Physicochemical Properties Of Drug Research Articles

Magnetic/Acoustic Dual-Controlled Microrobot Overcoming Oto-Biological Barrier for On-Demand Multidrug Delivery against Hearing Loss.

Multidrug combination therapy in the inner ear faces diverse challenges due to the distinct physicochemical properties of drugs and the difficulties of overcoming the oto-biologic barrier. Although nanomedicine platforms offer potential solutions to multidrug delivery, the access of drugs to the inner ear remains limited. Micro/nanomachines, capable of delivering cargo actively, are promising tools for overcoming bio-barriers. Herein, a novel microrobot-based strategy to penetrate the round window membrane (RWM) is presented and multidrug in on-demand manner is delivered. The tube-type microrobot (TTMR) is constructed using the template-assisted layer-by-layer (LbL) assembly of chitosan/ferroferric oxide/silicon dioxide (CS/Fe3O4/SiO2) and loaded with anti-ototoxic drugs (curcumin, CUR and tanshinone IIA, TSA) and perfluorohexane (PFH). Fe3O4 provides magnetic actuation, while PFH ensures acoustic propulsion. Upon ultrasound stimulation, the vaporization of PFH enables a microshotgun-like behavior, propelling the drugs through barriers and driving them into the inner ear. Notably, the proportion of drugs entering the inner ear can be precisely controlled by varying the feeding ratios. Furthermore, in vivo studies demonstrate that the drug-loaded microrobot exhibits superior protective effects and excellent biosafety toward cisplatin (CDDP)-induced hearing loss. Overall, the microrobot-based strategy provides a promising direction for on-demand multidrug delivery for ear diseases.

A literature review of drug transport mechanisms during lactation.

Despite the benefits of breastfeeding, lactating mothers who take prescribed medications may discontinue breastfeeding due to concerns associated with infant drug exposure in breastmilk. Consolidating the current knowledge of drug transport to breastmilk may inform understanding of the safety of medication use during lactation. This literature review summarizes the mechanisms of drug transport to breastmilk, details the physicochemical drug properties that may alter the extent of passive transport, and describes the expressional changes in mammary drug transporters that may affect active transport. During the period of 20 July 2023 to 11 August 2023, PubMed® was searched to identify journal articles pertinent to the mechanisms of drug transport from maternal plasma to breastmilk and the expression of mammary drug transporters during lactation. From the 28 studies included in this review, four mechanisms were identified for transporting drugs from maternal plasma to breastmilk: passive transport, active transport, lipid co-transport, and transcytosis. The lactational expression of 20 drug transporters was further summarized, with 9 transporters demonstrating downregulated expression during lactation and 11 transporters demonstrating upregulated expression during lactation. Understanding the mechanisms of drug transport to breastmilk may aid in estimating infant drug exposure, developing physiologically based pharmacokinetic (PBPK) models that describe drug transfer, and initiating clinical drug development programs in the lactating population.

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians.

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

Hot Melt Extrusion Technique for Developing Pharmaceutical Co-crystals: A Review

Background: In the era of pharmaceutical research and development, the most challenging aspect is to enhance the physicochemical properties of drugs. Hot Melt Extrusion (HME) is a solvent-free, one-step, continuous, scalable, and industrially feasible method for developing pharmaceutical co-crystals. Co-crystallization, as a technique, has gained significant attention for its potential to modify various physicochemical properties of drugs like solubility, stability, compressibility, permeability, taste masking, and therapeutic efficacy Methods: We determine the characteristic features of HME and explore published literature using the keywords, HME, co-crystals, and PAT, in databases, such as PubMed, Google Scholar, ScienceDirect, and Research Gate. Result: The present review embarks on a detailed journey through the multifaceted domain of HME and its pivotal role in co-crystal development. The process parameters, such as temperature, extruder type, screw configuration, screw speed, and feed rate, are involved in determining the characteristics of the co-crystals produced. Additionally, the review explores the role of materials, including Active Pharmaceutical Ingredients (APIs), plasticizers, polymers, and other pharmaceutical aids, underlining their impact on co-crystal development. The existing literature on HME and its application for pharmaceutical co-crystal production is comprehensively surveyed. Conclusion: The review highlights the utility of Process Analytical Technology (PAT) in real-time process control. The role of HME in the future of pharmaceutical co-crystal development is discussed, making this review essential for researchers and industry professionals alike.

On topological indices and QSPR analysis of some drugs used for treating Coronavirus patients

A topological index is a real number obtained from the molecular graph structure. It can predict the physicochemical and biological properties of many anticoronavirus drugs. In this article, the topological index of some drugs for the treatment of coronavirus was computed using the Wiener-Hosoya eigenvalues of the molecular structure of hydroxychloroquine, chloroquine, camostat, nafamostat, remdesivir, and lopinavir compounds, and the Quantitative Structure Property Relationship (QSPR) study of some properties: Boiling point, Molar weight, Flash point and Enthalpy were investigated. It was observed that the regression model value r is more than 0.6 and p value shows less than 0.05.

Estimating physico-chemical properties of drugs for prostate cancer using degree-based and neighbourhood degree-based topological descriptors

Prostate cancer is one of the most alarming diseases among men and leads to various illnesses. The main flaw in this disease is that there is not a single test that can find it. Prostate-specific antigens and prostate biopsies are used to identify this type of cancer. Many pharmaceutical industries do active research to identify non-steroidal drugs that can be used to treat prostate cancer effectively. QSPR analysis is one of the best practices that aid scientists in getting a deep insight into the physico-chemical properties of drugs without actually performing experiments in a wet lab, thereby cutting down on the cost of manufacturing such drugs. In this article, we perform a QSPR analysis of nineteen drugs primarily used to treat prostate cancer by using a set of ten degree-based indices and another set of ten novel neighbourhood-degree-based indices. In addition, we have done a comparative study of the findings obtained through these two different sets of indices over thirteen physico-chemical properties of prostate cancer drugs.

A micro-fabricated potentiometric platform with application in a COVID-19 drug quantification and the determination of its binding affinity to a supramolecular host

Recent applications in host–guest chemistry include advanced sensing technologies, drug formulations, and drug delivery. Quantification of host–guest binding constants is significant to the continued optimization of their use. Binding constants offer valuable information about the stability and affinity of the formedcomplex that is essential to both drug formulations and delivery. In this study a novel green, portable, disposable, and cost-efficient microfabricated potentiometric sensor is introduced and successfully applied to determine the concentration of remdesivir (RMD), a COVID-19 drug, and its binding affinity to the supramolecular host sulfobutylether-β-cyclodextrin (SBEβCD) as a compatible solubilizing agent; to overcome the low water solubility of RMD which presents a significant challenge in its intravenous administration. The sensor incorporates multi-walled carbon nanotubes to improve stability and detection limits. To reduce interference effects and enhance the selectivity of the sensor for RMD, 4-tert-butyl-calix[8]arene was employed as an ionophore. A Nernstian potentiometric response for RMD over a concentration range of 1.0 × 10−3 to 1.0 × 10−6 M with a slope of 58.2 ± 0.9 mV decade−1 and a detection limit of 0.23 µM were achieved. The binding constant of the RMD-SBEβCD complex was determined to be 9.76 × 103 M−1. The proposed sensor was shown to be effective for drug quantification and measurements of binding affinities, providing valuable insights into the physicochemical properties of target drugs.

Multicriteria decision making attributes and estimation of physicochemical properties of kidney cancer drugs via topological descriptors.

Based on topological descriptors, QSPR analysis is an incredibly helpful statistical method for examining many physical and chemical properties of compounds without demanding costly and time-consuming laboratory tests. Firstly, we discuss and provide research on kidney cancer drugs using topological indices and done partition of the edges of kidney cancer drugs which are based on the degree. Secondly, we examine the attributes of nineteen drugs casodex, eligard, mitoxanrone, rubraca, and zoladex, etc and among others, using linear QSPR model. The study in the article not only demonstrates a good correlation between TIs and physical characteristics with the QSPR model being the most suitable for predicting complexity, enthalpy, molar refractivity, and other factors and a best-fit model is attained in this study. This theoretical approach might benefit chemists and professionals in the pharmaceutical industry to forecast the characteristics of kidney cancer therapies. This leads towards new opportunities to paved the way for drug discovery and the formation of efficient and suitable treatment options in therapeutic targeting. We also employed multicriteria decision making techniques like COPRAS and PROMETHEE-II for ranking of said disease treatment drugs and physicochemical characteristics.

Novel inhaled andrographolide for treatment of lung cancer: In vitro assessment

Andrographolide is a plant-based compound that showed promising activity against lung cancer. However, the compound's poor water solubility and low bioavailability limit its oral administration. Inhaled drug delivery of andrographolide is highly favourable as it delivers active ingredients directly into the affected lungs. In the current study, we compared in vitro aerosol performance, anti-cancer activity and storages stability of two (2) inhalable andrographolide formulations. Formulation 1 was prepared using precipitation and spray drying techniques, while Formulation 2 was prepared via direct spray drying technique. Drug morphology and physicochemical properties were confirmed using scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. In vitro aerosol dispersion profile was evaluated using the next-generation impactor (NGI). Formulation 1 consisted of elongated crystals while Formulation 2 was made up of amorphous spherical particles. Both formulations had an inhalable fraction (<5 μm) of more than 40 %, making them suitable for pulmonary drug delivery. The formulations also showed an IC25 of less than 100 μg/mL against the human lung carcinoma cells (A549). Formulation 1 and 2 was stable in a vacuum condition at 30 °C for up to 6 and 3 months, respectively. Novel inhalable andrographolide dry powders were successfully produced with a good aerosol profile, potent anti-cancer activity and adequate storage stability, which deserve further in vivo investigations.

Investigating the properties of octane isomers by novel neighborhood product degree-based topological indices

A topological index is a real number calculated from the structure of a chemical compound to describe its topology. The use of molecular descriptors has been increasing in recent years, helping to determine the physicochemical and biological properties of drugs. The main purpose of this article is to investigate the properties of the octane isomers using the theoretical method. To study the structures of octane isomers, we have introduced a new approach called “neighborhood product degree” to calculate all the classical degree-based topological indices. The np-degree approach is applied to approximate eight properties of octane isomers, such as the acentric factor, density, refractive index, critical volume, molar volume, radius of curvature, critical pressure, and LogP. The np-degree-based topological indices are the estimated values of the properties of octane structures, so the linear and quadratic regression models and correlation coefficients are applied to check the validity of the estimated results. The quantitative structure property relation are obtained by using the linear, quadratic, exponential, logarithmic and sinusoidal regression methods with the help of SPSS. Two models are applied to all the compuations and three regression models are applied to the np-degree Randic index. The computation showed that quadratic regression model is suitable for study octane isomers and np-degree based graph invariants. If the values of the correlation coefficient r ⩾ 0.7, p-values ⩽ 0.05, and F-values ⩾ 2.5, then the results are significant. The results of np-degree-based topological indices satisfy all the criteria for being significant, so these newly introduced indices are valid to study octane isomers. The information determined in this article is beneficial for chemists and pharmacists.

Probing molecular interactions of an anti-epileptic drug, sodium valproate in aqueous MgCl2 solutions

Study of the physicochemical properties of anti-epileptic drugs in the presence of cosolutes in aqueous solutions has been a subject of interest of researchers because of their interaction with biological membranes to employ their effect. Such properties provide complete information regarding solute-solute and solute-solvent type interactions. As electrolytes are essential components of biological systems, therefore the study of drug-electrolyte chemistry is important to understand the mechanism of drug action at the molecular level and hence useful in drug design and development processes. Therefore, in the current report, the density and sound velocity of an anti-epileptic drug sodium valproate (SV) in aqueous and in aqueous solutions of an electrolyte viz. MgCl2 (mB = 0.024, 0.047, 0.070 mol kg−1) at different temperatures (288.15, 298.15, 308.15, and 318.15 K) and at a pressure of 0.101 MPa were measured along with 1H NMR spectroscopy. Various volumetric and acoustical parameters such as apparent molar volume (Vφ) and isentropic compressibility (Kφ) of the solute, apparent molar volume (Vφ°) and isentropic compressibility (Kφ°) of solute at infinite dilution, apparent molar expansibility (Eφ°) and their double derivatives (∂2Vφ°/∂T2)P, transfer volumes (∆trVφ°), hydration number (nH), acoustic impedance (Z), intermolecular free length (Lf), Wada's constant (W) and Rao's constant (R) were calculated from density and sound velocity data. The variation in all these parameters with cosolute concentration indicates the existence of hydrophilic/ionic-ionic interactions at lower concentrations but hydrophobic-ionic interactions at higher concentrations of MgCl2. The 1H NMR spectroscopic results also support the existence of hydrophobic-ionic interactions at higher concentrations of MgCl2. The decrease in electrostriction but increase in hydrophobic hydration of solute molecules has also been seen with rise in temperature.

Metformin-Mediated Improvement in Solubility, Stability, and Permeability of Nonsteroidal Anti-Inflammatory Drugs.

Nonsteroidal anti-inflammatory drugs (NSAIDs) are class II biopharmaceutics classification system drugs. The poor aqueous solubility of NSAIDs can lead to limited bioavailability after oral administration. Metformin (MET), a small-molecule compound, can be used in crystal engineering to modulate the physicochemical properties of drugs and to improve the bioavailability of orally administered drugs, according to the literature research and preliminary studies. We synthesized two drug-drug molecular salts (ketoprofen-metformin and phenylbutazone-metformin) with NSAIDs and thoroughly characterized them using SCXRD, PXRD, DSC, and IR analysis to improve the poor solubility of NSAIDs. In vitro evaluation studies revealed that the thermal stability and solubility of NSAIDs-MET were substantially enhanced compared with those of NSAIDs alone. Unexpectedly, an additional increase in permeability was observed. Since the structure determines the properties, the structure was analyzed using theoretical calculations to reveal the intermolecular interactions and to explain the reason for the change in properties. The salt formation of NSAIDs with MET could substantially increase the bio-absorption rate of NSAIDs, according to the in vivo pharmacokinetic findings, which provides an experimental basis for developing new antipyretic and analgesic drugs with rapid onset of action.

Mathematical modeling of irregularity indices for adriamycin and their statistical analysis for emetic drugs

Anthracyclines exert cytotoxic effects on cancer cells through genotoxicity, inducing damage to their genetic material and impeding their reproductive capacity. The compound possesses a molecular framework consisting of an anthracycline ring system, which confers its pharmacological activity against cancer. Adriamycin is an anthracycline chemotherapeutic agent characterized by a structurally intricate chemical composition. In this article, we computed irregularity indices like the Albertson index, total irregularity index, Randić irregularity index and other degree-based irregularity indices to estimate the biological and chemical properties of Adriamycin. The findings are illustrated through the use of numerical figures and graphical representations. Further, we proposed the relationship between irregularity indices and the physicochemical properties of emetic drugs. We examined that the irregularity indices showed a statistically significant relationship with Molecular Weight, Monoisotopic Mass, Polar Surface Area, Heavy Atom Count, Complexity, Boiling Point, Enthalpy of Vaporization, Flash Point, Molar Refractivity and Polarizability based on the p-value (<0.5). We proposed multiple linear regression models that will be helpful to estimate the physical properties of those drugs that were not calculated. The numerical results and visual representations of our analyses will be helpful in the advancement of knowledge regarding the structure-property correlations of these drugs.

Combined hydroxyphenyl-modified adhesive with the ion-pair strategy for long-lasting delivery of clonidine in single-layer matrix-type patch

Existing long-acting patches usually use controlled-release membranes to achieve constant rate delivery of the drug, which is complex and costly to prepare due to the 5-layer structure, so there is a necessity to develop a method to simplify the patch design and to control constant rate drug delivery. This study prepared a 7-day long-acting clonidine (CLO) patch using the ion-pair strategy based on hydroxyphenyl-modified pressure-sensitive adhesive (HP-PSA) and clarified the molecular mechanism of controlled delivery. Single factorial and central composite design (CCD) experiments were used to optimize the patch formulation, which was evaluated by a pharmacokinetic study. The controlled drug delivery mechanism was investigated by FTIR, 1H NMR, differential scanning calorimetry (DSC), confocal laser scanning microscopy (CLSM), molecular modeling, and rheology study. The optimized patch was formulated with 4.80% (w/w) CLO-AA (azelaic acid) as API and HP-PSA as PSA matrix and 95.00 μm thickness. The single-layer patch not only simplifies the preparation process but also has a zero-level skin penetration profile (r = 0.9592) in vitro. Compared with the commercial patch (AUC0-t = 7748.51 ± 662.76 h ng/ml, MRT0-t = 71.04 ± 9.30h), the pharmacokinetic behavior of the optimization group was semblable (AUC0-t = 8160.28 ± 694.04 h ng/ml, MRT0-t = 63.19 ± 12.38h). Mechanistic studies showed that ion-pair improved drug interaction with HP-PSA, leading to controlled drug release. Changes in drug physicochemical properties decreased skin permeability and increased drug-skin interaction, resulting in a constant delivery rate. In conclusion, the 7-day long-acting drug delivery of the CLO patch was achieved by the ion-pair strategy, which simplified the preparation process, and inspired a long-acting transdermal drug delivery system.

Piquing artificial intelligence towards drug discovery: Tools, techniques, and applications.

The purpose of this study was to discuss how artificial intelligence (AI) methods have affected the field of drug development. It looks at how AI models and data resources are reshaping the drug development process by offering more affordable and expedient options to conventional approaches. The paper opens with an overview of well-known information sources for drug development. The discussion then moves on to molecular representation techniques that make it possible to convert data into representations that computers can understand. The paper also gives a general overview of the algorithms used in the creation of drug discovery models based on AI. In particular, the paper looks at how AI algorithms might be used to forecast drug toxicity, drug bioactivity, and drug physicochemical properties. De novo drug design, binding affinity prediction, and other AI-based models for drug-target interaction were covered in deeper detail. Modern applications of AI in nanomedicine design and pharmacological synergism/antagonism prediction were also covered. The potential advantages of AI in drug development are highlighted as the evaluation comes to a close. It underlines how AI may greatly speed up and improve the efficiency of drug discovery, resulting in the creation of new and better medicines. To fully realize the promise of AI in drug discovery, the review acknowledges the difficulties that come with its uses in this field and advocates for more study and development.

Mouth dissolving film as a potential dosage form for paediatric usage

Drug delivery systems using thin films are being researched by the pharmaceutical industry. They're a diverse platform that can provide immediate, local, or systemic actions. Furthermore, these systems can be used independently, which is ideal for patients with dysphagia, elderly, pediatric, or bed-ridden patients, as well as those who may have difficulty consuming water. These drug delivery systems can be given by oral, buccal, sublingual, ocular and trans-dermal routes. This study explores mouth thin films in all of their characteristics from the current perspective, providing insight into the world's growing market share as a result of expanding research fields and technological breakthroughs. Simultaneously, It provides a summary of the key factors involved in formulation development that have an impact on thin films, such as thin film design, morphological and physiological limitations, production process selection, characterization techniques, and polymer and drug physicochemical properties. It also gives an overview of the most recent thin-film products made by major pharmaceutical firms.

Advancing Drug Delivery Paradigms: Polyvinyl Pyrolidone (PVP)-Based Amorphous Solid Dispersion for Enhanced Physicochemical Properties and Therapeutic Efficacy.

The current challenge in drug development lies in addressing the physicochemical issues that lead to low drug effectiveness. Solubility, a crucial physicochemical parameter, greatly influences various biopharmaceutical aspects of a drug, including dissolution rate, absorption, and bioavailability. Amorphous solid dispersion (ASD) has emerged as a widely explored approach to enhance drug solubility. The objective of this review is to discuss and summarize the development of polyvinylpyrrolidone (PVP)-based amorphous solid dispersion in improving the physicochemical properties of drugs, with a focus on the use of PVP as a novel approach. This review was conducted by examining relevant journals obtained from databases such as Scopus, PubMed, and Google Scholar, since 2018. The inclusion and exclusion criteria were applied to select suitable articles. This study demonstrated the versatility and efficacy of PVP in enhancing the solubility and bioavailability of poorly soluble drugs. Diverse preparation methods, including solvent evaporation, melt quenching, electrospinning, coprecipitation, and ball milling are discussed for the production of ASDs with tailored characteristics. PVP-based ASDs could offer significant advantages in the formulation strategies, stability, and performance of poorly soluble drugs to enhance their overall bioavailability. The diverse methodologies and findings presented in this review will pave the way for further advancements in the development of effective and tailored amorphous solid dispersions.

Empirical Analysis of Drug Targets for Nervous System Disorders.

The discovery and development of drugs to treat diseases of the nervous system remains challenging. There is a higher attrition rate in the clinical stage for nervous system experimental drugs compared to other disease areas. In the preclinical stage, additional challenges arise from the considerable effort required to find molecules that penetrate the blood-brain barrier (BBB) coupled with the poor predictive value of many preclinical models of nervous system diseases. In the era of target-based drug discovery, the critical first step of drug discovery projects is the selection of a therapeutic target which is largely driven by its presumed pathogenic involvement. For nervous system diseases, however, the feasibility of identifying potent molecules within the stringent range of molecular properties necessary for BBB penetration should represent another important factor in target selection. To address the latter, the present review analyzes the distribution of human protein targets of FDA-approved drugs for nervous system disorders and compares it with drugs for other disease areas. We observed a substantial difference in the distribution of therapeutic targets across the two clusters. We expanded on this finding by analyzing the physicochemical properties of nervous and non-nervous system drugs in each target class by using the central nervous system multiparameter optimization (CNS MPO) algorithm. These data may serve as useful guidance in making more informed decisions when selecting therapeutic targets for nervous system disorders.

The Effect of Solvents on the Crystal Morphology of Isosorbide Mononitrate and Its Molecular Mechanisms.

In this work, the modified attachment energy model was used to predict the crystal morphology of isosorbide mononitrate (ISMN) in the dichloromethane (CH2Cl2) solvent system and dichloromethane-n-hexane (CH2Cl2-C6H14) mixed solvent system. The solvent effect can significantly affect the crystal morphology, which can profoundly impact both the drug's physicochemical properties and the subsequent technological treatment process. In addition, the interactions between solvent molecules and crystal faces were investigated using molecular dynamics simulation, and radial distribution function (RDF) analysis was performed to determine the types of interactions. The structural parameter S was introduced to characterize the roughness of each crystal surface; the change in the CH2Cl2 diffusion coefficient before and after the addition of C6H14 was analyzed using mean square displacement (MSD). The calculation results of the modified attachment energy from the two solvent systems revealed that C6H14 could accelerate crystal growth, while the crystal morphology was not greatly affected, which is of some significance as a guide for the industrial crystallization process.

Effectiveness In Vivo and In Vitro of Polymeric Nanoparticles as a Drug Release System in the Treatment of Leishmaniasis.

Leishmaniasis is a neglected disease caused by the parasite of the genus Leishmania. Current treatment regimens are obsolete and cause several side effects, promoting poor patient compliance, in addition to the vast majority already having the potential for resistance. Therefore, polymeric nanoparticles emerge as one of the viable alternatives to overcome existing limitations, through passive or active vectorization. This review aims to summarize the latest studies of polymeric nanoparticles as an alternative treatment for leishmaniasis. In the first section, the main pharmacokinetic and pharmacodynamic challenges of current drugs are reported. The second section details how nanoparticles with and without functionalization are efficient in the treatment of leishmaniasis, discussing the characteristics of the polymer in the formulation. In this way, polymeric nanoparticles can improve the physicochemical properties of leishmanicidal drugs, improving solubility and stability, as well as improve the release of these drugs, directly or indirectly reaching monocytes/macrophages. 64.28% drugs were focused on the treatment of visceral leishmaniasis, and 28.57% on cutaneous leishmaniasis. The most chosen polymers in the literature are chitosan (35.71%) and PLGA (35.71%), the others represented 14.30% drugs, with all able to manage the drug release and increase the in vitro</i> and/or in vivo</i> efficacy of the original molecule. However, there are several barriers for these nanoformulations to cross laboratory research and is necessary more in-depth studies about the metabolites and degradation pathways of the polymers used in the formulations and plasma proteomics studies.