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W L Zielinski

Publications and source records attributed to W L Zielinski.

At least 19 recordsLinked to original sources
PubMed1999

Pharmaceutical fingerprinting in phase space. 1. Construction of phase fingerprints.

The present study proposes a general method for constructing pharmaceutical fingerprints in the analysis of HPLC trace organic impurity patterns. The approach considers signals in phase space and accounts for two different types of noise: additive and perturbative. The first type, additive noise, contributes to distortion of the absolute values of signal peaks. The second type, perturbative noise, contributes to variations of the retention times of signal peaks and distorts the time scale of the trace organic impurity patterns. The ability of the proposed approach to consider both types of noise significantly distinguishes it from existing methods of data analysis that are usually designed to treat only the additive noise. Analysis of the HPLC signals in phase space eliminates the problem of perturbation noise and enables detection and comparison of similar signal segments recorded at different retention times. The current study analyzes the chromatographic trace organic impurity patterns collected from six different manufacturers of L-tryptophan using three HPLC columns. For five manufacturers the variability of data recorded with the same column are in perfect agreement with the proposed model. A significant variance of parameters is detected for one manufacturer, thus indicating a possible change in its product consistency. The analysis in phase space is also used to explain the previously detected variability of HPLC signals across columns. The accompanying paper reports an application of the proposed approach for the pattern recognition of HPLC data.

Algorithms↗
PubMed1999

Pharmaceutical fingerprinting in phase space. 2. Pattern recognition.

The current study introduces an approach for pattern recognition of drug manufacturers according to their HPLC trace impurity data. This method considers signals in phase space and accounts for two different types of noise: additive and perturbative. The pharmaceutical fingerprints are estimated as mean trajectories of HPLC trace impurity data and are used as reference models for recognition of new data by the minimal length classifier. The chromatographic trace organic impurity patterns collected from six different manufacturers of L-tryptophan are analyzed as an example. The prediction ability of the new method tested using three different cross-validation procedures remains about 95% even if the number of available data in the training sets decreases by 5 times. The accuracy of prediction in phase space is superior compared to results calculated using a Window Preprocessing method and artificial neural networks. The difference in performance between new and previous methods becomes more significant under particular conditions that are more adequate for practical application of the method. In addition, the current approach enables simple and comprehensive interpretation of the calculated results.

Artificial Intelligence↗
PubMed1997

Monitoring recombinant protein drugs: a study of insulin by H/D exchange and electrospray ionization mass spectrometry.

The increasing emergence of new protein- and peptide-based drugs makes necessary the development of rapid and sensitive methods to check consistency between and within batches of biotechnology pharmaceuticals to ensure product quality. We evaluated electrospray ionization mass spectrometry in combination with H/D isotopic exchange as a potential tool, taking as examples for this case study the four insulins used for treating insulin-dependent diabetes. Two (bovine and porcine) are produced naturally, and two are produced by recombinant biotechnology techniques [recombinant human (r-human) and its human insulin analog (LysPro)]. The extent of H/D exchange at a given time was measured with less than 2 micrograms (< 350 pmol) of sample and was sufficient for discriminating among the different insulins. After 60 min, bovine, porcine, r-human, and LysPro insulins exchanged on average 25, 28, 30, and 38 amide protons, respectively. After prolonged incubation with D2O for 24 h, bovine and porcine insulins exchanged 31 protons, whereas r-human and LysPro insulins exchanged 34 and 43 amide protons, respectively. The differences in H/D exchange are protein signatures that relate to differences in conformation and folding. The extent of exchange distinguishes among the insulin types and assures the consistency of batch preparations for a given insulin.

Animals↗
PubMed1997

Preprocessing of HPLC trace impurity patterns by wavelet packets for pharmaceutical fingerprinting using artificial neural networks.

The immediate objective of this research program is to evaluate several computer-based classifiers as potential tools for pharmaceutical fingerprinting based on analysis of HPLC trace organic impurity patterns. In the present study, wavelet packets (WPs) are investigated for use as a preprocessor of the chromatographic data taken from commercial samples of L-tryptophan (LT) to extract input data appropriate for classifying the samples according to manufacturer using artificial neural networks (ANNs) and the standard classifiers KNN and SIMCA. Using the Haar function, WP decompositions for levels L = 0-10 were generated for the trace impurity patterns of 253 chromatograms corresponding to LT samples that had been produced by six commercial manufacturers. Input sets of N = 20, 30, 40, and 50 inputs were constructed, each one consisting of the first N/2 WP coefficents and corresponding positions from the overall best level (L = 2). The number of hidden nodes in the ANNs was also varied to optimize performance. Optimal ANN performance based on percent correct classifications of test set data was achieved by ANN-30-30-6 (97%) and ANN-20-10-6 (94%), where the integers refer to the numbers of input, hidden, and output nodes, respectively. This performance equals or exceeds that obtained previously (Welsh, W.J.; et al.Anal.Chem. 1996, 68, 3473) using 46 inputs from a so-called Window preprocessor (93%). KNN performance with 20 inputs (97%) or 30 inputs (90%) from the WP preprocessor also exceeded that obtained from the Window preprocessor (85%), while SIMCA performance with 20 inputs (86%) or 30 inputs (82%) from the WP preprocessor was slightly inferior to that obtained from the Window preprocessor (87%). These results indicate that, at least for the ANN and KNN classifiers considered here, the WP preprocessor can yield superior performance and with fewer inputs compared to the Window preprocessor.

Chromatography, High Pressure Liquid↗
PubMed1996

Pharmaceutical fingerprinting: evaluation of neural networks and chemometric techniques for distinguishing among same-product manufacturers.

The present study was undertaken to evaluate several computer-based classifiers as potential tools for pharmaceutical fingerprinting by utilizing normalized data obtained from HPLC trace organic impurity patterns. To assess the utility of this approach, samples of L-tryptophan (LT) drug substance were analyzed from commercial production lots of six different manufacturers. The performance of several artificial neural network (ANN) architectures was compared with that of two standard chemometric methods, K-nearest neighbors (KNN) and soft independent modeling of class analogy (SIMCA), as well as with a panel of human experts. The architecture of all three computer-based classifiers was varied with respect to the number of input variables. The ANNs were also optimized with respect to the number of nodes per hidden layer and to the number of hidden layers. A novel preprocessing scheme known as the Window method was devised for converting the output of 899 data entries extracted from each chromatogram into an appropriate input file for the classifiers. Analysis of the test set data revealed that an ANN with 46 inputs (i.e., ANN-46) was superior to all other classifiers evaluated, with 93% of the chromatograms correctly classified. Among the classifiers studied in detail, the order of performance was ANN-46 (93%) > SIMCA-46 (87%) > KNN-46 (85%) = ANN-899 (85%) > "human experts" (83%) > SIMCA-899 (78%) > or = ANN-22 (77%) = KNN-22 (77%) > or = KNN-899 (76%) > SIMCA-22 (73%). These results confirm that ANNs, particularly when used in conjunction with the Window preprocessing scheme, can provide a fast, accurate, and consistent methodology applicable to pharmaceutical fingerprinting. Particular attention was paid to variations in the HPLC patterns of same-manufacturer samples due to differences in LT production lots, HPLC columns, and even run-days to quantify how these factors might hinder correct classifications. The results from these classification studies indicate that the chromatograms evidenced variations across LT manufacturers, across the three HPLC columns and, for one manufacturer, across lots. The extent of column-to-column variations is particularly noteworthy in that all three columns had identical specifications with respect to their stationary-phase characteristics and two of the three columns were from the same vendor.

Chemistry, Pharmaceutical↗
PubMed1996

Use of moment of inertia in comparative molecular field analysis to model chromatographic retention of nonpolar solutes.

A quantitative structure-retention relationship (QSRR) was developed from chromatographic data on 31 unsubstituted 3-6 ring polycyclic aromatic hydrocarbons (PAHs) using the 3D-QSAR method known as comparative molecular field analysis (CoMFA). The resulting CoMFA model gave an excellent correlation to high-performance liquid chromatography retention data for these PAHs yielding r2 values of 0.947 (conventional) and 0.865 (cross-validated). The steric and electrostatic contributions to the CoMFA model were 100% and 0%, respectively. A unique feature of this study was the use of moment of inertia, I, as a basis for CoMFA alignment of the PAH molecules. The moment of inertia also provided an alternative method for calculating the solute length-to-breadth ratio (L/B), which has been applied in previous QSRR studies as a molecular descriptor for PAH retention. By virtue of its mathematical simplicity and lack of ambiguity, the present derivation of L/B from I offers several advantages over other geometry-based schemes. Finally, Ix was evaluated for use as a molecular descriptor in QSRR regression analysis to predict the log of the retention index (log I) for these PAHs. The correlation with PAH retention was weak when the moment of inertia was considered alone but improved dramatically (r2 = 0.928) when the moment of inertia and connectivity index chi were used in combination as descriptors.

Chromatography, High Pressure Liquid↗
PubMed1993

Synthesis and stability of isotopically labeled p-chloro-m-xylenol (PCMX).

The synthesis, reaction kinetics, and pH stability of isotopically labeled p-chloro-m-xylenol (PCMX) were evaluated. While base catalysis was more rapid than acid catalysis, the latter allowed the use of a cosolvent for deuterium and tritium labeling using as little as 250 microL labeled water. Both acid and base catalysis were markedly more rapid than that reported previously for the deuteration of PCMX and related phenols. Isotopic labeling occurred only at the 2 and 6 ring positions, ortho to the phenolic group of PCMX. No deuterium loss was observed after storage for 21 days at 37 degrees C over a pH range of 2-14. Isotopic loss was observed only below pH 2. The prepared 3H-labeled PCMX had a specific activity of 1.18 mCi/mmol, a radiochemical purity of 99.0%, and a chemical purity exceeding 99.0%, with a high stability during prolonged cold storage.

Anti-Infective Agents, Local↗
PubMed1979

Characterization of methanol extraction residue (MER) from Bacillus Calmette-Guérin (BCG).

Analysis of methanol extraction residue (MER) from Bacillus Calmette-Guerin (BCG) was carried out to determine some specific chemical compositional characteristics. Samples of MER were found to contain approximately 40% protein and/or peptide, 3% soluble lipids, 17% bound lipids, 8% elemental nitrogen, and less than 2% mycolic acids. Amino acid analysis showed the presence of alanine, glycine and glutamic acid as the major amino acids. The data are reported in terms of the range found for each constituent over the samples analyzed. Somewhat consistent results were obtained between different MER preparations, but notable compositional variations were observed in samples of MER suspensions.

Amino Acids↗
PubMed1977

Nondestructive distinction between aflatoxin B1 and ethoxyquin in thin-layer chromatography.

A rapid and simple method has been developed for the nondestructive distinction between aflatoxin B1 and the feed antioxidant, ethoxyquin. These two chemicals exhibit similar RF values in certain solvent systems and produce a similar bluish fluorescence under long UV (366 nm) radiation. The method involves the in situ generation of fluorescence spectra of the respective thin-layer chromatography spots. Since it is nondestructive, the method affords ancillary study of the separated aflatoxins.

Aflatoxins↗
PubMed1977

Separation of alkylated guanines, adenines, uracils and cytosines by thin-layer chromatography.

A one-dimensional thin-layer chromatographic (TLC) method using a mixture of two solvents and commercially available silica gel plates to separate mixtures of alkylated guanines, adenines, uracils and cytosines is presented. RF values for the bases and the solvent systems used are listed. The addition of approximately 1 ml of ammonium hydroxide to the solvent has been found to prevent streaking and results in non-distorted developed spots. A mixture of 19 adenine and uracil bases was resolved on silica gel plates employing two-dimensional TLC. Chloroform-methanol (90:10) was used for the first dimension and chloroform-propanol (90:30) for the second.

Adenine↗
PubMed1977

Determination of N1-methylnicotinamide in urine by high-pressure liquid chromatography.

This paper reports a precise method that is shorter than previously reported methods for the quantitative determination of N1-methylnicotinamide (MNA) in urine. The method employs a single column chromatographic isolation step, followed by high-pressure liquid chromatographic (HPLC) analysis. Potential interfering substances present in urine are removed during the column chromatography step. The combined MNA fractions eluted from this column were collected and concentrated for quantitative assay of MNA by HPLC. HPLC analysis was effected in less than 15 min using a strong cation- exchange column eluted with 0.25 M ammonium dihydrogen phosphate (pH 4.3). Linearity of MNA detection by HPLC at 254 nm extended below 20 ng, with an average recovery of 101% for 150, 250 and 500 microgram MNA added to 5 ml or urine.

Chromatography, High Pressure Liquid↗
PubMed1977

High performance liquid chromatographic analysis of supplemental vitamin E in feed.

Supplemental vitamin E is extracted from feed in one step with methanol and analyzed by reverse phase partition chromatography in less than 10 min, using isocratic elution with either methanol or water-methanol as the mobile phase. Detection response (as measured by peak area) was linear between 0.5 and 3.0 mug, and the coefficients of variation for retention time and peak height on replicate analyses of the standard sample were 0.8 and 2.3%, respectively.

Animal Feed↗