Selection and monitoring methods for xenotransplantation

Predictive engineering of a sample derived from a genetically optimized non-human donor suitable for xenotransplantation into a human having improved quality or performance is described. A training data set is constructed from a series of libraries, including at least one library comprising genomic, proteomic, and research data specific to non-humans. A predictive machine learning model is developed based on the constructed training data set and utilized to obtain a predicted quality or performance of a plurality of sequences for a candidate sample from the non-human donor specific to a human patient or patient population. A subset of sequences is selected for evaluation from the plurality of sequences based on the predicted quality or performance and candidate samples are designed derived from the non-human donor using the selected subset of sequences.