Structural descriptor and surrogate modeling for design of biodegradable scaffolds

Abstract

Biodegradable scaffolds are important to regenerative medicine in that they provide an amicable environment for tissue regrowth. However, establishing structure-property (SP) relationships for scaffold design is challenging due to the complexity of the three-dimensional porous scaffold geometry. The complexity requires high-dimensional geometric descriptors. The training of such a SP surrogate model will need a large amount of experimental or simulation data. In this work, a schema of constructing SP relationship surrogates is developed to predict the degraded mechanical properties from the initial scaffold geometry. A new structure descriptor, the extended surfacelet transform (EST), is proposed to capture important details of pores associated with the degradation of scaffolds. The efficiency is further enhanced with principal component analysis to reduce the high-dimensional EST data into a low-dimensional representation. The schema also includes a kinetic Monte Carlo biodegradation model to simulate the biodegradation of polymer scaffolds and to generate the training data for the formation of SP relationships. The schema is demonstrated with the design of polycaprolactone biodegradable scaffolds by connecting the initial scaffold geometry to the degraded compressive modulus.