The collaboration will initially use machine learning to identify correlations in molecular and imaging readings to differentiate lung cancer types
Bayer headquarters in Berlin-Wedding. (Credit: Fridolin freudenfett/Wikipedia.)
German life sciences firm Bayer has extended its partnership with UK-based Huma to classify certain lung cancer types using machine learning technology.
The collaboration aims to differentiate different types of non-small-cell lung carcinomas (NSCLCs) using CT scans, to enable patients to receive appropriate and timely treatment.
It will initially use machine learning to identify correlations in molecular and imaging assessments that can differentiate lung cancer types.
Huma and Bayer researchers will create, train and test AI models that can precisely diagnose various types of lung cancers.
Bayer oncology, pharmaceuticals division head Robert LaCaze said: “Rather than treating all lung cancer patients with standardised regimens, precision medicine can allow physicians to prescribe medicines tailored to the tumour’s specific oncogenic driver.
“Our collaboration leverages Huma’s proven expertise in Machine Learning and Bayer’s vast capabilities in Oncology and Medical Imaging to help accelerate the identification of those patients with certain types of non-small cell lung cancer who can most benefit from these tailored treatments.”
Huma is a health technology company that leverages digital biomarkers, predictive algorithms and real-world data from continuous patient monitoring to advance predictive care.
The company has developed a modular platform to support better care as a digital ‘hospital at home’ for a range of use cases across different disease areas.
The platform would also support research by backing some of the world’s largest decentralised clinical trials and studies in life sciences.
Huma CEO and founder Dan Vahdat said: “We have shown we can use machine learning to predict an individual’s risk of depression, anxiety, cardiac events and the impact of being infected by Covid-19, and we hope this work in cancer will be a new field for us.
“We know the importance of evidence-based, rigorous innovation and, by doing it the right way, we can more rapidly make meaningful, impactful changes and help people live longer, fuller lives.
“We want to start by providing more personalised care for people with non-small cell lung cancer. In the future, our vision is to include other cancers and even other therapeutic areas such as rare diseases.
“We want to broaden our existing smartphone platform to combine imaging, digital phenotyping, and genomics with the real-world, real-time data from patients that we already collect. We want to take therapies from bench to bedside to breakfast table.”