control.
Background
Organoids are miniaturized, self-assembled, and self-organized cellular constructs. They can recapitulate key morphology, cellular composition, and biological function of human organs, improving greatly upon the simplistic mono-cellular models in use for early drug development. At the same time, organoids’ human origin avoids the species mismatch inherent to animal testing, which currently contributes significantly to poor translatability from drug candidates to human clinical trials (not to mention inherent ethical concerns). Last but not least, being derived from individual human donors’ cell samples, organoids can be used to model both fully personalized response as well as true population-level sampling. Organoids are, however, sensitive to even small variations in their culture conditions over the often weeks-long course of their maturation, resulting in high variability of morphology, cell composition, and function.
Current mitigation approaches have focused on providing more homogenous conditions. We propose instead an entirely different approach, based on feedback-driven control of the chemical environment at the level of each individual organoid. This ability to generate highly homogenous organoid populations should further increase organoids’ attractiveness in replacing both overly simplistic cell models as well as ethically and functionally suspect animal models with something more meaningful.
Crossdisciplinary collaboration
In this project, we are establishing a new cross-disciplinary and complementary collaboration:
- Ioanna Miliou, Assoc. Prof., is an expert in data analysis and modeling, with proficiency in advanced statistical methods, machine learning, and predictive modeling, enabling the extraction of meaningful insights from complex datasets.
- Thomas E Winkler, Assoc. Prof., is an expert in microsystems integration for biomedical applications, such as organs-on-chips, with a focus on electrochemical sensors, microfluidic materials, and human-relevant cells or samples.
- Karolinska Institutet Stem Cell Organoid (KISCO) facility will lend its expertise regarding a range of cutting-edge organoid models and culture methods.
Contacts

Ioanna Miliou
Senior Lecturer, Department of Computer and Systems Sciences at Stockholm University, Co-PI: AI-based Asthma App using Spirometer, Co-PI: OrganoFeed: Feedback-enhanced organoid maturation towards higher reproducibility for in-vitro drug testing, Digital Futures Faculty
+46 8 161608ioanna.miliou@dsv.su.se

Thomas E Winkler
Associate Professor, Micro- and Nanosystems at KTH Royal Institute of Technology, Co-PI: OrganoFeed: Feedback-enhanced organoid maturation towards higher reproducibility for in-vitro drug testing
+46 73 270 2897winklert@kth.se