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In this study, a new drug product containing activated charcoal was designed and developed. The excipient levels in the pharmaceutical formulation were optimized using a mixture design approach. The adsorption power of the activated charcoal suspension was selected as the critical quality attribute influencing the efficacy of medical treatment. Significant prognostic models (p < 0.05) were obtained to describe in detail the interrelations between excipient levels and the adsorption power of the formulation. Liquid flavour had a critical impact on the adsorption power of the suspension. Formulations containing the largest amount of liquid flavour showed the lowest adsorption power. Sorbitol was not adsorbed onto activated charcoal so strongly as liquid flavour. A slight increase in the content of carboxymethylcellulose sodium led to a marked decrease in adsorption power. The obtained mathematical models and response surface allowed selection of the optimal composition of excipients in a final drug product

Purpose: This study assesses the Multilayer Perceptron (MLP) neural network, complemented by other Machine Learning techniques (CART, PCA), in predicting the antimicrobial activity of 140 newly designed imidazolium chlorides against Klebsiella pneumoniae before synthesis. Emphasis is on leveraging molecular properties for predictive analysis., Methods: Classification and regression decision trees (CART) identified the top 200 predictive molecular descriptors. Principal Component Analysis (PCA) reduced these descriptors to 5 components, retaining 99.57% of raw data information. Antimicrobial activity, categorized as high or low, was based on experimentally proven minimal inhibitory concentration (MIC), with a cut-point at MIC = 0.856 mol/L. A 12-fold cross-validation trained the MLP (architecture 5-12-2 with 5 Principal Components)., Results: The MLP exhibited commendable performance, achieving almost 90% correct classifications across learning, validation, and test sets, outperforming models without PCA dimension reduction. Key metrics, including accuracy (0.907), sensitivity (0.905), specificity (0.909), and precision (0.891), were notably high. These results highlight the MLP model's efficacy with PCA as a high-quality classifier for determining antimicrobial activity., Conclusions: The study concludes that the MLP neural network, along with CART and PCA, is a robust tool for predicting the antimicrobial activity class of imidazolium chlorides against Klebsiella pneumoniae. CART and PCA, used in this study, allowed input variable reduction without significant information loss. High classification accuracy and associated metrics affirm the method's potential utility in pre-synthesis assessments, offering valuable insights for antimicrobial compound design., (© 2024. The Author(s).)

The present work provides new evidence of the ongoing potential of surface-active ionic liquids (SAILs) and surface-active quaternary ammonium salts (surface-active QASs). To achieve this, a series of compounds were synthesized with a yield of ≥85%, and their thermal analyses were studied. Additionally, antimicrobial activity against both human pathogenic and soil microorganisms was investigated. Subsequently, their surface properties were explored with the aim of utilizing SAILs and surface-active QASs as alternatives to commercial amphiphilic compounds. Finally, we analyzed the wettability of the leaves' surface of plants occurring in agricultural fields at different temperatures (from 5 to 25 °C) and the model plant membrane of leaves. Our results show that the synthesized compounds exhibit higher activity than their commercial analogues such as, i.e., didecyldimethylammonium chloride (DDAC) and dodecyltrimethylammonium bromide (C 12 TAB), for which the CMC values are 2 mM and 15 mM. The effectiveness of the antimicrobial properties of synthesized compounds relies on their hydrophobic nature accompanied by a cut-off effect. Moreover, the best wettability of the leaves' surface was observed at 25 °C. Our research has yielded valuable insights into the potential effectiveness of SAILs and surface-active QASs as versatile compounds, offering a promising alternative to established antimicrobials and crop protection agents, all the while preserving substantial surface activity.

In this work, amidequats and esterquats based on caprylic acid were investigated as promising compounds with surface properties and biological activity that are in harmony with the principles of green chemistry. Herein, caprylic acid, which is an essential component of the above compounds, is a noteworthy natural resource. Structural analysis was performed with the amphiphilic cations of the tested amidequats and esterquats, revealing two distinct factors, i.e. , the elongation of the alkyl chain and the presence of two different functional groups; these factors undoubtedly affect the desired biological activity. These compounds were synthesized and characterized in terms of their physicochemical properties, among which surface activity is pivotal. In addition, the surfaces of the tested compounds were investigated through a detailed topographical analysis. The obtained results suggested that the esterquats exhibited higher surface activity, wettability and foamability than the amidequats. Antimicrobial studies, on the other hand, are not as conclusive. For shorter chains, esterquats are more active than amidequats, while for longer chains (over C12), the trend was the opposite. The amidequats and esterquats presented in this research may be a potential good replacement for antimicrobial formulations or as alternatives to surface-active agents used in industry., Competing Interests: The authors declare no conflicts of interest., (This journal is © The Royal Society of Chemistry.)

In this study, a series of 10 novel 1-methyl-3-octyloxymethylimidazolium derivatives carrying various anionic moieties (4-hydroxybenzenesulfonate, benzenesulfonate, carvacroloxyacetate, chloride, formate, propionate, thymoloxyacetate, vanillinoxyacetate, eugenoloxyacetate and trimethylacetate) were synthesized. Compounds were tested for their antimicrobial activity against six microbe strains (Staph-ylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli, Enterococcus faecalis, and Candida albicans), cytotoxic activity against the mouse melanoma cell line (B16 F10), and surface active properties. All synthesized compounds exhibited antimicrobial activity (expressed as minimum inhibitory concentration; in range of 0.10-27.82 mM/L), especially against Gram-positive bacteria and fungi. In addition, all compounds demonstrated cytotoxicity on B16 F10 cells (IC50 values 0.0101-0.0197 mM/L). Surface properties defined as CMC values, ranged from 0.72 to 32.35 mmol L-1. The obtained results provide an insight into the promising activity of a novel group of quaternary imidazolium derivatives having ionic liquid properties. The most potent compounds, containing a thymoloxyacetate and eugenoloxyacetate moiety, could be candidates for new antimicrobial agents or surfactants.

This paper presents the results of structure-activity relationship (SAR) studies of 140 3,3'-(α,ω-dioxaalkan)bis(1-alkylimidazolium) chlorides. In the SAR analysis, the dominance-based rough set approach (DRSA) was used. For analyzed compounds, minimum inhibitory concentration (MIC) against strains of Staphylococcus aureus and Pseudomonas aeruginosa was determined. In order to perform the SAR analysis, a tabular information system was formed, in which tested compounds were described by means of condition attributes, characterizing the structure (substructure parameters and molecular descriptors) and their surface properties, and a decision attribute, classifying compounds with respect to values of MIC. DRSA allows to induce decision rules from data describing the compounds in terms of condition and decision attributes, and to rank condition attributes with respect to relevance using a Bayesian confirmation measure. Decision rules present the most important relationships between structure and surface properties of the compounds on one hand, and their antibacterial activity on the other hand. They also indicate directions of synthesizing more efficient antibacterial compounds. Moreover, the analysis showed differences in the application of various parameters for Gram-positive and Gram-negative strains, respectively.

Multiple-unit pellet systems (MUPS) offer many advantages over conventional solid dosage forms both for the manufacturers and patients. Coated pellets can be efficiently compressed into MUPS in classic tableting process and enable controlled release of active pharmaceutical ingredient (APIs). For patients MUPS are divisible without affecting drug release and convenient to swallow. However, maintaining API release profile during the compression process can be a challenge. The aim of this work was to explore and discover relationships between data describing: composition, properties, process parameters (condition attributes) and quality (decision attribute, expressed as similarity factor f 2 ) of MUPS containing pellets with verapamil hydrochloride as API, by applying a dominance-based rough ret approach (DRSA) mathematical data mining technique. DRSA generated decision rules representing cause-effect relationships between condition attributes and decision attribute. Similar API release profiles from pellets before and after tableting can be ensured by proper polymer coating (Eudragit ® NE, absence of ethyl cellulose), compression force higher than 6 kN, microcrystalline cellulose (Avicel ® 102) as excipient and tablet hardness ≥42.4 N. DRSA can be useful for analysis of complex technological data. Decision rules with high values of confirmation measures can help technologist in optimal formulation development., Competing Interests: The authors and the companies Polpharma and Adamed Pharma declare no conflict of interest regarding publication of this paper.

Pharmaceutical pellets are spherical agglomerates manufactured in extrusion/spheronization process. The composition of the pellets, the amount of active pharmaceutical ingredient (API) and the type of used excipients have an influence on the shape and quality of dosage form. A proper quality of the pellets can also be achieved by identifying the most important technological process parameters. In this paper, a knowledge discovery method, called dominance-based rough set approach (DRSA) has been applied to evaluate critical process parameters in pellets manufacturing. For this purpose, a set of condition attributes (amount of API; type and amount of excipient used; process parameters such as screw and rotation speed, time and temperature of spheronization) and a decision attribute (quality of the pellets defined by the aspect ratio) were used to set up an information system. The DRSA analysis allowed to induce decision rules containing information about process parameters which have a significant impact on the quality of manufactured pellets. Those rules can be used to optimize the process of pellets manufacturing., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The progress of antimicrobial therapy contributes to the development of strains of fungi resistant to antimicrobial drugs. Since cationic surfactants have been described as good antifungals, we present a SAR study of a novel homologous series of 140 bis-quaternary imidazolium chlorides and analyze them with respect to their biological activity against Candida albicans as one of the major opportunistic pathogens causing a wide spectrum of diseases in human beings. We characterize a set of features of these compounds, concerning their structure, molecular descriptors, and surface active properties. SAR study was conducted with the help of the Dominance-Based Rough Set Approach (DRSA), which involves identification of relevant features and relevant combinations of features being in strong relationship with a high antifungal activity of the compounds. The SAR study shows, moreover, that the antifungal activity is dependent on the type of substituents and their position at the chloride moiety, as well as on the surface active properties of the compounds. We also show that molecular descriptors MlogP, HOMO-LUMO gap, total structure connectivity index, and Wiener index may be useful in prediction of antifungal activity of new chemical compounds.

A series of 70 new 3,3'(α,ω-dioxaalkyl)bis(1-alkylimidazolium) chlorides were synthesized. They were characterized with respect to surface active properties and antimicrobial activity against the following pathogens: Staphylococcus aureus, Enterococcus faecalis, Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Enterobacter cloacae, Pseudomonas aeruginosa, Candida krusei, and Candida albicans. In this article, besides description of the synthesis, we characterize a set of features of these compounds, concerning their structure (described by the length of the dioxaalkan spacer and the length of the alkyl substituent in the aromatic ring) and surface active properties (critical micelle concentration, value of surface tension at critical micelle concentration, value of surface excess, molecular area of a single particle, and free energy of adsorption of molecule). Then, we present a SAR study for Staphylococcus aureus, as one of the most widespread pathogenic strains, conducted with the help of the Dominance-based Rough Set Approach (DRSA), that involves identification of relevant features and relevant combinations of features being in strong relationship with a high antimicrobial activity of the compounds. The SAR study shows, moreover, that the antimicrobial activity is dependent on the type of substituents and their position at the chloride moiety, as well as on the surface active properties of the compounds., (© 2013 John Wiley & Sons A/S.)