University of Cambridge
Advanced Bioelectronic and Microphysiological Systems for Functional Studies of Stem Cell-Derived Neural Models
Abstract
dc:description.abstractThis thesis presents an integrated bioelectronic and computational framework for functional interrogation of stem cell-derived neural models. Motivated by the staggering failure rate (exceeding 90%) of neurological drug candidates in clinical trials, the work addresses limitations in preclinical modelling by combining advanced microfabrication, flexible electronics, and human-relevant in vitro systems. The research spans: • 2D compartmentalised cultures for studying tauopathy in Alzheimer’s disease using microphysiological and bioelectronic systems; • Air-liquid interface cerebral organoids (ALI-COs), interfaced with Neuroweb, a porous, ultra-flexible microelectrode array enabling chronic electrophysiology; • NeuroMaps, a modular MATLAB-based GUI for multimodal electrophysiological analysis, integrating spike sorting, spectral decomposition, and network mapping across longitudinal measurements. Key findings include: • Material and substrate-related effects on 2D stem-cell-derived neuronal growth. • Tau-induced hyperexcitability and synaptic disruption in iNeuron-astrocyte co-cultures. • Axonal swelling and lysosomal clustering in microfluidic chips following tau exposure. • Stable long-term recordings from ALI-COs, revealing maturation-linked shifts in firing rate, synchrony, and phase-amplitude coupling. • Neuroweb enabled the detection of cross-species differences in signalling using air-liquid interface cerebral organoids and changes in oscillatory activity possibly linked to metabolic recycling. • The development of a full GUI framework for electrophysiological analysis, providing morphological and electrophysiological context to analysis. Together, these platforms advance the field of neuroengineering by enabling scalable, non-invasive, and longitudinal interrogation of complex neural tissues, with implications for disease modelling, drug screening, and personalised medicine.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2025
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Haider, Belquis
- Advisors dc:contributor.advisor
-
- Kaminski Schierle, Gabriele
- Malliaras, George
Subjects
dc:subject × 13Rights
dc:rightsIdentifiers
dc:identifier.*- Author Identifier
- 0009-0005-9440-0842
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/395448