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ImpriMed unveils cancer treatment forecast technology

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ImpriMed, a precision medicine company, announced that it has expanded its services to include human oncology.

The aim is to provide drug-response predictions for routine blood cancers such as newly diagnosed multiple myeloma and acute myeloid leukemia. 

ImpriMed’s human precision medicine services will set their sights on complex blood cancers via a combination of genomic analysis, ex vivo drug sensitivity testing and machine learning.

Data from the company’s new research for naive non-Hodgkin lymphoma treatment outcomes will be presented at the EHA-SfPM meeting in Copenhagen, Denmark, September 25-27.

“The expansion of ImpriMed’s precision medicine services from veterinary to human oncology is a pivotal milestone in our mission to transform cancer treatment,” Dr. Sungwon Lim, ImpriMed chief executive officer, said in a statement.

“By empowering oncologists and researchers to leverage AI-driven technology to predict treatment outcomes, every patient can receive truly personalized therapy. With our expansion into contract research organization services, we look forward to supporting the development of novel cancer therapies and more personalized treatments, aiming to bring hope to many more patients in their cancer journeys.”

THE LARGER TREND

In August, ImpriMed announced the publication of research on a novel cell-sizing method for feline lymphomas in Veterinary Sciences. Data from the research revealed that by improving the precision of cell-size evaluation, ImpriMed’s technique can possibly transform veterinary oncology and give more dependable prognostic insights and improve treatment planning and patient outcomes.

In May, the company launched ImpriMed Drug Response Predictions, an AI service that brings personalized anticancer drug response projections for canine patients with lymphoma or leukemia. DRP is an addendum to the company’s personalized prediction profile, which features an “immunoprofile” report that gives clonality and immunophenotype data.



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