# Optimization and Simulation of Kidney Paired Donation Programs

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $342,292

## Abstract

OPTIMIZATION AND SIMULATION OF KIDNEY PAIRED DONATION PROGRAMS
ABSTRACT
An evolving strategy known as kidney paired donation (KPD) provides an approach to overcome the barriers
faced by many patients with kidney failure who present with willing, but immunologically or blood type
incompatible living donors. KPD programs use a computerized algorithm to match one incompatible
donor/recipient pair to another pair with a complementary incompatibility, such that the donor of the first pair
gives to the recipient of the second, and vice versa. More complex exchanges of organs involving three or
more pairs are also considered as are altruistic or non-directed donors (NDD) who donate a kidney voluntarily
and thereby have the potential to create a chain of kidney transplants. Such donors and chains have become
increasingly important in KPD programs. Checking the viability of all potential transplants in a pool is not
logistically possible, and so a fundamental problem in a KPD program is selecting an optimal subset of
matches to consider among the many possibilities that exist. We have previously developed methods of
selecting potential matches that take account of the uncertainty in the process; namely that potential
transplants that are identified on a computer algorithm often fail when an attempt is made to put them into
practice. We develop approaches to the problem that take account of this uncertainty and so provide new and
better strategies for choosing potential matches with a view to presenting fall back options when potential
transplants are found not to be viable. This approach has the potential to greatly increase the number and/or
utility of transplants performed.
 In this renewal, we will build on initial successes and extend our methods to incorporate several
important additional aspects of KPD. Our matching algorithms will be generalized to allow for
nontraditional sources of donors, including donors from compatible pairs, deceased donors, and
international KPD programs to unlock many potential transplants in existing KPDs. We will develop
computational algorithms that will allow selection of larger subsets, which in turn will lead to a greater
number of fallback options and increases in potential transplants. We will further develop our micro
simulation model to include and examine the results of innovative sources of donors and to enhance
the user interface and methods of visualization. We have developed and will refine calculators to
predict outcomes such as graft survival based on donor and recipient characteristics and incorporate
these calculations into our matching methods. This proposal aims to increase the number and quality of
kidney transplants with associated benefits in patient quality of life and reduced medical costs.

## Key facts

- **NIH application ID:** 9906203
- **Project number:** 5R01DK093513-08
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** John D Kalbfleisch
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $342,292
- **Award type:** 5
- **Project period:** 2012-04-25 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9906203

## Citation

> US National Institutes of Health, RePORTER application 9906203, Optimization and Simulation of Kidney Paired Donation Programs (5R01DK093513-08). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9906203. Licensed CC0.

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