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Related Experiment Video

Updated: Jun 19, 2026

Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay

Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay

Published on: February 7, 2025

IrregulAB: An open-source rule-based engine for automated red cell antibody panel interpretation.

Davide Crucitti^1,2, Violeta Vidal Ballester³, Jesús Gómez Fernández¹

¹Health Research Institute of Santiago de Compostela, Santiago de Compostela, Spain.

|June 18, 2026

Summary

IrregulAB is an open-source tool that aids in antibody identification during transfusion testing. It automates rule-based logic, improving accuracy and efficiency for immunohematology professionals.

Keywords:

antibody identification antibody panel interpretation decision support immunohematology rule‐based algorithm transfusion medicine

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Last Updated: Jun 19, 2026

Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay

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Published on: February 7, 2025

Methods for Quantitative Detection of Antibody-induced Complement Activation on Red Blood Cells

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Published on: January 29, 2014

A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood

A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood

Published on: February 8, 2016

Area of Science:

Immunohematology
Transfusion Medicine
Clinical Laboratory Science

Background:

Antibody identification in transfusion testing is manual and error-prone.
Current software lacks transparency and adaptability.
Delays and errors persist in antibody identification processes.

Purpose of the Study:

To develop an open-source, rule-based decision-support tool for antibody identification.
To improve transparency and verifiability in transfusion testing.
To address limitations of existing commercial software.

Main Methods:

Developed IrregulAB, an open-source web application encoding serologic decision rules.
Implemented a two-stage approach: rule-based screening and minimal-set solving.
Evaluated the system on 108 development and 35 validation antibody-identification panels.

Main Results:

The screening stage successfully retained antibody sets in over 90% of panels.
The minimal-set stage found valid antibody combinations in 87-89% of panels.
Demonstrated high performance in retrospective analysis.

Conclusions:

IrregulAB provides a transparent, rule-based decision-support system for immunohematology personnel.
Enables independent verification, local tuning, and standardized review of antibody workups.
Requires multicenter and multi-platform validation for clinical implementation.