A concept-stage research program exploring AI-assisted observation of bacterial growth dynamics, with a long-term direction toward faster, more accessible antimicrobial susceptibility guidance for clinical decision-making.
The problem we are addressing
is the minimum time required for conventional bacterial culture and antimicrobial susceptibility testing — during which a patient in sepsis may receive suboptimal or harmful antibiotic therapy.
The antimicrobial resistance crisis is, at its core, a diagnostics crisis. Antibiotics are prescribed without knowing which organism is causing infection, or whether the organism is susceptible to the chosen drug. This is not negligence — it is the rational response to a diagnostic system that provides answers too slowly to inform time-sensitive clinical decisions.
Our research approach
BactoSnap is exploring whether AI-assisted continuous optical observation of bacterial growth dynamics can provide earlier, more informative signals about antimicrobial susceptibility than conventional endpoint culture reads. The concept studies growth kinetics — how quickly bacteria multiply, how their optical density changes over time, how colony morphology evolves — as a richer data source than simple growth/no-growth endpoint detection.
The program explores a compact instrument that combines a precisely controlled growth chamber, multi-angle LED illumination, a high-sensitivity camera array, and an AI inference model trained on bacterial growth time-series data. The concept hypothesis is that AI pattern recognition applied to growth kinetics may identify susceptibility-correlated phenotypes earlier than conventional growth endpoints.
Correlation between AI-observed growth kinetic patterns and gold-standard MIC determination methods
What it's for
BactoSnap is a rapid bacterial-detection product that delivers answers in minutes, not days — simple, affordable, and ready for the point of care.
Intended deployment
A patient arrives with fever and suspected bacterial infection. BactoSnap is designed to help move the decision from empirical treatment toward a targeted, quality-gated answer at the first point of care.
A hospital team trying to reduce unnecessary antibiotic use needs fast, structured evidence. The program explores targeted bacterial detection pathways that can support antimicrobial stewardship.
During a suspected local outbreak, fast triage matters. BactoSnap is designed as a compact rapid-detection concept for frontline screening workflows where every hour changes containment.
Why it matters
An answer at the speed of the visit.
Designed for any hands, anywhere.
Built to be used widely, not sparingly.
No lab required to get a result.
The faster the catch, the better the care.
Questions
It is designed to detect bacterial signals rapidly at the point of need — framed at a high level here, without revealing the underlying mechanism.
Built for frontline and primary care, and for the wider mission of reaching communities beyond centralised healthcare.
BIQADX is at a pre-clinical, prototype stage — BactoSnap is not currently available for commercial sale. We welcome partnership and pilot conversations.