Lab-on-a-chip (LOC) are miniaturized analytical devices in which all functionalities are integrated in the same platform. Ideally a LOC device should contain enough intelligence and robustness to be used by non-skilled personal and should deliver the results directly on-site or to a central station. It is clear that achieving a portable, reliable and easy-to-use LOC device for diagnostics could offer significant advantages over standard methods. Although significant progress has been achieved at the LOC field during last years,very few stand-alone devices have emerged. Most of current devices are simple planar microfluidic devices which do not incorporate the detection and the read-out must be done with complex instrumentation in laboratory settings. That is the main reason why incorporating “on-chip” detection by using biosensors is a new technology that shows great promise.
In this project we intend to go beyond the state of the art by designing new photonic cutting-edge biosensing technological tools. On account of scalable fabrication and relevant sensitivities (pM-fM) for sensing, chip-integrated waveguide array structures are promising detection elements for lab-on-a-chip. The keys to translate these sensors from academic novelties to viable laboratory tools lie on the design of robust sensor architectures and interrogation instrumentation that facilitate the integration of advanced sensors into easily used LOC formats. Thus, our approach based on optimized nanophotonic waveguides in a novel interferometric configuration promises to improve the current systems best-in-class performance for label-free biosensing. One of the major challenges is the design and integration into a LOC platform. For such development several units must be incorporated on the same platform: (i) the photonic sensors, (ii) the flow cells and the
flow delivery system (iii) robust surface functionalization protocols (iv) the light sources and photodetectors array (v) processing electronics and, (vi) final packaging with the required software.
Another challenge is the practical demonstration of its viability for patient-bedside diagnostics. In particular, we aim at applying the LOC for Liver failure diagnostic. Liver failure is a syndrome caused by the incapacity of the liver to perform its functions. It may be due to acute diseases (Acute Liver Failure) or cirrhosis (Chronic Liver Failure, CLIF). CLIF is by far the most common presentation of liver failure. It is characterized by the development of complications such as ascites (accumulation of fluid in the abdomen), gastrointestinal hemorrhage, hepatic encephalopathy, renal failure or bacterial infections (of ascitic fluid or blood stream). The probability of survival of patients with CLIF is short (less than 3 years) unless patients undergo liver transplantation. Patients with CLIF are at risk of developing liver cancer. The mechanism of CLIF is complex and not related to the impairment of liver function alone, but also it is associated with functional failure of several other organs (brain, kidneys, etc…). Nowadays there is a lack of strategies for remote monitoring of liver disease for early identification of liver failure. It is of high relevance a continuous follow-up of the patient´s biomarkers of bad prognosis which are indicative of complications related to CLIF and to select those patients that should be transplanted with higher priority.
According with the knowledge of our clinical partner, we have preliminary selected as relevant biomarkers the following (other potentially useful biomarkers might be incorporated during the project): Renin, C-reactive protein, procalcitonin and NGAL (Neutrophil gelatinase Asociated Lipocain). An additional analysis of the abnormal levels of physiological bacteria in ascetic fluid is also relevant to ensure an accurate diagnostic, since the increased concentration of these bacteria is a major indication of complications related to liver damage and cirrhosis. The analysis of ascetic fluid and blood/serum patients´samples with the LOC sensing platform will give a reliable picture of the patient’s condition.