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Over the past decade, high HLA epitope mismatch scores have been associated with inferior transplant outcomes using several tools, of which HLAMatchmaker is most well-known. This software uses theoretically defined polymorphic amino acid configurations, called eplets, for HLA compatibility analysis. Although consideration of eplet mismatch loads has potential for immunological risk stratification of transplant patients, the use of eplet matching in organ allocation algorithms is hindered by lacking knowledge of the immunogenicity of individual eplets, and the possibility that single mismatched amino acids, rather than complete eplets, are responsible for HLA antibody induction.There are several approaches to define eplet immunogenicity, such as antibody verification of individual eplets, and data-driven approaches using large datasets that correlate specific eplet mismatches to donor specific antibody formation or inferior transplant outcomes. Data-driven approaches can also be used to define whether single amino acid mismatches may be more informative than eplet mismatches for predicting HLA antibody induction.When using epitope knowledge for the assignment of unacceptable antigens, it important to realize that alleles sharing an eplet to which antibodies have formed are not automatically all unacceptable since multiple contact sites determine the binding strength and thus biological function and pathogenicity of an antibody, which may differ between reactive alleles.While the future looks bright for using HLA epitopes in clinical decision making, major steps need to be taken to make this a clinical reality.(c) 2021 The Author(s). Published by Elsevier Inc. on behalf of American Society for Histocompatibility and Immunogenetics. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).