TY  - JOUR
A1  - Pawellek, Ruben
A1  - Krmar, Jovana
A1  - Leistner, Adrian
A1  - Djajić, Nevena
A1  - Otašević, Biljana
A1  - Protić, Ana
A1  - Holzgrabe, Ulrike
T1  - Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach
JF  - Journal of Cheminformatics
N2  - 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% (Q\(^2\): 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 (R-2: 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.
KW  - High-performance liquid chromatography (HPLC)
KW  - Charged aerosol detector (CAD)
KW  - Gradient boosted trees (GBT)
KW  - Quantitative structure-property relationship modeling (QSPR)
KW  - Fatty acids
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-261618
VL  - 13
IS  - 1
ER  - 
TY  - JOUR
A1  - Walther, Rasmus
A1  - Krmar, Jovana
A1  - Leistner, Adrian
A1  - Svrkota, Bojana
A1  - Otašević, Biljana
A1  - Malenović, Andjelija
A1  - Holzgrabe, Ulrike
A1  - Protić, Ana
T1  - Analytical Quality by Design: achieving robustness of an LC-CAD method for the analysis of non-volatile fatty acids
JF  - Pharmaceuticals
N2  - An alternative to the time-consuming and error-prone pharmacopoeial gas chromatography method for the analysis of fatty acids (FAs) is urgently needed. The objective was therefore to propose a robust liquid chromatography method with charged aerosol detection for the analysis of polysorbate 80 (PS80) and magnesium stearate. FAs with different numbers of carbon atoms in the chain necessitated the use of a gradient method with a Hypersil Gold C\(_{18}\) column and acetonitrile as organic modifier. The risk-based Analytical Quality by Design approach was applied to define the Method Operable Design Region (MODR). Formic acid concentration, initial and final percentages of acetonitrile, gradient elution time, column temperature, and mobile phase flow rate were identified as critical method parameters (CMPs). The initial and final percentages of acetonitrile were fixed while the remaining CMPs were fine-tuned using response surface methodology. Critical method attributes included the baseline separation of adjacent peaks (α-linolenic and myristic acid, and oleic and petroselinic acid) and the retention factor of the last compound eluted, stearic acid. The MODR was calculated by Monte Carlo simulations with a probability equal or greater than 90%. Finally, the column temperature was set at 33 °C, the flow rate was 0.575 mL/min, and acetonitrile linearly increased from 70 to 80% (v/v) within 14.2 min.
KW  - Analytical Quality by Design
KW  - fatty acids
KW  - charged aerosol detector
KW  - polysorbate 80
KW  - magnesium stearate
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-311265
SN  - 1424-8247
VL  - 16
IS  - 4
ER  -