Early Sepsis Recognition Platform Could Identify Pre-Symptomatic Patients at POC Using Culture-Free Diagnostic Test

Early sepsis recognition is vital in improving patient prognosis and reducing mortality. Now, a new diagnostic system for early-stage sepsis condition could allow doctors to predict the future appearance and evolution of sepsis within a short period of time and thus, provide a suitable clinical response even before the symptoms arise.

DeepUll (Barcelona, Spain), a biotech company, is creating rapid, affordable and accessible diagnostic solutions with a specific focus on culture-free diagnostics to enable sepsis recognition in pre-symptomatic patients. DeepUll’s technology aims to not only rapidly identify the causative infective agent(s) within a few hours, but will also provide phenotypic antimicrobial susceptibility results, thus reducing the unnecessary use of antimicrobials. The product will also utilize artificial intelligence (AI) to offer seamless medical decision support across all phases of patient management, from early disease recognition, to precise diagnostics, up to therapy guidance.

Image: An early sepsis recognition platform could be more rapid, affordable and accessible (Photo courtesy of Pexels)

DeepUll’s first-in-class sepsis recognition platform is designed to detect more than 250 different pathogens and about 15 resistance genes in one hour starting from 10mL of whole blood. The product will generate phenotypic antimicrobial susceptibility results in about eight hours, without requiring a positive blood culture. The product will be a desktop system with end-to-end automation with the aim to be placed in any clinical setting (laboratory, ER, ICU).

“Early identification of sepsis is absolutely crucial to a patient’s prognosis, but the tools caregivers have available today are woefully inadequate,” said Jordi Carrera, Chief Executive Officer and Co-Founder of DeepUll. “Our mission is to change this and this financing will allow us to ramp up our efforts to bring our first-in-class sepsis recognition platform to market.”

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