Abstract
Biomaterial development is a long process consisting of multiple stages of design and evaluation within the context of both in vitro and in vivo testing. To streamline this process, mathematical and computational modeling displays potential as a tool for rapid biomaterial characterization, enabling the prediction of optimal physicochemical parameters. In this work, a Langmuir isotherm-based model was used to describe protein and cell adhesion on a biomimetic hydroxyapatite surface, both independently and in a one-way coupled system. The results indicated that increased protein surface coverage leads to improved cell adhesion and spread, with maximal protein coverage occurring within 48 h. In addition, the Langmuir model displayed a good fit with the experimental data. Overall, computational modeling is an exciting avenue that may lead to savings in terms of time and cost during the biomaterial development process.
Highlights
Careful evaluation of novel biomaterials is necessary to ensure complete fulfillment of their intended function
scanning electron microscopy (SEM) imaging showed the presence of entangled crystals on the surface of the material, surrounding the original granules of α-TCP (Figure 1B)
Mathematical computational models were successfully developed and applied to describe basic biological properties for both hydroxyapatite (HA) and tissue culture polystyrene (TCPS), using results obtained from experimental characterization
Summary
Careful evaluation of novel biomaterials is necessary to ensure complete fulfillment of their intended function. The assessment includes characterization of physicochemical and biocompatibility properties, with the latter implying subsequent in vitro and in vivo studies.[1] the lack of correlation between in vitro and in vivo assays[2] leads to an iterative, long, and expensive process.[3] This could partially explain why, despite extensive biomaterial developments over the last decades, only a small fraction of biomaterials have been fully translated into the clinical environment.[4,5]. While computational modeling has been revolutionary in discovering new therapeutics, its usage has not yet been fully extended into the development of new biomaterials, despite its promising potential.[6] Within the field of biomaterial development, computational models have been used to predict the macroscopic mechanical behavior of materials,[7] mainly using either finite-element methods or simple mathematical expressions that define the parameter under study.[8,9] Computational modeling is useful in predicting experimental results during the biological characterization of biomaterials. The degradation of magnesium-based implants both in vitro and in vivo,[12] as well as the bone regeneration and turnover process have been studied with the use of computational models.[13,14]
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