Garazi Serna Alonso is a Postdoctoral Researcher at VHIO, Spain who received an EACR Travel Fellowship to visit and work at EKFZ, Germany in December 2023.

The EACR is supported by Worldwide Cancer Research to provide Travel Fellowships of up to €3,500 to enable early-career cancer researchers to gain new skills through a short-term visit to a lab or research group in another country.

You can read about other Travel Fellows and their experiences here.


Name: Garazi Serna Alonso
Job title: Postdoctoral Researcher
Home institute: Vall d’Hebron Institute of Oncology, Spain
Host institute: Else Kröner Fresenius Zentrum für Digitale Gesundheit, Germany
Dates of visit: 01 – 23 December 2023
Research: I employ advanced artificial intelligence to analyse cancer tissue images, specifically focusing on predicting HER2 levels and anticipating responses to anti-HER2 therapies in breast cancer patients. By teaching computers to understand patterns in these images, we can enhance the precision of cancer diagnosis and tailor treatments for better outcomes without the need of complex and expensive technologies. This research combines cutting-edge technology with pathology to revolutionise how we approach cancer care, striving for more personalised and effective treatment strategies.


How did you choose the host lab?

Selecting the Clinical Artificial Intelligence lab was a meticulously considered decision rooted in alignment with my research goals and the unique strengths of the host institution. The lab’s global reputation as pioneers in precision oncology, particularly in the application of deep learning to extract actionable knowledge from clinical data, resonated with my commitment to advancing cancer research through innovative technologies.

The host lab’s interdisciplinary composition was a key factor and the exceptional resources and expertise of the Clinical Artificial Intelligence group in utilising deep learning for clinically actionable insights from histopathology slides presented a unique learning opportunity. The focus on developing advanced AI models for cancer diagnosis aligned seamlessly with my research ambitions.

“This experience was invaluable, providing opportunities and insights that were otherwise inaccessible in my home lab”

Can you summarise the research you did and what you learned on your visit?

During my stay, I dedicated efforts to propel cancer diagnostics forward by integrating histology images and mass-spectrometry data with cutting-edge artificial intelligence techniques. A pivotal aspect was acquiring advanced skills in deep learning tailored for histological images, a crucial step in developing state-of-the-art AI models for cancer diagnosis and prognosis.

I learned how to create AI models designed to identify levels of HER2 in breast cancer cases from standard haematoxylin and eosin (HE) images. While the models are still evolving, ongoing efforts involve refining and optimising them, with a particular focus on enhancing accuracy through the incorporation of additional cases and data.

Simultaneously, the visit facilitated the development of predictive models for patient responses to anti-HER2 treatment based on HE images. Continuous refinement and expansion of the dataset aim to improve the models’ predictive accuracy. This collaborative journey not only lays the foundation for revolutionary advancements in cancer diagnostics but also emphasises the iterative nature of AI model development, underscoring the ongoing commitment to enhancement through the addition of more cases and meticulous data refinement. The research conducted during this visit represents a dynamic and evolving stride towards more effective and personalised cancer care.

Garazi and the host lab team

What were you able to do that you could not have achieved in your home lab?

During my visit, I was exposed to a wealth of knowledge and resources that were unavailable in my home lab. The host institution provided critical support in bridging gaps in my understanding, from basic script knowledge to running and interpreting models effectively. Their expertise extended beyond technical aspects, encompassing practical insights on model improvement and application of different algorithms. The collaborative environment allowed me to set up these processes in my home lab, ensuring continuity. Additionally, being an active participant in the host lab’s meetings and workshops offered a unique perspective, exposing me to different dynamics and methodologies that have significantly enriched my approach to research. This experience was invaluable, providing opportunities and insights that were otherwise inaccessible in my home lab.

Did you take part in any interesting local activities?

While my primary focus was on the intensive work during my visit, I managed to explore the local culture, especially through the enchanting Christmas markets. Being pregnant, my energy was dedicated to maximising my learning experience within the lab. Despite missing out on some traditional tourist activities like visiting museums, I did attend a thesis defence, adding a unique academic and cultural dimension to my visit.

To balance the demanding work schedule, I seized the opportunity to not just visit Dresden but travel to captivating destinations like Berlin, Leipzig, Prague, and the surrounding forests. These excursions provided a refreshing change of scenery and climate, allowing me to appreciate the cultural diversity and architectural richness of the region. Although I missed some traditional cultural experiences, the combination of work and travel enriched my overall experience, creating lasting memories of both professional and personal significance.

Garazi during her visit to Dresden

Was the host institution very different from your own?

The host institution presented a stark contrast to my home lab, which has a strong focus on clinical support, collaborations, and clinical trials. What struck me about the host institution was its concentrated emphasis on research and publication. Nearly everyone in the lab was engaged in their own projects, simultaneously working on more than 10 papers. Their streamlined approach, relying predominantly on computers and data rather than wet lab experiments, enabled a significantly faster research pace compared to our laboratory.

I particularly appreciated their collaborative culture, where individuals with diverse backgrounds—computational scientists, medical doctors, engineers, biologists—came together seamlessly. The dynamic interdisciplinary environment fostered a spirit of mutual assistance and shared expertise. The lab’s commitment to a collaborative platform for sharing papers and talks underscored their collective dedication to advancing knowledge in a rapidly evolving field. This experience broadened my perspective on research dynamics and collaboration models, leaving a lasting impression on my approach to scientific endeavours.

Have you brought back any specific knowledge that has benefited your home lab?

Undoubtedly, my experience at the Clinical Artificial Intelligence lab has positioned me as one of the foremost experts in AI applied to histopathology images within my institution. Despite the relatively short duration of the visit, I dedicated extensive efforts to learning and application. I’ve successfully installed the programs and executed the algorithms used during my time there within our lab.

This newfound expertise empowers my home lab to embark on numerous projects leveraging our extensive collection of histopathology images. By integrating AI techniques into our research, we are poised to become pioneers within the institution, advancing state-of-the-art models for cancer diagnosis and prognosis. This not only establishes us as key contributors but also positions me to share this knowledge with my colleagues, fostering a culture of innovation within our institution.

Given our connection to the hospital, the potential for acquiring a vast quantity of images, coupled with the knowledge I’ve gained and will continue to acquire, creates an incredible opportunity. This synergy, combined with the prospect of involving more collaborators, holds the promise of transformative advancements in cancer diagnostics, making a lasting impact on both our institution and the broader field.


Want to find out more?

If you are interested in applying for the Travel Fellowship scheme, please click here for more information: EACR Travel Fellowships.