Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces

• Main Authors: Epa, V. Chandana (Author), Yang, Jing (Author), Mei, Ying (Contributor), Hook, Andrew L. (Author), Davies, Martyn C. (Author), Alexander, Morgan R. (Author), Winkler, David A. (Author), Anderson, Daniel Griffith (Contributor), Langer, Robert S (Author)
• Other Authors: Harvard University- (Contributor), Massachusetts Institute of Technology. Department of Chemical Engineering (Contributor), Koch Institute for Integrative Cancer Research at MIT (Contributor), Langer, Robert (Contributor)
• Format: Article
• Language: English
• Published: Royal Society of Chemistry, 2014-10-21T19:29:00Z.
• Subjects: Article
• Online Access: Get fulltext

 Designing materials to control biology is an intense focus of biomaterials and regenerative medicine research. Discovering and designing materials with appropriate biological compatibility or active control of cells and tissues is being increasingly undertaken using high throughput synthesis and assessment methods. We report a relatively simple but powerful machine-learning method of generating models that link microscopic or molecular properties of polymers or other materials to their biological effects. We illustrate the potential of these methods by developing the first robust, predictive, quantitative, and purely computational models of adhesion of human embryonic stem cell embryoid bodies (hEB) to the surfaces of a 496-member polymer micro array library.