A Critical Comparative Review of Analytical Techniques for Cloxacillin and Oxacillin Across Diverse Matrices

ABSTRACT

Cloxacillin (CLX) and oxacillin (OXA), two isoxazolyl β‐lactam antibiotics widely used against penicillinase‐producing Staphylococcus aureus , have attracted increasing attention due to their environmental persistence, residue occurrence, and analytical complexity across diverse matrices. This review provides a critical and integrated comparison of analytical techniques for the determination of CLX and OXA in pharmaceutical, biological, food, and environmental samples, addressing key challenges, including β‐lactam instability, low intrinsic detectability, strong protein binding, and matrix interferences. Chromatographic methods, particularly HPLC and LC–MS/MS, remain the most reliable approaches, offering high selectivity and stability‐indicating capability, with LC–MS/MS achieving superior sensitivity at ng/mL levels suitable for trace analysis, albeit at higher cost and with greater operational demands. Electrochemical techniques, especially nanomaterial‐ and molecularly imprinted‐based sensors, demonstrate promising sensitivity and rapid response, though limitations in reproducibility and standardization persist. In contrast, spectroscopic methods are economical and simple but restricted by low sensitivity and poor selectivity in complex matrices. Overall, no single technique is universally optimal, and analytical performance is strongly matrix‐dependent. Future perspectives should prioritize the development of hybrid, standardized, and green analytical platforms that balance sensitivity, robustness, and cost‐effectiveness, alongside harmonized validation strategies to enable reliable and sustainable monitoring of CLX and OXA in real‐world applications.

1. Introduction

Beta‐lactam antibiotics are a class of chemicals widely used and easily identified by the presence of a four‐member lactam ring that confers their biological function. These drugs belong to several families, including penicillins, cephalosporins, carbapenems, and monobactams, all of which act by inhibiting bacterial cell wall synthesis. Given their extensive use in humans and animals as well as agriculture, beta‐lactams are found in many different and diverse settings, such as drug formulation, body fluids, food, and environmental systems (Kulapina and Snesarev 2012; Tayeb et al. 2025; Farooq et al. 2025).

CLX and OXA are isoxazolyl penicillins (β‐lactams) that are important because they resist β‐lactamases. Their use has been increasing, with evidence of effectiveness against penicillinase‐producing Staphylococcus infections, but their use raises concerns about environmental persistence, possible toxicity, and contributions to antimicrobial resistance due to their extensive use. For example, there is growing evidence that OXA is not readily biodegradable in wastewater and is accumulating within the environment. Therefore, OXA has a documented accumulation and corresponding potential ecological effects in the environment (Takács et al. 2022; Mahfoudhi et al. 2024; Kulkarni 2024; Chelaru et al. 2025).

CLX and OXA were selected for joint evaluation because they belong to the isoxazolyl penicillin subclass and share highly similar chemical structures, physicochemical properties, pharmacokinetic characteristics, and therapeutic indications. Although they are not routinely co‐administered or formulated together, they are commonly used as therapeutic alternatives for infections caused by penicillinase‐producing Staphylococcus aureus . Their close structural similarity results in comparable analytical challenges, including β‐lactam instability, high plasma protein binding, weak intrinsic UV absorbance, and potential interference from structurally related β‐lactam antibiotics. Consequently, many analytical methods employ similar sample preparation procedures, chromatographic conditions, and detection strategies for both compounds. Therefore, a combined critical evaluation provides a scientifically meaningful framework for comparing analytical performance, identifying common limitations, and highlighting future directions for method development (Mahfoudhi et al. 2024; Copete‐Pertuz et al. 2018; Legrand et al. 2016; Rathinavel et al. 2008).

The precise determination of CLX and OXA in various sample types poses significant testing difficulties. The testing process faces difficulties because the substances exist at trace levels and their chemical structures are unstable, as the β‐lactam ring undergoes hydrolysis, and other materials present in the complex samples cause testing problems. Researchers have created numerous analytical methods, which include spectrophotometry, chromatography, electrochemistry, chemiluminescence, and biosensor technology (Kulapina and Snesarev 2012; Mahfoudhi et al. 2024; Gebretsadik et al. 2023).

Analytical techniques, such as UV–Vis spectrophotometry, are cost‐effective because they offer straightforward operation. The methods suffer from two main problems, which prevent them from detecting trace amounts of material. The use of high‐performance liquid chromatography (HPLC) and liquid chromatography–mass spectrometry as analytical techniques provides superior detection capabilities, enabling regulatory testing and studies of how drugs move through the body. The methods require two main components: sample preparation must be done beforehand, and they require advanced equipment to function properly, which makes them unsuitable for standard use in places with limited resources. The new methods, including electrochemical nano sensors and chemiluminescence‐based systems, demonstrate high detection capabilities, but they still face challenges in reproducibility and standardization. Analytical progress has led to a growing focus on investigating how β‐lactam antibiotics behave under various environmental conditions. Research has investigated how reactive oxygen species (ROS) interact with hydroxyl and peroxyl radicals to elucidate fundamental mechanisms and develop specialized detection methods. Researchers have examined advanced oxidation processes to study how they can break down and eliminate harmful substances, which requires combining analytical methods with environmental cleanup techniques (Mahfoudhi et al. 2024; Berczyński et al. 2017; Larmené‐Beld et al. 2014; Eticha and Gebretsadikan 2022).

Although previous reviews have discussed β‐lactam antibiotics or individual analytical techniques, a comprehensive and critical evaluation specifically focused on CLX and OXA across pharmaceutical, biological, food, and environmental matrices remains unavailable. Existing publications have primarily summarized analytical methods without systematically comparing their analytical performance, matrix compatibility, sample preparation requirements, practical applicability, and current limitations. The present review addresses these gaps by providing an integrated and critical comparison of chromatographic, spectrophotometric, electrochemical, and emerging analytical approaches for CLX and OXA determination. In addition to summarizing the available evidence, this review critically evaluates the strengths and limitations of each analytical platform, identifies current knowledge gaps, and highlights future research priorities, thereby providing practical guidance for method selection and supporting the development of more reliable, sensitive, and sustainable analytical strategies.

2. Literature Search Strategy and Article Selection

A structured literature search was conducted following the general principles of the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA 2020) to identify published studies on analytical methods for CLX and OXA. Electronic databases, including Scopus, Web of Science, PubMed, and ScienceDirect, were searched for articles published between 2000 and 2026. The search strategy combined controlled vocabulary and free‐text terms using Boolean operators (AND/OR). Search terms included “cloxacillin” OR “oxacillin”, combined with “analysis”, “determination”, “quantification”, “detection”, “analytical method”, “HPLC”, “UHPLC”, “LC–MS/MS”, “electrochemical”, “spectrophotometry”, “sensor”, “electrochemical sensor”, and “biosensor”, together with “pharmaceutical”, “biological”, “food”, and “environmental”. These keywords were selected to maximize retrieval of studies describing validated analytical methodologies while accounting for variations in terminology used across the analytical chemistry literature. Additional relevant publications were identified through manual screening of the reference lists of key review articles and original research papers.

Eligible studies included peer‐reviewed original research articles and review papers describing validated analytical methods for CLX and/or OXA. Studies were required to report analytical performance characteristics, including method development, linear range, limits of detection (LOD), limits of quantification (LOQ), precision, accuracy, and application to pharmaceutical, biological, food, or environmental matrices where applicable. Studies focusing exclusively on pharmacological, microbiological, or clinical outcomes without analytical methodology, conference abstracts lacking complete methodological information, and non‐English publications were excluded.

Following duplicate removal, titles and abstracts were screened for relevance, and potentially eligible articles underwent full‐text assessment according to the predefined inclusion and exclusion criteria. The final eligible studies were categorized according to analytical technique (chromatographic, spectrophotometric, electrochemical, and emerging sensor‐based methods) and application matrix (pharmaceutical, biological, food, and environmental) to facilitate critical comparison throughout the review. The numbers of records identified, duplicate records removed, articles screened, full‐text articles assessed, and studies included are summarized in the PRISMA‐style flow diagram (Figure 1).

FIGURE 1.

PRISMA‐style flow diagram illustrating the literature search, screening, eligibility assessment, and study selection process for this review.

3. Chemical and Pharmacological Profile of CLX and OXA

CLX and OXA (Figure 2) (Larmené‐Beld et al. 2014) are semi‐synthetic β‐lactam antibiotics that belong to the isoxazolyl penicillin subclass because they have a special structure that includes a four‐membered β‐lactam ring, which connects to a thiazolidine ring and creates the 6‐aminopenicillanic acid (6‐APA) core. The structural framework functions as an essential component of antibacterial activity but also introduces chemical instability because the β‐lactam ring is highly susceptible to hydrolytic breakdown in acidic, basic, or enzymatic environments. Chemically, CLX is designated as (2S,5R,6R)‐6‐[(3‐(2‐chlorophenyl)‐5‐methylisoxazole‐4‐carbonyl)amino]‐3,3‐dimethyl‐7‐oxo‐4‐thia‐1‐azabicyclo[3.2.0]heptane‐2‐carboxylic acid, with an empirical formula of C₁₉H₁₇ClN₃O₅S and a molar mass of approximately 435.88 g/mol (≈457.9 g/mol as the sodium salt). In contrast, OXA is chemically defined as (2S,5R,6R)‐6‐[(5‐methyl‐3‐phenylisoxazole‐4‐carbonyl)amino]‐3,3‐dimethyl‐7‐oxo‐4‐thia‐1‐azabicyclo[3.2.0]heptane‐2‐carboxylic acid, with an empirical formula of C₁₉H₁₉N₃O₅S and a molar mass of approximately 401.43 g/mol (≈423.4 g/mol in its sodium salt form). The primary structural difference between the two compounds is that CLX contains a chlorinated aromatic substituent, which slightly increases lipophilicity and affects both distribution characteristics and analytical results (Gebretsadik et al. 2023; Espinosa‐Mansilla et al. 2006; Marchetti et al. 2001; Legrand et al. 2016; Gebretsadik et al. 2023; Abdullahi et al., 2019; Verdier et al. 2011) (Table 1).

FIGURE 2.

Chemical structure of CLX and OXA (Larmené‐Beld et al. 2014).

TABLE 1.

Salient features of CLX and OXA.

Parameter	CLX	OXA
Generic name	CLX (INN, BAN)	OXA (INN, BAN, USAN)
Brand names	Orbenin, Cloxapen, Tegopen	Bactocill, Prostaphlin
Drug class	β‐Lactam antibiotic (Isoxazolyl penicillin)	β‐Lactam antibiotic (Isoxazolyl penicillin)
Indication	Infections caused by penicillinase‐producing Staphylococcus aureus	Same indication
Molecular formula	C19H17ClN3O5S	C19H19N3O5S
Molar mass (g/mol)	435.88 (≈457.9 sodium salt)	401.43 (≈423.4 sodium salt)
Mechanism of action	Inhibits PBPs → cell wall synthesis	Same
β‐Lactamase resistance	Resistant	Resistant
Spectrum	Narrow (Gram‐positive)	Narrow (Gram‐positive)
Formulations	Capsules, oral suspension, injectable	Injectable (IV/IM), limited oral
Protein binding	~90%–95%	~89%–94%
Half‐life	~0.5–1 h	~0.5–1 h
Metabolism	Partial hepatic	Partial
Excretion	Renal	Renal
Stability	β‐Lactam hydrolysis sensitive	Same
Environmental behavior	Persistent	Poorly biodegradable

Both compounds have bulky isoxazolyl substituents that impose steric hindrance on the β‐lactam ring, making them resistant to β‐lactamases. This modification improves the pharmacological stability of the compounds against enzymatic degradation; however, it also complicates analytical determination due to differences in polarity, solubility, and/or interactions with biological matrices. Both compounds are typically formulated as sodium salts; therefore, vascular solubility and blood protein binding are moderately high (more than 90% of the drug is bound in plasma). As a result of high protein binding, there is less free drug available for antimicrobial activity; thus, the extraction from biological matrices is more difficult when employing protein precipitation or solid phase extraction techniques (Legrand et al. 2016; Vu and Do 2010).

CLX and OXA function as pharmaceuticals by binding to penicillin‐binding proteins, thereby disrupting bacterial cell wall synthesis. Their resistance to β‐lactamase‐mediated hydrolysis makes them effective against penicillinase‐producing Staphylococcus aureus , although their antibacterial spectrum remains relatively narrow and does not extend to organisms with altered PBPs, such as methicillin‐resistant strains. The time‐dependent nature of their pharmacodynamic activity requires doctors to maintain drug concentrations above the minimum inhibitory concentration (MIC) level for an essential timeframe to achieve therapeutic success (Legrand et al. 2016; Ghule and Ramesh 2016).

Modestly bioavailable when taken orally, β‐lactam antibiotics from biological systems may be partially metabolized or primarily excreted via the renal pathway. Biologically and environmentally sampled β‐lactam antibiotics can contain many different species (e.g., active metabolites, inactive metabolites, and degradation products resulting from β‐lactam ring opening), thereby complicating their quantification. Very weak UV absorption, due to the absence of indicative chromophores, in β‐lactam antibiotics can cause decreased sensitivity when using direct UV spectrophotometric methods and therefore requires derivatization or more advanced analytical techniques for quantification (Abdullahi et al., 2019; Verdier et al. 2011; Adrianzén Vargas et al. 2004).

CLX and OXA not only act as antibiotics but also exhibit significant chemical reactivity, most notably in oxidative and radical‐mediated reactions. Chemiluminescence and spectrophotometric studies have been conducted to explore their interactions with ROS (hydroxyl and peroxyl radicals) and demonstrate that, although CLX and OXA exhibit little antioxidant capacity, each produces a measurable effect on radical‐induced reactions. These properties are useful for both understanding the biological actions of CLX and OXA and for developing new types of indirect analytical methods that rely on oxidative reactions. Studies of the environment have demonstrated that OXA has extremely limited biodegradability, contributing to its long‐term presence in wastewater treatment systems. The use of Advanced Oxidation Processes, such as ionizing radiation and radical‐driven reactions, has been shown to lead to the degradation of the β‐lactam structure, reducing the antibacterial activity and increasing biodegradability (Eb et al. 2021; Elmolla and Chaudhuri 2009; Wojnárovits et al. 2022).

The development of analytical testing methods for CLX and OXA poses multiple challenges arising from their chemical and pharmacological properties. The compounds require advanced detection methods because their structural instability and strong matrix interactions preclude detection by basic analytical methods. Although chromatographic methods serve as standard references due to their reliable performance and flexibility, they incur higher operational costs and impose more stringent handling requirements. Although electrochemical sensors and nanoscale detection systems offer improved detection capabilities and faster testing times, their performance suffers from challenges in maintaining consistent results and establishing common testing procedures. The research needs to assess different analytical methods because this will help identify the best techniques that provide precise measurement results across multiple material testing situations (Mahfoudhi et al. 2024; Larmené‐Beld et al. 2014; Cámara et al. 2013).

4. Analytical Challenges in CLX and OXA Analysis

The analytical determination of CLX and OXA is complicated because they have similar β‐lactam structures and physicochemical properties, and they behave similarly across a variety of matrices. Unlike many other small‐molecule drugs, these isoxazolyl penicillins also have inherent chemical instability, high protein binding, and limited direct detection, making them difficult to quantify accurately. While all of the above limitations are more easily addressed when working with pharmaceutical formulations, in matrices from biological, food, or environmental sources, these problems are magnified due to lower compound concentrations and additional interference from matrix complexity.

The main problem with these challenges is that the β‐lactam ring structure is susceptible to hydrolytic and oxidative damage during sample handling, preparation, and analysis. The material's instability has two negative effects: it destroys the analyte while producing transformation products that prevent detection. The determination of CLX and OXA becomes more complex because matrix‐dependent effects lead to varying extraction efficiencies and signal responses in protein‐rich biological samples and lipid‐containing food matrices.

Conventional analysis methods, such as spectrophotometry and HPLC with UV detection, have poor detection sensitivity (at trace levels) due to the lack of chromophores (chromophoric properties) of the compounds tested. Because CLX and OXA are in the same chemical class as β‐lactam antibiotics (similar structures), it will be difficult to achieve sufficient selectivity in the testing of these two drugs due to the potential for co‐elution/cross‐reactivity. The combined analysis of the analytic issues associated with CLX/OXA shows how these issues are interrelated and require new methods that deliver high performance by integrating their respective factors (such as stability control, matrix compatibility, detection sensitivity, and specificity). The next subsections will review these issues, specifically as they relate to the establishment of invalid methods (invalid genetic loci) and their impact on analytic performance.

4.1. Chemical Instability of the β‐Lactam Ring

The intrinsic instability of the β‐lactam ring, which serves as the fundamental structural element for their antibacterial properties, creates substantial challenges for analytical methods used to measure CLX and OXA. The two compounds are highly susceptible to non‐enzymatic degradation because their bulky isoxazolyl side chains protect them from β‐lactamase enzymes, resulting in deterioration under standard analytical testing conditions, including changes in pH and temperature and exposure to oxidizing agents. The unstable compound decomposes via hydrolytic ring‐opening to produce inactive substances, including penicilloic acids, which can coexist with the parent drug and disrupt precise measurement (Wadher Shailesh, Kalyankar Tukaram, and Shivpuje Shivraj 2017; Patel et al. 2015).

Trace‐level analysis poses serious challenges because even minor degradation in sample handling or preparation can significantly increase analytical error. OXA has been shown to undergo degradation via a radical‐mediated process, with the primary degradation occurring through hydroxyl radical attack, altering its β‐lactam structure and leading to the loss of its biological activity. Since CLX is structurally similar to OXA, it would be expected that both drugs would have similar pathways for degradation, particularly under oxidative and/or environmental conditions (Takács et al. 2022; Legrand et al. 2016; Mortensen et al. 2022).

The instability requires stability testing methods that can separate unaltered drug substances from their broken‐down components. The chromatographic methods HPLC and UHPLC offer sufficient separation, but their analytical performance must be controlled under precise conditions to avoid process contamination. The β‐lactam instability of these antibiotics serves as a fundamental restriction that affects both their identification process and the determination of their existence (Legrand et al. 2016; Patel et al. 2015).

4.2. Matrix Complexity and Sample Preparation

Analyzing how to determine CLX and OXA is complicated by the different matrices used to analyze these antibiotics. These include plasma, urine, milk, meat, and environmental waters. As a result, both CLX and OXA exhibit strong binding to proteins, lipids, and dissolved organic matter across these different matrix types. This binding affects extraction efficiencies and analytical responses; so, while both drugs bind to greater than 90% of the plasma proteins, the bound fraction of each drug greatly influences the recovery of free drug from the sample, thus quantitatively bounding recovered analytes to the efficacy with which the samples were prepared (Larmené‐Beld et al. 2014; Marchetti et al. 2001).

The proteins present in biological samples create a binding problem with CLX and OXA, which requires either protein precipitation or enzymatic treatment to free the bound fraction for analysis. The presence of fats and casein in milk and food matrices creates additional problems because this requires multiple extraction steps, including solid‐phase extraction (SPE) and molecularly imprinted polymer (MIP) cleanup, to achieve adequate selectivity. The analysis of environmental samples becomes more complicated because humic substances, salts, and coexisting pharmaceuticals can create matrix effects that suppress or enhance signals, depending on the chosen analytical method (Legrand et al. 2016; Díaz‐Bao et al. 2015).

Advanced sample preparation techniques yield better test results through higher selectivity and improved recovery rates. The testing procedures for these methods become more difficult because they require more time to complete and yield less dependable results. The matrix components that remain in the sample after processing pose different problems for instruments, including column fouling in chromatographic systems and electrode surface contamination in electrochemical sensors. The selection process for sample preparation methods requires evaluating three key factors, which include extraction efficiency, reproducibility, and detection technique compatibility (Du et al. 2018; Karageorgou et al. 2012).

The matrix complexity of CLX and OXA presents a significant challenge that directly impacts their analytical sensitivity and accuracy and the overall strength of the testing methods used to trace trace‐level and multiple residue samples (Karageorgou et al. 2012).

4.3. Limited Sensitivity of Conventional Methods

The difficulty of measuring CLX and OXA by conventional analytical techniques is mainly due to their limited inherent detectability, as they lack strong chromophoric groups in their chemical structures. Because of this, UV–Vis spectrophotometric techniques typically have high detection limits and are used primarily for the analysis of pharmaceutical formulations rather than for trace analysis of CLX or OXA in biological or environmental matrices. Similarly, the sensitivity of HPLC‐UV methods that are routinely used to perform quality control on pharmaceuticals would generally be insufficient for tracking residues because the concentrations typically found in the residue monitoring will be in the ng/mL or μg/L ranges (Gebretsadik et al. 2023; Vu and Do 2010; Rahman and Khan 2016; Obiyenwa et al. 2018; Gandhi and Sonawane 2018).

The restriction becomes especially important when examining complex matrices such as milk, plasma, and wastewater, because both CLX and OXA are present at low levels and matrix interference complicates their detection. The derivatization methods used to improve UV absorbance add complexity to the testing procedure and reduce the reproducibility of results. The exclusive use of traditional detection techniques results in two problems, which include both the wrong estimation of substance levels and the inability to find very small amounts of material (Vu and Do 2010; Ito et al. 2001).

The need for advanced analytical methods has been met by adopting LC–MS/MS and chemiluminescence and electrochemical sensors, which provide greater detection capacity and extended detection ranges. The methods require specialized equipment and expert knowledge, which create challenges for their use in ordinary laboratory environments (Mahfoudhi et al. 2024; Rezende et al. 2012).

The conventional analytical methods have a limited sensitivity, which creates major challenges for accurate CLX and OXA measurement in applications that need ultra‐trace detection and high analytical precision (Rezende et al. 2012).

4.4. Selectivity and Differentiation From Structurally Similar Compounds

Because of the high structural similarity among CLX, OXA, and many other β‐lactam antibiotics, selecting the right method for their selective determination will remain a major challenge. Like the other β‐lactam antibiotics, CLX and OXA are both β‐lactam compounds that have a β‐lactam moiety‐core, thiazolidine ring structure in common (with many derivatives, including ampicillin, penicillin G, dicloxacillin, and isoxazolyl penicillins), therefore increasing the likelihood of co‐elution of all these structures when analyzing pharmaceuticals, biological samples, or environmental matrices by chromatographic systems, and so may cause cross‐reactivity when using other non‐separative techniques (e.g., UV techniques) where the spectra of the compounds are similar (Cámara et al. 2013; Holstege et al. 2002).

Detecting multiple β‐lactams through simultaneous testing becomes more difficult in multi‐residue analysis. The standard testing conditions require that the mobile‐phase composition, gradient profiles, and column selection be optimized, as CLX and OXA exhibit only minimal differences in polarity and functional groups. The application of UHPLC advanced techniques fails to provide proper separation because complex matrices cause peak overlap, which results in quantification mistakes (Chen et al. 2017; Li et al. 2026).

Non‐chromatographic techniques face selectivity challenges through electrochemical methods and sensor‐based systems. MIPs, together with nanomaterial‐based sensors, achieve improved detection accuracy, but their performance depends on their ability to bind β‐lactams with similar molecular structures. The presence of multiple antibiotics causes two issues because it generates signal overlap and produces signal levels that exceed their true values (Li et al. 2026; Dorival‐García et al. 2016).

The close structural similarity among β‐lactam antibiotics prevents the development of methods to identify CLX and OXA separately. The problem requires separation methods with high selectivity, together with mass spectrometry as a confirmatory method, to achieve accurate identification and measurement results in complex testing environments (Varela‐Rey et al. 2025; Junza et al. 2011).

5. Analytical Strategies in CLX and OXA Determination

The analytical determination of CLX and OXA requires carefully selected strategies that directly address their β‐lactam instability, weak intrinsic detectability, and strong matrix‐dependent behavior. The drugs pose an analytical challenge because their measurement must account for both their actual content and their breakdown during testing, as well as their presence in complex samples and their resemblance to other β‐lactam antibiotics. The selection of a suitable analytical method requires consideration of specific analytical conditions, matrix characteristics, and sensitivity requirements.

Analytical methods for the determination of CLX and OXA have evolved into three primary types of instrumentation: chromatography, electrochemistry, and spectroscopy (each offering unique benefits for addressing these analytical issues). The primary benefit of chromatographic methods is the ability to separate CLX and OXA from their degradation products and from other penicillins that may be present, since both compounds are subject to degradation via β‐lactam ring hydrolysis. Electrochemical methods exploit the ability of CLX and OXA to undergo oxidation or reduction, thereby enabling detection of both compounds with improved sensitivity compared with chromatographic techniques; however, reproducibility is limited due to differences in electrode surface conditions. Spectroscopic methods are suitable for everyday pharmaceutical analysis, but because of the low UV absorbance of both compounds and the lack of selectivity in complex sample matrices, these techniques have limited utility in routine pharmaceutical analysis.

The analytical strategies work together because their distinct methods address the specific problems that arise during CLX and OXA measurements. The actual performance of these methods needs to be assessed through rigorous testing to determine their proper use across various testing scenarios. The testing results and limitations of these methods will be evaluated in the next sections of the document to determine their effectiveness in measuring CLX and OXA across different sample types.

5.1. HPLC

The primary analytical method for identifying CLX and OXA in products remains HPLC, as the technique can effectively separate these two highly similar β‐lactam antibiotics from all other substances present with them or formed during their breakdown. The β‐lactam ring structure requires a stability‐indicating separation because both CLX and OXA hydrolyze during sample handling before analysis. Most of the available methods use reversed‐phase high‐performance liquid chromatography (RP‐HPLC) with C18 columns and ultraviolet or diode array detection (UV or DAD) to enable simultaneous detection of CLX and OXA and other related penicillins in both pharmaceutical products and biological samples (Legrand et al. 2016; Clarin 2020).

HPLC methods for analyzing CLX and OXA have seen widespread use but also have limitations. One major problem with these two compounds is their very low UV absorption, which makes them hard to detect. This makes it even more difficult to detect them in the environment or in food, given the high demand for low detection limits. Additional optimizations to the method to improve testing include changing the mobile‐phase composition and pH, selecting different wavelengths, or using more advanced methods such as LC–MS/MS. Another issue is that the sample matrix contains so many components that multiple sample‐preparation steps (such as protein precipitation and SPE) are usually required to eliminate interferences and improve recovery. The extra steps required for testing take longer to complete and may produce unknown variations in the results (Mahfoudhi et al. 2024; Xie et al. 2022).

The analysis process requires a proper selectivity assessment to detect CLX and OXA while differentiating them from other β‐lactam antibiotics with similar retention properties. The combination of gradient elution with contemporary column systems yields better separations, but complete separation remains impossible without meeting optimal operating conditions. The analysis process requires precise control of temperature and mobile‐phase pH because CLX and OXA are prone to degradation during testing. The analysis process needs precise control of temperature and mobile‐phase pH because CLX and OXA face degradation risks during testing procedures (Rehm and Rentsch 2020; de Almeida et al. 2015).

HPLC is an effective and dependable method for measuring CLX and OXA, especially in pharmaceutical quality control and established laboratory environments. The method requires optimization to achieve adequate performance, while its sensitivity limitations, matrix effects, and operational challenges necessitate additional testing methods in complex situations (Gebretsadik et al. 2023; Rezende et al. 2012). The study includes representative chromatograms from published research, which are shown in Figure 3 to facilitate visual comparison of the analytical methods. The profiles demonstrate differences in retention time, resolution, and peak shape between the two methods, with RP‐HPLC producing clearly separated peaks and LC–MS/MS delivering sharper peaks with reduced analysis time, thereby improving method evaluation results by (Rathinavel et al. 2008). Table 2 presents a comprehensive description and tabulation of the analytical and experimental procedures used to identify CLX and OXA by chromatographic techniques.

FIGURE 3.

The chromatographic display for CLX and OXA from established methods shows different retention times, peak shapes, and analytical equipment resolution abilities (Rathinavel et al. 2008).

TABLE 2.

Summary of chromatographic approaches for evaluating the CLX and OXA drugs in diverse samples.

Analyte	Chromatographic conditions	Dynamic range	LOQ and LOD	Application	References
CLX	System: HPLC Detector: DAD (220 nm) Mobile phase: Formate buffer (pH 3, 100 mmol/L)/Acetonitrile/Methanol (73:12:15 → gradient to 12:88 B:C) Column: Nova‐Pak C18 (150 × 3.9 mm, 4 μm, 60 Å) Injection volume: 20 μL Retention time: 7.9 min Total run time: 15 min Flow rate: 1.0 mL/min	2.5–20 μg/mL	LOQ: 1.37 μg/mL (0.94 μg/mL in urine) LOD: 0.41–0.87 μg/mL	Human urine (spiked and real samples)	(Espinosa‐Mansilla et al. 2006)
CLX	System: HPLC Detector: PDA (323 nm, after derivatization) Mobile phase: Phosphate buffer (pH 6.5)/Acetonitrile/Methanol (gradient: A → B → C) Column: Nova‐Pak C18 (150 × 3.9 mm, 4 μm) Injection volume: 100 μL Retention time: ~30–40 min Total run time: 60 min Flow rate: 1.0 mL/min	1–2000 ng/mL	LOQ: < 20 ng/mL LOD: 11–14 ng/mL	Cattle and pig serum	(Sørensen and Snor 2001)
CLX	System: Capillary HPLC Detector: DAD (220 nm) Mobile phase: Water +0.01% TFA/ACN + 0.01% TFA (5% → 60% B gradient) Column: Luna C18 (150 × 0.5 mm, 5 μm) Injection volume: 7 μL Retention time: 12–14 min Total run time: 15–16 min Flow rate: 14 μL/min	Milk: 1.10–100 μg/L Meat: 1.20–400 μg/kg Water: 0.05–10 μg/L	LOQ: 3.6 μg/L (milk), 4.0 μg/kg (meat), 0.16 μg/L (water) LOD: 1.10 μg/L (milk), 1.20 μg/kg (meat), 0.05 μg/L (water)	Milk, chicken, and environmental water	(Bailón‐Pérez et al. 2009)
CLX	System: HPLC Detector: DAD (210 nm) Mobile phase: 25 mM phosphate buffer (pH 3.4)/Acetonitrile (gradient: 15% → 75% B) Column: Supelcosil LC‐18 (150 × 4.6 mm, 5 μm) Injection volume: 100 μL Retention time: 8–9 min Total run time: 10–13 min Flow rate: 1.0 mL/min	2–20 μg/kg	LOQ: 3.9 μg/kg LOD: 2.5 μg/kg	Ewe milk	(Cámara et al. 2013)
CLX	System: HPLC Detector: UV–Vis (206 nm) Mobile phase: Acetonitrile/0.008 M KH2PO4 buffer (pH 5.7) (30:70, v/v), isocratic Column: LiChroCART RP‐18e (150 × 4.6 mm, 5 μm) + guard column Injection volume: 20 μL Retention time: 4.6 min Total run time: 5–10 min Flow rate: 1.0 mL/min	13.03–28,019 ng/g	LOQ: 13.03 ng/g LOD: 4.30 ng/g	Bovine milk	(Burmańczuk et al. 2017)
CLX	System: RP‐HPLC Detector: UV (254 nm) Mobile phase: Acetonitrile:Phosphate buffer (pH 5) (35:65, v/v) Column: Hypersil C18 (250 × 4.6 mm, 5 μm) Injection volume: 20 μL Retention time: 7.9–8.1 min Total run time: 10–15 min Flow rate: 1.0 mL/min	20–100 μg/mL	LOQ: 0.010 μg/mL LOD: 0.00341 μg/mL	Capsule dosage form	(Battula and Shivaraj 2017)
CLX	System: RP‐HPLC Detector: UV (225 nm) Mobile phase: 0.01 M KH2PO4 buffer (pH 5.0): Acetonitrile (15:85, v/v) Column: Inertsil ODS‐2/C18 Retention time: 15–20 min Total run time: 20 min Flow rate: 5.0 mL/min	300–1500 μg/mL	LOD = 300 μg/mL	Tablet/pure formulation	(Ghule and Ramesh 2016)
CLX	System: RP‐HPLC Detector: UV (238.8 nm) Mobile phase: Water:Acetonitrile:Methanol (70:20:10, v/v/v) Column: C18 (250 × 4.6 mm, 5 μm) Injection volume: 20 μL Retention time: 14.036 min Total run time: 20 min Flow rate: 1.4 mL/min	20–100 μg/mL	LOQ: 0.247 μg/mL LOD: 0.082 μg/mL	Pharmaceutical dosage form	(Wadher Shailesh, Kalyankar Tukaram, and Shivpuje Shivraj 2017)
CLX	System: RP‐HPLC Detector: UV (225 nm) Mobile phase: Acetonitrile:0.002 M phosphate buffer (pH 3.0) (35:65, v/v) Column: P. Hypersil C18 (150 × 4.6 mm, 5 μm) Injection volume: 20 μL Retention time: 6.0 min Total run time: 10 min Flow rate: 1.0–1.8 mL/min	0.1728–0.2594 μg/mL	LOQ: 0.19 μg/mL LOD: 0.05 μg/mL	Capsule dosage form	(Swetha et al. 2017)
CLX	System: RP‐HPLC Detector: UV (225 nm) Mobile phase: Phosphate buffer (pH 3):Acetonitrile (70:30, v/v) Column: HiQsil C8 (250 × 4.5 mm, 5 μm) Injection volume: 50 μL Retention time: 6.0–6.1 min Total run time: 10 min Flow rate: 1.0 mL/min	5–30 μg/mL	LOQ: 0.439 μg/mL LOD: 0.145 μg/mL	Bulk and tablet dosage form	(Madhuri and Priyanka 2020)
CLX	System: RP‐HPLC Detector: UV (225 nm) Mobile phase: 30 mM KH2PO₄ buffer (pH 4.0)/Acetonitrile (gradient: 10% → 72% B) Column: Shodex C18 (250 × 4.6 mm, 5 μm) Injection volume: 20 μL Retention time: 11–13 min Total run time: 16 min Flow rate: 1.0 mL/min	50–300 μg/mL	LOD: 50 μg/mL	Pharmaceutical formulations (capsules, powders for injection)	(Gebretsadik et al. 2023)
CLX	System: Headspace Gas Chromatography Detector: Flame Ionization Detector (FID) Mobile phase/Carrier gas: Nitrogen (velocity 37.3 cm/s; pressure 10 kPa; split 1:1) Column: Elite‐5 fused silica capillary column (30 m × 0.32 mm) Retention time: Methanol (~2.78 min), Ethyl acetate (~4.38 min), Toluene (~6.53 min) Total run time: ~35 min Flow rate: Controlled via carrier gas (GC system)	Methanol: 200–3000 μg/mL Ethyl acetate: 100–1000 μg/mL Toluene: 100–500 μg/mL	LOQ: 50 μg/mL LOD: 30 μg/mL	Drug	(Gujral et al. 2010)
CLX	System: HPLC Detector: Diode‐array UV (350 nm) Mobile phase: Phosphate buffer (with Na2S2O3 + tetrabutylammonium hydrogen sulfate as ion‐pair reagent)/Acetonitrile (gradient: 5% → 85% B) Column: C‐2 column (150 × 5 mm, 10 μm) Injection volume: 400–450 μL Retention time: 19.3 min Total run time: 30 min Flow rate: 1.0 mL/min	4–80 μg/L	LOQ: 4 μg/L	Residues in cow milk	(Marchetti et al. 2001)
CLX	System: UPLC–MS/MS Detector: Tandem mass spectrometry (ESI+, MRM mode; transition m/z 436 → 160) Mobile phase: Water +0.1% formic acid (A)/Acetonitrile +0.1% formic acid (B) (gradient: 60:40 → 40:60, followed by 95% ACN wash) Column: BEH C18 (2.1 × 50 mm, 1.7 μm) Injection volume: 20 μL Retention time: 0.77 min Total run time: 2–3 min	0.1–5.0 mg/L	LOQ (LLOQ): 0.1 mg/L	Microanalysis samples	(Larmené‐Beld et al. 2014)
CLX	System: RP‐HPLC Detector: UV (224 nm) Mobile phase: 20 mM KH2PO₄ buffer (pH 3.0, OPA): Acetonitrile (20:80, v/v), isocratic Column: Thermo C18 (250 × 4.6 mm, 5 μm) Injection volume: 20 μL Retention time: 3.989 min Total run time: < 6 min Flow rate: 1.0 mL/min	5–25 μg/mL	LOQ: 0.271 μg/mL LOD: 0.095 μg/mL	Bulk and capsule dosage form	(Chourasiya et al. 2019)
CLX	System: HPLC Detector: UV (225 nm) Mobile phase: Acetonitrile:Potassium acetate buffer (pH 6) (5:95, v/v) Column: Kromasil ODS C18 (150 × 4.6 mm, 5 μm) Injection volume: 20 μL Flow rate: 0.8 mL/min	0.5–500 μg/g	LOQ: 0.1 μg/g LOD: 0.03 μg/g	Shrimp samples	(Du et al. 2018)
CLX	System: HPLC Detector: PDA (Photodiode Array Detector), 240 nm Mobile phase: A = 0.1% TFA (aqueous)/B = ACN–MeOH (90:10 v/v) → gradient: 85:15 → 50:50 (20 min) → 30:70 (25 min) Column: Perfectsil ODS‐2 C18 (250 × 4 mm, 5 μm) Injection volume: 50 μL Retention time: 21.0–21.1 min Total run time: 22–25 min Flow rate: 1.1 mL/min	1–10 ng/μL	LOQ: 10 ng/μL LOD: 3 ng/μL	Bovine plasma and veterinary drug formulations	(Samanidou et al. 2009)
CLX	System: RP‐HPLC Detector: UV (225 nm) Mobile phase: Phosphate buffer (pH 5.0): Acetonitrile:Methanol (80:17:3, v/v/v), isocratic Column: C18 (250 × 4.6 mm, 5 μm) Injection volume: 20 μL Retention time: 6.2 min Total run time: 10 min Flow rate: 2.0 mL/min	400–600 μg/mL	LOD = 400 μg/mL	Tablet dosage form	(Rathinavel et al. 2008)
CLX	System: RP‐HPLC Detector: UV (225 nm) Mobile phase: 0.01 M KH2PO4 buffer: Methanol (45:55, v/v), isocratic Column: Apollo C18 (150 × 4.6 mm, 5 μm) Injection volume: 20 μL Retention time: 4.00 min Total run time: 6–8 min Flow rate: 1.0 mL/min	60–140 μg/mL	LOD = 60 μg/mL	Capsule dosage form	(Vu and Do 2010)
CLX	System: RP‐HPLC Detector: UV/PDA (225 nm) Mobile phase: Acetonitrile:Phosphate buffer (pH 5.0) (gradient: 15:85 → 30:70 → 15:85 over 20 min) Column: Inertsil ODS‐2 C18 (250 × 4.6 mm, 5 μm) Injection volume: 5 μL Retention time: 12.2–12.5 min Total run time: 20 min Flow rate: 1.0 mL/min	50–1000 μg/mL	LOD = 50 μg/mL	Capsule dosage form	(Kumar et al. 2007)
CLX	System: UHPLC Detector: UV–DAD (230 nm for CLX) Mobile phase: 10 mM phosphoric acid (A)/Acetonitrile (B), gradient: 0–1 min (100% A), then B ↑ to 55% (1–11 min), re‐equilibration to initial (11–13 min) Column: Hypersil Gold PFP (2.1 × 100 mm, 1.9 μm) Injection volume: 10 μL Retention time: 11.46 min Total run time: ≤ 13 min Flow rate: 0.5 mL/min	2–100 mg/L	LOQ (LLOQ): 2 mg/L	Human plasma	(Legrand et al. 2016)
CLX	System: RP‐UPLC Detector: UV/PDA (225 nm) Mobile phase: A: 20 mM phosphate buffer (pH 6.8)/B: Methanol: Acetonitrile (75:25), gradient elution Column: BEH C18 (2.1 × 100 mm, 1.7 μm) Injection volume: 10 μL Retention time: 6.9 min Total run time: 13 min Flow rate: 0.35 mL/min	0.025–75 μg/mL	LOD = 0.025 μg/mL	Bulk and pharmaceutical formulation	(Patel et al. 2015)
CLX	System: HPLC Detector: DAD (210 nm) Mobile phase: Water (A)/Acetonitrile (B), gradient: 5%–22% B (0–6 min), 22%–10% B (6–6.5 min), re‐equilibration to 22% B (up to ~12–13 min) Column: C18‐PFP (150 × 4.6 mm, 3 μm) Injection volume: 20 μL Retention time: 6–8 min Total run time: 12–13 min Flow rate: 0.4–0.9 mL/min	0.05–1.5 μg/L	LOD: 0.29–0.37 μg/L LOQ: 0.8–0.98 μg/L	Drinking and river water	(Garcinuño et al. 2023)
CLX	System: LC with on‐line RAM Detector: UV (215 nm) Mobile phase: Phosphate buffer (25 mM, pH 4.0):Acetonitrile (72:28, v/v), isocratic Column: Nova‐Pak C18 (150 × 3.9 mm, 4 μm) + RAM pre‐column (XDS‐DEAE) Injection volume: 100 μL Retention time: 10–12 min Total run time: 17 min Flow rate: 1.2 mL/min	50–5000 ng/mL	LOQ: 50 ng/mL LOD: 15 ng/mL	Human plasma	(Rbeida et al. 2005)
CLX	System: RP‐HPLC Detector: UV/PDA (215 nm & 254 nm) Mobile phase: Buffer (tetrabutylammonium hydroxide, pH 6.8):Acetonitrile, gradient elution (A: 850:150, B: 250:750) Column: Symmetry C18 (75 × 4.6 mm, 3.5 μm) Injection volume: 20 μL Retention time: 31.23 min Total run time: 50 min Flow rate: 1.0 mL/min	1–15 μg/mL	LOQ: 1.136 μg/mL	Pharmaceutical manufacturing	(Trivedi et al. 2012)
CLX	System: RP‐HPLC Detector: UV (225 nm) Mobile phase: Phosphate buffer (25 mM, pH 4.6): Methanol:Acetonitrile (40:45:15, v/v/v), isocratic Column: CAPCELL PAK C8 (250 × 4.6 mm, 5 μm) Injection volume: 10 μL Retention time: 9.18–9.19 min Total run time: 11 min Flow rate: 1.0 mL/min	0.5–40 μg/mL	LOQ: 0.39 μg/mL LOD: 0.03 μg/mL	Human plasma	(Bhinge et al. 2012)
CLX	System: HPLC Detector: UV (225 nm) Mobile phase: Acetonitrile:tetra‐butyl ammonium hydroxide buffer in the ratio of 45:55 and pH adjusted to 4 with orthophosphoric acid Column: HiQ sil C‐8 (4.6 × 250 mm) Injection volume: 20 μL Retention time: 11.90 min Flow rate: 1.0 mL/min	25–125 μg/mL	LOD = 0.18 μg/mL	Tablet dosage form	(Wankhede et al. 2010)
CLX	System: HPLC Detector: UV (225 nm) Mobile phase: 30 mM phosphate buffer, pH 4.0 (mobile phase A) and acetonitrile (mobile phase B) Column: Shodex C18 (250 3 4.6 mm, 5 mm) Injection volume: 20 μL Flow rate: 1 mL/min	0.05–0.3 mg/mL	LOD = 0.05 mg/mL	Pharmaceutical formulations	(Eticha and Gebretsadikan 2022)
CLX	System: HPLC Detector: UV Detector Mobile phase: water solution containing 6.3 mmol/L NaHCO3 and 1.1 mmol/L Na2CO3 Column = TSK gel Super IC‐AP anion column (4.6 × 150 mm,6 μm) Injection volume: 10 μL Retention time: 3 min Total run time: 5 min Flow rate: 0.8 mL/min	0.99–99 μg/mL	LOD = 0.99 μg/mL	Drug	(Wen et al. 2016)
CLX	System: HPLC Detector: UV (225 nm) Mobile phase: Acetonitrile and Phosphate buffer pH 5 Column = Hypersil C18, 250 × 4.6 mm, 5 μ Injection volume: 20 μL Retention time: 7.907 min Flow rate: 1 mL min−1	NA	NA	Capsule dosage form	(Dharmamoorthy et al., 2022)
CLX	System: LC–MS Detector: Tandem mass spectrometry (ESI+, MRM mode; transition) Column: C18 Injection volume: 5 μL Flow rate: 1 mL/min	0.5–100 μg/mL	LOD = 0.5 μg/mL	Capsule dosage form	(Mahfoudhi et al. 2024)
CLX	System: HPLC Detector: UV (225 nm) Mobile phase: 0.02 mol/L phosphate buffer–acetonitrile 65:35, adjusted pH to 4.6 with phosphoric acids Column = Sino Chrom ODS‐BP column (5 μm, 250 × 4.6 mm) Injection volume: 20 μL Flow rate: 1.1 mL/min	0.25–40.0 μg/mL	LOD = 0.20 μg/mL	Plasma samples	(Ma et al. 2007)
CLX	System: HPTLC Mobile phase: n‐Butanol:Methanol:Water:Formic acid (8:6:4:0.3 v/v/v)	150–600 ng/spot	LOQ = 60 ng/spot LOD = 20 ng/spot	Tablet dosage form	(Pawar et al. 2010)
OXA	System: Capillary HPLC–DAD Detector: Diode array detector (DAD), λ = 220 nm Mobile phase: Solvent A: Water +0.01% TFA Solvent B: Acetonitrile +0.01% TFA Column: Luna C18 (150 × 0.5 mm, 5 μm) Injection volume: 7 μL Flow rate: 14 μL/min Retention time: 15–16 min Total run time: 16 min	A. Cow raw milk Dynamic range: 1.20–100 μg/L B. Chicken muscle dynamic range: 1.10–400 μg/kg C. Well water dynamic range: 0.05–10 μg/L D. River water dynamic range: 0.06–10 μg/L	A. Cow raw milk LOD: 1.20 μg/L LOQ: 4.00 μg/L B. Chicken muscle LOD: 1.10 μg/kg LOQ: 3.80 μg/kg C. Well water LOD: 0.05 μg/L LOQ: 0.16 μg/L D. River water LOD: 0.06 μg/L LOQ: 0.20 μg/L	Milk Chicken meat Environmental waters (river and well water)	(Bailón‐Pérez et al. 2009)
OXA	System: LC–DAD Detector: DAD (210 nm) Mobile phase: 25 mM phosphate buffer (pH 3.4)/Acetonitrile (gradient) Column = Supelcosil LC‐18 DB (15 cm × 4.6 mm, 5 μm) Injection volume: 100 μL Retention time: 8–9 min Total run time: 10 min Flow rate: 1 mL/min	2–20 μg·kg−1	LOQ = 3.9 μg·kg−1 LOD = 2.5 μg·kg−1	Ewe milk samples	(Cámara et al. 2013)
OXA	System: HPLC–UV Detector: UV detection at 270 nm Mobile phase: Octanesulphonic acid buffer (pH 2.52)/Acetonitrile–Methanol (gradient, ion‐pair) Column = Nova‐Pak Phenyl column (150 × 3.9 mm) Injection volume: 100 μL Retention time: 45.98 min Total run time: 45–50 min Flow rate: 1.0 mL·min−1	20–200 mg/kg	LOQ = 20 mg/kg	Raw bovine milk	(Sørensen and Snor 2000)
OXA	System: HPLC–DAD Detector: Diode‐array detector (350 nm for CLX derivative) Mobile phase: Acetonitrile/phosphate buffer (with sodium thiosulfate + tetrabutylammonium hydrogen sulfate as ion‐pair reagent; gradient) Column = C‐2 column (150 × 5 mm, 10 μm) Injection volume: 400–450 μL Retention time: 19.3 min Total run time: 30 min Flow rate: 1 mL/min	4–80 μg/L	LOD = 10 μg/L	Cow's milk	(Marchetti et al. 2001)
OXA	System: HPLC–UV/DAD Detector: UV detection (220–240 nm) Mobile phase: Water (buffer, often phosphate or TFA)/Acetonitrile (isocratic or gradient) Column = C18 column (typical dimensions: 150–250 × 4.6 mm, 5 μm)	NA	LOD = 0.04–0.06 μg/L (water samples) 0.80–1.40 μg/L (food samples) 1–2 ng/mL (milk/beef) 6–12 μg/kg (milk)	Milk Chicken muscle Beef Environmental water Pharmaceutical and biological samples	(Lara et al. 2012)
OXA	System: UHPLC–UV Detector: UV detection at 230 nm Column = Hypersil Gold PFP column (2.1 × 100 mm, 1.9 μm) Mobile phase: A = 10 mM phosphoric acid B = Acetonitrile Mode: Gradient elution Flow rate: 500 μL/min Column temperature: 40°C Injection volume: 10 μL Retention time: 11.46 min Total run time: ≤ 13 min	2–100 mg/L	LLOQ: 2 mg/L	Human plasma	(Legrand et al. 2016)
OXA	System: LC–MS Detector: PDA detector, 215 and 254 nm Column = Symmetry C18 (4.6 × 75 mm, 3.5 μm) Mobile phase: Solvent A = Buffer (tetrabutylammonium hydroxide, pH 6.8): acetonitrile (850:150) Solvent B = Buffer: acetonitrile (250:750) Flow rate: 1.0 mL/min Injection volume: 20 μL Retention time: 31.23 min Total run time: 50 min	1–15 μg/mL	LOQ: 1.136 μg/mL	Pharmaceutical production	(Trivedi et al. 2012)

When evaluating chromatographic results for samples, it is evident that each drug exhibits varying levels of effectiveness depending on matrix complexity and analytical needs. Most RP‐HPLC‐UV/DAD methods that have been employed for pharmaceutical dosage forms (tablets, capsules, bulk drug) have appropriate performance characteristics when evaluated within a dynamic range of μg/mL (for example: 5–100 μg/mL or greater), short retention periods of approximately four to 10 min, and limited sensitivity of less than or equal to 0.03–0.40 μg/mL or 0.1–0.5 μg/mL as determined by the LOD, and thus are ideal for routine quality control involving these types of drugs due to their ease of use, reproducibility, and low cost; however, there are exceptions to this as some RP‐HPLC‐UV/DAD methods will display limited sensitivity of LOD ranging from 5 to 400 μg/mL, which is indicative of inadequate optimization and limits those methods for use beyond high concentration formulations.

Conversely, biological matrices (plasma, serum, urine) require much greater sensitivity and selectivity than traditional analytical techniques because of protein binding, endogenous interference, and low concentrations of analyte; therefore, LC/MS/MS and UPLC/MS/MS are clearly superior to traditional HPLC by offering approximately ng/mL LOD in very short (< 3 min) analysis times, very low LOD, excellent selectivity, while HPLC/UV often requires derivatization, large‐volume injections and still has problems with matrix effects, resulting in longer analysis times and decreased robustness. For analysis of animal products (milk, meat, shrimp) due to total fat and total protein complexity, both capillary HPLC/DAD and optimized HPLC/UV can provide μg/kg to μg/L detection levels, which are adequate for monitoring residues, with reasonable time frames (approximately 10–16 min); however, sensitivity is variable depending on how the sample was prepared, and although certain methods are showing low LODs (approximately 0.03 μg/g), they continue to show lower selectivity compared with methods that use mass spectra.

Capillary or HPLC‐DAD can be used to analyze environmental samples (river water, drinking water) where analytes are present at ultra‐trace levels (μg/L to below μg/L); however, there are still limitations with respect to selectivity and interference removal when compared with LC–MS/MS, which would be the best choice for confirmatory analysis but typically costs more. For veterinary and residue analysis of animal‐derived samples, derivatization in HPLC‐PDA and ion‐pair chromatography will provide improved sensitivity down to the ng/mL level; however, these methods require lengthy run times of 60 min or more and increased methodological complexity, making them less effective for high‐throughput applications.

The study shows that RP‐HPLC–UV/DAD represents the optimal method for testing pharmaceutical formulations, whereas capillary HPLC and UHPLC show equal performance for analysis of food and environmental samples, and LC–MS/MS and UPLC–MS/MS serve as the most effective methods for testing biological samples and ultra‐trace analysis because they deliver superior results, although they require more complex operations.

From a critical perspective, there is no single best way to do things. While the standard dual‐UV HPLC method is cost‐effective and yields good results, it cannot separate components in many complex sample matrices. Derivatization can increase sensitivity, but it also has greater time and variability than an HPLC system would normally have. There are advantages and disadvantages to using a capillary or UHPLC system over an HPLC system in terms of efficiency; however, they also require substantial effort for sample prep. On the other hand, using an LC/MS–MS method to detect compounds has some advantages, such as higher sensitivity and selectivity; however, it also has disadvantages, namely the costs associated with running the method and matrix effects (e.g., suppression). While studies conducted thus far on available methods for testing compounds have produced mixed results, it is very difficult to make direct comparisons among them. The decision‐making process involved in selecting a method for testing compounds should include three items: (1) the level of detection performance; (2) the complexity of the sample matrix in question; and (3) the practicality of using the method (e.g., cost and ease of use). Future research should focus on developing standardized, cost‐effective stability testing methods.

Although HPLC remains the most widely employed analytical technique for determining CLX and OXA, its suitability varies considerably depending on the analytical objective and sample matrix. For pharmaceutical quality control, HPLC provides excellent robustness, reproducibility, and regulatory acceptance while maintaining relatively low operational costs. However, conventional HPLC coupled with UV detection is fundamentally limited by the weak chromophoric properties of CLX and OXA, resulting in insufficient sensitivity for monitoring trace‐level residues in biological and environmental samples. Furthermore, extensive sample preparation is frequently required to minimize matrix interference, thereby increasing analytical time and potential variability. Compared with LC–MS/MS, HPLC generally exhibits higher detection limits and lower selectivity when structurally related β‐lactam antibiotics coexist. Consequently, HPLC should be regarded as the preferred technique for routine pharmaceutical analysis and stability studies, whereas more advanced chromatographic approaches are recommended whenever ultra‐trace quantification or highly complex matrices are involved. LC–MS/MS currently represents the analytical benchmark for determining CLX and OXA because it combines outstanding sensitivity, excellent molecular selectivity, and reliable confirmation of analyte identity. These advantages make the technique particularly valuable for pharmacokinetic investigations, therapeutic drug monitoring, food residue surveillance, and environmental analysis where analyte concentrations are often extremely low. Nevertheless, its widespread implementation remains constrained by high instrument cost, extensive maintenance requirements, and the need for experienced personnel. Matrix‐induced ion suppression or enhancement remains a significant analytical challenge, necessitating rigorous sample preparation and careful validation. Therefore, although LC–MS/MS offers the highest analytical performance, its routine use may not be economically justified for laboratories that perform only pharmaceutical quality control.

The superior analytical performance of chromatographic methods is primarily attributed to efficient chromatographic separation combined with highly selective detection. Appropriate stationary‐phase selection, optimized mobile‐phase composition, and gradient elution improve analyte resolution and reduce matrix interference. When coupled with tandem mass spectrometry, molecular selectivity is further enhanced through precursor‐to‐product ion monitoring, allowing accurate quantification of trace concentrations in complex biological and environmental samples.

5.2. Electrochemical Techniques

Voltammetric methods are the most reliable for CLX and OXA assays because their electroactive functional groups are present at both the β‐lactam and isoxazolyl structural sites. Electrochemical methods provide high sensitivity, rapid response times, and low operational costs, making them ideal for analyzing pharmaceuticals and monitoring environmental conditions that require extreme sensitivity and trace‐level detection across diverse environmental materials. Research has demonstrated that modified electrodes containing nanomaterials or MIPs enable improved electron transfer rates and enhanced signal detection capabilities for β‐lactam antibiotics, including CLX and OXA (Golkarieh et al. 2021; Koseoglu and Demirhan 2025).

The performance of electrochemical methods depends on two factors: matrix effects and electrode surface characteristics, which make it difficult to achieve reliable results and to use the methods under different testing conditions. Complex matrices in biological fluids and wastewater contain interfering species such as proteins, salts, and organic compounds, which lead to signal suppression, electrode fouling, and nonspecific responses, rendering accurate measurement impossible. The problem is especially pronounced for CLX and OXA because their active components in the samples interact with the matrix materials at the concentrations detected (Golkarieh et al. 2021; Koseoglu and Demirhan 2025).

Selectivity is another challenge due to potential overlap with structurally related β‐lactam antibiotics (e.g., CLX and OXA) or electrically active materials, making detection of CLX and OXA difficult. While modification techniques used to enhance selectivity can improve detection times and increase precision in CLX and OXA measurements, they often require precise fabrication and optimization to yield informative results and performance that may differ across detectors. Furthermore, long‐term stability and reproducibility are still issues, especially in nanosensor applications, where variability or degradation of a surface eventually may lead to variable analysis of CLX and OXA (Golkarieh et al. 2021; Rohani Moghadam et al. 2019).

Electrochemical techniques have developed into useful complementary methods that support chromatographic methods, especially for rapid and field testing. The determination of CLX and OXA through these methods requires precise control over three aspects, which include electrode material selection, experimental condition setup, and sample preparation testing to achieve accurate results (Rohani Moghadam et al. 2019; Benachio et al. 2021). Figure 4 illustrates the general electrochemical sensing strategy for determining CLX and OXA. Following electrode modification and functionalization, interaction of the analytes with the modified surface generates an electrochemical signal proportional to their concentration. As demonstrated by the representative voltammograms, modified electrodes enhance analytical sensitivity, selectivity, and signal response, highlighting their potential for rapid and reliable determination of β‐lactam antibiotics (Jafari, Dehghani, Nasirizadeh, and Baghersad 2019) (Rohani Moghadam et al. 2019). In the electroanalytical procedures for CLX and OXA analysis listed in Table 3, Sensitivity, electrode types, and medium compositions vary significantly.

FIGURE 4.

Representative differential pulse voltammograms of CLX and OXA and schematic illustration of the electrochemical sensor fabrication, sensing mechanism, and signal generation for their determination (Jafari, Dehghani, Nasirizadeh, and Baghersad 2019) (Rohani Moghadam et al. 2019).

TABLE 3.

Overview of electroanalytical methods utilized to analyze CLX and OXA in different samples.

Analyte(s)	Method	Modification and medium	Linear range	LOD/LOQ and sample	References
CLX CLX	DPV DPV	Working electrode (WE): Screen‐printed carbon electrode (SPCE) modified with graphene oxide (GO) and gold nanorods (AuNRs) Reference electrode (RE): Integrated in SPCE (Ag/AgCl typical) Auxiliary electrode (AE): Integrated carbon electrode (SPCE) Buffer solution (BS): 0.1 M phosphate buffer, pH = 7.0 WE: Carbon ceramic electrode (CCE) modified with MIP + MWCNT RE: Ag/AgCl AE: Platinum electrode BS: 0.1 M phosphate buffer (pH 7.0)	5.0–775.0 nM 110–750 nM	LOD: 1.6 nM Sample = Aqueous solutions (environmental water/adsorption experiments) LOD = 100 nM Sample = Milk	(Golkarieh et al. 2021) (Jafari, Dehghani, Nasirizadeh, and Baghersad 2019)
CLX	DPV	WE: Screen‐printed carbon electrode (SPCE) modified with graphene oxide (GO) + gold nanoparticles (AuNPs) + MIP (pre‐concentration step) RE: Not explicitly stated (standard SPCE system) AE: Not explicitly stated BS: 0.1 M phosphate buffer (pH 7.0)	110–750 nM	LOD = 36 nM Sample = Milk	(Jafari, Dehghani, Nasirizadeh, Baghersad, and Azimzadeh 2019)
CLX	Electrochemical Impedance Spectroscopy (EIS)/Photoelectrochemical (PEC–EIS)	WE: ITO glass modified with PAH/POM (poly (allylamine hydrochloride) + tetrabutylammonium octamolybdate) RE: Saturated calomel electrode (SCE) AE: Platinum plate Electrolyte: 10−2 M ammonium acetate buffer (pH 7) Condition: Dark + UV illumination (320 nm LED)	10−11—10−7 M	LOD: 10−11–10−11.5 M Sample: Aqueous systems (water/wastewater context)	(Najlaoui et al. 2019)
CLX	DPV	WE = MWCNT‐modified carbon composite (MWCNT/CC) RE = Ag/AgCl AE = platinum wire BS = phosphate buffer pH = 5	20–950 nM	LOD = 8.0 nM Sample = Pharmaceutical contaminants	75
CLX	DPV	WE = NT1/AY/PGE, NT2/AY/PGE, NT1/AY/GCE, NT2/AY/GCE, NT1/AY/PtE, NT2/AY/PtE RE = Ag/AgCl AE = platinum wire BS = phosphate buffer pH = 5	0.05–0.5 mM	LOD = 0.0088 mM, 0.0141 mM, 0.0118 mM, 0.0126 mM, 0.0165 mM, and 0.0118 mM for NT1/AY/PGE, NT2/AY/PGE, NT1/AY/GCE, NT2/AY/GCE, NT1/AY/PtE, NT2/AY/PtE Sample = Real samples	(Koseoglu and Demirhan 2025)
CLX	CV	WE = glassy carbon electrode RE = Ag/AgCl AE = platinum wire BS = phosphate buffer pH = 3	NR	NR Sample = Pharmaceutical dosage forms	(Vidyasagar et al. 2012)
OXA	SWV	WE: Hanging Mercury Drop Electrode (HMDE) RE: Ag/AgCl AE: Platinum wire BS: Britton–Robinson (B–R) buffer, pH 7.4	NA	NA Sample = Aqueous solution	(Coşkun et al. 2017)
OXA	SWV	WE: Hanging Mercury Drop Electrode (HMDE) RE: Ag/AgCl AE: Platinum wire BS: Britton–Robinson (B–R) buffer, pH 7.0	4.9 × 10−10–1.0 × 10−7 M	LOD = 1.2 × 10−10 M Sample = Pharmaceutical dosage forms	(Biçer and Coşkun 2007)
OXA	DPV	WE = Boron‐Doped Diamond Electrode (BDDE) RE = Ag/AgCl (3 M KCl) AE = Platinum wire BS = 0.2 M acetate buffer (pH 4.5)	50–1000 μM	LOD = 10.9 μg/mL Sample = Pharmaceutical capsules, Human urine, River water	(Feier et al. 2017)
OXA	Electrochemical anodic oxidation (Ti/IrO2 anode system)	Anode = Ti/IrO2 (DSA electrode) Cathode = Zirconium spiral electrode Electrolyte = NaCl (0.05–0.4 mol L−1) Reactor = Undivided electrochemical cell pH = 3–9 (optimal ≈ natural pH ~ 6)	0.006–1.624 mM	LOD = 0.006 mM Sample = Water (environmental/wastewater matrices)	(Giraldo et al. 2015)
OXA	DPV	WE = Indium Tin Oxide (ITO) electrode Modification = MIP/Co nanoparticles–chitosan/β‐cyclodextrin–MWCNTs nanocomposite RE = Saturated Calomel Electrode (SCE) AE = Platinum wire BS = Phosphate buffer (0.2 M, pH 7.0)	0.0002–0.1 mM	LOD = 0.0000069 mM Sample = Human blood serum	(Hu et al. 2012)
OXA	Potentiometry	WE = PVC membrane ion‐selective electrode Modification = Organic ion exchanger (tetraalkylammonium, TAA) + silver complex Ag (Ox)2 − RE = Ag/AgCl electrode BS = Aqueous solution (pH = 7.5)	0.05–100 mM	LOD = 0.006 mM Sample = Model mixtures (β‐lactam antibiotics), aqueous solutions	(Kulapina and Snesarev 2012)
OXA	DPV	WE = Screen‐printed carbon electrode (SPCE) Modification = Molecularly imprinted polyaniline (MIP)/gold nanourchins (GNU)/graphene oxide (GO) RE = Ag/AgCl (integrated SPCE) AE = Platinum (integrated SPCE) BS = Phosphate buffer (0.1 M, pH 7.0)	0.0000007–0.000575 mM	LOD = 0.0000002 mM Sample = Milk (cow's milk samples)	(Rohani Moghadam et al. 2019)

Abbreviations: CV, cyclic voltammetry; DPV, differential pulse voltammetry; SWV, square‐wave voltammetry.

Electroanalytical methods (summarized in Table 3) exhibit considerable variation in performance depending on the electrode type and, more importantly, on the sample matrix, enabling direct comparison between CLX and OXA. For CLX determined in aqueous and environmental water samples, the PEC–EIS method outperformed all other methods by 4 orders of magnitude based on a LOD of approximately 10⁻¹¹ mol L⁻¹ over a broad linear range (10⁻¹¹–10⁻⁷ molL⁻¹) due to the photochemical enhancement provided with this technique; while the DPV method with GO/AuNRs–SPCE had a LOD of 1.6 nm (linear range: 5–775 nm) and MWCNT/CC based electrodes had a LOD of 8 nm (range: 20–950 nm), showing that nanostructured electrodes have improved sensitivity, but they do not have the same capability as PEC–EIS, while non‐nanostructured NT/AY modified electrodes only show significantly higher ranges (0.05–0.5 mM), which are not suitable for trace environmental monitoring due to trace concentrations > LOD.

When it comes to environmental OXA analysis, electrochemical oxidation systems have a much lower detection limit (LOD: 0.006 mM) than other methods; therefore, they are best suited for degradation rather than quantification. In drug formulations, SWV with HMDE has much higher sensitivity (LOD 1.2 × 10⁻¹⁰ M; 4.9 × 10⁻¹⁰–1.0 × 10⁻⁷ M) than DPV with BDDE (LOD 10.9 μg/mL; 50–1000 μg/mL). Thus, mercury‐based electrodes still provide superior electroanalytical performance, despite their toxicity and sustainability concerns, while CV‐based CLX approaches have not been shown to achieve high sensitivity, making them less reliable for accurate quantification. In biological matrices, such as human plasma or serum, the MIP/Co‐chitosan/β‐CD‐MWCNT‐modified ITO electrode provides good sensitivity (LOD 6.9 × 10⁻⁶ mM; 0.0002–0.1 mM) and is far better than potentiometric sensors (LOD 0.006 mM; 0.05–100 mM), indicating the importance of molecular imprinting and nanocomposite design in mitigating matrices and increasing selectivity.

The use of MIP‐based DPV systems for milk CLX quantification yielded LODs of 100 and 36 nM (in the range of 110–750 nM), signifying that these MIP systems have acceptable levels of selectivity but lower sensitivity due to interference from proteins and fats; conversely, the SPCE‐MIP/GNU/GO system for OXA has LODs of 2 × 10⁻⁷ μM (in the range of 7 × 10⁻⁷–5.75 × 10⁻⁴ mM) and provides superior performance to all other CLX–milk quantification methods due to the synergistic impact of nano‐structures and imprinting in both the MIP and SPCE substrates. Ultimately, based on comparison using four sample types, PEC–EIS is indisputably the most appropriate method for environmental water due to its capability to detect ultratrace levels, SWV (HMDE) as the method of choice for pharmaceutical formulations as a result of very low LODs, nanocomposite DPV sensors being ideally suited for biological matrices as a result of a balance between sensitivity and selectivity, and MIP‐based nanostructured SPCE systems being the best‐suited technique for food products as a function of selectivity.

Advanced electroanalytical techniques offer greater sensitivity than existing methods, but their high implementation costs, operational difficulties, and inconsistent stability limit their effectiveness. The use of mercury‐based electrodes poses environmental problems, while basic methods do not achieve the required detection sensitivity, so we must find a method that combines effective performance, practical applicability, and an environmentally friendly design.

Electrochemical approaches have emerged as attractive alternatives because they provide rapid analysis, relatively inexpensive instrumentation, low sample consumption, and excellent portability. The incorporation of nanomaterials, MIPs, and advanced electrode materials has substantially improved analytical sensitivity, in some cases approaching that of chromatographic techniques. Despite these advantages, electrochemical methods remain limited by insufficient standardization, electrode fouling, reproducibility issues, and a lack of inter‐laboratory validation studies. Most reported sensors have been evaluated under laboratory conditions using limited sample numbers, making their long‐term robustness uncertain. Consequently, electrochemical techniques currently complement rather than replace chromatographic methods for routine quantitative analysis.

Beyond analytical performance, the sensing mechanism plays a fundamental role in determining the effectiveness of electrochemical platforms for CLX and OXA analysis. Electrode modification with conductive nanomaterials, including graphene, carbon nanotubes, and metal nanoparticles, enhances electron‐transfer kinetics by increasing the electroactive surface area and electrical conductivity. These modifications provide more active sites for analyte oxidation while facilitating rapid charge transfer between the electrode surface and the analyte. In addition, functional recognition layers, such as MIPs or biopolymer coatings, improve selectivity through specific analyte–surface interactions and reduce nonspecific adsorption. The synergistic effects of improved conductivity, enhanced adsorption, and selective recognition collectively contribute to lower detection limits, higher sensitivity, and improved analytical reliability in complex sample matrices.

5.3. Spectroscopic Techniques

Analytical methods such as UV–Vis and derivative spectrophotometry include the determination of CLX and OXA in most cases, where matrix interference is low and analyte concentrations are relatively high. These methods are advantageous because they are simple and provide rapid analyses at low operational costs. They have also been routinely performed to assess the quality of both CLX and OXA, either alone or in conjunction with other β‐lactam antibiotics. Sometimes, derivative or ratio spectrophotometric methods are used to improve the resolution of the overlapping spectra of structurally similar compounds (Rahman and Khan 2016; Kamat 2005).

Their UV absorbance properties limit the application of spectroscopic techniques to CLX and OXA. This limitation reduces sensitivity and becomes critical in biological and environmental samples, where trace drug levels are present amid interfering substances that can damage the analytical signal. The direct spectrophotometric method shows insufficient sensitivity and selectivity, which makes it impossible to measure quantities accurately outside of controlled pharmaceutical environments (Kamat 2005; Ilyasa et al., 2015).

In addition, CLX and OXA have spectroscopic properties similar to those of other beta‐lactam antibiotics, leading to potential spectral overlap and misinterpretation due to their lower‐than‐expected selectivity. The use of mathematical treatment methodologies (e.g., derivative spectroscopy) can alleviate some of the problems associated with overlapping spectra; however, their effectiveness is strongly influenced by the quality of the spectral data and may not necessarily be effective for analyzing compounds of interest in complex sample matrices. Lastly, in general, there is limited ability to differentiate between the parent drug and its degradation products using any spectroscopic techniques, which presents additional issues since the beta‐lactam ring is unstable in the presence of moisture (Gandhi and Sonawane 2018; Ghosh et al. 2020).

Spectral analysis methods provide an affordable way to test CLX and OXA frequently across basic sample types, but their limited testing capabilities prevent their use in certain situations. The procedure requires additional support from advanced methods because accurate measurement is necessary in complex situations with low concentrations (Obiyenwa et al. 2018). Figure 5 illustrates the general UV–Vis spectrophotometric workflow for CLX determination. Following sample preparation and reaction with a chromogenic reagent in an alkaline medium, a colored complex is formed and measured at the optimum wavelength (λ_max ≈ 440 nm). The representative absorption spectra demonstrate the characteristic absorbance behavior of the CLX‐based system, while the calibration step enables accurate quantitative determination of CLX in different sample matrices (Yoldaş et al. 2026). The spectrophotometric techniques reported in Table 4 for testing CLX and OXA showed wide variation in sensitivity and media composition.

FIGURE 5.

Schematic illustration of the UV–vis spectrophotometric workflow for CLX determination, including sample preparation, color‐forming reaction, absorbance measurement at λ_max ≈ 440 nm, calibration, and quantification, together with representative UV–Vis absorption spectra under alkaline conditions (Yoldaş et al. 2026).

TABLE 4.

Overview of spectroscopic techniques for evaluating CLX and OXA across diverse matrices.

Analyte(s)	Linear range	LOD/LOQ	Sample	Wavelength	References
CLX	5.0–30.0 μg/mL	LOD = 5 μg/mL	Pharmaceutical dosage form	220–260 nm	(Gandhi and Sonawane 2018)
CLX	13.03–28,019 ng/g	LOD = 4.30 ng/g LOQ = 13.03 ng/g	Bovine milk	206 nm	(Burmańczuk et al. 2017)
CLX	1–5 μg/mL	LOD = 1 μg/mL	Aqueous solution (wastewater model)	217 nm	(Naeem et al. 2024)
CLX	0.5–50 mg/g	LOD = 0.07 mg/g LOQ = 0.25 mg/g	Pharmaceutical formulation	245 nm	(Du et al. 2016)
CLX	0.05–30.00 mg/L	LOD = 0.026 mg/L	Environmental water and pharmaceutical preparation	425 nm	(Khataee et al. 2015)
CLX	35–560 nM	LOD = 5 nM	Milk	405 nm	(Ferrari et al. 2017)
CLX	60.0–140.0 μg/mL	LOD = 60 μg/mL	Pharmaceutical capsules	258.7 nm	(Vu and Do 2010)
CLX	0.008–22.0 mg/L	LOD = 5.8 μg/L	Environmental water and pharmaceutical formulation	580 nm	(Khataee et al. 2016)
CLX	10–80 μg/mL	LOD = 0.77 μg/mL LOQ = 2.33 μg/mL	Pharmaceutical dosage forms	228 nm	(Rahman and Khan 2016)
CLX	1–120 μg/mL	LOD = 0.3099 μg/mL LOQ = 1.033 μg/mL	Pharmaceutical preparations	450 nm	(Ilyasa et al., 2015)
CLX	10–50 μg/mL	LOD = 10 μg/mL	Pharmaceutical dosage form	249 nm	(Ghosh et al. 2020)
OXA	0.1–1 mM	LOD = 0.1 mM	Pharmaceutical formulation	251 nm	(Berczyński et al. 2017)
OXA	5–50 μg/mL	LOD = 5 μg/mL	Pharmaceutical powder (vials, injection form)	282 nm	(Karpova et al. 2023)
OXA	2–8 μg/mL	LOD = 0.39 μg/mL LOQ = 1.18 μg/mL	Human urine samples	365 nm	(Gujral et al. 2009)

The different spectroscopic methods in Table 4 show that performance characteristics vary with sample matrix type; therefore, each of the three sample matrices (pharmaceuticals, environmental samples, and biological samples) has its own unique performance characteristics, as determined by these data. Although most of the UV‐based methods used for analyzing pharmaceutical dosage forms (220–260 nm) have medium sensitivity (with LODs between 0.3099 and 60 μg/mL), and linear ranges (5.0–30.0, 10–80, and up to 60–140 μg/mL), they are sufficient to be used for routine Quality Control. However, they lack the sensitivity required for trace‐level detection. The most sensitive UV‐based method in this category had an LOD of 0.3099 μg/mL; however, compared with other matrix types, it performed poorly due to the lower LODs observed for methods used to analyze environmental water samples. Specifically, the methods used to analyze environmental water samples have very low LODs (5.8 μg/L and 0.026 mg/L) and can provide very wide linear ranges (e.g., an LOD of 5.8 μg/L and 0.08–22.0 mg/L) due to the implementation of methods such as preconcentration or derivative analysis to reduce matrix effects and increase the ability of the spectroscopic methods to detect analytes.

Based on visible spectrophotometric measurements of CLX and OXA in biological matrices and milk, visible spectrophotometry is more sensitive and specific than UV‐based methods, demonstrating that chromogenic reactions or complex formation provide much greater selectivity and sensitivity. For example, in biological matrices, CLX can be detected at an LOD of 4.30 ng/g or 5 nM when measured in the visible region (405 nm), making it the most sensitive method available across all matrices. This result illustrates how optimized sample preparation and selective detection enhance the ability to quantify trace levels. Similarly, OXA can be quantitatively determined in urine at an LOD of 0.39 μg/mL, a sensitivity that exceeds that previously reported for OXA in pharmaceutical matrices. Conversely, some methods used in pharmaceutical matrices exhibit very low sensitivity (e.g., LOD = 0.1 mM) for OXA due to the lack of enhancement afforded by direct UV detection.

The sensitivity of biological samples peaks with milk samples, while water samples from environmental sources show lower sensitivity than pharmaceutical products, which maintain their basic functionality. Spectroscopic techniques achieve their optimal performance through sample‐matrix customization, enabling derivatization‐based visible methods to handle complex analyses at trace levels, while conventional UV methods are effective for testing high‐concentration pharmaceutical products.

Spectroscopic methods use basic techniques that are less expensive to execute, but their ability to identify specific substances decreases when testing complex material samples. UV methods are prone to interference, while visible methods require more complex testing to achieve better detection. The methods provide suitable performance for routine tests, but their effectiveness declines when handling extremely small amounts or extremely difficult samples, which require advanced analysis methods.

Spectrophotometric methods remain attractive because of their simplicity, rapid operation, and minimal instrumental requirements. These characteristics make them particularly suitable for routine pharmaceutical quality control in laboratories with limited analytical resources. However, the absence of strong chromophores in CLX and OXA substantially reduces analytical sensitivity, while poor selectivity limits direct application in complex biological and environmental matrices. Derivatization strategies improve sensitivity but introduce additional analytical steps that may reduce reproducibility and increase experimental variability. Consequently, spectrophotometric methods should be considered primarily as preliminary or screening techniques rather than definitive quantitative methods when high analytical accuracy is required.

The efficiency of the color‐forming reaction between CLX or OXA and the chromogenic reagent largely governs the analytical performance of spectrophotometric methods. The formation of a stable, colored complex increases molar absorptivity at the characteristic wavelength, thereby improving signal intensity and analytical sensitivity. Reaction conditions, including pH, reagent concentration, and reaction time, directly influence complex stability and absorbance, ultimately affecting method accuracy, precision, and detection capability.

6. Applications Across Diverse Matrices

The analytical assessment of CLX and OXA is largely dependent upon the matrix characteristics of the samples analyzed, because of the physicochemical properties of these drugs (i.e., strong protein binding, instability caused by beta‐lactam ring open) and low intrinsic detectability, which behave differently in different sample matrices (i.e., biological, food, environmental, and pharmaceutical). Unlike standard pharmaceutical products, actual sample matrices contain an unpredictable degree of complexity, which ultimately affects (negatively) the speed and specificity of methods used to analyze these compounds; therefore, strategies for quantification must be matrix‐ and compound‐specific.

Both CLX and OXA are present at low concentrations in plasma, serum, and urine because they are more than 90% protein‐bound, which makes their detection difficult. The sample preparation method used for the identification and quantification of CLX and OXA must be efficient enough to release bound drugs from their binding sites while preserving the integrity of the β‐lactam (i.e., the ring structure). The presence of many natural substances in biological matrices also complicates the detection of CLX and OXA, as they can severely hinder the performance of UV‐based methods, especially when LC–MS/MS and improved chromatographic separation techniques are used.

It is necessary to use various methods to analyze food, environmental, and pharmaceutical samples, depending on the requirements of each application and its regulatory environment. Analyses of food‐borne samples (milk, meat, shrimp) are difficult due to the presence of lipids (full‐fat milk), proteins (source), and casein (milk protein), which pose challenges for target‐sample recovery and signal suppression. Analyses of environmental vectors (wastewater, surface water) are increasingly difficult due to ultra‐trace analyte levels, dissolved organic matter, and the presence of other pharmaceuticals that affect both the LOD and analyte stability. Solely based on the simplicity of the matrix of pharmaceutical preparations, there are fewer issues; however, due to the need to develop stability‐indicating assays for the identification of CLX and OXA and their residue products, and due to the ongoing analytical challenge of their degradation associated with the storage and processing conditions, the challenges of creating good quality assurance are very difficult to obtain.

Matrix dependence directly influences the performance and suitability of various analytical methods, as established by previous research. The sensitivity and selectivity requirements of pharmaceutical testing methods restrict their application in biological and environmental contexts, while highly sensitive methods create operational challenges that limit their use. The determination of CLX and OXA requires matrix‐oriented analytical methods in accordance with established testing procedures.

The following subsections present a critical evaluation of analytical techniques used to study CLX and OXA in biological samples (including plasma, serum, and urine), as well as in food products, environmental samples, and pharmaceutical materials. The focus of their assessment is on three main areas: method performance, existing limitations, and the practical use of the methods.

6.1. CLX and OXA Analysis in Plasma, Serum, and Urine

Due to high protein binding, low circulating concentrations, and the chemical instability of the β‐lactam ring, determining CLX and OXA concentrations in plasma, serum, and urine is among the most analytically challenging applications. Both drugs are > 90% bound to plasma/serum proteins, severely limiting the amount of analyte available for analysis and making estimating the analyte present dependent on the efficiency of sample preparation. Therefore, analytical methods typically include protein precipitation, SPE, or online clean‐up systems to release the analyte from its polyprotein binding site and minimize degradation during processing (Legrand et al. 2016; Verdier et al. 2011).

The determination of CLX and OXA in biological matrices is commonly performed using RP‐HPLC and UHPLC. The performance of these systems depends on the complexity of the testing environment. HPLC‐UV methods provide higher‐concentration testing but lack the necessary sensitivity for pharmacokinetic studies and residue‐level research, which require ng/mL detection limits. The preferred analysis methods now use LC–MS/MS and UPLC–MS/MS because these techniques provide better detection power and faster testing processes while better handling natural background noise. The use of mass spectrometry‐based methods allows for rapid identification of CLX at sub‐mg/L levels in plasma because these methods require little operating time, making them appropriate for processing large volumes of biological samples (Abdullahi et al., 2019; Yang et al. 2007).

The essential advantages of biological analysis for CLX and OXA research are hindered by matrix effects, including ion suppression in LC–MS systems, as well as sample handling degradation risks, which together slow research progress. Urine samples show lower protein interference than plasma samples, yet their pH variations and the presence of metabolites and degradation products make quantification more difficult. Accurate measurement of CLX and OXA in biological matrices requires striking the right balance among effective extraction methods, methods that maintain compound stability, and methods that provide precise detection. Advanced chromatographic–mass spectrometric techniques deliver the best performance results when used in these measurement conditions (Espinosa‐Mansilla et al. 2006; Jonsson et al. 2014).

6.2. CLX and OXA Analysis in Food, Environmental, and Pharmaceutical Matrices

Analytical requirements for determining CLX and OXA in food (milk, meat, and shrimp), environmental, and pharmaceutical matrices differ substantially due to matrix complexity, compound concentrations, and regulatory expectations for their use. Trace levels (μg/kg–μg/L) of CLX and OXA are generally present in food matrices, and these compounds can be significantly influenced by the presence of lipids, proteins, and casein in those matrices, making the extraction process less efficient; signal suppression occurs due to these components being present (Cámara et al. 2013; Solís‐Robles et al. 2026). The chromatographic studies contained within the dataset demonstrate that μg/kg‐level detection is achievable using optimized methods such as HPLC and capillary HPLC; however, sensitivity and selectivity will remain highly variable depending on the analytical strategies applied, e.g., SPE or derivatives. Although these analytical techniques are suitable for the routine monitoring of residue levels, they are not as robust or as consistent as mass spectrometric methods (Huth et al. 2002; Mogaddam et al. 2023).

The environmental matrices of river water and wastewater contain both CLX and OXA at ultra‐trace levels, which are below the sub‐μg/L threshold, and experience degradation through their interactions with dissolved organic matter, making their detection more complex. HPLC‐DAD and capillary HPLC are suitable methods for testing. However, their selectivity becomes inadequate when pharmaceuticals and natural organic compounds are present in the testing sample. The analytical method LC–MS/MS is preferred for confirmatory testing because it offers better sensitivity and specificity, although it incurs higher operational expenses and is vulnerable to ion suppression caused by matrix components (Elmolla and Chaudhuri 2009; Elmolla and Chaudhuri 2010).

The use of simple matrices in pharmaceutical formulations enables the apply standard RP‐HPLC‐UV techniques, which produce satisfactory results across the entire μg/mL concentration spectrum. The instability of CLX and OXA requires stability‐indicating methods that can differentiate between the original drug and its storage and processing degradation products (Gebretsadik et al. 2023; Vu and Do 2010).

The analysis results show that CLX and OXA testing across different matrices demonstrate variable performance because the testing methods depend on the specific matrix being analyzed. The basic performance of chromatographic techniques delivers consistent results, while highly sensitive confirmatory testing needs advanced methods such as LC–MS/MS. The different results demonstrate that one must develop specific testing methods for each matrix to achieve trustworthy results, which can be used in actual fieldwork (Legrand et al. 2016; Palayer et al. 2023).

7. Comparative Analysis of Analytical Techniques for CLX and OXA

No single analytical technique is universally optimal for determining CLX and OXA, and the analytical objective, sample matrix, required sensitivity, available instrumentation, and operational constraints should guide method selection. Chromatographic techniques, particularly RP‐HPLC and UHPLC, remain the most reliable and widely adopted methods for routine pharmaceutical quality control because of their excellent reproducibility, robustness, and ability to separate CLX and OXA from structurally related β‐lactam antibiotics and degradation products. However, their analytical sensitivity is often insufficient for ultra‐trace determination in complex biological and environmental matrices when UV detection is employed, frequently necessitating derivatization or coupling with mass spectrometry (Gebretsadik et al. 2023; Vu and Do 2010; Clarin 2020).

Among all analytical platforms, LC–MS/MS provides the highest overall analytical performance owing to its superior molecular selectivity, trace‐level sensitivity, and minimal interference from coexisting compounds. These advantages make it the preferred technique for pharmacokinetic studies, therapeutic drug monitoring, residue analysis, and environmental monitoring. Nevertheless, its widespread application is limited by high instrumentation costs, complex operation, extensive sample preparation, and susceptibility to matrix‐induced ion suppression, making it less suitable for routine quality‐control laboratories (Legrand et al. 2016; Palayer et al. 2023; Khuroo et al. 2008).

Electrochemical methods have emerged as attractive alternatives because of their rapid response, low cost, portability, and excellent analytical sensitivity, particularly when nanomaterials or MIPs are incorporated into the sensing interface. Despite these advantages, their analytical performance remains highly dependent on electrode fabrication, surface stability, and sample composition. Electrode fouling, sensor‐to‐sensor variability, and insufficient inter‐laboratory validation continue to limit their routine implementation, especially for complex biological samples (Golkarieh et al. 2021; Koseoglu and Demirhan 2025).

Spectrophotometric methods remain the simplest and most economical analytical approaches, requiring minimal instrumentation and straightforward sample preparation. However, their relatively poor selectivity and higher detection limits, resulting from the weak intrinsic UV absorbance of CLX and OXA, restrict their application primarily to pharmaceutical formulations and routine quality‐control testing rather than trace analysis (Vu and Do 2010; Wadher Shailesh, Patwekar Shailesh, et al. 2017).

Overall, each analytical platform exhibits distinct advantages and limitations. LC–MS/MS remains the analytical benchmark when maximum sensitivity and selectivity are required, whereas HPLC provides the most practical balance between analytical performance, cost, and routine applicability. Electrochemical sensors represent the most promising emerging technology for rapid and portable analysis but require further standardization and large‐scale validation before widespread adoption. Consequently, future analytical development should prioritize methods that combine high sensitivity and selectivity with simplified sample preparation, lower operational cost, improved reproducibility, and environmentally sustainable analytical workflows. (Legrand et al. 2016; Clarin 2020; Golkarieh et al. 2021; Ghosh et al. 2020) (Table 5).

TABLE 5.

Critical comparison of analytical methods for CLX and OXA determination.

Method	Sensitivity	Selectivity	Detection limit	Linear range	Analysis time	Sample preparation	Instrument complexity	Cost	Routine suitability	Major strengths	Major limitations	Best application
HPLC/UPLC‐UV/DAD	Good	Good	μg/mL–ng/mL	Wide	5–20 min	Moderate	Moderate	Moderate	Excellent	Robust, reproducible, stability‐indicating	Limited sensitivity with UV detection	Pharmaceutical QC, stability testing
LC–MS/MS	Excellent	Excellent	ng/mL–sub‐ng/mL	Wide	2–10 min	Moderate–extensive	High	Very high	Moderate	Highest sensitivity and confirmatory selectivity	High cost, ion suppression, expert operation	Biological, environmental, residue analysis
Spectrophotometry	Moderate	Low–moderate	μg/mL	Moderate	< 5 min	Simple	Low	Low	Good	Simple, rapid, inexpensive	Poor selectivity, unsuitable for trace matrices	Simple pharmaceutical formulations
Electrochemical sensors	Good–excellent	Moderate–good	nM–pM	Wide	Few minutes	Simple–moderate	Low–moderate	Low	Emerging	Rapid, portable, sensitive	Electrode fouling, reproducibility, limited validation	Rapid screening, water/plasma analysis

8. Future Perspectives

Future analytical development efforts for CLX and OXA should shift from incremental improvements in individual methods to integrated methods that address the limitations of available chromatographic, electrochemical, and spectroscopic analysis techniques. Developing robust, stability‐indicating platforms for the simultaneous quantification of intact drugs and the identification of β‐lactam degradation products in real samples will be a major goal, particularly in biological and environmental matrices, where hydrolysis and oxidation can occur during sampling and analysis. In particular, hyphenated techniques such as UHPLC–HRMS and LC–MS/MS with improved ionization control will continue to be used extensively; however, future work should focus on reducing matrix‐induced ion suppression using advanced sample preparation techniques (e.g., automated online SPE, microextraction, and bulk material calibration) and developing standardized validation guidelines to increase the reproducibility of results across laboratories.

Simultaneously, there is a growing need for effective and portable alternatives, especially electrochemical and sensor‐based types, by combining nanostructured materials with molecular imprinting methods to improve the selectivity of CLX and OXA over similar β‐lactams. However, long‐term stability, reproducibility, and consistency across devices are critical barriers that must be overcome before routine use can occur. From an optical standpoint, the future direction of research may be the integration of optical techniques and chemometric tools, or indirect detection methods, to overcome inherent sensitivity limits, but expect future use to be limited to simplified matrices unless considerable advancements occur. As β‐lactams continue to grow in terms of environmental consideration and regulations, the creation of ultra‐trace level analytical methods for the detection of β‐lactams in multiple different matrices will also require the creation of analytical methods that will provide a deterministic ability to perform acute and chronic studies into their degradation and fate (by performing an advanced oxidation technique and using real‐time monitoring systems, etc.). In addition, there remains a significant need to standardize the methods developed and harmonize reporting criteria (e.g., LOD, LOQ, recovery, and matrix effects) to allow meaningful comparisons of results between studies. At present, variability in results across methodologies prevents the evaluation of methods of comparison. Therefore, the future of analytical methodologies for CLX and OXA should focus on the development of integrated, application‐based frameworks that will enable scientifically reliable, cost‐effective, and sustainable sources of environmentally friendly strategies that maximize the use of innovations in miniaturization, automation, and green analytical chemistry, resulting in both scientifically sound and practically applicable methods to use in both routine and regulatory applications.

Future analytical developments should increasingly focus on understanding the mechanistic relationship between sensing material properties and analytical performance. Rational design of sensing interfaces based on electron‐transfer behavior, surface chemistry, and analyte recognition mechanisms will facilitate the development of more sensitive, selective, and robust analytical platforms for the determination of CLX and OXA. Future analytical platforms are expected to increasingly incorporate digital and intelligent technologies to improve the determination of CLX and OXA. Artificial intelligence (AI) and machine learning (ML) algorithms have considerable potential to enhance signal processing, pattern recognition, calibration modeling, and data interpretation, thereby improving analytical accuracy and reducing human intervention. In parallel, smartphone‐assisted sensing platforms, wearable and portable electrochemical devices, and wireless Internet of Things (IoT)‐enabled sensors are expected to facilitate rapid, on‐site, and real‐time monitoring of CLX and OXA in pharmaceutical, clinical, food, and environmental samples. Furthermore, integration with cloud‐based data management systems could enable continuous remote monitoring, automated data analysis, and rapid decision‐making. The convergence of advanced sensing materials with digital analytical technologies is therefore expected to accelerate the development of intelligent, decentralized, and sustainable analytical systems for future antibiotic monitoring.

9. Conclusion

This paper presents a concise yet thorough explanation of the key analytical approaches employed in CLX and OXA. The literature review identified a variety of measurement methods (n = 61), including spectrophotometry and voltammetry, which are significantly less common. Detection technologies for HPLC analysis of antibiotics in user samples and prescription dose forms were also developed and characterized.

The analytical determination of CLX and OXA remains challenging because of their β‐lactam instability, strong protein binding, limited intrinsic detectability, and pronounced matrix‐dependent effects. Although numerous analytical methods have been developed, no single platform is universally suitable for all analytical applications. Instead, the optimal method depends on the sample matrix, the required analytical sensitivity, the available instrumentation, and the intended application. Among the currently available techniques, LC–MS/MS represents the analytical benchmark for trace‐level quantification owing to its exceptional sensitivity, selectivity, and ability to distinguish target analytes from structurally related compounds and degradation products. However, its high cost, technical complexity, and susceptibility to matrix effects limit its routine implementation. In contrast, HPLC remains the most practical and robust approach for pharmaceutical quality control because of its reliability, accessibility, and well‐established validation protocols, despite its lower sensitivity compared with mass spectrometric methods.

Emerging electrochemical and sensor‐based technologies have demonstrated considerable potential for rapid, portable, and cost‐effective analysis, particularly with the incorporation of nanomaterials and MIPs. Nevertheless, limited method standardization, insufficient validation using real‐world samples, and reproducibility challenges continue to restrict their broader analytical and regulatory acceptance. Likewise, spectrophotometric methods remain valuable for routine pharmaceutical applications but are generally inadequate for trace analysis in complex biological and environmental matrices because of their limited selectivity and sensitivity.

Despite substantial progress, several important challenges remain unresolved. Future research should prioritize the development of standardized analytical protocols, simplified and environmentally sustainable sample preparation procedures, improved matrix‐effect control, and comprehensive inter‐laboratory validation. In addition, integrating green analytical chemistry principles with automated, miniaturized, and intelligent analytical platforms may significantly enhance analytical efficiency while reducing environmental impact. Addressing these challenges will facilitate the development of more robust, sensitive, and sustainable analytical methodologies for the reliable determination of CLX and OXA across diverse pharmaceutical, biological, food, and environmental applications.

Author Contributions

Hemn A.H. Barzani: conceptualization; supervision; methodology; validation; writing – original draft; writing – review and editing. Khalamala Ibrahim Salih Barzani: software; validation. Ali Sedeeq Noaman: Data curation; software; formal analysis. Kovan Dilawer Issa: software; validation. Seerwan Hamadameen Sulaiman: data curation; software; validation.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.