@article{PawellekKrmarLeistneretal.2021,
  author    = {Pawellek, Ruben and Krmar, Jovana and Leistner, Adrian and Djajić, Nevena and Otašević, Biljana and Protić, Ana and Holzgrabe, Ulrike},
  title     = {Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach},
  series = {Journal of Cheminformatics},
  volume    = {13},
  journal   = {Journal of Cheminformatics},
  number    = {1},
  doi       = {10.1186/s13321-021-00532-0},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-261618},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Pawellek2021,
  author    = {Pawellek, Ruben},
  title     = {Charged Aerosol Detector Performance Evaluation and Development of Optimization Strategies for the Analysis of Amino Acids},
  doi       = {10.25972/OPUS-24319},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-243197},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {The charged aerosol detector (CAD) is an aerosol-based detector employed in liquid chromatography which has become established in the field of pharmaceutical analysis due to its outstanding performance characteristics, e.g. the almost uniform response for nonvolatile analytes. Owing to its principle of detection, the response of the CAD depends on the volatility of a compound and is inherently nonlinear. However, the newly implemented instrumental settings evaporation temperature and power function value (PFV) are valuable tools to overcome some of these drawbacks and can even enhance the detector's capabilities when adjusted properly. This thesis aimed to evaluate the impact of the new instrumental settings on the CAD performance. Additionally, the influence of modern separation techniques for small polar compounds on the CAD was assessed and the applicability of hyphenated UV-CAD techniques explored. The optimization strategies derived from the evaluation procedures and the conjunction of the instrumental and chromatographic techniques investigated were utilized for the challenging impurity profiling of amino acids and amino acid-like drugs. The results of the method validation procedures confirmed the broad applicability of the CAD in the pharmaceutical analysis of nonvolatile compounds, supported by satisfactory sensitivity and reproducibility for meeting the regulatory requirements with respect to the ICH guidelines Q2(R1) and Q3A(R2). The limits of applicability include the analysis of semivolatile compounds, and the method transfer between current and legacy CAD models. Further advances in the definition and standardization of allowed ranges for the instrumental settings and the establishment of general optimization procedures in the method development could lead to a more widespread use of the detection technique in compendial methods.},
  subject      = {Instrumentelle Analytik},
  language  = {en}
}