High-throughput organ-on-chip platform with integrated programmable fluid flow and real-time sensing for complex tissue models in drug development workflows.

Drug development suffers from a lack of predictive and human-relevant in vitro models. Organ-on-chip (OOC) technology provides advanced culture capabilities to generate physiologically appropriate, human-based tissue in vitro, therefore providing a route to a predictive in vitro model. However, OOC technologies are often created at the expense of throughput, industry-standard form factors, and compatibility with state-of-the-art data collection tools. Here we present an OOC platform with advanced culture capabilities supporting a variety of human tissue models including liver, vascular, gastrointestinal, and kidney. The platform has 96 devices per industry standard plate and compatibility with contemporary high-throughput data collection tools. Specifically, we demonstrate programmable flow control over two physiologically relevant flow regimes: perfusion flow that enhances hepatic tissue function and high-shear stress flow that aligns endothelial monolayers. In addition, we integrate electrical sensors, demonstrating quantification of barrier function of primary gut colon tissue in real-time. We utilize optical access to the tissues to directly quantify renal active transport and oxygen consumption via integrated oxygen sensors. Finally, we leverage the compatibility and throughput of the platform to screen all 96 devices using high content screening (HCS) and evaluate gene expression using RNA sequencing (RNA-seq). By combining these capabilities in one platform, physiologically-relevant tissues can be generated and measured, accelerating optimization of an in vitro model, and ultimately increasing predictive accuracy of in vitro drug screening.

Evaluation of pre-hospital trauma triage criteria: a prospective study at a Danish level I trauma centre.

BACKGROUND: The aim of the present study was to evaluate the precision of our trauma triage protocol [based on the American College of Surgeons, Committee on Trauma (ACS COT)] in identifying severely injured defined as an injury severity score (ISS) > 15. Our hypothesis was that isolated mechanism-of-injury criteria were responsible for a significant over-triage leading to over-use of our trauma team. DESIGN: A prospective cohort study. SETTING: A level I trauma centre, Aarhus, Denmark. PATIENTS AND PARTICIPANTS: Among all injured patients admitted during a 6-month period in 2003 we identified severely injured. During the study period, trauma team activations were consecutively registered and triage criteria were prospectively collected. Sensitivity, specificity, positive predictive value, over-triage and under-triage were calculated. RESULTS: Out of 15,162 patients in the emergency department, 848 injured patients were included and 59 (7%) were severely injured. We had 242 trauma team activations with 54 (22%) severely injured. Sensitivity was 92%, specificity 76%, giving an over-triage of 24% and an under-triage of 8%. The positive predictive value was 22%. Among 60 patients with mechanism-of-injury as the only criterion, five were severely injured in contrast to 12 out of 20 patients with mechanism-of-injury combined with physiological and/or anatomical criteria. CONCLUSION: The positive predictive value of our triage protocol was low, only 22%. This was mainly as a result of a significant over-triage from isolated mechanism-of-injury criteria. We recommend revision of the triage protocol and reallocation of our trauma team resources.