An Automated Continuous Synthesis and Isolation for the Scalable Production of Aryl Sulfonyl Chlorides.

In this work, a continuous system to produce multi-hundred-gram quantities of aryl sulfonyl chlorides is described. The scheme employs multiple continuous stirred-tank reactors (CSTRs) and a continuous filtration system and incorporates an automated process control scheme. The experimental process outlined is intended to safely produce the desired sulfonyl chloride at laboratory scale. Suitable reaction conditions were first determined using a batch-chemistry design of experiments (DOE) and several isolation methods. The hazards and incompatibilities of the heated chlorosulfonic acid reaction mixture were addressed by careful equipment selection, process monitoring, and automation. The approximations of the CSTR fill levels and pumping performance were measured by real-time data from gravimetric balances, ultimately leading to the incorporation of feedback controllers. The introduction of process automation demonstrated in this work resulted in significant improvements in process setpoint consistency, reliability, and spacetime yield, as demonstrated in medium- and large-scale continuous manufacturing runs.

Response surface methodology based on central composite design accompanied by multivariate curve resolution to model gradient hydrophilic interaction liquid chromatography: Prediction of separation for five major opium alkaloids.

Hydrophilic interaction liquid chromatography on bare silica presents some benefits for analysis and purification of ionizable basic alkaloids. This mode was used to separate five major opium alkaloids: morphine, codeine, thebaine, papaverine, and noscapine. Central composite design based on response surface methodology was applied for experimental design, modeling, and optimization in a single-step gradient method. The main effects and their interactions (initial percentage of modifier, changing range of modifier in run time, pH of buffer, and its concentration) were investigated in 30 experiments. Multivariate curve resolution-alternating least squares, by resolving overlapped curves, helped in the accurate calculation of baseline resolution factors to be modeled and optimized more accurately. Then three crucial resolution factors besides elution time were modeled in quadratic and cubic equations and optimized. In addition to the four factors, five extra logarithmic, and nonlogarithmic factors extracted from the four factors to give nine factors overall were inspected on mechanism of retention. It was shown that a linear combination consist of four independence variables successfully describes morphinans retentivity in a single-step gradient method.

Central composite design with the help of multivariate curve resolution in loadability optimization of RP-HPLC to scale-up a binary mixture.

Chromatographic method development for preparative targets is a time-consuming and subjective process. This can be particularly problematic because of the use of valuable samples for isolation and the large consumption of solvents in preparative scale. These processes could be improved by using statistical computations to save time, solvent and experimental efforts. Thus, contributed by ESI-MS, after applying DryLab software to gain an overview of the most effective parameters in separation of synthesized celecoxib and its co-eluted compounds, design of experiment software that relies on multivariate modeling as a chemometric approach was used to predict the optimized touching-band overloading conditions by objective functions according to the relationship between selectivity and stationary phase properties. The loadability of the method was investigated on the analytical and semi-preparative scales, and the performance of this chemometric approach was approved by peak shapes beside recovery and purity of products.

Elimination of chromatographic and mass spectrometric problems in GC-MS analysis of Lavender essential oil by multivariate curve resolution techniques: Improving the peak purity assessment by variable size moving window-evolving factor analysis.

In analysis of complex natural matrices by gas chromatography-mass spectrometry (GC-MS), many disturbing factors such as baseline drift, spectral background, homoscedastic and heteroscedastic noise, peak shape deformation (non-Gaussian peaks), low S/N ratio and co-elution (overlapped and/or embedded peaks) lead the researchers to handle them to serve time, money and experimental efforts. This study aimed to improve the GC-MS analysis of complex natural matrices utilizing multivariate curve resolution (MCR) methods. In addition, to assess the peak purity of the two-dimensional data, a method called variable size moving window-evolving factor analysis (VSMW-EFA) is introduced and examined. The proposed methodology was applied to the GC-MS analysis of Iranian Lavender essential oil, which resulted in extending the number of identified constituents from 56 to 143 components. It was found that the most abundant constituents of the Iranian Lavender essential oil are α-pinene (16.51%), camphor (10.20%), 1,8-cineole (9.50%), bornyl acetate (8.11%) and camphene (6.50%). This indicates that the Iranian type Lavender contains a relatively high percentage of α-pinene. Comparison of different types of Lavender essential oils showed the composition similarity between Iranian and Italian (Sardinia Island) Lavenders.

The use of multivariate curve resolution methods to improve the analysis of muramic acid as bacterial marker using gas chromatography-mass spectrometry: an alternative method to gas chromatography-tandem mass spectrometry.

In analysis of muramic acid (MA) as bacterial marker, two dominant disturbing factors lead the researchers to use gas chromatography-tandem mass spectrometry (GC-MS/MS) technique instead of gas chromatography-mass spectrometry (GC-MS). These factors are the trace concentration of MA and fundamental disturbance of base line mass channels in GC-MS technique. This study aimed to utilize multivariate curve resolution (MCR) methods combined with GC-MS to improve the analysis of MA. First, the background and noise in GC-MS analysis were corrected and reduced using MCR methods. In addition, the MA overlapped peaks were resolved to its pure chromatographic and mass spectral profiles. Then the two-way response of each component was reconstructed by the outer product of the pure chromatographic and mass spectral profiles. The overall volume integration (OVI) method was used for quantitative determination. The MA peak area was decreased dramatically after the background correction and noise reduction. The findings severely ratify the appropriateness of using MCR techniques combined with GC-MS analysis as a simple, fast and inexpensive method for the analysis of MA in complex mixtures. The proposed method may be considered as an alternative method to GC-MS/MS for thorough analysis of the bacterial marker.

Metabolomics fingerprinting of the human seminal plasma of asthenozoospermic patients.

It is estimated that 20% of couples are infertile, and half of these infertility cases are linked to men. One of conditions that can affect male fertility is asthenozoospermia. We applied Raman spectroscopy to the analysis of the metabolome of the human seminal plasma, and used chemometrics on the patterns of Raman spectra obtained. Significant changes were observed in the metabolome of the human seminal plasma of asthenozoospermic patients.