Biomedical subjects

G Vivó-Truyols

Publications and source records attributed to G Vivó-Truyols.

10 recordsLinked to original sources

PubMed2005

Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals part I: peak detection.

A series of two papers describing a procedure for automated peak deconvolution is presented. The goal is to develop a package of routines that can be used by non-experienced users. Part I (this paper) concerns peak detection, whereas Part II is dedicated to the deconvolution itself. In this first part, the most interesting features of the peak detection algorithms, which precede the deconvolution step, are outlined. High-order derivatives provide valuable information to assess the number of underlying compounds under a given peak cluster. A smoothing technique was found essential to compute properly the derivatives, since the noise is amplified when differences are calculated. The Savitsky-Golay smoother was applied in combination with the Durbin-Watson criterion to automate the window size selection. This strategy removed the noise without loosing valuable information. In some cases, it was found preferable to split the chromatogram in different elution regions, and apply the Durbin-Watson test and the Savitsky-Golay smoother to each region, separately. The derivatives allowed obtaining estimates of both peak parameters and the corresponding ranges for each eluting compound to be used in the deconvolution. An algorithm oriented to compare peaks from different chromatograms is also presented to perform deconvolution, using information from several related chromatograms.

Algorithms↗

PubMed2005

Robust interpretive optimisation in high-performance liquid chromatography considering uncertainties in peak position.

In the context of interpretive chromatographic optimisation, robustness is usually calculated by introducing deliberated shifts in the nominal optimal conditions and evaluating their effects on the monitored objective function, mimicking thus the experimental procedures used in method validation. However, such strategy ignores a major source of error: the uncertainties associated to the modelling step, that may give rise to deceiving results when conditions that were expected to yield baseline separation are reproduced in the chromatograph. Two approaches, based on the peak purity concept, are here proposed to evaluate the robustness of the objective function under the perspective of measurement errors and modelling. The first approach implements these uncertainties as an extra band broadening for each chromatographic peak. The second one implements them as peak fluctuations in simulated replicated assays, which gives rise to a distribution of peak purities, easily computed through Monte-Carlo simulations. Both approaches predict satisfactorily a decreased separation capability, with respect to the conventional approach, for those situations where the uncertainties in peak position make the objective function critical. The first approach is less optimistic and formally less rigorous than the second one, but its computation is simpler. It can be used to map the critical resolution regions, to be comprehensively appraised further by the slower, although more rigorous, Monte-Carlo approach.

Amino Acids↗

PubMed2005

Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals part II: peak model and deconvolution algorithms.

Several interlinked algorithms for peak deconvolution by non-linear regression are presented. These procedures, together with the peak detection methods outlined in Part I, have allowed the implementation of an automatic method able to process multi-overlapped signals, requiring little user interaction. A criterion based on the evaluation of the multivariate selectivity of the chromatographic signal is used to auto-select the most efficient deconvolution procedure for each chromatographic situation. In this way, non-optimal local solutions are avoided in cases of high overlap, and short computation times are obtained in situations of high resolution. A new algorithm, fitting both the original signal and the second derivatives is proved to avoid local optima in intermediate coelution situations. This allows achieving the global optimum without the need of background knowledge by the user. A previously reported peak model, a Gaussian with a polynomial standard deviation whose complexity can be modulated to enhance the fitting quality, was applied. However, the original formulation was modified to account baseline outside the peak region. Also, the optimal model complexity was auto-selected via error propagation theory. The method is able to process simultaneously several related chromatograms. The software was tested with both simulated and experimental chromatograms obtained with monolithic silica columns.

Algorithms↗

PubMed2005

Limits of multi-linear gradient optimisation in reversed-phase liquid chromatography.

The concept of limiting peak purity was applied to quantify the degree of completion of the separation capability of a chromatographic system using multi-linear gradients. The objective was to check whether the complexity of a gradient program deserves be increased to enhance resolution by inserting more linear segments, or on the contrary, no significant improvements can be expected under more complex gradients. A set of 19 isoindole derivatives of primary amino acids was selected to test the performance of isocratic, single linear and multi-linear gradients. Accurate simulated chromatograms were obtained via numerical integration of the general equation of gradient elution, using pre-established start and end conditions of the gradient program. The overall peak purity was selected as objective function. Good--although not baseline--resolution was achieved with an optimal trilinear gradient. Excellent agreement between experimental and predicted optimal chromatograms was found. With the proposed approach, a degree of completion of the separation capability of the chromatographic system of 21.2, 49.7, 81.5 and 88.5% was accomplished with optimal gradients with one, two, three and four segments, respectively. More complex gradients did not enhance the latter figure significantly. Also, multi-linear gradients gave rise to more benefits than complementary gradients.

Chromatography, Liquid↗

PubMed2004

Estimation of significant solvent concentration ranges and its application to the enhancement of the accuracy of gradient predictions.

The solvent concentration range actually useful for gradient predictions is significantly narrower than the total range scanned in a gradient run. This range, called "solvent informative range" (SIR), if known with the highest accuracy, allows to predict gradient retention times (t(g) with minimal error. The small size of the SIR supports the application of the linear solvent strength theory (LSST). Furthermore, LSST allows a closed-form solution to the integral required to predict gradient retention times, which eliminates numerical integration, needed with other retention models. A methodology that calculates the SIR by applying error analysis, and uses it to improve the accuracy in the prediction of t(g) from isocratic experiments, is proposed. The importance of those mobile-phase compositions that do not contribute significantly to the prediction of t(g) is selectively attenuated within the prediction algorithm, relying the predictions more heavily on the SIR. As a result, t(g) was found to be predicted with similar accuracy using isocratic training data with regard to predictions based on gradient training data. The approach is useful for all situations where the chromatographer is able to provide predictions of retention at constant solvent concentration, and wish to predict the retention in gradient mode.

Algorithms↗

PubMed2003

Enhanced calculation of optimal gradient programs in reversed-phase liquid chromatography.

The resolution of a mixture of 16 beta-blockers under gradient elution was optimised using both isocratic and gradient training sets, with a reversed-phase column and acetonitrile-water eluents. Error theory was applied to measure the information extracted from different gradient experimental designs. This allows checking the expected accuracy when gradient predictions exceed the initial solvent concentrations tested in the training set. This work applies the results on modelling found in a previous study [J. Chromatogr. A 1018 (2003) 169] where the performance of several retention models was compared. Enhanced retention predictions were applied to the optimisation of gradient programs involving three factors (gradient slope, initial solvent composition and gradient curvature), using the peak purity criterion as resolution assessment. Peak shape parameters required in peak purity evaluation were modelled by adapting previous developments in isocratic mode. The mixture, which required prohibitive analysis times under isocratic elution, was almost baseline resolved in less than 35 min with linear gradients. Curvilinear gradients did not enhance this result significantly.

Chromatography, High Pressure Liquid↗

PubMed2003

Error analysis and performance of different retention models in the transference of data from/to isocratic/gradient elution.

The transferability of retention data among isocratic and gradient RPLC elution modes is studied. For this purpose, 16 beta-blockers were chromatographed under both isocratic and gradient elution with acetonitrile-water mobile phases. Taking into account the elution mode where the experimental data come from, and the mode where the retention should be predicted, the following combinations are possible: isocratic predictions from (i) isocratic or (ii) gradient experimental designs; and gradient predictions from (iii) isocratic or (iv) gradient data. Each of these possibilities was checked using three retention models that relate the logarithm of the retention factor: (a) linearly and (b) quadratically with the volume fraction of organic solvent, and (c) linearly with a normalised mobile phase polarity parameter. The study was carried out under two different perspectives: a straightforward examination of the prediction errors and the analysis of the uncertainties derived from the variance-covariance matrix of the fitted models. The best combinations of prediction mode and model were: (i)-(b), (ii)-(c), (iii)-(b), and (iv)-(a) or (c).

Chromatography, Liquid↗

PubMed2003

Net analyte signal as a deconvolution-oriented resolution criterion in the optimisation of chromatographic techniques.

The performance of two multivariate calibration measurements, multivariate selectivity (SEL(s)) and scalar net analyte signal (scalar NAS), as chromatographic objective functions (COFs), was investigated. Since both assessments are straightforwardly related to the quantification of analytes in the presence of interferents, they were expected to confer new features in the optimisation of compound resolution, not present in conventional assessments. These capabilities are especially interesting in situations of low resolution, where peak deconvolution becomes an attractive alternative. For comparison purposes, chromatographic resolution (R(s)) and peak purity (p(s)) were used as reference COFs. In order to correlate COFs with the probability of deconvolution error, an artificial peak crossing was used to generate 73 different peak arrangements, which were deconvolved using three different methods. SEL(s) exhibited the best correlation, which allowed predicting properly the risk of obtaining inaccurate deconvolutions. The optimisation of a poorly resolved mixture of 16 aromatic compounds by reversed-phase liquid chromatography with methanol-water and acetonitrile-water mobile phases was examined to investigate the differences in performance among the resolution criteria. In situations like these, SEL(s) tends to consider acceptable mobile phase compositions with partial coelution, which permits however the deconvolution with low errors. In contrast, p(s) selects compositions where the resolution of some compounds is sacrificed to enhance the separation of others. Scalar NAS was not so favourable as expected, since it depends on sampling frequency and peak widening. SEL(s) was not affected by these factors.

Acetonitriles↗

PubMed2002

Peak deconvolution in one-dimensional chromatography using a two-way data approach.

A deconvolution methodology for overlapped chromatographic signals is proposed. Several single-wavelength chromatograms of binary mixtures, obtained in different runs at diverse concentration ratios of the individual components, were simultaneously processed (multi-batch approach), after being arranged as two-way data. The chromatograms were modelled as linear combinations of forced peak profiles according to a polynomially modified Gaussian equation. The fitting was performed with a previously reported hybrid genetic algorithm with local search, leaving all model parameters free. The approach yielded more accurate solutions than those found when each experimental chromatogram was fitted independently to the peak model (single-batch approach). The improvement was especially significant for those chromatograms where the peaks were severely affected by the tails of the preceding compounds. Peak shifts among chromatograms, which are a usual source of non-bilinearity, were modelled in a continuous domain instead of in a discrete way, which avoided some drawbacks associated with latent variable methods. An experimental design involving simulated chromatograms was applied to check the method performance. Five main factors affecting the deconvolution were examined: concentration pattern, chromatographic resolution, number of batches and replicates, and noise level, which were evaluated using first- and second-order figures of merit. The method was also tested on three real samples containing compounds showing different overlap. Four multi-batch deconvolution methods were considered differing in the nature of the processed information and kind of peak matching among chromatograms. In all cases, the multi-batch deconvolution yielded better performance than the single-batch approach.

Chromatography↗

PubMed2000

Complementary mobile-phase optimisation for resolution enhancement in high-performance liquid chromatography.

An optimisation methodology in high-performance liquid chromatography (HPLC) is presented for the selection of two or more mobile phases having an optimal complementary resolution. The complementary mobile phases (CMPs) are selected in such a way that each one resolves optimally only some compounds in the mixture, while the remainder, resolved by the other mobile phase(s), can overlap among them. The methodology is based on the computation of a peak purity measurement for each solute, using an asymmetrical peak model for peak simulation. Two global resolution criteria (product of elementary resolutions and worst elementary resolution) and two methods for solving the problem (a systematic examination of all possible solute arrangements, and the use of genetic algorithms to expedite the calculation time) were used to find the optimal CMPs. The CMP optimisation methodology was applied to the resolution of a mixture of 10 diuretics and beta-blockers, which could not be resolved using a single mobile phase; virtual baseline resolution was achieved, however, with two CMPs.

Algorithms↗