Javier García, Technical Director and co-founder of Sycai Medical: “The support of CDTI Innovation and the European funds MRR has allowed us to develop a system capable of improving diagnostic accuracy and detection of pancreatic cancer”

In the field of diagnostic imaging, artificial intelligence is driving profound transformations that enable healthcare professionals to detect increasingly complex diseases at increasingly early stages. Among them, pancreatic cancer remains one of the biggest challenges: its late diagnosis considerably limits therapeutic options and reduces survival. Given this reality, support for high-impact technologies becomes essential so that new solutions can be transferred to the clinical environment and contribute to improving the prognosis of these diseases. In this scenario of health need and technological opportunity, Sycai Medical emerges.
 

From technology to healthcare

Sycai Medical emerged as a Spanish startup dedicated to artificial intelligence in medical imaging, with an origin focused on technological innovation and, as Javier García, Technical Director of the company, recalls, “In the beginning we did not have a specific medical objective, we wanted to develop advanced technology of image analysis.”

Subsequently, the shift towards the health sector came with an unexpected event: the COVID-19 pandemic. The company was faced with a situation that combined health urgency, hospital saturation and the need for tools capable of supporting radiologists. As García explains, “With the arrival of the pandemic we are faced with an urgent need: to support the health system in the diagnosis and management of patients with COVID-19. From there we developed our first medical image analysis software, capable of detecting signs of the disease on chest X-rays.”

That first product marked a before and an after. The validation in a real clinical environment allowed us to verify that its technology could provide a tangible value and opened a new perspective within the team. “During that process, we realized the enormous potential that our technology had within the medical field, especially to improve accuracy and efficiency in diagnostic imaging,” he adds.

As a result of that experience, Sycai Medical reoriented its goal towards a clinical challenge of enormous impact: the early detection of premalignant abdominal lesions, with special focus on pancreatic cancer. This disease, one of the most deadly, is usually diagnosed in advanced stages because it does not present symptoms in its initial stage. The team identified here a clinical vacuum in which artificial intelligence could make a vital difference.

This is how the company consolidated its current mission: “Detecting early and premalignant abdominal injuries from routine radiological imaging, even when scans are performed for unrelated reasons,” says Garcia. Its technology, trained with more than 300,000 images and clinically validated, not only detects injuries, but also automatically monitors their evolution over time by analyzing previous studies. The results support this bet: "Our patented diagnostic method has proven to be very accurate, reliably detecting injuries and tracking their evolution with a high level of accuracy," he says.
 

A pioneering solution for the early detection of pancreatic cancer

The heart of the project that Sycai Medical develops with the support of Neotec of the CDTI Innovation, an initiative cofinanced with the European funds of the Recovery and Resilience Mechanism (MRR), is a unique artificial intelligence solution in Europe. The tool not only identifies premalignant lesions, but is also able to detect pancreatic cancer itself and stratify it, providing clinically relevant information on its possible evolution.

As detailed by its Technical Director, “Prior to the support of the CDTI, we had a first viable minimum product that allowed early diagnosis of patients with a high probability of developing pancreatic cancer.” However, Neotec’s support was a decisive qualitative leap for the company: “Thanks to this initiative, we were able to move towards a more sophisticated and clinically powerful tool. In addition, we went one step further: not only did we identify precancerous lesions, but also pancreatic cancer itself.”

To achieve this, the company developed new neural networks specially trained for this type of detection and stratification. The complexity of this technological challenge is enormous. Pancreatic cancer has an enormous heterogeneity in shape, morphology, location and clinical behavior, and must also be distinguished from a wide range of cystic and non-cancerous lesions with variable characteristics. Therefore, García recognizes that one of the most complex challenges of the project has been precisely “To achieve a set of neural networks that is able to learn this heterogeneity in different medical imaging protocols”.

However, the difficulty is not only technological, it is also clinical. Sycai Medical has developed a tool aimed at incidental detection: “It is a system capable of alerting the radiologist to lesions compatible with cancer risk in tests that were not aimed at studying the pancreas.” This approach required a high level of reliability and an integrable model in hospital workflows. As García points out, “Offering an incidental detection tool for pancreatic lesions represents a clinical challenge. Our goal has been to develop a value proposition that helps early detection, saves time in diagnosis, unifies and standardizes reporting, and can be easily integrated into existing systems.”
 

Validation, benefits and leap to the clinical market

The development of the system relies on computed tomography (CT) imaging, the most widespread test for a patient’s initial radiological assessment. “The neural network model was trained using an extensive set of computed tomography data from patients with confirmed pancreatic cancer, as well as other CTs from other pathologies or from healthy patients,” explains García. By relying on the most common radiological test, the tool maximizes its ability to generate incidental detections and increase early diagnosis.

All of this technology has been subjected to rigorous validation and certification processes. The Sycai Medical solution already has CE marking and fully complies with the European MDR regulation. In addition, it has been evaluated multi-centred in several hospitals, which guarantees its real applicability. As García summarizes: “Our product has been validated to ensure reliability and accuracy.”

The result is a fully developed technology and ready for clinical implementation. In addition, the Technical Director assures that “It is already in the commercialization phase”.

The benefits for hospitals, radiology centers and clinical professionals are extensive: “Early detection, alleviation of the workload, standardization of reports, elimination of inter-observer variability and better understanding of the response to treatment” are, according to García, some of the key advantages of the tool.

Technology from Sycai Medical, a system capable of identifying premalignant lesions and cancer

Long-term vision

Sycai Medical’s work does not end with the commercialization of its first product. The company has an ambitious long-term vision: to consolidate itself as an international reference in the incidental diagnosis of abdominal cancer lesions and in the prediction of their evolution. As Javier García explains: “Achieving this goal involves not only perfecting the solution developed for the pancreas, but also expanding the technology to other organs and pathologies, incorporating increasingly advanced predictive capabilities.”
 

Technological innovation at the service of health

In an international context where the demand for advanced AI tools in health is growing rapidly, Sycai Medical is positioned as an actor capable of combining technological innovation, clinical evidence and a strong commitment to safety and regulatory reliability. The company aims to further expand its training database, integrate new clinical and temporal variables, and refine its longitudinal analysis capability to anticipate the evolution of injuries over time.
 

Towards a future of precision in medical imaging

For its part, Sycai Medical today represents one of the strongest bets of the innovative Spanish ecosystem in the field of artificial intelligence-assisted diagnosis. Its technology allows early detection of one of the most silent and deadly diseases, with undeniable transformative potential for healthcare systems. With the development of this project, the company positions itself as a reference in precision medicine applied to medical imaging.

“Our goal is for this technology to become a common tool in hospitals and radiology centers, improving early detection and ultimately saving lives,” Garcia concludes.

Founding team of Sycai Medical, a startup specializing in artificial intelligence applied to diagnostic imaging
 

CDTI Innovation

The Center for Technological Development and Innovation, CDTI E.P.E. It is the innovation agency of the Ministry of Science, Innovation and Universities, whose objective is the promotion of technological innovation in the business environment. The mission of the CDTI is to ensure that the Spanish business fabric generates and transforms scientific and technical knowledge into globally competitive, sustainable and inclusive growth. In 2024, within the framework of a new strategic plan, the CDTI provided more than 2.3 billion euros of support to Spanish companies and startups.
 

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