ABSTRACT

This Smart and Connected Health (SCH) award will contribute to improved patient access to kidney transplantation by studying the inclusion of a personalized antibody removal regimen known as ?desensitization? into a kidney paired donation (KPD) system. Kidney transplantation is the definitive, gold standard treatment that provides the best quality of life for end-stage renal disease patients. The treatment, however, is not accessible to many due to constraints such as blood type or human leukocyte antigen tissue type incompatibility between transplant candidates and their kidney donors. To overcome these incompatibilities, the transplant community has devised several novel schemes including KPD and desensitization. KPD allows patients with a willing - but incompatible - living donor to swap their incompatible donor with a more compatible donor, also in the KPD donor-patient pool, while the desensitization procedure removes antibodies from transplant recipients? blood streams prior to surgery to reduce the risk of potential rejection of donated kidneys. Currently, both of these schemes have limitations. To overcome the limitations, prominent transplant experts have been advocating for combining the two schemes. This project aims to develop stochastic simulation and optimization-based algorithms for matching donors and recipients in a KPD system with desensitization therapy. In contrast to a conventional KPD system where transplant candidates simply swap their incompatible donors for more compatible donors in the system, the envisioned KPD systems would offer patients the additional option of undergoing a personalized desensitization therapy along with the option of swapping donors to significantly increase their likelihood of a match.

The research objective is to develop an integrated dynamic stochastic simulation-optimization model comprised of: (i) an optimization strategy to identify the optimal personalized protocol for desensitization; (ii) improved robust/stochastic optimization methods to integrate the desensitization therapy into the KPD matching; and (iii) a decision-support tool to help patients decide whether to accept the desensitization regimen with a less compatible kidney, or wait for a more compatible one. The output of the integrated dynamic stochastic simulation-optimization model will include the suggested paired matchings from the combinatorial and simulation optimization algorithms, the realized matchings based on simulated patient behavior, and statistical estimates of key performance system metrics. In the last year of the project, the team will tailor the algorithms for the George Washington University Transplant Institute (GWTI) and Virginia Commonwealth University (VCU) Health Hume-Lee Transplant Center, which are interested in developing a joint local KPD exchange.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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