Projects

Cancer Virtual Lab

An open-source platform for cancer research

Funding: IFAB call for projects

Enabling technology: Artificial Intelligence, HL7 FHIR standard model, Knowledge Graph

Sustainable Development Goals

The Cancer Lab project aims to bring artificial intelligence into oncology research, offering researchers and clinicians advanced tools for a deeper understanding of cancer. By building a platform that analyzes anonymized data from cancer patients, researchers will have access to a tool that, while safeguarding privacy and through the application of AI and Machine Learning algorithms, will make it possible to derive new insights thanks to its ability to semantically interpret data and available scientific evidence — speeding up the review of scientific literature and opening new paths toward the medicine of the future.

Objectives

Providing researchers with a platform that integrates clinical information and evidence from scientific literature.
Facilitating the application of Machine Learning and Artificial Intelligence techniques to search for correlations.
Enabling quick access to the latest research and developments in the field of oncology.
Supporting a greater capacity for data understanding through the use of Knowledge Graphs and standard models for representing clinical data.

Initial challenge

Cancer research faces the complexity of cancer-related data, which is often inconsistent and scattered across different sources. Electronic health records (EHRs) contain a large amount of information that is essential for advancing therapies, but access to this data is currently not straightforward, for both technical and privacy-related reasons. There is therefore a growing need to integrate this data efficiently in order to speed up research and the process of discovering new treatments. The Cancer Virtual Lab was created to address this challenge within IRST, the Romagna Institute for the Study of Tumors “Dino Amadori” (also an IRCCS for “Advanced Therapies in Medical Oncology”), a center of excellence entirely dedicated to care, research, and training in oncology, specializing in developing alternative therapies through translational research, and treating more than 27,000 patients each year.

Solution

Through the use of Machine Learning and Artificial Intelligence, the platform aims to create anonymized patient avatars, combining clinical data from the care pathway with knowledge derived from scientific literature, which researchers can then analyze using a tool designed to simplify their day-to-day work.

The project thus intends to develop an MVP/prototype with a versatile, integrated interface that facilitates the comprehensive analysis of cancer-related information, strengthening research that can rely on the analysis of connected, semantically represented data — leading to significant acceleration and helping to overcome certain biases.

Ultimately, the project aims to become an operational platform, with its features continuously improved over time.

Benefits

The Cancer Virtual Lab project enables secure, simplified access to data, applying strategies and techniques designed to overcome the obstacles researchers typically face when trying to use data collected both for primary research purposes and for secondary use.

In this way, researchers will be able to reduce analysis time and will have access to a tool that helps them carry forward the creative process of scientific research.

The IFAB team

IFAB took part in the project as a funding body, selecting it as part of its investment lines in research, innovation, and technology transfer. IFAB’s contribution consisted of recognizing the project’s scientific and practical value and providing financial support, making it possible to carry out the research activities conducted by the technical partners. This involvement confirms IFAB’s mission as an accelerator of high-impact initiatives for the local area and productive system.