The objective of this article is to present selected examples of priority policies recently implemented in the health systems of Brazil, China, and Russia. In Brazil, two major initiatives are mentioned: the Family Health Strategy, which reorganizes Primary Health Care through territorially defined multidisciplinary teams responsible for delivering comprehensive, community-based services; and the Popular Pharmacy Program of Brazil, which expands access to essential medicines, thereby strengthening financial protection and promoting equity within the Unified Health System. In China, reforms are guided by the Healthy China 2030 strategy, a comprehensive national agenda aimed at improving the general health of the population, reinforcing preventive approaches, modernizing service delivery, and advancing digital health innovation. Emphasis is placed on tuberculosis control policies that integrate patient-centred care with coordinated public health actions, enhancing continuity of care and treatment outcomes. In Russia, priority initiatives include policies designed to support ageing populations, strengthen primary care and preventive services. In doing this, they aim to maximize patient satisfaction as a system-level performance indicator within the framework of Mandatory Health Insurance. The dissemination of these priority policies within the BRICS framework may facilitate the exchange of policy experiences, technical expertise, and institutional innovations, thereby contributing to South—South cooperation in health. The BRICS Network of Research in Public Health and Health Systems represents a promising platform for advancing collaborative research and promoting such benchmarking initiatives.

Continuous professional education is an important component of efforts to improve maternal and newborn care, particularly in countries with heterogeneous healthcare systems and significant training needs.

Aim. To describe the structure, geographical reach, participant characteristics, and immediate evaluation outcomes of the international training program “Ways to reduce maternal and infant mortality” implemented by the Kulakov National Medical Research Center between 2012 and 2025.

Materials and Methods. A retrospective descriptive study was conducted using aggregated administrative reports from training activities involving healthcare professionals from 11 BRICS members and partner countries. Available variables included country and year of participation, demographic and professional characteristics, training format, and post- training feedback. Descriptive statistics were used; no inferential analyses were performed.

Results. The analysis included 1,055 participant records from 11 countries. Most records were from the Commonwealth of Independent States, particularly Uzbekistan, while program coverage expanded in 2022–2025 to include broader participation from Latin America, Southeast Asia, Africa, and the Middle East. Obstetricians-gynecologists, neonatologists and pediatricians, as well as anesthesiology and intensive care specialists accounted for 91.2% of records. The program combined multilingual, simulation-based, multidisciplinary, center-based, and on-site training. Mean post-training ratings ranged from 4.55 to 5.00 on a five-point scale.

Conclusion. The program was very international in scope and showed high immediate acceptability among participants. However, to evaluate the influence of training on clinical competence, routine practice, or maternal and newborn outcomes, future evaluation should include standardized competency assessment and long-term follow-ups.

Artificial intelligence (AI) is increasingly used to support organizational and managerial processes in healthcare, although evidence of real-world effects remains heterogeneous.

Aim. To identify and critically evaluate the evidence on the impact of AI technologies on organizational processes in healthcare and to assess their potential applicability BRICS healthcare systems.

Methods. A systematic review with narrative followed PRISMA 2020. PubMed and eLibrary.ru (incorporating the Russian Science Citation Index) and CyberLeninka were searched between January and February 2026. Primary empirical and implementation studies, reviews, and selected methodological, governance-related, and contextual papers published between 2017 and 2026 were eligible. After multistage screening, 78 publications were included.

Results. The strongest evidence concerned predictive analytics for patient flow management and resource allocation, which reduced patient waiting times by 18–26% and achieving high predictive accuracy. Machine learning algorithms applied to operating room scheduling reduced idle time and improved resource utilization. Ambient and generative AI documentation tools were associated with reduced administrative workload and reduced clinician burnout. Evidence for revenue cycle management, conversational AI, logistics, and supply chain optimization was mainly based on model-development studies, reviews, or limited implementation reports. Several large-scale BRICS-related implementation studies came from Russia, while evidence from other BRICS healthcare systems was less consistently represented. Major barriers included fragmented infrastructure, limited interoperability, workforce gaps, and governance challenges.

Conclusion. AI may improve selected organizational processes, but long- term economic effectiveness, scalability, sustainability, and reproducibility require further evaluation in diverse healthcare settings.

Mathematical modeling methods and new approaches to evaluating drug properties and selecting delivery devices may reduce resource expenditure and improve the quality and speed of research.

Aim. To examine the dispersion of chitosan aerogel microparticles when administered into the nasal cavity using mathematical and computer modeling.

Materials and methods. A virtual geometry of the nasal airways was modeled from computed tomography data processed in a 3D Slicer. The mathematical model that is used to analyze the dry microparticles spraying and movement was based on the mechanics of continuous and heterogeneous media and implemented using computational fluid dynamics. Calculations were performed in The ANSYS Fluent 17.0. Chitosan aerogel microparticles was chosen as the study object.

Results. A virtual geometry of the nasal cavity was developed. Airflow hydrodynamics was studied to identify stagnation zones. Computational experiments were conducted on spraying dry chitosan aerogel microparticles from a dosing device. Agreement between the experimental and calculated data was shown. Airflow hydrodynamics with suspended chitosan aerogel microparticles was studied to determine the deposition zones in the nasal cavity. The optimal parameters for achieving the maximum proportion of microparticles (14.67%) deposited in the upper nasal cavity: the spray angle of the dosing device was 5°; the initial velocity was 6.95 m/s; the average diameter was 100 µm.

Conclusion. This study proposes an approach for modeling the dispersion, movement, and deposition of dry microparticles in the nasal cavity, enabling the selection of dosing device characteristics and optimization of drug formulations. This method may facilitate initial evaluation of samples to accelerate and improve the efficiency of pharmaceutical development.

The objective of this study was to provide a comprehensive overview of the CAR-T (chimeric antigen receptor T-cells) therapy landscape in Russia, including the types of products used, their target antigens, indications, the role of CAR-T therapy in treatment pathways, clinical trials, marketing authorization, and production infrastructure data. A key feature of the Russian landscape is the emergence of a hybrid ecosystem in which academically developed products coexist with the first industrial CAR-T products. Monospecific constructs targeting cluster of differentiation (CD) 19 are the most common. Bispecific and polyspecific CAR-T variants are also being developed. This technology has been used for the treatment of nine lymphoproliferative diseases. In the vast majority of cases, CAR-T therapy was used as a salvage therapy in later stages of treatment. The expected number of patients in clinical trials exceeds 200. One commercial CAR-T product has been approved, and another is in the final stages of research and obtaining marketing authorization. The number of licensed organizations with CAR-T production infrastructure is growing. Currently, five organizations hold authorizations for the production and use of individual biomedical cell products, and five hold licenses for the manufacture of gene therapy biological medicinal products. Further development of this technology will depend on how successfully key challenges are addressed, including production scale-up, patient routing, payment models, and the systematic collection of real-world clinical data. For BRICS countries, the Russian experience may be considered one example of how complex and high-cost cell therapy can be introduced into a national healthcare system. International cooperation on regulatory and funding issues, as well as joint clinical trials of industrial CAR-T technologies, could accelerate the development of this field in the BRICS countries.