Bioinformatics Working Group – Zsolt Torok, MD, MBA

The objective of Bioinformatics Working Group:
The aim of this working group is to facilitate the adaptation of modern bioinformatics tools and methodology related to the field of personalized medicine. We will also focus on evaluating and introducing international trends to non-IT personnel.
Members of the Bioinformatics Working Group are:
Zsolt Török
Zsuzsanna Maros-Szabó
Edit Tukacs
Bálint Domokos
Péter Szilágyi
Anett Balla

Short introduction on bioinformatics:

The findings in recent years have suggested that individual patients within different treatment groups suffering from the same symptoms and disease react to a given therapy in several different ways. This difference might stem from variant genetic backgrounds of patients and thus, has led to an alteration in the concept of disease and its relevant diagnostic and therapeutic procedures involved with medical treatment.

This approach is widely known as personalized medicine and is beyond classical disease diagnostics. Within particular patient groups, we can define sub-groups with distinct genetic codes and variant responses to therapeutic agents.

The classification of patients in clinical practice is done through the identification of different biomarkers. Biomarkers may be used to screen some conditions, establish diagnoses, predict and/or monitor clinical outcomes, etc. In some cases, biomarkers can also function as therapeutic targets.

The concept of personalized medicine has had a major impact on academic research and related industries. (E.g diagnostic industries). The pharmaceutical industry has turned away from the blockbuster approach of drug development strategy due to its decreasing efficiency and oriented towards personalized medicine. Biomarkers used as therapeutic targets are the basis for rational pharmaceutical development.

Unfortunately, the practical implementation of personalized medicine in the recent years has been below expectations. The number and effectiveness of authorized medicinal products and diagnostic markers through implementation of personalized medicine has been mediocre. Experts in the field suggest that the source of the problem is the lack of a sufficiently large, well-defined patient population available for research purposes as well as the unreliability of the results derived from throughput experiments.

There is a severe need for a standardized software that is able to integrate patient and biological sample data efficiently into a user-friendly data base. This will not only improve patient data access among research groups, but will also lead to accurate biomarker discovery. Hence, our work in constructing a standardized research data-management system and providing bioinformatics data-analysis for genomics research is crucial for solving such problems.
Related data-intensive fields:
High throughput technologies of genomics and proteomics.
Constructing standardized research data-management systems
Genetic counseling implemented with the contribution of DTC and doctors, enterprises collecting data on diseases/patients.
Bioinformatics – data processing, data interpretation, bio-bank systems.
Laboratory IT and IT management systems.
Hospital IT systems.
Systems supporting clinical researches.

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