Chromatographic Method For Analysis Research Articles

Chromatographic’s image analysis in phytohomeopathies

Plants signal when establishing interaction with homeopathies in different succussions, however, the type of signaling is not always understandable. Recognizing symptomatic patterns in plants begins by understanding the behavior of homeopathy itself, through varied methods, widely disseminated in scientific literature¹. The present study proposes a new thin-layer chromatography (TLC) analysis method to identify patterns in different phytohomeopathic applications. CCDs were made on Sulfur 9Ch, Nux and Bell 11CH; Calc Ph 29CH; Bry and Cal Carb 30CH; Hyp 50CH; Mag Ph 200CH and Graph Nat 200CH. The analysis of the chromatographic stains was developed with ultraviolet light and the images were analyzed using the Fast Fourier Transform (FFT) method². The statistical design, ANOVA, consisted of 5 completely randomized, double-blind replications for each of the preparations. The results showed significant differences after a few minutes of chromatography, highlighting the order of signals between homeopathies: Bell < Sulph < Mag Ph < Graph Nat < Hyp < Bry < Calc Ph < Cal Carb < Nux. From these results, it is possible to identify phytohomeopathic’ signs and symptoms during the course of the treatment.

SEAWEED: A Complete Medical Overview

Objective of current work is to make everyone aware about the medical potentials of seaweed and to know various species of seaweed. The NOAA is an American scientific and regulatory agency which gives information about valuable health benefits of seaweed and its varieties. According to CDC report Approximately 190 million preschool-aged children worldwide suffer from vitamin A insufficiency. This article will put a retrospect on future scope of seaweed, as we can formulate many clinically useful formulations from isolated extract of the same using various chromatographic analytical methods like HPLC and spectroscopy.

Separation and Characterization of Wenjin Tongluo San Essential Oil with a Comprehensive Chromatographic Separation

The essential oil components of traditional Chinese medicine in-hospital preparation were complex, and one-dimensional chromatographic separation was difficult to completely separate them due to the limited peak capacity. This study was carried out to establish a comprehensive two-dimensional chromatographic separation and analysis method based on countercurrent chromatography (CCC) and gas chromatography (GC). In this paper, we focused on the separation of the essential oil of the traditional Chinese medicine in-hospital preparation Wenjing Tongluo San by CCC × GC, and explored the orthogonality between the two chromatographic techniques to provide the new technical support for the screening of the active ingredients. A solvent system composed of n-hexane-ethyl acetate-methanol-water (9.5:0.5:8.5:1.5, v/v) was chosen for the first-dimensional CCC separation. All the fractions collected from CCC were transferred to GC for plotting two-dimensional contours map. The calculated capacity of the two-dimensional separation system exceeded 3000, which was 8 times more than that of the one-dimensional separation system. High orthogonality (r = 0.42) and spatial coverage factor (70.42%) were obtained. Meanwhile, all the fractions were identified by GC-MS. Our research provided a new methodology for separating essential oils in traditional Chinese medicine as well as an approach for evaluating the quality of traditional Chinese medicinal in-hospital preparation based on two-dimensional chromatographic fingerprints.

Direct ion chromatographic method for speciation micro analysis of arsenic forms in industrial samples with “rich” matrix composition

The speciation analysis of arsenic has consistently been a subject of great interest. However, it remains challenging to analyze complex matrix samples that contain both arsenic and interfering components. In this case, it can be hard to choose the right combinations of different instrumental methods, or a separation method followed by detection, which is usually done using a spectral approach (hybrid methods). In the production control of copper electrorefining, the determination of the concentration of As (III) and As (V) helps to improve the quality of the cathode copper produced. This work investigated the possibility of directly determining both arsenic forms and total As in an electrolyte bath using ion chromatography (IC) with conductometric detection. The use of the ion chromatographic approach for the determination of As(V) in complex matrix samples such as copper electrolyte must take into account the presence of potential interferences from anions such as sulphates, sulfites, selenites, selenates, etc. The results revealed that the method is accurate and precise, with As(V) quantification limits of 15 µg.L-1 and detection limits of 5 µg.L-1. This method is suitable for assessing various types of arsenic in the production of electrolytic copper, with the aim of replacing the current technique that requires liquid-liquid extraction and ICP-OES detection. This led to the following improvements: Enhanced efficiency: The method eliminates the need for extensive and time-consuming sample preparation for the initial separation of arsenic forms. At the same time, the method's characteristics are comparable to those of ICP-OES with liquid-liquid extraction, which is often used in the speciation analysis of arsenic. The method is environmentally friendly as it avoids the use of organic and poisonous extractants. The method can simultaneously analyze other anions (PO43-, SO42-, F-, Cl-, etc.) with arsenates with appropriate calibration.

Development and Validation of a High-Performance Thin-Layer Chromatography Method for the Qualitative Analysis and Quantification of Hispidulin in Hydroethanol Extract of S. barbata D. Don

Background: Hispidulin, a flavonoid renowned for its diverse pharmacological activities, is abundant in S. barbata D. Don. Given its prevalence, it is essential to establish a dependable analytical method for quantifying hispidulin in this plant. Methods: This study introduces a sensitive and reliable high-performance thin-layer chromatographic (HPTLC) method for both qualitative and quantitative analysis of hispidulin in S. barbata D. Don. Pre-coated TLC aluminum plates were utilized, and after testing various mobile phase combinations, the most effective separation was achieved with Toluene-ethyl acetate-formic acid (5:4:1, v/v/v). The method underwent extensive validation for linearity, specification, instrument precision, precision, limits of LOD and LOQ, accuracy, and robustness. Results: The developed method demonstrated excellent linearity over a specified concentration range, with a determination coefficient (r2) of 0.988. A well-defined spot at Rf 0.7, corresponding to hispidulin, was observed. The concentration of hispidulin in the hydroethanolic extract of S. barbata D. Don was quantified as 13.02 μg/mg of extract. Conclusion: In conclusion, the HPTLC method presented in this study offers a simple, accurate, and robust tool for quantitatively analyzing hispidulin in the hydroethanol extract of S. barbata D. Don. This method is suitable for routine quality control and standardization of herbal formulations containing S. barbata D. Don, thereby contributing to the advancement of research in natural product- based pharmaceuticals.

Validation and optimisation of reduced glutathione quantification in erythrocytes by means of a coulometric high-performance liquid chromatography analytical method.

Glutathione (GSH), a tripeptide that consists of cysteine, glutamate and glycine, is present in all mammalian tissues in the millimolar range. Besides having numerous cellular functions, GSH is an important antioxidant and is considered a valuable biomarker in evaluating oxidative stress. This paper provides a sensitive analytical method using HPLC-ECD to quantify GSH in erythrocytes, validated using the ICH guidelines for Bioanalytical Method Validation. The sample preparation was optimised using centrifugal filtration and a hypotonic phosphate buffer for extracting GSH from erythrocytes. HPLC-ECD parameters were adjusted to allow a fast, reversed phase, isocratic separation in 10min. The detector response was linear between 0.3 and 9.5μg/mL with a satisfactory regression coefficient and a LOQ of 0.11 μg/mL. Intra- and inter-day repeatability ranged between 1.10% and 8.57% with recoveries ranging from 94.3% to 106.0%. Dilution integrity, benchtop, freeze-thaw and long-term stability were investigated. Samples were stable for up to 6months at -80°C. This method has a good linear response and is repeatable, precise and accurate. It minimises GSH auto-oxidation using a centrifugal filter during sample preparation, instead of acidification. Therefore, this analytical method is suitable for quantifying GSH in erythrocytes as a marker of oxidative stress.

Foreign experience in determining the group hydrocarbon composition of petroleum feedstock and petroleum products

Determination of the group hydrocarbon composition (saturated and aromatic hydrocarbons, resins, asphaltenes) of petroleum dispersed systems is predominantly carried out using chromatographic analysis methods: liquid adsorption chromatography, high-performance liquid chromatography, thin-layer chromatography with flame ionization detection. The specificity of standard methods developed for the analysis of petroleum feedstock and petroleum products using a particular method often results in the incompatibility of results both in terms of the nomenclature of the identified hydrocarbon groups and the determined concentration values. This review provides a comparative assessment of chromatographic methods for analyzing the group hydrocarbon composition of petroleum feedstock and petroleum products, their features, advantages, and disadvantages. The main options for modifying standard methods aimed at achieving correlation between the results obtained by different analysis methods are described.

A Sustainable Chromatographic Method for Simultaneous Analysis of Fluoxetine and Olanzapine Antidepressants: Assessment of Greenness with Green Metric Tools .

The combination of Fluoxetine HCL and Olanzapine treats depression in bipolar disorder and patients unresponsive to other antidepressants. The research aims to optimize a sensitive, simple, rapid, reliable, eco-friendly liquid chromatographic method by minimizing feedstock’s, reagents, energy, and waste to protect the environment and conserve resources, additionally assessed the environmental impact of a method using various green metric tools, and applied the method to pharmaceuticals. The separation was conducted using isocratic RP-HPLC with a DAD at 227nm. The mobile phase used was a 40:40:20 (v/v/v) ratios of buffer, acetonitrile, and ethanol. An L1 column (150 x 4.6mm, 5µm) was utilized with a flow rate of 1.5mL/min and injection volume of 5µL. The column oven and auto-sampler were both maintained at 45°C and 25°C respectively. The optimized method was validated as per ICH guidelines and found to be specific, precise, and robust to slight changes in mobile phase flow, column temperature, and buffer pH. Linearity was demonstrated from 0.1-150µg/mL for olanzapine and 0.4-610µg/mL for fluoxetine HCL. The accuracy was tested with recovery ranges of 0.1–157 µg/mL for olanzapine and 0.4–606 µg/mL for fluoxetine HCl in tablet placebo, and 0.1–150 µg/mL for olanzapine and 0.4–605 µg/mL for fluoxetine HCl in capsule placebo, indicating that the method is suitable for both tablet and capsule dosage forms. The method’s greenness was evaluated using AES, NEMI, GAPI, and AGREE tools. The optimized method was successfully applied to pharmaceutical analysis. The newly optimized method found simple, sensitive, rapid, eco-friendly, incorporating green analytical concepts, has been successfully achieved for the identification and quantification of Fluoxetine HCL and Olanzapine present in pharmaceuticals.

UHPLC method for simultaneous assessment of pharmacokinetic parameters of co-administered voriconazole and omeprazole using rat plasma

Voriconazole (VRC) is a first-line therapeutic agent for the treatment of invasive fungal infections, whereas omeprazole (OMZ) is a commonly used acid suppressant; however, the two drugs are often used in combination in clinical practice. The aim of this research was to investigate how the co-administration of OMZ and VRC affects the pharmacokinetic characteristics of VRC in rats. A new ultra high-performance liquid chromatography (UHPLC) analytical method was developed and validated for simultaneous analysis of co-administered drugs using VRC and OMZ. A Shim-pack GIST-HP C18 column with 0.1 M triethylamine:acetonitrile (70:30, v/v) as the mobile phase (flow rate: 0.3 mL/min) was used, and UV detection was performed at 240 nm. Liquid–liquid extraction of plasma samples was carried out using dichloromethane. The bioanalytical method was linear over a range of VRC concentrations (100–2000 ng/mL) and OMZ (50–10,000 ng/mL) concentrations, and exhibited both accuracy and precision within the acceptable respective ranges. The average extraction recoveries for VRC and OMZ in plasma were 94.88 % and 82.76 %, respectively. Additionally, the method was successfully applied in vivo to estimate the pharmacokinetic features of VRC in the plasma of rats receiving gavage with low and high doses of OMZ. In conclusion, using a new UHPLC method, we determined that co-administration of OMZ substantially decreased the bioavailability of VRC in rats. Potentially significant drug interactions should be considered in patients receiving the combination of OMZ and VRC.

An Overview of Biotechnological Drug’s Various Techniques of Downstream Process, Guideline’s And Different Chromatographic Analysis

Abstract: Biotechnology, a field discovered in 1919, unites biology and engineering to harness living organisms for medical purposes. Fueled by using DNA's discovery in the 1950s, biotechnology has converted through genetic engineering, yielding impactful merchandise regulated by means of entities like the FDA. The manufacturing involves upstream and downstream processing including the various techniques involved in the downstream processing of biotechnological drugs, along with relevant guidelines and chromatographic analysis methods. The biotechnological industry, which integrates biological science with engineering, has significantly advanced since the discovery of DNA's structure, leading to the development of biopharmaceuticals. These drugs, including monoclonal antibodies, recombinant proteins, and gene therapies, are produced using living organisms and hold the potential for treating complex diseases. The downstream process, a crucial phase in biopharmaceutical production, involves the purification and formulation of drug products to meet stringent regulatory standards. Traditional techniques such as centrifugation, filtration, and chromatography are employed to extract and purify biopharmaceuticals. Chromatographic techniques, including ion exchange, affinity, and size exclusion chromatography, play a pivotal role in achieving the desired purity levels. However, these methods are often time-- consuming and expensive, necessitating continuous advancements in the field. The paper highlights the importance of regulatory guidelines, including cGMP, in ensuring the quality and safety of biopharmaceuticals. It also discusses the significant role of organizations such as the FDA and EMA in regulating biotechnological drug production. The evolution of downstream processing techniques and the development of novel methods promise greater efficiency, scalability, and cost-effectiveness in biopharmaceutical production. Understanding these advancements is essential for continued growth and innovation in the industry, ultimately contributing to improved patient care and pharmaceutical innovation.

Recognition of Rice Species Based on Gas Chromatography-Ion Mobility Spectrometry and Deep Learning

To address the challenge of relying on complex biochemical methods for identifying rice species, a prediction model that combines gas chromatography-ion mobility spectroscopy (GC-IMS) with a convolutional neural network (CNN) was developed. The model utilizes the GC-IMS fingerprint data of each rice variety sample, and an improved CNN structure is employed to increase the recognition accuracy. First, an improved generative adversarial network based on the diffusion model (DGAN) is used for data enhancement to expand the dataset size. Then, on the basis of a residual network called ResNet50, a transfer learning method is introduced to improve the training effect of the model under the condition of a small sample. In addition, a new attention mechanism called Triplet is introduced to further highlight useful features and improve the feature extraction performance of the model. Finally, to reduce the number of model parameters and improve the efficiency of the model, a method called knowledge distillation is used to compress the model. The results of our experiments revealed that the recognition accuracy for identifying the 10 rice varieties was close to 96%; hence, the proposed model significantly outperformed traditional models such as principal component analysis and support vector machine. Furthermore, compared to the traditional CNN, our model reduced the number of parameters and number of computations by 53% and 55%, respectively, without compromising classification accuracy. The study also suggests that the combination of GC-IMS and our proposed deep learning method had better discrimination abilities for rice varieties than traditional chromatography and other spectral analysis methods and that it effectively identified rice varieties.

Application of seven tools for evaluation of greenness of chromatographic methods for Remdesivir analysis

Green analytical chemistry is concerned with making analytical techniques more secure and environmentally friendly. A crucial aspect of this approach is the assessment of the greenness of analytical methods. Remdesivir, a SARS-CoV-2 nucleotide analog RNA polymerase inhibitor, has been authorized by USFDA as the initial course of therapy for hospitalized COVID-19 patients. The proposed study evaluates greenness of several reported chromatographic methods for estimation of Remdesivir using seven different tools namely ComplexGAPI, BAGI, AGREE, AGREEprep, AMGS, ChlorTox and RGBfast.

Extraction and Chromatographic Approaches for Coumarin, Furocoumarin, and Polymethoxyflavone Characterization in Foods.

Oxygen heterocyclic compounds play a beneficial role in plants, and their presence in foods, such as Citrus fruits, cinnamon, carrots, and parsley, has been documented in recent years. Published research articles reported several extractions and chromatographic techniques for their determination. The aim of this review was to take into consideration the research articles published from 2016 to 2024 in which the authors developed extraction and chromatographic analysis methods of oxygen heterocyclic compounds in foods. The objective of this review was to assist researchers in choosing the best approach for their future work by identifying all the possible approaches to characterize coumarins, furocoumarins, and polymethoxyflavones in foodstuffs.

Chemometrics‐Empowered Optimization of a Reliable Reversed Phase–High Performance Liquid Chromatography Method for the Simultaneous Estimation of Erythromycin and Adapalene in Pharmaceutical Nanoformulation

ABSTRACTAn innovative, simple, economical, and sensitive reversed phase–high performance liquid chromatography (RP–HPLC) chromatographic method for simultaneous analysis of erythromycin (ERY) and adapalene (ADP) in bulk and pharmaceutical nanoformulation was developed by analytical quality‐by‐design (AQbD) avenue. According to published research, there is no strategy that integrates RP–HPLC with AQbD for estimating ERY and ADP. The analysis was carried out with Box–Behnken design, which reduced trial runs and design points. Acetonitrile: orthophosphoric acid (OPA) (0.1% triethanolamine) in pH 6.2 water was used as the mobile phase. The ratio was set to 35:65 (v/v) at 0.8 mL/min flow rate to detect the analytes at 231 nm. As per the guidelines in International Conference on Harmonization Q1A (R2), the developed approach was validated. ERY and ADP regression coefficients (r2) were found to be 0.9998 and 0.9999, respectively, over 5–25 µg/mL range. Validation parameters comprising linearity, sensitivity, system suitability, precision, robustness, and accuracy were performed. To assess stability, the drugs were subjected to stress conditions (hydrolytic, oxidative, thermal, and photolytic), and drugs were most vulnerable to degrade in alkaline and oxidative conditions. A new technique successfully analyzed novel drug carriers loaded with ERY and ADP.

Flow analysis-solid phase extraction system and UHPLC-MS/MS analytical methodology for the determination of antiviral drugs in surface water

An automated flow analysis-solid phase extraction (FA-SPE) system and methodology of ultra-high-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) analysis were developed for the determination of selected antiviral drugs (acyclovir, amantadine, rimantadine, and oseltamivir) in water samples. The proposed FA-SPE approach enables the integration of various extraction stages and elimination of the sample evaporation step and offers individual customisation of SPE parameters, inter alia sample, and eluate flow rate and volume. Using the developed FA-SPE procedure, e.g. a 100-fold preconcentration of the target analytes in 1 h was achieved. A method for chromatographic analysis was also developed to determine the selected antiviral drugs in combination with the use of the FA-SPE system. The developed FA-SPE UHPLC-MS/MS method was validated including the determination of linearity of analytical graphs, limits of detection (5.5–99.9 pg mL−1) and quantification (18.3–329.8 pg mL−1), intra-day (1.8–8.3%) and inter-day (3.0–9.2%) precision, recovery (95.6–105.3%), and matrix effects (− 12.9 to 13.2%). The proposed method was successfully applied to analyse tap, drinking, and river water samples, revealing the presence of amantadine at a concentration of 40.1 pg mL−1 in one sample. The environmental impact of the developed FA-SPE sample preparation procedure was also assessed using the AGREEprep metric tool and compared with five other literature methods, achieving the most sustainable outcome.Graphical abstract

Authentication of Mentha arvensis essential oil using attenuated total reflectance-Fourier transform infrared spectrophotometry coupled with chemometrics

Mentha arvensis essential oil is considered a product of high economic value that finds application in the food, pharmaceutical, and cosmetic industries. They are subjected to adulteration with synthetic chemicals and low-cost vegetable oils with higher boiling points. A rapid, non-destructive method using infrared spectroscopy has been investigated to authenticate Mentha arvensis Essential oils, helping to maintain their quality and trustworthiness for users who rely on them for their beneficial properties. Authentic samples of Mentha arvensis essential oil were obtained and analyzed using Attenuated Total Reflectance-Fourier Transform Infrared spectroscopy in the wavenumber range of 500–4000 cm−1. The resulting spectra were pre-processed with Multiplicative Scatter Correction. The initial investigation involved exploratory analysis using Principal Component Analysis, followed by discriminant analysis using Principal Component Analysis-Linear Discriminant Analysis, Partial Least Squares-Discriminant Analysis, and Soft Independent Modelling for Class Analogy. The classification models developed have a high accuracy of 100 % thus demonstrating higher efficiency in distinguishing different adulterants in Mentha arvensis essential oil with both high specificity and sensitivity. To assess the extent of adulteration in Mentha arvensis essential oil, Partial Least Squares Regression and Principal Component Regression were employed. The regression models were capable of identifying adulteration levels as low as 5 % in the essential oil thus enabling FTIR spectroscopy coupled with chemometrics to serve as a non-destructive method for identifying commonly used adulterants, potentially replacing traditionally used Chromatographic and Thermo-Gravimetric Analysis methods.

Unveiling Hidden Insights in Gas Chromatography Data Analysis with Generative Adversarial Networks

The gas chromatography analysis method for chemical substances enables accurate analysis to precisely distinguish the components of a mixture. This paper presents a technique for augmenting time-series data of chemicals measured by gas chromatography instruments with artificial intelligence techniques such as generative adversarial networks (GAN). We propose a novel GAN algorithm called GCGAN for gas chromatography data, a unified model of autoencoder (AE) and GAN for effective time-series data learning with an attention mechanism. The proposed GCGAN utilizes AE to learn a limited number of data more effectively. We also build a layer of high-performance generative adversarial neural networks based on the analysis of the features of data measured by gas chromatography instruments. Then, based on the proposed learning, we synthesize the features embedded in the gas chromatography data into a feature distribution that extracts the temporal variability. GCGAN synthesizes the features embedded in the gas chromatography data into a feature distribution that extracts the temporal variability of the data over time. We have fully implemented the proposed GCGAN and experimentally verified that the data augmented by the GCGAN have the characteristic properties of the original gas chromatography data. The augmented data demonstrate high quality with the Pearson correlation coefficient, Spearman correlation coefficient, and cosine similarity all exceeding 0.9, significantly enhancing the performance of AI classification models by 40%. This research can be effectively applied to various small dataset domains other than gas chromatography data, where data samples are limited and difficult to obtain.

Development of an HPLC method using relative molar sensitivity for the measurement of blood concentrations of nine pharmaceutical compounds

We developed a reliable high-performance liquid chromatographic analysis method using a relative molar sensitivity (RMS) technique that does not require an authentic, identical reference analyte material to quantify blood serum carbamazepine, phenytoin, voriconazole, lamotrigine, meropenem, mycophenolic acid, linezolid, vancomycin, and caffeine levels for routine blood concentration measurements. Carbamazepine and caffeine were also used as non-analyte reference materials to calculate the RMS of each analyte. The RMS was calculated from the ratio of the slope of the calibration equation (analyte/non-analyte reference material), then used to quantify analytes in control serum samples spiked with carbamazepine, phenytoin, voriconazole, meropenem, mycophenolic acid, linezolid or vancomycin. In addition, the concentrations of these six drugs in control serum samples determined by the proposed RMS method agreed well with that obtained using a conventional method. The proposed RMS method is a promising tool for the clinical determination of nine drugs, given the accuracy, precision, and efficiency of quantifying these analytes.

Validation of Commercial Formulation of Difenoconazole Using HPLC Equipped with Dad

Effective, selective, precise, and accurate liquid chromatographic analytical methods for the determination of difenoconazole fungicide in the formulation have been optimized and validated to meet the accreditation requirements, the performance characteristics of the analytical method were validated which is also one of the basic requirements of ISO Standard 17025:2017, for the rapid determination of difenoconazole by HPLC-DAD. The used method involves the extraction of the substances by sonication of the sample with acetonitrile, followed by dilution in acetonitrile, and direct injection on a liquid chromatography system. For the analysis LC system from Agilent Technologies 1290 Infinity II was used. Good separation was achieved on a Luna C18 column (3µm, 100°A, 3x150mm) with a guard column (C18 4x2.0mm I.D), an isocratic mobile elution consisting of acetonitrile and water acidified 0.075% with formic acid (85:15, v/v), at a flow rate of 0.7 ml/minute and UV detection at 220 nm. The column temperature was 25⁰C, injected volume was 1 μL. The analysis duration was 10 minutes (the retention time of difenoconazole and 4 – Hydroxybenzoic acid – methyl ester was 1.846 and 1.135 minutes, respectively. The linearity within the concentration range of 750-125 µg mL-1, with the internal standard at a concentration of 250 µg mL-1 with an average correlation coefficient (R2) of 0.9998. We have considered precision, repeatability, and selectivity in the validation.

Combination of Chromatographic Analysis and Chemometric Methods with Bioactivity Evaluation of the Antibacterial Properties of Helichrysum italicum Essential Oil.

Helichrysum italicum (immortelle) essential oil is one of the most popular essential oils worldwide and it has many beneficial properties, including antimicrobial. However, in this plant, the chemical diversity of the essential oil is very pronounced. The aim of this work was to process the GC-MS results of four samples of H. italicum essential oil of Serbian origin by chemometric tools, and evaluate the antimicrobial activity in vitro and in silico. Overall, 47 compounds were identified, the most abundant were γ-curcumene, α-pinene, and ar-curcumene, followed by α-ylangene, neryl acetate, trans-caryophyllene, italicene, α-selinene, limonene, and italidiones. Although the four samples of H. italicum essential oil used in this study were obtained from different producers in Serbia, they belong to the type of essential oil rich in sesquiterpenes (γ-curcumene and ar-curcumene chemotype). In vitro antimicrobial potential showed that five were sensitive among ten strains of tested microorganisms: Staphylococcus aureus, Listeria monocytogenes, Bacillus cereus, Saccharomyces cerevisiae, and Candida albicans. Therefore, these microorganism models were used further for in silico molecular docking through the mechanism of ATP-ase inhibitory activity. Results showed that among all compounds from H. italicum essential oil, neryl acetate has the highest predicted binding energy. Artificial neural network modeling (ANN) showed that two major compounds γ-curcumene and α-pinene, as well as minor compounds such as trans-β-ocimene, terpinolene, terpinene-4-ol, isoitalicene, italicene, cis-α-bergamotene, trans-α-bergamotene, italidiones, trans-β-farnesene, γ-selinene, β-selinene, α-selinene, and guaiol are responsible for the antimicrobial activity of H. italicum essential oil. The results of this study indicate that H. italicum essential oil samples rich in γ-curcumene, α-pinene, and ar-curcumene cultivated in Serbia (Balkan) have antimicrobial potential both in vitro and in silico. In addition, according to ANN modeling, the proportion of neryl acetate and other compounds detected in these samples has the potential to exhibit antimicrobial activity.