SOFOSBUVIR: TREATMENT OF CHRONIC HEPATITIS C AND THE MAIN TRENDS IN PATENT PROTECTION

The purpose of the study was to analyze and systematize the literature data on the benefit/risk ratio of sofosbuvir administration in the treatment of patients with chronic hepatitis C and the main trends in its patent protection. Studies were conducted using databases on the Internet: Ukrainian patent office, the European patent office, the US patent office, the Food and drug administration, European Medicines Agency (EMEA), State enterprise “The State Expert Center” of the Ministry of Health of Ukraine. It has used retrospective, logical, systematic and analytical methods. Data from clinical studies abroad and meta-analyses indicate that sofosbuvir is one of the most promising drugs for the treatment of chronic HCV infection. Its indisputable advantages are that this drug can be used with different genotypes of the virus, decompensated liver function, it is well tolerated. Sofosbuvir has an improved safety profile and a low probability of viral resistance. The high cost of sofosbuvir is due to the powerful patent protection. As mechanisms for working with patent barriers, it is recommended to use the flexible mechanisms of the TRIPS Agreement: the grant of compulsory licenses, the implementation of parallel imports, the tightening of the criteria for patentability (prohibition of patenting new forms that do not improve therapeutic efficacy)

Scientific and Methodological Approaches to Modeling the Optimal Strategy for Increasing the Competitiveness of Pharmacy Chains of Different Sizes

The aim of the work is to develop scientific and methodological approaches to modelling the optimal strategy to increase the competitiveness of pharmacy chains (PC), which belong to different clusters. Materials and methods. The algorithm for determining the optimal strategy for increasing the competitiveness of PC for different clusters using the method of constructing a decision tree and cluster analysis is proposed. To solve this problem, an expert survey of more than 400 pharmacy managers, who were part of the PC of different sizes, was previously conducted. According to the results of an expert survey using hierarchical clustering methods based on the values of 13 input variables - scores of the strengths of the competitiveness of the PC, three clusters of networks were identified, each of which proposed its own algorithm for modelling the optimal strategy of competitiveness. Results. Using modern economic and mathematical tools, the distribution of PC depending on their size into clusters for modelling the dynamics of competitiveness is substantiated. Indicators are identified, which show a significant difference between clusters, which was taken into account in the process of modelling and selection of the optimal strategy to increase the competitiveness of PC. It is established that the biggest negative impact on the strategy of increasing the competitiveness of small networks has a slow response to changes in market conditions, the biggest positive impact – the availability of additional services in the networks; for medium PC the most important factors influencing the level of competitiveness are the location of pharmacies and competent management; for large PC – the use of modern automated management programs, the level of efficiency of the marketing complex and location features. The algorithm of the generalized model of “decision tree” for a choice of optimum strategy of increase of competitiveness depending on the size of PC is constructed. It was found that the following factors are of the greatest importance: the size of the PC, the use of the discount card system, and the least - the speed of response to market changes and the stability of the financial condition. Conclusions. The proposed generalized mathematical model of the “decision tree” allows a reasonable approach to choosing the optimal strategy to increase the competitiveness of PC depending on its size. The assessment of the importance of predictor variables for each cluster of PC allows determining the priority factors in the implementation of measures aimed at implementing the chosen strategy to increase competitivenes