Metadx: rapid diagnosis of fungal, bacterial, and viral infections using whole metagenomic sequencing

The National Institute of Allergy and Infectious Diseases awarded Parabon Nanolabs, Inc. $295,294 on June 12, 2026, under the Allergy and Infectious Diseases Research program (CFDA 93.855) to develop METADX, a software platform for rapid diagnosis of invasive fungal infections using whole metagenomic sequencing and machine learning.

METADX leverages whole metagenomic sequencing, bioinformatics, and machine learning to diagnose invasive fungal infections and predict antifungal resistance in a single test within 24 hours or less. The platform simultaneously sequences DNA from all organisms in a sample—fungi, bacteria, and viruses—without requiring separate tests, addressing the current clinical challenge of slow diagnostic methods that delay treatment and allow infections to become systemic. The system capitalizes on long-read Nanopore sequencing technology to enable rapid turnaround and real-time data analysis.

Parabon Nanolabs, a small business based in Reston, Virginia, is the recipient. The period of performance runs through August 31, 2027, with work performed in Reston, VA.

Abstract

Invasive fungal infections (IFIS) represent a serious health risk to patients due to their difficult diagnosis, limited treatment options, and high mortality rates. Current methods of diagnosing fungal infections are slow and difficult to implement, resulting in many such infections going undiagnosed and becoming systemic before they can be effectively treated. In particular, the symptoms of an IFI are difficult to distinguish from a bacterial infection, so fungi often are not tested for until bacteria have been ruled out, further delaying diagnosis. Meanwhile, antifungal resistance (AFR) continues to spread, making treatment increasingly difficult when there are only four classes of antifungal drugs. Rapid, simultaneous identification of all pathogenic species and characterization of their drug resistance profiles is sorely needed to allow efficient diagnosis and effective, targeted treatment. Such a system would directly improve patient outcomes, while also decreasing the need for broad-spectrum treatments that can lead to increased drug resistance. This project proposes to develop metadx, a groundbreaking software solution leveraging whole metagenomic sequencing (WMS), bioinformatics, and machine learning to diagnose invasive fungal infections and predict antifungal resistance in a single test within 24 hours or less. Unlike traditional diagnostics that isolate and analyze individual organisms over days or weeks, WMS simultaneously and rapidly sequences DNA from all organisms in a sample. This comprehensive approach can identify all potential pathogens, including fungi, bacteria, and viruses, without requiring separate tests. The proposed work capitalizes on advancements in next-generation sequencing technologies, particularly long-read nanopore sequencing, which offers rapid turnaround times and real-time data analysis capabilities, enabling the production of clinically relevant results within hours. Phase I of this project is dedicated to demonstrating the feasibility of utilizing nanopore sequencing for the rapid characterization of fungal infections. The proposed work will extend parabon's existing software tools for the analysis of nanopore metagenomic sequencing data, currently used for the identification of bacteria and viruses and the prediction of antibiotic resistance, to include the identification of fungal species and known antifungal resistance variants, as well as build novel machine learning models for prediction of AFR. Upon successful completion of this project, healthcare providers will have access to a groundbreaking capability to protect patients from amputation and death due to undiagnosed or late-diagnosed fungal infections.