Software development and automated data analysis for organ-on-a-chip applications

Leuven - Master projects
About a week ago

Evaluate drug-interactions in organ-on-a-chip devices.

Pharmaceutical companies face ever-increasing costs in drug development while the number of marketed drugs per year is decreasing. The cost to bring to a single drug to the market reaches an estimated $2.7 billion. Despite extensive toxicity screening during drug development, traditional in vitro tests still offer poor predictability for success in clinical trials. Organ-on-chip systems promise to improve the predictive value of in vitro cellular assays by creating more relevant and physiological models. These systems merge both cell biology and lab-on-a-chip devices in a single platform to create multi-cellular structures and organoids.

Imec is developing novel organ-on-chip platform for pharmacological studies and development of precision medicine. These devices are based on a high-density microelectrode array (MEA) that offer multiparametric analysis of cellular properties (Lopez et al., 2018). They record the electrical activity of electrogenic cells (such as cardiac and neuronal cells) as well as the impedance of non-electrically active cells. Moreover, reflective lens-free imaging (RLFI) devices may simultaneously and non-invasively record rapid cellular movements. In the case of heart-on-a-chip devices, the combined recording of cardiac contraction by RLFI with electrical activity by MEA offers more in-depth analysis of drug-induced cardiotoxicity (Pauwelyn et al., 2018).

The work in this project involves development and implementation of new software for the imec organ-on-chip platform. The data analysis part of the project focusses on detecting drug-induced effects from MEA and LFI recordings. The software development part focuses on the control and interfacing of the lens-free imaging device. The student is required to have experience with Python/Matlab and it would be beneficial to have experience with C++ and LabView.


Lopez, C. M., Chun, H. S., Berti, L., Wang, S., Putzeys, J., Van Den Bulcke, C., … Van Helleputte, N. (2018). A 16384-electrode 1024-channel multimodal CMOS MEA for high-throughput intracellular action potential measurements and impedance spectroscopy in drug-screening applications. In Digest of Technical Papers - IEEE International Solid-State Circuits Conference (Vol. 61).

Pauwelyn, T., Stahl, R., Mayo, L., Zheng, X., Lambrechts, A., Janssens, S., … Braeken, D. (2018). Reflective lens-free imaging on high-density silicon microelectrode arrays for monitoring and evaluation of in vitro cardiac contractility. Biomedical Optics Express, 9(4), 1827–1841.

Type of project: Internship

Duration: minimum 4 months

Required degree: Master of Engineering Technology, Master of Science, Master of Engineering Science

Required background: Biomedical engineering, Computer Science

Supervising scientist(s): For further information or for application, please contact: Dries Braeken ( and Thomas Pauwelyn (

Only for self-supporting students

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