

Spain's largest AI oncology platform

To take a step further in personalized cancer medicine by integrating clinical, genomic, anatomopathological, and radiomic data, using AI models to choose the most appropriate treatment.
A multimodal platform to store, process and integrate all patient datasets in a single centralized repository for AI modeling, with a focus on continuous and iterative model training.
The project is expected to provide objective guidance for individual clinical management but also to help develop national health strategies to prevent, early diagnose and treat the most prevalent...
Spain
Seven leading institutions in Spain (MC Anderson Cancer Center, Eurofins, Genomcore, Pangaea Oncology, Atrys, Quibim, Artelnics) joined forces. It counted with €7,5M in funding from the European Union through the Spanish Ministry of Economic Affairs and Digital Transformation.
Dipcan (Digitalization and Management of Personalized Medicine in Cancer) is an observational study designed to serve as a tool for clinical practice in Oncology. It champions the development of personalized medicine by integrating clinical, genomic, anatomopathological, and radiomic data through the use of technology. A total of 2,000 patients with non-hematological metastatic tumors participated in the Dipcan study from 2021 to 2024.
Seven leading institutions in Spain (MC Anderson Cancer Center, Eurofins, Genomcore, Pangaea Oncology, Atrys, Quibim, Artelnics) joined forces to enhance the understanding of cancer in individual patients for earlier and more accurate diagnosis, targeted treatment, and a multidimensional analysis of tumor data. Here, the AI models contribute to the development of national health strategies to manage these diseases in a more efficiently and cost-effective manner.
Multidisciplinary cancer care needs holistic views, integrating omic data. By unifying various medical disciplines along with bioinformatic and technological knowledge, oncologists will be able to make better decisions to improve the patient's quality of life and survival based on their particular case. Thus, the study results will serve to improve daily clinical practice in Oncology, with a clear commitment to personalized medicine. In that sense, Genomcore's platform offered a GDPR and HIPAA-compliant framework for the store, management, standardization and integration of all kinds of datasets, and the Dipcan App streamlined patient registration, data retrieval, and follow-up. It provides PDF reports and facilitates communication. Data was automatically saved and structured on Genomcore's platform, enabling AI modeling and custom workflows.
This project (MIA.2021.M02.0006 2021-2024) has file number: TSI-100206-2021-5 and belongs to the Convocatoria Programa Misiones de I+D en Inteligencia Artificial 2021. It is funded by the Ministerio de Asuntos Económicos y Transformación Digital of Spain, through the Secretaría de Estado de Digitalización e Inteligencia Artificial and the Plan de Recuperación, Transformación y Resiliencia (PRTR). It also receives co-financing from the European Union – NextGenerationEU, within the framework of the Recovery and Resilience Facility (RRF).

“I believe the time has come to systematize the collection of this data in an intuitive, agile way that does not depend so much on the subjectivity of the doctor collecting it, and that specially will allow us to analyze and interpret this data in the future.”






