GE HealthCare has collaborated with University Medicine Essen (UME) to establish a new Theranostics Centre of Excellence in Germany to enhance precision care and expand access to personalised cancer treatment.

The centre will feature the latest technologies and solutions for supporting clinical practice and advanced research in the country and across the globe.

The partnership focuses on increasing the production and access to radioisotopes for precise diagnoses and monitoring of diseases. It will provide facilities for dose calculation, enhanced quality of images, care coordination and operations.

UME Clinic for Nuclear Medicine scientific advisory board MD, director and chair Ken Herrmann said: "Theranostics has revolutionised the way we approach patient care by combining targeted therapy with precise diagnostic tools, offering a personalised treatment strategy.

“As we advance precision medicine, it is crucial that we collaborate with industry leaders – like GE HealthCare – and invest in innovation to refine and expand personalised medicine, helping ensure even better outcomes for patients in the future.”

Theranostics combines the use of diagnostic tracers with radioisotopes to provide detailed molecular information unique to each patient's cancer cells. Therefore, GE HealthCare will equip UME's new tracer development centre with a comprehensive suite of radiopharmacy solutions including synthesiser, cyclotron and lab technologies to support the production and supply of radioactive materials.

Molecular imaging techniques, vital for visualising disease and treatment efficacy, will be supported by GE HealthCare's new Omni Legend 32cm PET/CT, SIGNA PET/MR and several SPECT/CT systems.

These systems are improved by AI and deep learning solutions including Precision DL, auto positioning, Clarify DL and digital technologies from MIM Software's digital workflow solutions and imaging analytics suite.

Researchers at UME are also working with GE HealthCare to expand the potential of PET/CT technology, which is crucial for diagnosis of the disease, staging, therapeutic planning and evaluation of treatment response, particularly for cancer.

The collaboration has previously validated AI models to predict the response of patients to immunotherapies, with a 70–80% accuracy in predicting efficacy outcomes and the likelihood of developing immune-related adverse events.