Guillermo Siman, CEO & Co-Founder
When it comes to managing pandemics, molecular testing is crucial for diagnosing and tracking the spread of the virus—testing is the only way to reveal how many people have been and could become infected. Although viral testing is key, the availability of tests has proven to be a major limiting factor on diagnostic capacity.
Sample pooling, or combining samples from several patients at a time, could help expand the testing capacity. However, when larger populations are infected, it is difficult to accurately predict which samples can and cannot be pooled together. wePool developed a solution that is specifically designed to address this problem.
wePool AI is a decision support software that uses sociodemographic and healthcare data to drastically increase COVID-19 testing capacity by up to 300%, saving up to 70% of test kits used. With AI, the platform arranges and recommends test groups that most likely only contain samples which will be negative for COVID. This minimizes the retesting that is needed today when a positive sample is found in an otherwise negative test group.
Born out of MIT, wePool is the only group offering the intelligent pooling approach commercially to maximize testing capacity. Their technology and methods/systems for efficient sample pooling in diagnostic testing has now been filed for a provisional patent as of July 2020.
wePool’s work does not end when COVID-19 is eradicated. The technology can be applied for PCR, Antibody, Antigen, Next Generation Sequencing, and other infectious disease testing assays (e.g., Influenza A/B, Malaria, HIV, HPV, and others). wePool AI will become a valuable standard tool for large scale or mass testing, specifically in the context of epidemic and pandemic preparedness scenarios.