Clinical metagenomic next-generation sequencing (mNGS) is an emerging approach for broad-based diagnosis of infections, whether caused by bacteria, viruses, fungi, or parasites. Here we will discuss recent improvements in turnaround time, performance, and bioinformatics that make these tests increasingly accessible to clinical and public health laboratories. We will also discuss how machine learning-based host response analyses of human RNA mNGS data can be leveraged to aid in the diagnosis of infections.

In high-risk oncology patients, invasive fungal infections (IFI) remain a major cause of morbidity and mortality. This is due, in part, to challenges associated with IFI diagnosis, which currently relies on a combination of risk stratification, limited laboratory methods and imaging studies. In this talk, the current data on the potential of microbial metagenomics sequencing to improve IFI diagnosis will be reviewed, including remaining gaps and future opportunities.

The clinical and diagnostic utility of microbial whole-genome sequencing (WGS) is vast. It includes speciation/classification of microorganisms, virulence genotyping, antimicrobial resistance (AMR) prediction, emerging pathogen and AMR mechanism surveillance, and outbreak investigation. This talk will describe the real-world implementation of microbial WGS testing and its integration into routine patient care and infection prevention practice at a large academic medical center.

There are many different options available for respiratory testing, ranging from detecting a single pathogen to multiplex testing for numerous pathogens simultaneously. The choice of what pathogens to test for involves many different factors, such as the target patient population, testing setting, and what viruses are circulating at the time of testing. These factors can also dramatically change in certain circumstances, such as during the SARS-CoV-2 pandemic. The goal of this talk is to cover several different respiratory testing scenarios and what options for testing could be utilized in each case.

Controlled human challenge models are ideal study designs for monitoring host:pathogen interactions for colonization and mild to moderate symptomatic infections. Active models include a diversity of respiratory viruses, dengue, norovirus, a variety of bacterial gastrointestinal and genitourinary pathogens, and malaria. Precise inoculation times and serial sampling, often under quarantine, allow for dense timepoints supporting more precise kinetics of physiological and molecular responses. In addition to efficient evaluation of potential early phase vaccines and therapeutics, inoculated individuals can serve as their own controls for digital and clinico-molecular biomarker development and validation.

Host-response technologies offer the promise for rapid assessments (diagnostic and prognostic) of patients with suspected acute infection and sepsis. However, improving outcomes depends on test design, performance, and implementation. We will discuss practical challenges and solutions in improving patient outcomes in this challenging patient segment.

This session will highlight the importance of diagnostic test stewardship in parallel with antibiotic stewardship to provide value to diagnostic testing for infectious diseases in the emergency department (ED) setting. Opportunities and challenges with implementation of new ID diagnostic tests in the ED will be illustrated with use cases.

Inappropriate use of laboratory tests to guide management of individuals can lead to suboptimal patient outcomes and inappropriate use of antibiotics. Data suggests diagnostic tests, when ordered judiciously, can decrease time to receipt of appropriate antibiotics and decrease unwarranted use of antibiotics. However, indiscriminate use tests may result in excess costs and overuse of antibiotics, owing to reaction to false positive results.