A parameterised mathematical model to elucidate osteoblast cell growth in a phosphate-glass microcarrier culture

Author:

Burova Iva1ORCID,Peticone Carlotta2,De Silva Thompson David2,Knowles Jonathan C3456,Wall Ivan57ORCID,Shipley Rebecca J1

Affiliation:

1. Department of Mechanical Engineering, University College London, London, UK

2. Department of Biochemical Engineering, University College London, London, UK

3. Division of Biomaterials and Tissue Engineering, Eastman Dental Institute, University College London, London, UK

4. The Discoveries Centre for Regenerative and Precision Medicine, London, UK

5. Department of Nanobiomedical Science & BK21 PLUS NBM Global Research Center for Regenerative Medicine, Dankook University, Cheonan, Republic of Korea

6. UCL Eastman-Korea Dental Medicine Innovation Centre, Dankook University, Cheonan, Republic of Korea

7. Aston Medical Research Institute and School of Life & Health Sciences, Aston University, Birmingham, UK

Abstract

Tissue engineering has the potential to augment bone grafting. Employing microcarriers as cell-expansion vehicles is a promising bottom-up bone tissue engineering strategy. Here we propose a collaborative approach between experimental work and mathematical modelling to develop protocols for growing microcarrier-based engineered constructs of clinically relevant size. Experiments in 96-well plates characterise cell growth with the model human cell line MG-63 using four phosphate glass microcarrier materials. Three of the materials are doped with 5 mol% TiO2 and contain 0%, 2% or 5% CoO, and the fourth material is doped only with 7% TiO2 (0% CoO). A mathematical model of cell growth is parameterised by finding material-specific growth coefficients through data-fitting against these experiments. The parameterised mathematical model offers more insight into the material performance by comparing culture outcome against clinically relevant criteria: maximising final cell number starting with the lowest cell number in the shortest time frame. Based on this analysis, material 7% TiO2 is identified as the most promising.

Funder

Horizon 2020 Framework Programme

Engineering and Physical Sciences Research Council

Rosetrees Trust

Publisher

SAGE Publications

Subject

Biomedical Engineering,Biomaterials,Medicine (miscellaneous)

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