University of Tartu and Celvia partner up to develop cancer prediction tools

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In October, the University of Tartu and the biotechnology company Celvia signed a cooperation agreement to create an industrial doctoral student place. Sergio Vela, who is a researcher at Celvia, focuses in his doctoral thesis on predicting and diagnosing endometrial cancer with the help of artificial intelligence.

During Sergio Vela’s studies, he has had the opportunity to learn about personalised medicine and the application of bioinformatics to this topic. “My interest in the field increased as I worked on different projects related to my research. I specifically got interested in the application of bioinformatics for the discovery of possible diagnosis and prognostic biomarkers in cancer, mainly by studying breast cancer and lung adenocarcinoma. I thought it could be helpful for people suffering from such conditions as it allows to get a better insight into a patient’s personal condition and prepare adjusted treatments for every case.” 

Vela’s main expectation for his doctoral studies at the University of Tartu is to develop prediction tools for the early diagnosis and prognosis of endometrial cancer. “For this purpose, I will mainly focus on three projects that use clinical data and data obtained by minimally invasive methods such as liquid biopsies and magnetic resonance images. Other expectations involve improving the knowledge about artificial intelligence and cancer, working in a collaborative environment with my supervisors, and enhancing in managing scientific projects.” 

Sergio Vela explained that artificial intelligence can reveal hidden patterns. “Despite two patients having the same diagnosis, for example, endometrial cancer, the outcome for each patient might be very different, even when classified in the same molecular subgroup. This is due to the tumour heterogeneity within the two patients, which can lead to differences such as a higher risk of recurrence after surgery or a treatment working better, or not working at all for one patient in comparison to the other patient. The use of artificial intelligence allows to find different patterns in the data that might not seem obvious and that can explain these differences between patients.” 

Vela added that based on these patterns the goal is to try to make accurate and reliable predictions to determine the kind of treatment that works better in every case or how often a patient should have follow-up sessions based on the estimated risk of cancer recurrence after surgery. 

Vela says that studying for an industrial PhD gives him the opportunity to continue his education while researching the topic he is most interested in and work in a company where he can experience first-hand the application of that research and its effect on people’s quality of life. 

Working at Celvia CC AS, Sergio Vela has already been enrolled in several projects that aim to provide clinicians with different tools that help with the early diagnosis and prognosis of different diseases using minimally invasive methods, such as InvisibleMi, ultimately leading to increasing the quality of life of people suffering from those diseases.

The supervisors of Sergio Vela’s doctoral thesis “Development of Bioinformatic Methods to Improve Prognosis  and Diagnosis of Endometrial Cancer” are Vijayachitra Modhukur and Andres Salumets.

Industrial doctorate is a form of cooperation between the university, the partner organisation and the doctoral student to enhance the applicability of research and its relevance to the needs of society and increase the share of doctoral graduates working in enterprises and institutions. Read more on the university’s website.