Fuzzy-logic–driven predictions of multi-tissue ingrowth for rapid screening of mechanically instructive tissue-engineering scaffolds

High retear rates in surgical intervention of interfacial/transitional tissues (bone-tendon, bone-ligament) drive a need to design tissue engineering scaffolds that can successfully mimic healthy tissue mechanics. Current testing mechanisms of scaffolds depend on bioreactor systems or animal models of damaged tissue. While valuable, these methods present bottlenecks in time and cost to determine potential scaffold design efficacy. Computational models of tissue healing on a scaffold are a promising alternative but have been limited to predicting bone growth on scaffolds. Herein, we present the development of a fuzzy logic controller to predict bone and tendon ingrowth on melt electrowritten, graded scaffolds using two controllers; one controller simulating growth through the examination of how scaffold strains instruct primary cell behavior (osteoblasts and tenocytes) and another simulating how scaffold strains induce mesenchymal stem cell (MSC) differentiation. We found that gradient scaffolds produced mechanically exclusive stimuli early in the healing scenario such that it generated regions that mechanically instructed both bone and tendon growth. These scaffolds also produced mechanical gradients ranging from 20 MPa to 400 kPa, generating a two order of magnitude gradient of mechanical properties that, when implanted, could reduce the stress concentrations observed in a repaired bone-tendon interface. Interestingly, we found that our scaffolds were not graded enough to induce substantial regions of MSC differentiation into tendon, with bone primarily dominating the differentiation response. Creating a need to further investigate the induction of larger gradients on this scaffold, or higher strain levels to induce regions of distinct tenocyte and osteoblast differentiation on these graded scaffold designs. To our knowledge this is the first attempt at using fuzzy logic to predict tissue healing of multiple tissue types on a scaffold substrate.