Macula-on-a-Chip Research

• Program Understanding macular diseases requires models that accurately replicate human retinal physiology. Traditional in vivo models, such as rodents, lack a true macula, limiting their relevance in studying human-specific disease mechanisms. To bridge this gap, our lab has developed the Macula-on-a-Chip (MoaC) research program, an advanced ex vivo perfusion system that preserves the structural and metabolic integrity of human macular tissue. The Macula-on-a-Chip platform utilizes post-mortem human eyes, obtained from the NSW Eye Bank, which are maintained in a perfusion system that mimics physiological conditions. This system allows us to sustain retinal structure and cellular viability for extended periods (up to seven days) after tissue extraction, investigate metabolic processes using stable isotope tracing to track nutrient flux in the macula, study disease-specific stress responses, and test new therapeutic strategies by evaluating the impact of potential drug candidates on cellular metabolism, oxidative stress, and inflammatory pathways. The ability to simulate disease conditions ex vivo provides a powerful tool for testing new interventions before moving to clinical trials. By refining our Macula-on-a-Chip system, we aim to narrow the translational gap between laboratory discoveries and clinical treatments for macular diseases such as AMD, DR and MacTel. 

Eye to AI Research Program

• The Eye to AI research program leverages cutting-edge multi-omics analysis and artificial intelligence to uncover novel therapeutic targets for macular diseases. By integrating bulk, single-cell, and spatial omics data, we analyse human post-mortem retinal tissue to map disease-specific molecular signatures and identify key pathways driving retinal degeneration. Our approach combines transcriptomics, proteomics, metabolomics, and lipidomics to create a comprehensive dataset that reflects the complexity of macular disease progression. Advanced machine learning models process vast amounts of biological data, detecting subtle molecular patterns that may otherwise be overlooked. These AI-driven insights guide the identification and validation of potential drug targets, accelerating the transition from fundamental research to therapeutic development. With a focus on diseases such as AMD, DR and MacTel, the Eye to AI program aims to bridge the gap between data science and clinical applications, transforming big data into actionable treatment strategies that can improve patient outcomes.

NanoVision Research Program

• The NanoVision Project focuses on developing a comprehensive RNA-LNP (lipid nanoparticle) drug pipeline to advance targeted therapies for retinal diseases. Traditional drug delivery to the retina faces significant barriers, including the internal limiting membrane and the need for cell-specific targeting. To overcome these challenges, our lab engineers customized lipid nanoparticles capable of encapsulating RNA therapeutics, optimizing their composition for efficient penetration and precise delivery to retinal cells. This platform supports high-throughput screening, delivery optimization, and preclinical validation of RNA-based treatments, ensuring their stability, efficacy, and safety. We tailor RNA-LNP formulations to specific disease pathways, enhancing their therapeutic potential. With applications in AMD, DR and MacTel, the NanoVision Project bridges the gap between RNA drug discovery and clinical translation, laying the groundwork for next-generation gene and molecular therapies in ophthalmology.

• Professor Mark Gillies 
• Associate Professor Ling Zhu 
• Dr Ting Zhang
• Dr Shaoxue Zeng
• Ms SoRa Lee 
• Ms Michelle Yam