ARTIFICIAL INTELLIGENCE IN TRANSPLANTATION: Edited by Javier BriceñoPrecision transplant pathologyWood-Trageser, Michelle A.a,b; Xu, Qinyonga,b; Zeevi, Adrianaa,b; Randhawa, Parmjeeta,b; Lesniak, Drewa,b; Demetris, Anthony J.a,b Author Information aThomas E. Starzl Transplantation Institute, University of Pittsburgh bDivision of Liver and Transplantation Pathology, Department of Pathology, University of Pittsburgh, Pennsylvania, USA Correspondence to Anthony J. Demetris, UPMC Montefiore, E741, 3459 Fifth Avenue, Pittsburgh, PA 15213, USA. Tel: +1 412 647 2072; fax: +1 412 647 2084; e-mail: [email protected] Current Opinion in Organ Transplantation: August 2020 - Volume 25 - Issue 4 - p 412-419 doi: 10.1097/MOT.0000000000000772 Buy Metrics Abstract Purpose of review Transplant pathology contributes substantially to personalized treatment of organ allograft recipients. Rapidly advancing next-generation human leukocyte antigen (HLA) sequencing and pathology are enhancing the abilities to improve donor/recipient matching and allograft monitoring. Recent findings The present review summarizes the workflow of a prototypical patient through a pathology practice, highlighting histocompatibility assessment and pathologic review of tissues as areas that are evolving to incorporate next-generation technologies while emphasizing critical needs of the field. Summary Successful organ transplantation starts with the most precise pratical donor–recipient histocompatibility matching. Next-generation sequencing provides the highest resolution donor–recipient matching and enables eplet mismatch scores and more precise monitoring of donor-specific antibodies (DSAs) that may arise after transplant. Multiplex labeling combined with hand-crafted machine learning is transforming traditional histopathology. The combination of traditional blood/body fluid laboratory tests, eplet and DSA analysis, traditional and next-generation histopathology, and -omics-based platforms enables risk stratification and identification of early subclinical molecular-based changes that precede a decline in allograft function. Needs include software integration of data derived from diverse platforms that can render the most accurate assessment of allograft health and needs for immunosuppression adjustments. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.