Biosample collection in a biobank to solve problems of personalized medicine

Aim. To present an approach to collection of biosamples of patients with rare and scientifically interesting clinical situations for solving the problems of personalized medicine, as well as to analyze related 8-year experience. Material and methods . The approach and a collection of biosamples of blood and its derivatives is developed at the National Medical Research Center for Therapy and Preventive Medicine within the project "Interesting Cases at the National Medical Research Center for Therapy and Preventive Medicine". The collection of biomaterial from project patients was carried out on a planned basis with the inpatient department, as well as upon referral from outpatient doctors. All included patients signed informed consent. Each biosample is accompanied by an extensive annotation, including socio-demographic, clinical, genetic and other types of data. The article presents the project results as of August 12, 2024. Results. An expert group developed 15 disease groups and related inclusion criteria. At the time of analysis, 4525 inpatients and outpatients were included in the project. Positive changes in the number of people included annually is noted. Genetic testing was performed on >2500 patients. The proposed approach allows solving a wide range of clinical and research problems in personalized medicine as follows: timely diagnosis or clarification; formation of patient cohorts to study the genetic aspects of diseases; identification of new genetic variants of hereditary diseases; development of genetic diagnostic panels; study of rare diseases; reduction of sample creation time in case of novel scientific ideas. Conclusion . The proposed approach to the collection and preservation of biosamples and related clinical, socio-demographic, genetic and other types of data in patients with rare clinical cases of scientific interest is important and effective for solving practical and research problems of personalized medicine. The algorithm is well developed, standardized and easily implemented within the clinics, regardless of their size. Preanalytical phase standardization creates the prerequisites for multicenter national and international cooperation.