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Getting the data of gene donors on their doctors’ desk

A doctoral thesis written at the University of Tartu moves us closer to bringing precision medicine into practice.

4 min read
© Renee Altrov

Medicine is always personal because the relationship between a doctor and a patient is personal. Personalised medicine or precision medicine means that treatment decisions, such as drug dosage, are based on the specific person’s health condition and genetic information. A doctoral thesis written at the University of Tartu moves us closer to bringing this theoretical development in precision medicine into practice or on to the doctor’s work desk.

Our genetic data and e-Health data allows very precise treatment decisions to be made, for example, to say what amount of a drug a patient should take, because the same dose can cause side effects in one patient but have no effect whatsoever on another, and this is in part influenced by genetic variability.

  © Sulev Reisberg

Unfortunately, e-Health data, for example, has not been collected for a scientific purpose, so it is not perfect for using in scientific research to help create personalised medicine solutions.

That is why the thesis in bioinformatics by Sulev Reisberg is special. Using e-Health data and genetic data, he developed a software programme that can create a personalised report for 44 thousand gene donors, i.e., specify which amount of a medication should be prescribed for the specific person.

Almost every person needs an adjusted amount of medicine

This is important because 99.8 per cent of gene donors have gene variants which would require an adjustment to the dosage of some drugs according to their genetic information. “We created a workflow for estimating a person’s so-called pharmacogenomic phenotype for 11 genes, based on which it is much easier to either dose or prescribe a specific drug,” said Reisberg.

The opponent of the doctoral thesis, Patrick Kemmeren, is an associate professor at the Princess Máxima Center for Pediatric Oncology in Utrecht. In the case of this doctoral thesis, he especially highlighted the capability of making digital health information usable. “Estonia has indeed developed a lot in terms of making digital health information usable, but at the same time, this information has been gathered for clinical use and not for applying to research.”

According to Kemmeren, the models of Reisberg’s doctoral thesis might be generally useful in clinical practice, and also in paediatric cancer treatment – the field in which Kemmeren works. While a child’s treatment is presently determined based on their age and weight, the treatment should actually be prescribed individually.

Physicians, informaticians, statisticians and biologists working together

Estonian scientists have conducted a lot of research in the field of personalised medicine, but there is a long way from research to reaching the doctor’s desk. “There are a lot of unsolved challenges and problems between fundamental research and application, which all need to be resolved before anything reaches actual clinical practice. And I hope that my thesis has helped to take a step closer to this,” said Sulev Reisberg.

In his dissertation, he writes that the application of the concept of personalised medicine in clinical practice means collaboration between various parties – physicians, bioinformaticians, statisticians and biologists – which is why special personalised medicine programmes in several countries have been initiated on a national level in support of this. Furthermore, this requires many issues from various fields to be solved, incl. regulatory, technical, ethical, educational and financial.

A national personalised medicine programme has also been launched in Estonia. And by now, the creation of an IT infrastructure has begun, which would enable to apply the results of this doctoral thesis to common clinical workflows.

Risk assessments biased towards Europe

Sulev Reisberg’s doctoral thesis was very multi-directional, and one of them revealed another interesting aspect. Namely, the polygenetic risk scores – mathematical models to estimate the genetic risk of developing certain diseases – have mostly been calculated based on the genetic material of Europeans. However, this means that these risk assessments might not be valid for people from other populations such as Africa or Asia.

The opponent, Patrick Kemmeren, also pointed out that Sulev Reisberg’s thesis puts pressure on developing genetic risk scores for other populations as well, and on taking this into account in the precision treatment of people.

Source: Research in Estonia

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