Design, Synthesis, and Cytotoxic Assessment of New Haloperidol Analogues as Potential Anticancer Compounds Targeting Sigma Receptors.

Sigma receptors (SRs), including SR1 and SR2 subtypes, have attracted increasing interest in recent years due to their involvement in a wide range of activities, including the modulation of opioid analgesia, neuroprotection, and potential anticancer activity. In this context, haloperidol (HAL), a commonly used antipsychotic drug, also possesses SR activity and cytotoxic effects. Herein, we describe the identification of novel SR ligands, obtained by a chemical hybridization approach. There wereendowed with pan-affinity for both SR subtypes and evaluated their potential anticancer activity against SH-SY5Y and HUH-7 cancer cell lines. Through a chemical hybridization approach, we identified novel compounds (4d, 4e, 4g, and 4j) with dual affinity for SR1 and SR2 receptors. These compounds were subjected to cytotoxicity testing using a resazurin assay. The results revealed potent cytotoxic effects against both cancer cell lines, with IC50 values comparable to HAL. Interestingly, the cytotoxic potency of the novel compounds resembled that of the SR1 antagonist HAL rather than the SR2 agonist siramesine (SRM), indicating the potential role of SR1 antagonism in their mechanism of action. The further exploration of their structure-activity relationships and their evaluation in additional cancer cell lines will elucidate their therapeutic potential and may pave the way for the development of novel anticancer agents that target SRs.

Design, synthesis and anti-inflammatory assessment of certain substituted 1,2,4-triazoles bearing tetrahydroisoquinoline scaffold as COX 1/2-inhibitors.

Aiming to discover effective and safe non-steroidal anti-inflammatory agents, a new set of 1,2,4-triazole tetrahydroisoquinoline hybrids 9a-g, 11a-g and 12a-g was synthesized and evaluated as inhibitors of COX-1 and COX-2. In order to overcome the adverse effects of highly selective COX-2 and non-selective COX-2 inhibitors, the compounds of this study were designed with the goal of obtaining moderately selective COX-2 inhibitors. In this study compounds 9e, 9g and 11f are the most effective derivatives against COX-2 with IC50 values 0.87, 1.27 and 0.58 µM, respectively which are better than or comparable to the standard drug celecoxib (IC50 = 0.82 µM) but with lower selectivity indices as required by our goal design. The results of the in vivo anti-inflammatory inhibition test revealed that compounds 9e, 9g and 11f displayed a higher significant anti-inflammatory activity than celecoxib at all-time intervals. In addition, these compounds significantly decreased the production of inflammatory mediators PGE-2, TNF-ɑ and IL-6. Compounds 9e, 9g and 11f had a safe gastric profile compared to indomethacin, also compound 11f (ulcerogenic index = 1.33) was less ulcerous than the safe celecoxib (ulcerogenic index = 3). Moreover, histopathological investigations revealed a normal architecture of both paw skin and gastric mucosa after oral treatment of rats with compound 11f. Furthermore, molecular docking studies were performed on COX-1 and COX-2 to study the binding pattern of compounds 9e, 9g and 11f on both isoenzymes.

Designing Antitrypanosomal and Antileishmanial BODIPY Derivatives: A Computational and In Vitro Assessment.

Leishmaniasis and Human African trypanosomiasis pose significant public health threats in resource-limited regions, accentuated by the drawbacks of the current antiprotozoal treatments and the lack of approved vaccines. Considering the demand for novel therapeutic drugs, a series of BODIPY derivatives with several functionalizations at the meso, 2 and/or 6 positions of the core were synthesized and characterized. The in vitro activity against Trypanosoma brucei and Leishmania major parasites was carried out alongside a human healthy cell line (MRC-5) to establish selectivity indices (SIs). Notably, the meso-substituted BODIPY, with 1-dimethylaminonaphthalene (1b) and anthracene moiety (1c), were the most active against L. major, displaying IC50 = 4.84 and 5.41 µM, with a 16 and 18-fold selectivity over MRC-5 cells, respectively. In contrast, the mono-formylated analogues 2b and 2c exhibited the highest toxicity (IC50 = 2.84 and 6.17 µM, respectively) and selectivity (SI = 24 and 11, respectively) against T. brucei. Further insights on the activity of these compounds were gathered from molecular docking studies. The results suggest that these BODIPYs act as competitive inhibitors targeting the NADPH/NADP+ linkage site of the pteridine reductase (PR) enzyme. Additionally, these findings unveil a range of quasi-degenerate binding complexes formed between the PRs and the investigated BODIPY derivatives. These results suggest a potential correlation between the anti-parasitic activity and the presence of multiple configurations that block the same site of the enzyme.

Thiadiazole/Thiadiazine Derivatives as Insecticidal Agent: Design, Synthesis, and Biological Assessment of 1,3,4-(Thiadiazine/Thiadiazole)-Benzenesulfonamide Derivatives as IGRs Analogues against Spodoptera littoralis.

In keeping with our investigation, a simple and practical synthesis of novel heterocyclic compounds with a sulfamoyl moiety that can be employed as insecticidal agents was reported. The compound 2-hydrazinyl-N-(4-sulfamoylphenyl)-2-thioxoacetamide 1 was coupled smoothly with triethylorthoformate or a variety of halo compounds, namely phenacyl chloride, chloroacetyl chloride, chloroacetaldehyde, chloroacetone, 1,3-dichloropropane, 1,2-dichloroethane, ethyl chloroformate, 2,3-dichloro-1,4-naphthoquinone, and chloroanil respectively, which afforded the 1,3,4-thiadiazole and 1,3,4-thiadiazine derivatives. The new products structure was determined using elemental and spectral analysis. Under laboratory conditions, the biological and toxicological effects of the synthetic compounds were also evaluated as insecticides against Spodoptera littoralis (Boisd.). Compounds 3 and 5 had LC50 values of 6.42 and 6.90 mg/L, respectively. The investigated compounds (from 2 to 11) had been undergoing molecular docking investigation for prediction of the optimal arrangement and strength of binding between the ligand (herein, the investigated compounds (from 2 to 11)) and a receptor (herein, the 2CH5) molecule. The binding affinity within docking score (S, kcal/mol) ranged between -8.23 (for compound 5), -8.12 (for compound 3) and -8.03 (for compound 9) to -6.01 (for compound 8). These compounds were shown to have a variety of binding interactions within the 2CH5 active site, as evidenced by protein-ligand docking configurations. This study gives evidence that those compounds have 2CH5-inhibitory capabilities and hence may be used for 2CH5-targeting development. Furthermore, the three top-ranked compounds (5, 3, and 9) and the standard buprofezin were subjected to density functional theory (DFT) analysis. The highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) energy difference (ΔE) of compounds 5, 3, and 9 was found to be comparable to that of buprofezin. These findings highlighted the potential and relevance of charge transfer at the molecular level.

Assessment of Nucleobase Protomeric and Tautomeric States in Nucleic Acid Structures for Interaction Analysis and Structure-Based Ligand Design.

With increasing interest in RNA as a therapeutic and a potential target, the role of RNA structures has become more important. Even slight changes in nucleobases, such as modifications or protomeric and tautomeric states, can have a large impact on RNA structure and function, while local environments in turn affect protonation and tautomerization. In this work, the application of empirical tools for pKa and tautomer prediction for RNA modifications was elucidated and compared with ab initio quantum mechanics (QM) methods and expanded toward macromolecular RNA structures, where QM is no longer feasible. In this regard, the Protonate3D functionality within the molecular operating environment (MOE) was expanded for nucleobase protomer and tautomer predictions and applied to reported examples of altered protonation states depending on the local environment. Overall, observations of nonstandard protomers and tautomers were well reproduced, including structural C+G:C(A) and A+GG motifs, several mismatches, and protonation of adenosine or cytidine as the general acid in nucleolytic ribozymes. Special cases, such as cobalt hexamine-soaked complexes or the deprotonation of guanosine as the general base in nucleolytic ribozymes, proved to be challenging. The collected set of examples shall serve as a starting point for the development of further RNA protonation prediction tools, while the presented Protonate3D implementation already delivers reasonable protonation predictions for RNA and DNA macromolecules. For cases where higher accuracy is needed, like following catalytic pathways of ribozymes, incorporation of QM-based methods can build upon the Protonate3D-generated starting structures. Likewise, this protonation prediction can be used for structure-based RNA-ligand design approaches.

In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives.

Eight QSAR models (M1-M8) were developed from a dataset of 118 benzo-fused heteronuclear derivatives targeting VEGFR-2 by Monte Carlo optimization method of CORALSEA 2023 software. Models were generated with hybrid optimal descriptors using both SMILES and Graphs with zero- and first-order Morgan extended connectivity index from a training set of 103 derivatives. All statistical parameters for model validation were within the prescribed limits, establishing the models to be robust and of excellent quality. Among all models, split-2 of M5 was the best-fit as reflected by rvalidation2, Qvalidation2 and MAE. Mechanistic interpretation of this model assisted the identification of structural descriptors as promoters and hinderers for VEGFR-2 inhibition. These descriptors were utilized to design novel VEGFR-2 inhibitors (YS01-YS07) by bringing modifications in compound MS90 in the dataset. Docking of all designed compounds, MS90 and sorafenib with VEGFR-2 binding site revealed favourable binding interactions. Docking score of YS07 was higher than that of MS90 and sorafenib. Molecular dynamics simulation study revealed sustained interactions of YS07 with key amino acids of VEGFR-2 at a run time of 100 ns. This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.

Optimization of benzenesulfonyl derivatives as anti-Trypanosomatidae agents: Structural design, synthesis, and pharmacological assessment against Trypanosoma cruzi and Leishmania infantum.

Leishmaniasis and Chagas disease are neglected tropical diseases caused by Trypanosomatidae parasites. Given the numerous limitations associated with current treatments, such as extended treatment duration, variable efficacy, and severe side effects, there is an urgent imperative to explore novel therapeutic options. This study details the early stages of hit-to-lead optimization for a benzenesulfonyl derivative, denoted as initial hit, against Trypanossoma cruzi (T. cruzi), Leishmania infantum (L. infantum) and Leishmania braziliensis (L. braziliensis). We investigated structure - activity relationships using a series of 26 newly designed derivatives, ultimately yielding potential lead candidates with potent low-micromolar and sub-micromolar activities against T. cruzi and Leishmania spp, respectively, and low in vitro cytotoxicity against mammalian cells. These discoveries emphasize the significant promise of this chemical class in the fight against Chagas disease and leishmaniasis.

Pharmaceutical and biotech industry perspectives on optimizing patient experience and treatment adherence through subcutaneous drug delivery design.

Subcutaneous (SC) drug delivery can be a safe, effective alternative to the traditional intravenous route of administration, potentially offering notable advantages for both patients and healthcare providers. The SC Drug Development & Delivery Consortium convened in 2018 to raise awareness of industry challenges to advance the development of patient-centric SC drug delivery strategies. The SC Consortium identified better understanding of patient preferences and perspectives as necessary to optimize SC product design attributes and help guide design decisions during SC product development. This manuscript provides a comprehensive overview of patient-centric factors for consideration in the SC drug delivery design and development process with the aim of establishing a foundation of existing knowledge for patient experiences related to SC drug delivery. This overview is informed by the outcomes of a multi-step survey of Consortium members and key pharmaceutical stakeholders. Framed in the context of the patient's treatment journey, the survey findings offer future perspectives to fill data gaps to advance patient-centric SC drug delivery.

A high-throughput target-based screening approach for the identification and assessment of Mycobacterium tuberculosis mycothione reductase inhibitors.

The World Health Organization's goal to combat tuberculosis (TB) is hindered by the emergence of anti-microbial resistance, therefore necessitating the exploration of new drug targets. Multidrug regimens are indispensable in TB therapy as they provide synergetic bactericidal effects, shorten treatment duration, and reduce the risk of resistance development. The research within our European RespiriTB consortium explores Mycobacterium tuberculosis energy metabolism to identify new drug candidates that synergize with bedaquiline, with the aim of discovering more efficient combination drug regimens. In this study, we describe the development and validation of a luminescence-coupled, target-based assay for the identification of novel compounds inhibiting Mycobacterium tuberculosis mycothione reductase (MtrMtb), an enzyme with a role in the protection against oxidative stress. Recombinant MtrMtb was employed for the development of a highly sensitive, robust high-throughput screening (HTS) assay by coupling enzyme activity to a bioluminescent readout. Its application in a semi-automated setting resulted in the screening of a diverse library of ~130,000 compounds, from which 19 hits were retained after an assessment of their potency, selectivity, and specificity. The selected hits formed two clusters and four fragment molecules, which were further evaluated in whole-cell and intracellular infection assays. The established HTS discovery pipeline offers an opportunity to deliver novel MtrMtb inhibitors and lays the foundation for future efforts in developing robust biochemical assays for the identification and triaging of inhibitors from high-throughput library screens. IMPORTANCE: The growing anti-microbial resistance poses a global public health threat, impeding progress toward eradicating tuberculosis. Despite decades of active research, there is still a dire need for the discovery of drugs with novel modes of action and exploration of combination drug regimens. Within the European RespiriTB consortium, we explore Mycobacterium tuberculosis energy metabolism to identify new drug candidates that synergize with bedaquiline, with the aim of discovering more efficient combination drug regimens. In this study, we present the development of a high-throughput screening pipeline that led to the identification of M. tuberculosis mycothione reductase inhibitors.

An Assessment of Dispersion-Corrected DFT Methods for Modeling Nonbonded Interactions in Protein Kinase Inhibitor Complexes.

Accurate modeling of nonbonded interactions between protein kinases and their small molecule inhibitors is essential for structure-based drug design. Quantum chemical methods such as density functional theory (DFT) hold significant promise for quantifying the strengths of these key protein-ligand interactions. However, the accuracy of DFT methods can vary substantially depending on the choice of exchange-correlation functionals and associated basis sets. In this study, a comprehensive benchmarking of nine widely used DFT methods was carried out to identify an optimal approach for quantitative modeling of nonbonded interactions, balancing both accuracy and computational efficiency. From a database of 2139 kinase-inhibitor crystal structures, a diverse library of 49 nonbonded interaction motifs was extracted, encompassing CH-π, π-π stacking, cation-π, hydrogen bonding, and salt bridge interactions. The strengths of nonbonded interaction energies for all 49 motifs were calculated at the advanced CCSD(T)/CBS level of theory, which serve as references for a systematic benchmarking of BLYP, TPSS, B97, ωB97X, B3LYP, M062X, PW6B95, B2PLYP, and PWPB95 functionals with D3BJ dispersion correction alongside def2-SVP, def2-TZVP, and def2-QZVP basis sets. The RI, RIJK, and RIJCOSX approximations were used for selected functionals. It was found that the B3LYP/def2-TZVP and RIJK RI-B2PLYP/def2-QZVP methods delivered the best combination of accuracy and computational efficiency, making them well-suited for efficient modeling of nonbonded interactions responsible for molecular recognition of protein kinase inhibitors in their targets.

Designing greener active pharmaceutical ingredients: Insights from pharmaceutical industry into drug discovery and development.

Active pharmaceutical ingredients (APIs), their metabolites and transformation products (TPs) are found as pollutants in the environment. They can impact human and environmental health. To address this issue, an efficient, long-term prevention strategy could be the design of APIs that have less impact on the natural environment, i.e. the design of greener APIs, by the implementation of environmental parameters into the drug discovery and development process (also abbreviated R&D for 'research and development'). Our study aimed to evaluate the feasibility of the design of greener APIs based on insights from drug design experts working in large, research-based pharmaceutical companies. The feasibility evaluation also identified needs and incentives for process modification. For this purpose, 30 R&D and environmental experts from seven globally active pharmaceutical companies were interviewed along a structured questionnaire. Main findings are that the interviewed experts saw manifold opportunities to include properties rendering APIs greener in different stages along the R&D process. This implementation would be favoured by the fact that the pharmaceutical R&D process is very flexible and relies on balancing multiple parameters. Furthermore, some API properties that reduce environmental risks were considered compatible with common desirable properties for application. Environmental properties should be considered early during R&D, i.e. when molecules are screened and optimized. It has been found that availability of suitable in silico models and in vitro assays is crucial for this environmental consideration. Their attributes, e.g. throughput and costs, determine at which process stage they can be successfully applied. An intensified exchange between R&D and environmental experts within and outside companies would push the industrial application of the benign by design approach for APIs forward. Collaboration across pharmaceutical companies, authorities, and academia is seen as highly promising in this respect. Financial, social, and regulatory incentives would support future design of greener APIs.

Molecular medicinal insights into scaffold hopping-based drug discovery success.

In both academia and the pharmaceutical industry, innovative hypotheses, methodologies and technologies that can shorten the drug research and development, leading to higher success rates, are vital. In this review, we demonstrate how innovative variations of the scaffold-hopping strategy have been used to create new druggable molecular spaces, drugs, clinical candidates, preclinical candidates, and bioactive agents. We also analyze molecular modulations that enabled improvements of the pharmacodynamic (PD), physiochemical, and pharmacokinetic (PK) properties (P3 properties) of the drugs resulting from these scaffold-hopping strategies.

Medication adherence and pharmaceutical design strategies for pediatric patients: An overview.

Medication adherence in pediatric patients is a key factor in drug development and dosage form design. High medication adherence is not only important to achieve the expected treatment effects but can also effectively reduce medical costs. It is an ongoing task to accurately identify differences in medication adherence between children and adults and analyze the factors related to pediatric medication adherence. This is necessary to guide the development of pediatric drugs. This review focuses on factors that influence pediatric medication adherence as well as pharmaceutical design strategies to improve adherence. Current new dosage forms, new technologies, and new devices are comprehensively summarized in terms of their advantages and limitations.

Drug design education in China.

With the emergence of innovative technologies, including combinatorial chemistry, high-throughput screening, computer-aided drug design (CADD), artificial intelligence (AI) and big data, the importance of drug design in the field of drug discovery and development is increasing. Additionally, education in drug design plays an important role in the training of pharmaceutical talent. Starting with undergraduates, cultivating pharmaceutical design thinking, developing innovation and creativity, and establishing an interdisciplinary knowledge system will not only provide students with a solid knowledge basis but also promote the development of the pharmaceutical industry in China. This article presents the current status of pharmaceutical education and the distribution of drug design courses in China and summarizes the employment prospects of graduates, thus providing valuable references and evidence for global pharmaceutical design education.

High-Quality Conformer Generation with CONFORGE: Algorithm and Performance Assessment.

Knowledge of the putative bound-state conformation of a molecule is an essential prerequisite for the successful application of many computer-aided drug design methods that aim to assess or predict its capability to bind to a particular target receptor. An established approach to predict bioactive conformers in the absence of receptor structure information is to sample the low-energy conformational space of the investigated molecules and derive representative conformer ensembles that can be expected to comprise members closely resembling possible bound-state ligand conformations. The high relevance of such conformer generation functionality led to the development of a wide panel of dedicated commercial and open-source software tools throughout the last decades. Several published benchmarking studies have shown that open-source tools usually lag behind their commercial competitors in many key aspects. In this work, we introduce the open-source conformer ensemble generator CONFORGE, which aims at delivering state-of-the-art performance for all types of organic molecules in drug-like chemical space. The ability of CONFORGE and several well-known commercial and open-source conformer ensemble generators to reproduce experimental 3D structures as well as their computational efficiency and robustness has been assessed thoroughly for both typical drug-like molecules and macrocyclic structures. For small molecules, CONFORGE clearly outperformed all other tested open-source conformer generators and performed at least equally well as the evaluated commercial generators in terms of both processing speed and accuracy. In the case of macrocyclic structures, CONFORGE achieved the best average accuracy among all benchmarked generators, with RDKit's generator coming close in second place.

Revolutionizing Pharmaceutical Industry: The Radical Impact of Artificial Intelligence and Machine Learning.

This article explores the significant impact of artificial intelligence (AI) and machine learning (ML) on the pharmaceutical industry, which has transformed the drug development process. AI and ML technologies provide powerful tools for analysis, decision-making, and prediction by simplifying complex procedures from drug design to formulation design. These techniques could potentially speed up the development of better medications and drug development processes, improving the lives of millions of people. However, the use of these techniques requires trained personnel and human surveillance for AI to function effectively, if not there is a possibility of errors like security breaches of personal data and bias can also occur. Thus, the present review article discusses the transformative power of AI and ML in the pharmaceutical industry and provides insights into the future of drug development and patient care.

A Method for the In Vitro Cytotoxicity Assessment of Anti-cancer Compounds and Materials Using High Content Screening Analysis.

To date, there is a large bottleneck associated with cancer drug design and development: a lack of appropriate methodologies for screening their potential toxicity. This issue not only causes a high attrition rate for these compounds but also slows down the drug discovery process in general. To overcome this problem, robust, accurate, and reproducible methodologies for assessing anti-cancer compounds are essential. Multiparametric technique and high-throughput analysis, in particular, are favored due to the time- and cost-effective way in which they assess large panels of materials, and due to their large informational output. Following extensive work within our group, we have developed a protocol for assessing the toxicity of anti-cancer compounds using a high-content screening and analysis (HCSA) platform, which is both time-effective and reproducible.

De-Novo Design of pre-miR-21 Maturation Inhibitors: Synthesis and Activity Assessment.

Targeting RNA with small molecules is a major challenge of current medicinal chemistry, and the identification and design of original scaffolds able to selectively interact with an RNA target remains difficult. Various approaches have been developed based on classical medicinal chemistry strategies (fragment-based drug design, dynamic combinatorial chemistry, HTS or DNA-encoded libraries) as well as on advanced structural biology and biochemistry methodologies (such as X-ray, cryo-EM, NMR, or SHAPE). Here, we report the de novo design, synthesis, and biological evaluation of RNA ligands by using a straightforward and sustainable chemistry combined with molecular docking and biochemical and biophysical studies that allowed us to identify a novel pharmacophore for RNA binding. Specifically, we focused on targeting the biogenesis of microRNA-21, the well-known oncogene. This led us not only to promising inhibitors but also to a better understanding of the interactions between the small-molecule compounds and the RNA target paving the way for the rational design of efficient inhibitors with potential anticancer activity.

De novo drug design by iterative multiobjective deep reinforcement learning with graph-based molecular quality assessment.

MOTIVATION: Generating molecules of high quality and drug-likeness in the vast chemical space is a big challenge in the drug discovery. Most existing molecule generative methods focus on diversity and novelty of molecules, but ignoring drug potentials of the generated molecules during the generation process. RESULTS: In this study, we present a novel de novo multiobjective quality assessment-based drug design approach (QADD), which integrates an iterative refinement framework with a novel graph-based molecular quality assessment model on drug potentials. QADD designs a multiobjective deep reinforcement learning pipeline to generate molecules with multiple desired properties iteratively, where a graph neural network-based model for accurate molecular quality assessment on drug potentials is introduced to guide molecule generation. Experimental results show that QADD can jointly optimize multiple molecular properties with a promising performance and the quality assessment module is capable of guiding the generated molecules with high drug potentials. Furthermore, applying QADD to generate novel molecules binding to a biological target protein DRD2 also demonstrates the algorithm's efficacy. AVAILABILITY AND IMPLEMENTATION: QADD is freely available online for academic use at https://github.com/yifang000/QADD or http://www.csbio.sjtu.edu.cn/bioinf/QADD.

Políticas públicas de medicamentos e a relação de medicamentos essenciais / Public policies on medicines and the list of essential medicines / Las políticas públicas sobre medicamentos y la lista de medicamentos esenciales

Através da edição da Norma Operacional de Assistência à Saúde realizada em 2001 e da publicação do Pacto pela Saúde realizado em 2006 o processo de acesso à saúde, ganhou maior ênfase no quesito de inovações e melhorias do sistema de saúde. A assistência farmacêutica sobreveio como parte fundamental nos serviços e programas de saúde. Neste sentido, o objetivo do presente estudo foi de expor as principais políticas públicas acerca da temática de medicamentos essenciais. Para tanto, foi realizada uma revisão integrativa de literatura, tendo como base de dados o Ministério da Saúde, as Resoluções da Agência Nacional de Vigilância Sanitária, artigos científicos e as publicações da Relação Nacional de Medicamentos (RENAME). No ano de 1998 através da portaria nº 3.916, de 30 de outubro 1998, apresenta-se a população a terminologia de Políticas públicas e, como resposta às diretrizes resultantes desta política, no presente artigo teremos ênfase na RENAME, criada através da portaria nº 3.047, de 28 de novembro de 2019, a qual atende aos princípios básicos e fundamentais do Sistema Único de Saúde: universalidade, equidade e a integralidade, para atender aos tratamentos das diversas doenças e agravos que acometem a população brasileira. Sendo assim, conclui- se que não se trata apenas de políticas públicas, e sim de manter o direito do cidadão estabelecidos pela Constituição da República Federativa do Brasil, para que o paciente consiga adquirir a medicação adequada e na quantidade necessária, permitindo aos profissionais alcançar mais aproveitamento no gerenciamento do ciclo da assistência farmacêutica.

Through the edition of the Operational Norm for Health Care carried out in 2001 and the publication of the Pact for Health carried out in 2006, the process of access to health gained greater emphasis on the issue of innovations and improvements in the health system. Pharmaceutical assistance emerged as a fundamental part of health services and programs. In this sense, the objective of the present study was to expose the main public policies on the subject of essential medicines. Therefore, an integrative literature review was carried out, using the Ministry of Health, the National Health Surveillance Agency's Resolutions, scientific articles and the publications of the National Medicines List (RENAME) as a database. In 1998, through ordinance nº 3.916, of October 30, 1998, the public policy terminology is presented to the population and, in response to the guidelines resulting from this policy, in this article we will emphasize RENAME, created through ordinance nº 3.047 , of November 28, 2019, which meets the basic and fundamental principles of the Unified Health System: universality, equity and integrality, to meet the treatments of the various diseases and conditions that affect the Brazilian population. Therefore, it is concluded that it is not just about public policies, but about maintaining the right of the citizen established by the Constitution of the Federative Republic of Brazil, so that the patient can acquire the appropriate medication and in the necessary quantity, allowing professionals to achieve more use in the management of the pharmaceutical care cycle.

A través de la edición de la Norma Operativa de Atención a la Salud realizada en 2001 y de la publicación del Pacto por la Salud realizada en 2006, el proceso de acceso a la salud ganó mayor énfasis en el tema de innovaciones y mejoras en el sistema de salud. La asistencia farmacéutica surgió como parte fundamental de los servicios y programas de salud. En este sentido, el objetivo del presente estudio fue exponer las principales políticas públicas sobre el tema de los medicamentos esenciales. Para ello, se realizó una revisión bibliográfica integradora, utilizando como base de datos el Ministerio de Salud, las Resoluciones de la Agencia Nacional de Vigilancia Sanitaria, artículos científicos y las publicaciones de la Lista Nacional de Medicamentos (RENAME). En 1998, a través de la ordenanza nº 3.916, de 30 de octubre de 1998, se presenta a la población la política pública de terminología y, en respuesta a las directrices resultantes de esta política, en este artículo haremos hincapié en el RENAME, creado a través de la ordenanza nº 3.047, de 28 de noviembre de 2019, que cumple con los principios básicos y fundamentales del Sistema Único de Salud: universalidad, equidad e integralidad, para atender los tratamientos de las diversas enfermedades y afecciones que afectan a la población brasileña. Por lo tanto, se concluye que no se trata sólo de políticas públicas, sino de mantener el derecho del ciudadano establecido por la Constitución de la República Federativa de Brasil, para que el paciente pueda adquirir el medicamento adecuado y en la cantidad necesaria, permitiendo que los profesionales logren un mayor aprovechamiento en la gestión del ciclo de atención farmacéutica.