The group aims to validate the tool, called OncoWatch, in a study involving nine countries this year.
The firm is developing a point-of-need blood test that it anticipates launching as an additional option in the market for active TB screening.
The companies are aiming to use microbial biomarkers to predict the development of precancerous adenomas and carcinomas.
After comparing manual methods with the firm's pcr.ai tool in more than 20,000 cases, they found that the use of AI improved test accuracy and reliability.
The IMCB-A!maginostic Joint Lab of Excellence will provide AI- and machine learning-based solutions to support computational digital and multiplex pathology.
The test, which is in development using perspiration as a sample, has shown promising performance in a preliminary study.
The results are of interest to drugmakers looking for scalable technology solutions for assessment of PD-L1 for predicting immunotherapy response.
The company received an initial $1.25 million and could receive another $6.5 million to develop and commercialize a machine-learning-based sepsis detection algorithm.
As part of the initiative, the company has developed a machine learning-based solution to improve sepsis identification and decrease sepsis-related deaths.
The algorithm uses age, sex, and information about troponin concentrations in patients to determine the likelihood of a heart attack.