Accelerate Pheno System, Accelerate PhenoTest BC Kit

The Accelerate PhenoTest™ BC kit and Accelerate Pheno™ system provide rapid microbial identification from positive blood cultures using fluorescence in situ hybridization (FISH) and determine antimicrobial susceptibility through morphokinetic cellular analysis (MCA). This automated platform aims to accelerate diagnostic turnaround times for bacteremia and fungemia by analyzing organism-specific ribosomal RNA for identification and observing real-time cellular responses to antibiotics for susceptibility profiling.

The Accelerate PhenoTest™ BC kit, used with the Accelerate Pheno™ system, is an in vitro diagnostic tool designed for rapid identification and antimicrobial susceptibility testing (AST) of microorganisms directly from positive blood cultures. It aims to aid in the diagnosis of bacteremia and fungemia by identifying a broad panel of Gram-positive and Gram-negative bacteria, as well as Candida albicans and Candida glabrata, typically within two hours using qualitative nucleic acid fluorescence in situ hybridization (FISH). The system then performs AST for detected bacterial organisms against a comprehensive list of relevant antimicrobial agents, with results available in approximately seven hours total, employing quantitative morphokinetic cellular analysis (MCA) to determine antimicrobial susceptibility. The system's methodology involves automated sample preparation via gel electrofiltration, followed by cell capture and FISH targeting ribosomal RNA for identification, enhanced by an optical filter and noise rejection algorithms. For AST, MCA technology leverages digital microscopy and machine learning to monitor the real-time morphokinetic responses of individual microbial cells and microcolonies to various antimicrobials, enabling the derivation of Minimum Inhibitory Concentration (MIC) values. Recent updates include revised algorithms for specific Pseudomonas aeruginosa assays (aztreonam, cefepime, ceftazidime, meropenem, piperacillin-tazobactam), automated quality control, and an improved computing architecture. Performance evaluations for these modified P. aeruginosa assays generally showed high essential and categorical agreement with reference methods, although specific antimicrobials exhibited variations in error rates that were further analyzed.

AI Regulatory Concerns

Powered by

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. How does the Morphokinetic Cellular Analysis (MCA) differentiate between bacteriostatic and bactericidal effects of antimicrobials at the single-cell level, and are these differentiations reflected in the MIC reporting?; What is the observed impact of the additional 720-760 nm optical filter and noise rejection algorithms on the identification accuracy and rate of indeterminate results, particularly in samples with high debris levels?; Given the reported variations in error rates for certain Pseudomonas aeruginosa-antibiotic combinations (e.g., meropenem minor errors, initial cefepime/ceftazidime very major errors), what specific morphokinetic features or algorithmic adjustments contribute to these discrepancies, and what is the clinical implication of MICs tending to be higher for cefepime and meropenem with P. aeruginosa?; For polymicrobial infections, what is the system's sensitivity and specificity for detecting and identifying each individual organism, and how does it prioritize which organism(s) proceed to AST if multiple treatable bacteria are identified?; Considering the automated QC process uses complementary sequences coupled to polymer microspheres, how does this method's stability and performance compare to traditional biological QC strains over extended periods and across different reagent lot variations?