Accelerating and Enhancing Assistive Robotics—From Development to Deployment
The increasing sophistication of assistive robots and their widespread deployment at scale and into continuous use in the industry and healthcare sector—from the plants, to hospitals, to home. Deploying assistive robots requires more than just purchasing and installing individual robots. Each robot must be deployed based on its suitability, and best practices and regulations must be followed.
Deployment Forum is the most exciting interdisciplinary conference on the strategy and efforts for integration and coordination relating to assistive robots. The Forum is specifically designed to provide suppliers, end-users, R&D personnel and others, with the information, guidance and peer networking opportunities they need to successfully develop and safely deploy the assistive robotics systems responsibly. The dialogue will share key aspects on deploying assistive robotics including end-user needs, best practices, lessons learned, success stories, challenges, new business models, and need for research within key topics such as AI, machine learning, standardization.
Thyroid nodules are frequent but mostly benign, and postoperative rate of benign nodules reaches 90%. Therefore, there is a need for identification of reliable preoperative diagnosis markers for patients with thyroid cytology. In particular, there is a gap in studies of interrelationships between diurnal profiles of expression of circadian clock genes and TSH receptor in thyroid tissue exposed to different concentrations of TSH. These interrelationships might be investigated in future in vitro experiments on benign and malignant thyrocytes cultivated under normal and challenged TSH levels. Results of this investigation might help to bridge previous studies of preoperative biomarkers for thyroid carcinoma that explore diagnostic value of diurnal profiles of serum TSH levels, expression of its receptor and circadian clock genes.
Rare tumor-specific mutations in patient samples serve as excellent markers to monitor the course of malignant disease and responses to therapy in clinical routine, and improved assay techniques are needed for broad adoption. We describe herein - superRCA assays - which provides for rapid and highly specific detection of DNA sequence variants present at very low frequencies in DNA samples. Using a standard flow cytometer we demonstrate precise, ultra-sensitive detection of single-nucleotide mutant sequences from malignant cells against a 100,000-fold excess of DNA, to follow the course of patients treated for acute myeloid leukemia (AML) and Lung Cancer patients.
Quanterix® has developed an ultra‐sensitive platform capable of measuring individual proteins at concentrations a thousand times lower than conventional immunoassays. The Single Molecule Array (Simoa®) technology at the foundation of this platform enables the detection and quantification of biomarkers previously difficult or impossible to measure, opening new applications to address significant unmet needs in life science research and diagnostics. Simoa® assays have the potential to be used to monitor cancer risk, identify early-stage cancers, and discriminate between benign and malignant cells. Simoa biomarkers also have the potential to be used prognostically to predict disease outcome, predict progression-free survival and monitor reoccurrence, as well as to be used to monitor sensitivity to therapy. Finally, Simoa technology and platforms have been designed with flexibility in mind to enable the discovery and testing of novel cancer relevant biomarkers. Simoa ultra-sensitive custom assays have been successfully developed and employed for several interesting applications ranging from tumor derived exosomes and miRNA quantification to study the PK/PD of anti-tumorigenic drugs.
The SuFIDA technology is a single molecule counting technology. It is an advanced ultrasensitive immunoassay technology that enables the detection of biomarkers that were previously undetectable down to lower femtomolar concentrations. SuFIDA is the evolution of the sandwich ELISA with greater selectivity, higher sensitivity and the digital readout using an optical imaging technique. In SuFIDA, capture antibodies are immobilized on a glass surface and bind the analyte from the sample. A fluorescence-labeled antibody is used as the detection probe, which recognizes an epitope on the target molecule that is not occupied by the capture antibody. Using highly sensitive TIRF microscopy, all individual fluorescence-labeled probes on the surface will be detected and virtually counted individually. By using an in-house developed analysis software, the huge image volumes are evaluated in a short time with various analysis functions.
Sepsis is a clinical syndrome characterized by dysregulated response to infection. It represents a leading cause of mortality in ICU patients worldwide. Although sepsis is in the point of interest of research for several decades, its clinical management and patient survival are improving slowly. Monitoring of the biomarkers and their combinations could help in early diagnosis, estimation of prognosis and patient’s stratification and development of new targeted treatment. This presentation recapitulates results of last 5 years of our collaborative translation research in the field. Promising new molecules such as Soluble Endoglin, Hepcidin, Ferritin or different cellular markers on immune cells could have predictive potential in Septic shock, critical Covid-19 and/or post-surgery patients.
Pancreatic cancer leads to a poor life expectancy (4-6 months) due to its silent nature. Thus, an early detection strategy would save a large number of lives. We focus on glycoprotein mucin 1 (MUC1), which is overexpressed in 90% of cancers while patients generate antibodies against it. We have developed a very sensitive detection system for these antibodies by generating an unnatural peptide with higher affinity for the antibodies, and binding the unnatural peptides to gold nanoparticles. In a clinical study, we found significant differences between pancreatic cancer patients and healthy volunteers (p<0.0001). A ROC analysis produced an area under the curve of 0.918, with 85% sensitivity and 90% specificity. We are looking for partners to commercialize this detection system.
