Robotic Next Generation Sequencing Platform Accurately Screens Thousands of COVID-19 Samples at Once
|
By HospiMedica International staff writers Posted on 04 Mar 2021 |
|
Image: Jeff Wrana, left, is seen in this undated file photo at the Lunenfeld-Tanenbaum Research Institute in Toronto, Canada (Photo courtesy of Sinai Health)
A robotics platform to screen thousands of COVID-19 samples at once has the potential to revolutionize how labs track the spread of viruses and other pathogens, according to new findings.
The study by researchers from the Lunenfeld-Tanenbaum Research Institute (LTRI) at Sinai Health (Toronto, ON, Canada) found that their next-generation, ultra-high-throughput sequencing platform, called C19-SPAR-Se, has a sensitivity rate greater than 95% in positive cases during peak onset. The platform is also cost-effective. The study notes it only costs about USD 8 per test when running thousands of samples at once, as the cost per sample decreases due to economies of scale.
"Identifying positive samples quickly and accurately is critical in beating this pandemic," said Dr. Jeff Wrana, senior investigator at the LTRI and professor in the Department of Molecular Genetics at the University of Toronto. "With new and potentially dangerous variants now circulating, this is a platform that is scalable, automated and capable of analyzing thousands of COVID-19 patient samples in a single instrument run."
Related Links:
Lunenfeld-Tanenbaum Research Institute
The study by researchers from the Lunenfeld-Tanenbaum Research Institute (LTRI) at Sinai Health (Toronto, ON, Canada) found that their next-generation, ultra-high-throughput sequencing platform, called C19-SPAR-Se, has a sensitivity rate greater than 95% in positive cases during peak onset. The platform is also cost-effective. The study notes it only costs about USD 8 per test when running thousands of samples at once, as the cost per sample decreases due to economies of scale.
"Identifying positive samples quickly and accurately is critical in beating this pandemic," said Dr. Jeff Wrana, senior investigator at the LTRI and professor in the Department of Molecular Genetics at the University of Toronto. "With new and potentially dangerous variants now circulating, this is a platform that is scalable, automated and capable of analyzing thousands of COVID-19 patient samples in a single instrument run."
Related Links:
Lunenfeld-Tanenbaum Research Institute
Gold Member
SARS‑CoV‑2/Flu A/Flu B/RSV Sample-To-Answer Test
SARS‑CoV‑2/Flu A/Flu B/RSV Cartridge (CE-IVD)
Patient Preoperative Skin Preparation
BD ChloraPrep
Gas Analyzer
GE SAM
Latest COVID-19 News
- Low-Cost System Detects SARS-CoV-2 Virus in Hospital Air Using High-Tech Bubbles
- World's First Inhalable COVID-19 Vaccine Approved in China
- COVID-19 Vaccine Patch Fights SARS-CoV-2 Variants Better than Needles
- Blood Viscosity Testing Can Predict Risk of Death in Hospitalized COVID-19 Patients
- ‘Covid Computer’ Uses AI to Detect COVID-19 from Chest CT Scans
- MRI Lung-Imaging Technique Shows Cause of Long-COVID Symptoms
- Chest CT Scans of COVID-19 Patients Could Help Distinguish Between SARS-CoV-2 Variants
- Specialized MRI Detects Lung Abnormalities in Non-Hospitalized Long COVID Patients
- AI Algorithm Identifies Hospitalized Patients at Highest Risk of Dying From COVID-19
- Sweat Sensor Detects Key Biomarkers That Provide Early Warning of COVID-19 and Flu
- Study Assesses Impact of COVID-19 on Ventilation/Perfusion Scintigraphy
- CT Imaging Study Finds Vaccination Reduces Risk of COVID-19 Associated Pulmonary Embolism
- Third Day in Hospital a ‘Tipping Point’ in Severity of COVID-19 Pneumonia
- Longer Interval Between COVID-19 Vaccines Generates Up to Nine Times as Many Antibodies
- AI Model for Monitoring COVID-19 Predicts Mortality Within First 30 Days of Admission
- AI Predicts COVID Prognosis at Near-Expert Level Based Off CT Scans
Channels
Artificial Intelligence
view channel
AI Tool Predicts Chronic Kidney Disease Risk in Diabetes
Chronic kidney disease is a common and serious complication of type 2 diabetes and often progresses without obvious early symptoms, increasing morbidity and straining health systems. Many risk models were... Read more
AI Trends Report Guides Responsible, Effective Healthcare Deployment
Hospitals are under growing pressure to adopt artificial intelligence tools that improve safety, efficiency, and continuity of care without compromising quality. At the same time, clinicians need clearer... Read more
Critical Care
view channel
Wearable Microneedle Patch Monitors Antibiotic Levels in Real Time
Therapeutic drug monitoring for agents with narrow therapeutic windows often relies on intermittent blood draws and laboratory analysis, providing only snapshots of exposure. Real-time, minimally invasive... Read more
AI Analysis of EMS Calls Aids Pediatric Trauma Decision-Making
Accurate trauma triage is difficult when decisions rely on brief, noisy reports from emergency medical services (EMS). Misclassification can delay lifesaving interventions or lead to overuse of critical... Read more
Surgical Techniques
view channel
AI-Designed Microneedle Patch Accelerates Diabetic Wound Healing
Chronic diabetic wounds are slow to heal and prone to infection, often leading to repeated procedures and prolonged care. Standard closure methods bring wound edges together but do not adapt to changing... Read more
Focused Ultrasound System Gains CE Mark for Liver Tumor Treatment
Liver tumors remain a major global health challenge, and many patients are not candidates for resection or conventional thermal ablation. Tumor location, underlying liver disease, and other clinical factors... Read more
Patient Care
view channel
AI Avatar Doctor Improves Patient Understanding Before Radiotherapy
Radiation oncology consultations require patients to grasp complex concepts quickly, yet anxiety and information overload often undermine understanding and informed consent. Poor comprehension can also... Read more
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Health IT
view channel
Weekly Remote Symptom Monitoring Improves Symptom Control in Advanced Cancer
Patients receiving treatment for advanced cancer often struggle with uncontrolled symptoms and fragmented communication with clinicians. These gaps can impair daily function, increase emergency department... Read more
Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation
Atrial fibrillation is an erratic, quivering heartbeat and a leading cause of stroke. Catheter ablation is widely used to interrupt arrhythmogenic tissue, yet many patients—especially with persistent ... Read more
Point of Care
view channel
New Brain Ultrasound Platform Enables Bedside Postoperative Imaging
Transporting postoperative patients for CT or MRI can create operational burdens, delays, and disruptions in care. Bedside visualization may help reduce transport demands, lower radiation exposure, and... Read more
Handheld Ultrasound Expands Point-of-Care Imaging Access in Brazil
Rapid access to diagnostic imaging is essential across hospitals, emergency departments, clinics, and municipal health systems, but large markets still face uneven availability, particularly in rural regions.... Read more
Business
view channel
AI Care Platform Adds Quantitative MRI Analysis for Multiple Sclerosis
Neurodegenerative diseases such as multiple sclerosis require timely identification and coordinated, long-term management. As health systems seek consistent decision-making at scale, quantitative neuroimaging... Read more
