📋 Tender Overview
Development Of A Lung Metastasis-On-A-Chip Model For Osteosarcoma As A Biomimetic Testing Platform For Drug Discovery And Therapeutic Innovation
Objective
Osteosarcoma is a highly aggressive bone cancer that primarily affects children. Secondary lung metastasis is the most critical clinical factor, with 70% of those who develop lung metastasis succumbing to the disease within 3 years. Despite the resonating clinical urgency for newer, more effective treatment options, there have been no changes in treatment since the introduction of chemotherapy in the 1970s. Furthermore, osteosarcoma is a rare disease making the conduct of large clinical trials investigating novel therapies very challenging. META-CHIP proposes to embark upon frontier research by being the first to develop a lung metastasis-on-a-chip model for osteosarcoma, for use by both the research community and the pharmaceutical industry. This will be realized by first testing the hypothesis that patient derived tumour spheroids (PDTS) generated from patient biopsies will recapitulate the primary tumour and thus be a superior drug development model than traditional cell culture models (Aim 1). An osteosarcoma-on-a-chip device will be developed integrating PDTS, microfluidic technology, and novel biomaterial design to provide a more accurate model of the tumour microenvironment (Aim 2). To validate the device, the ability to predict clinical outcomes on tumour growth following treatment with two anti-angiogenic drugs, which have progressed to Phase II clinical trials will be assessed (Aim 3). Finally, META-CHIP will develop a much-needed platform which mimics key aspects of osteosarcoma metastatic disease progression to the lung. This will be achieved through functional-coupling of the osteosarcoma-on-a-chip device with an established lung-chip to create a medium-throughput, cost-effective, human systemic model of osteosarcoma metastasis (Aim 4). META-CHIP has the potential to revolutionise drug development and treatment of osteosarcoma patients by being the first ex vivo testing platform capable of predicting a patient’s response to therapies in real-time.
Funded Under
European Research Council (Erc)
Total Cost
€ 1 499 884,00
Eu Contribution
€ 1 499 884,00
Coordinated By
University College Dublin, National University Of Ireland, Dublin
Ireland
