Revealing the inner workings of the power function algorithm in Charged Aerosol Detection: A simple and effective approach to optimizing power function value for quantitative analysis

Monitoring stability indicating impurities and aldehyde content in lipid nanoparticle raw material and formulated drugs

Lipid nanoparticles (LNPs) are designed to protect and transport sensitive payloads or active pharmaceutical ingredients as part of new therapeutic modalities. As a multi-component particle, a high degree of quality control is necessary to ensure raw materials are free of critical impurities that could adversely impact the drug product. In this study, we demonstrate a reversed phase liquid chromatography method hyphenated with a single quadrupole mass spectrometer (RPLC-MS) as an alternative platform to methods that incorporate evaporative light scattering or charged aerosol detectors in the detection and quantitation of critical impurities associated with LNPs. The proposed RPLC-MS method offers an increase of up to 2 orders of magnitude in dynamic range and 3 orders of magnitude in sensitivity in the analysis of impurities associated with LNPs compared to conventional detectors. Access to complementary mass data enabled the detection and identification of stability indicating impurities as part of stress studies carried out on an ionizable lipid. In addition to confirmation of peak identity, complementary mass data was also used to assess residual aldehydes in raw material and formulated LNPs in accordance with regulatory guidance. Following derivatization using 2,4-dinitrophenylhydrazine, aldehyde content in the ionizable lipid raw material was determined to exceed the reporting threshold of 0.05% in 30% of the test cases. The experimental findings observed in this study demonstrate the utility of the proposed RPLC-MS method in the identification and monitoring of stability-indicating attributes associated with LNPs as part of current Good Manufacturing Practices for improved consumer safety in drug products.

An optimization strategy for charged aerosol detection to linearize the detector response in the multicomponent quantitative analysis of Qishen Yiqi dripping pills

Charged aerosol detection, increasingly recognized for quantifying pharmaceutical compounds with weak ultraviolet absorption, is a universal detection technique for high-performance liquid chromatography (HPLC). Charged aerosol detection shows a non-linear response with increasing analyte concentration over a wide range, limiting its versatility in various analytical applications. In this work, a co-optimization strategy for power function value (PFV) and power laws was proposed and applied to broaden the linear range of the standard curve of saccharides in Qishen Yiqi dripping pills using the HPLC-charged aerosol detection (HPLC-CAD) method. Power function values for all analytes were optimized based on empirical models. Subsequently, the optimum power laws were investigated based on a preferred PFV. Additionally, various regression equations were evaluated to ensure the accuracy and precision of the results. With the optimized PFV and power law, the ordinary least squares model demonstrated a satisfactory fit. The optimal PFVs and power laws expanded the standard curve's linear range by 2.7 times compared to default settings, reducing model uncertainty. This paper presents a vital method for developing a multi-component quantitative HPLC-CAD approach without external data transformation outside the provided software, especially suitable for analytical applications of traditional Chinese medicine with significant quality differences.

Automated Composition Assessment of Natural Extracts: Untargeted Mass Spectrometry-Based Metabolite Profiling Integrating Semiquantitative Detection

Recent developments in mass spectrometry-based metabolite profiling allow unprecedented qualitative coverage of complex biological extract composition. However, the electrospray ionization used in metabolite profiling generates multiple artifactual signals for a single analyte. This leads to thousands of signals per analysis without satisfactory means of filtering those corresponding to abundant constituents. Generic approaches are therefore needed for the qualitative and quantitative annotation of a broad range of relevant constituents. For this, we used an analytical platform combining liquid chromatography-mass spectrometry (LC-MS) with Charged Aerosol Detection (CAD). We established a generic metabolite profiling for the concomitant recording of qualitative MS data and semiquantitative CAD profiles. The MS features (recorded in high-resolution tandem MS) are grouped and annotated using state-of-the-art tools. To efficiently attribute features to their corresponding extracted and integrated CAD peaks, a custom signal pretreatment and peak-shape comparison workflow is built. This strategy allows us to automatically contextualize features at both major and minor metabolome levels, together with a detailed reporting of their annotation including relevant orthogonal information (taxonomy, retention time). Signals not attributed to CAD peaks are considered minor metabolites. Results are illustrated on an ethanolic extract of Swertia chirayita (Roxb.) H. Karst., a bitter plant of industrial interest, exhibiting the typical complexity of plant extracts as a proof of concept. This generic qualitative and quantitative approach paves the way to automatically assess the composition of single natural extracts of interest or broader collections, thus facilitating new ingredient registrations or natural-extracts-based drug discovery campaigns.

Universal response method for accurate quantitative analysis of the impurities in quinolone antibiotics using liquid chromatography coupled with diode array detector and charged aerosol detector

HPLC method is the standard method for the separation and quantification of impurities from quinolone antibiotics. However, due to the large differences in the UV absorption of the impurities in quinolone antibiotics, quantitative analysis without the availability of corresponding reference substances currently poses a challenge. A sensitive and direct method using high performance liquid chromatography coupled with diode array detector and charged aerosol detector (HPLC-DAD-CAD) was developed for the analysis of impurities in quinolone antibiotics. The chromatographic conditions were optimized for good separation and output signal of CAD detector by response surface method (RSM). The systematic variation of CAD parameter settings, such as nebulization temperature, filter constant and power function value (PFV), were used to study the effect of on the detector response of signal-to-noise ratios (S/N) and linearity for ofloxacin, ciprofloxacin and their impurities. In the method validation, good linearity of each component was obtained with coefficient of determination (r) greater than 0.999 in the range of 0.5-300 μg mL-1. The average recoveries of each component were 99.02-102.39 % by DAD, were 98.22-101.91 % by CAD, RSDs were less than 2.5 % for intra-day and inter-day precision by DAD-CAD, with good precision and accuracy. The correction factor experimental results showed that the developed method provided a uniform response to the impurities with differences chromophores and could unbiasedly and directly detect the impurities in quinolone antibiotics. The method is first reported application of HPLC-DAD-CAD method for the analysis of impurities in quinolone antibiotics and it can be used for quality control of quinolone antibiotics.

Challenges and emerging trends in liquid chromatography-based analyses of mRNA pharmaceuticals

Lipid encapsulated messenger RNA (LNP mRNA) has garnered a significant amount of interest from the pharmaceutical industry and general public alike. This attention has been catalyzed by the clinical success of LNP mRNA for SARS-CoV-2 vaccination as well as future promises that might be fulfilled by the biotechnology pipeline, such as the in vivo delivery of a CRISPR/Cas9 complex that can edit patient cells to reduce levels of low-density lipoprotein. LNP mRNAs are comprised of various chemically diverse molecules brought together in a sophisticated intermolecular complex. This can make it challenging to achieve thorough analytical characterization. Nevertheless, liquid chromatography is becoming an increasingly relied upon technique for LNP mRNA analyses. Although there have been significant advances in all types of LNP mRNA analyses, this review focuses on recent developments and the possibilities of applying anion exchange (AEX) and ion pairing reversed phase (IP-RP) liquid chromatography for intact mRNAs as well as techniques for oligo mapping analysis, 5' endcap testing and lipid compositional assays.

Qualitative and quantitative studies on two commercial specifications of Polygonatum odoratum

The rhizoma of Polygonatum odoratum (PO) is used to treat yin injuries of the lung and stomach in traditional Chinese medicine. The chemical constituents of this herb are steroidal saponins, homoisoflavanones, and alkaloids. Xiangyuzhu (XPO) and Guanyuzhu (GPO) are available in the market as two specifications of the commodity. Nonetheless, systematic research on the identification and comparison of chemical constituents of these two commercial specifications is yet lacking. Herein, an integrated method combing ultra-high-performance liquid chromatography-quadruple time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) with ultra-high-performance liquid chromatography-charged aerosol detection (UHPLC-CAD) was employed for the comprehensively qualitative and quantitative analyses of PO. A total of 62 compounds were identified by UHPLC-Q-TOF/MS, among which 13 potential chemical markers were screened out to distinguish two commercial specifications. Subsequently, the absolute determination method for polygodoraside G, polygonatumoside F, and timosaponin H1 was established and validated by UHPLC-CAD. The contents of the three compounds were 13.33-236.24 μg/g, 50.55-545.04 μg/g, and 13.34-407.83 μg/g, respectively. Furthermore, the ratio of timosaponin H1/polygodoraside G could be applied to differentiate the two specifications. Samples with a ratio <2 are considered XPO and >5 are considered GPO. Therefore, the above results provide a valuable means for the quality control of PO.

Determination of Glycerophospholipids in Biological Material Using High-Performance Liquid Chromatography with Charged Aerosol Detector HPLC-CAD-A New Approach for Isolation and Quantification

The method of using high-performance liquid chromatography with a charged aerosol detector method (HPLC-CAD) was developed for the separation and determination of phospholipids isolated from cell membranes. The established cell lines—normal and neoplastic prostate cells and normal skin fibroblasts and melanoma cells—were selected for the study. Chromatographic separation was performed in the diol stationary phase using a gradient elution based on a mixture of n-hexane, isopropanol and water with the addition of triethylamine and acetic acid as buffer additives. Taking the elements of the Folch and Bligh–Dyer methods, an improved procedure for lipid isolation from biological material was devised. Ultrasound-assisted extraction included three extraction steps and changed the composition of the extraction solvent, which led to higher recovery of the tested phospholipids. This method was validated by assessing the analytical range, precision, intermediate precision and accuracy. The analytical range was adjusted to the expected concentrations in cell extracts of various origins (from 40 µg/mL for PS up to 10 mg/mL for PC). Both precision and intermediate precision were at a similar level and ranged from 3.5% to 9.0%. The recovery for all determined phospholipids was found to be between 95% and 110%. The robustness of the method in terms of the use of equivalent columns was also confirmed. Due to the curvilinear response of CAD, the quantification was based on an internal standard method combined with a power function transformation of the normalized peak areas, allowing the linearization of the signal with an R² greater than 0.996. The developed method was applied for the isolation and determination of glycerophospholipids from cell membranes, showing that the profile of the tested substances was characteristic of various types of cells. This method can be used to assess changes in metabolism between normal cells and neoplastic cells or cells with certain pathologies or genetic changes.

Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach

The charged aerosol detector (CAD) is the latest representative of aerosol-based detectors that generate a response independent of the analytes' chemical structure. This study was aimed at accurately predicting the CAD response of homologous fatty acids under varying experimental conditions. Fatty acids from C12 to C18 were used as model substances due to semivolatile characterics that caused non-uniform CAD behaviour. Considering both experimental conditions and molecular descriptors, a mixed quantitative structure-property relationship (QSPR) modeling was performed using Gradient Boosted Trees (GBT). The ensemble of 10 decisions trees (learning rate set at 0.55, the maximal depth set at 5, and the sample rate set at 1.0) was able to explain approximately 99% (Q²: 0.987, RMSE: 0.051) of the observed variance in CAD responses. Validation using an external test compound confirmed the high predictive ability of the model established (R²: 0.990, RMSEP: 0.050). With respect to the intrinsic attribute selection strategy, GBT used almost all independent variables during model building. Finally, it attributed the highest importance to the power function value, the flow rate of the mobile phase, evaporation temperature, the content of the organic solvent in the mobile phase and the molecular descriptors such as molecular weight (MW), Radial Distribution Function-080/weighted by mass (RDF080m) and average coefficient of the last eigenvector from distance/detour matrix (Ve2_D/Dt). The identification of the factors most relevant to the CAD responsiveness has contributed to a better understanding of the underlying mechanisms of signal generation. An increased CAD response that was obtained for acetone as organic modifier demonstrated its potential to replace the more expensive and environmentally harmful acetonitrile.

Benefits and Pitfalls of HPLC Coupled to Diode-Array, Charged Aerosol, and Coulometric Detections: Effect of Detection on Screening of Bioactive Compounds in Apples

The new screening method for rapid evaluation of major phenolic compounds in apples has been developed. Suitability of coupling HPLC/UHPLC separation with the diode-array detection and universal charged aerosol detection with respect to the presence of interfering substances was tested. Characteristics of both detection techniques were compared and method linearity, limits of detection and quantitation, and selectivity of them determined. Student t-test based on slopes of calibration plots was applied for the detailed comparison. The diode-array detection provided the best results regarding sensitivity and selectivity of the developed method in terms of evaluation of phenolics profiles. The response of the charged aerosol detector was negatively affected by co-eluting substances during rapid-screening analyses. Coulometric detection was used for advanced characterization of extracts in terms of antioxidant content and strength to obtain more complex information concerning sample composition. This detection also allowed evaluation of unidentified compounds with antioxidant activity. HPLC/UHPLC separation using a combination of diode-array and coulometric detectors thus represented the best approach enabling quick, yet complex characterization of bioactive compounds in apples.

Impurity profiling of Compound Amino Acid Injection (6AA) using ion-pair high performance liquid chromatography coupled with corona-charged aerosol detection and high resolution mass spectrometry

The complex industrial production process of amino acids (AAs) leads to the existence of a certain amount of impurities in Compound Amino Acid Injection (6AA). It is difficult to obtain its comprehensive and systematic impurity profile using conventional ultraviolet (UV) detectors due to lack of a suitable chromophore in the structures of AAs and their impurities. In our study, a universal ion-pair high performance liquid chromatography (HPLC) method combined with high resolution mass spectrometer (HRMS) and charged aerosol detection (CAD) was developed to identify and determine the content of impurities in Compound Amino Acid Injection (6AA), respectively. After optimizing the content of trifluoroacetic acid (TFA) and heptafluorobutyric acid (HFBA) in the mobile phase on a C18 AQ column, HPLC-CAD method was developed and nine unknown impurities were detected. These impurities were successfully identified using HPLC coupled with orbitrap mass spectrometry and confirmed with their reference substances. The CAD parameters setting was optimized to improve the sensitivity and linearity of the methods before the developed method was validated. The results of validation reflected that the limit of detection (LOD) was approximately 2 ng (corresponding to approximately 0.02 % of L-isoleucine in injection). Under the optimized power function value (PFV) of CAD, the linear range of each impurity was 1 ∼ 200 μg mL^-1 (the linear range of one of the impurities with higher content was 2 ∼ 400 μg mL^-1) with coefficients of determination (R²) greater than 0.998. The recovery rates for nine impurities were 93.37 % ∼ 110.23 %. This study made full use of the qualitative functions of HRMS and the versatility of CAD, revealing possible impurities in the 6AA injection, which could provide reference for the safety research of it.

Simultaneous determination of six main components in Bushen Huoxue prescription by HPLC-CAD

BACKGROUND

The Bushen Huoxue prescription is a traditional Chinese medicine formula treating diabetic retinopathy, which was developed by our research group. Catalpol, puerarin, salvianolic acid B, ginsenoside Rg1, ginsenoside Rb1 and ginsenoside Rd are six of main effective components, which could be partly representative of this prescription. The corona charged aerosol detector (corona CAD) is one kind of universal detectors equipped with the high performance liquid chromatography (HPLC). The CAD has many advantages for the analysis of complex mixtures, but too few applications in traditional Chinese medicine compounds.

OBJECTIVE

The aims of this study are to establish a method for the determination of six components in Bushen Huoxue prescription, and to increase the use of the CAD in traditional Chinese medicine compounds.

METHODS

HPLC-CAD analysis was performed on an Inertsil ODS-SP (4.6 mm × 250 mm, 5 μm) with a mobile phase consisting of 0.5 % formic acid solution(A)-acetonitrile(B) at a flow rate of 1 mL/min (0-7 min, 1 % B; 7-12 min, 1 %-12 % B; 12-22 min, 12 %-19 % B; 22-40 min, 19 %-28 % B; 40-43 min, 28 %-33 % B; 43-50 min, 33 % B; 50-65 min, 33 %-42 % B). The column temperature maintained at 30 ℃, the injection volume was 20 μL, the atomization temperature mode was LOW, the filtration constant (filter) was 3.6 and data collection rate was 10 Hz. The methodology was examined and the linearity of regression of different functions was compared. Sixteen batches of samples were prepared and their contents were determined.

RESULTS

The six compounds showed a better linearity (R² > 0.9990) in their concentration ranges when using the linear function. The average recoveries were 99.18 %-101.30 %. Although the RSD value of puerarin and ginsenoside Rg1 was slightly out of 3 % during the average recovery investigation, all the other methodological investigations of the six components were within 3 %. The precision, stability and repeatability of the method were good. In sixteen batches of Bushen Huoxue prescription samples, the contents of six components were 0.3138 %-0.6042 % for catalpol, 0.8095 %-1.2917 % for puerarin, 0.7416 %-1.1189 % for salvianolic acid B, 0.0231 %-0.0418 % for ginsenoside Rg1, 0.0702 %-0.1724 % for ginsenoside Rb1, 0.0384 %-0.1196 % for ginsenoside Rd.

CONCLUSION

In this experiment, a method for the determination of six components in Bushen Huoxue prescription based on HPLC-CAD was established with high accuracy, good repeatability and simple operation, and it can provide references for the improvement of quality standard of the Bushen Huoxue prescription. It is reasonable and accessible for the CAD application in the determination of traditional Chinese medicine compound prescriptions.

Charged aerosol detection in early and late-stage pharmaceutical development: selection of regressionmodels at optimum power function value

In recent years, the use of quantitative liquid chromatography (LC) coupled charged aerosol detection (CAD) for poor UV absorbing analytes in multicomponent mixtures has grown exponentially across academic and industrial sectors. The ballpark of previous LC-CAD reports is focused on practical applications, as well as optimization of critical parameters such as: response dependencies on temperature, nebulization process, analyte volatility, and mobile-phase composition. However, straightforward approaches to deal with the characteristic nonlinear response of CAD still scarce. A highly overlooked parameter is the power function value (PFV), whose optimization enables a detection signal that is more linear with higher signal-to-noise ratio (S/N) and lower relative standard deviation (RSD) of area counts. Herein, a systematic investigation of different regression models (log-log, first-and second-degree polynomial) by both interpolation and extrapolation process in conjunction with PFV optimization throughout the development of LC-CAD assays is reported. The accuracy of the results via interpolation is always good (< 5%) when operating in the vicinity of the optimum PFV regardless the regression model choice. On the contrary, extrapolation process only worked when applying log-log regression at the optimum PFV (accuracy <5%). This outcome indicates that a first-order regression via interpolation can be a safe and simple choice for quantitative LC-CAD in highly regulated laboratories (GLP, GMP, etc.). Whereas a straightforward extrapolation combined with log-log regression can enable the deployment of high-throughput LC-CAD assays, especially but not limited to laboratories where the synthetic process route is undergoing rapid change and optimization (medicinal chemistry, discovery, biocatalysis, process chemistry, etc.). This approach is crucial in developing quantitative LC-CAD assays for poor UV absorbing pharmaceuticals that are sensitive, precise, accurate and robust across early and late-stage pharmaceutical development.

Power function setting in charged aerosol detection for the linearization of detector response - optimization strategies and their application

Charged aerosol detection (CAD) is an universal technique in liquid chromatography that is increasingly used for the quality control of drugs. Consequently, it has found its way into compendial monographs promoted by its simple and robust application. However, the response of CAD is inherently nonlinear due to its principle of function. Thus, easy and rapid linearization procedures, in particular regarding compendial applications, are highly desirable. One effective approach to linearize the detector's signal makes use of the built-in power function value (PFV) setting of the instrument. The PFV is basically a multiplication factor to the power law exponent of the equation describing the CAD's response, thereby altering the detector's signal output to optimize the quasi-linear range of the response curve. The experimental optimization of the PFV for a series of analytes is a time-consuming process, limiting the practicability of this approach. Here, two independent approaches for the determination of the optimal PFV based on an empirical model and a mathematical transformation in each case, are evaluated. Both approaches can be utilized to predict the optimal PFV for each analyte solely based on the experimental results of a series of calibration standards obtained at a single PFV. The approaches were applied to the HPLC-UV-CAD impurity analysis of the drug gabapentin to improve the observed nonlinear response of the impurities in the range of interest. The predicted optimal PFV of both approaches were in good agreement with the experimentally obtained optimal PFV of the analytes. As a result, the accuracy of the method was significantly improved when using the optimal PFV (90 - 105% versus 81 - 115% recovery rate for quantitation by either single-point calibration or linear regression) for the majority of the analytes. The final method with a PFV adjusted to 1.30 was validated with respect to ICH guideline Q2(R1).

Universal response method for the quantitative analysis of multi-components in josamycin and midecamycin using liquid chromatography coupled with charged aerosol detector

Josamycin and midecamycin are consisted of three groups of components with different ultraviolet maximum absorption wavelengths (λ_max), which are 231 nm, 280 nm and 205 nm. The quantitative analysis of all these components is challengeable due to the absence of the respective reference substances. To address this problem, universal and reliable methods were developed using high performance liquid chromatography coupled with charged aerosol detector (HPLC-CAD) for the quantitative analysis of components in josamycin and midecamycin. The chromatographic conditions and CAD parameters setting were optimized. Subsequently, the components were identified using HPLC coupled with ion trap/time-of-flight mass spectrometry (IT/TOF MS). The developed methods were validated by assessing linearity, limit of quantitation (LOQ), accuracy, precision and robustness. Good separations were achieved for all components and the adjustment of the filter valve and power function value efficiently improved sensitivity. The developed methods were more comprehensive than current HPLC-UV method. The experimental results demonstrated good linearity with coefficients of determination (R²) greater than 0.999 in the range of 0.002-0.30 mg mL^-1. The limits of detection (LOD) were ranging from 1.8 to 2.0 μg·mL^-1. The intra-day and inter-day RSD values were less than 2.0 % (n = 6) and 5.6 % (n = 9) respectively. The recoveries were 95.0 %-124.0 % at the spiked concentration levels of 0.05 %, 0.50 %, 0.10 % and 2.5 % with relative standard deviations (RSDs, n = 3) lower than 2.0 %. Finally, the developed methods were successfully applied to the quantitative analysis of minor components and used main components (leucomycin A₃ and midecamycin A₁) as alternative reference substance of minor components. The overall results demonstrated that the HPLC-CAD was a good alternative for the quantitative analysis of multi-components in 16-membered macrolides.