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Herein, we describe two practical approaches to synthesize ( R )-(+)-1,2-epoxy-5-hexene from inexpensive and readily available raw materials and reagents. The first approach is a two-step sequence, involving an epoxidation with meta -chloroperoxybenzoic acid (mCPBA) and a chiral resolution with (salen)Co(II), producing ( R )-(+)-1,2-epoxy-5-hexene in 24-30% overall yield. The second approach utilizes readily available ( R )-epichlorohydrin as the starting material and features an epoxide ring-opening reaction with allylMgCl and the NaOH-mediated ring closure reaction. Development of this two-step process affords R -(+)-1,2-epoxy-5-hexene in overall isolated yields of 55-60% with an exceptional purity profile. Both approaches have been successfully demonstrated on 100-200 g scales., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

In this work, a new model with broad utility for quantitative spectroscopy development is reported. A primary objective of this work is to create a novel modeling procedure that may allow for higher automation of the model development process. The fundamental concept is simple yet powerful even for complex spectra and is employed with no additional preprocessing. This approach is applicable for several types of spectroscopic data to develop regression models that have similar or greater quality than the current methods. The key modeling steps are a matrix transformation and subsequent feature selection process that are collectively referred to as iterative regression of corrective baselines (IRCB). The transformed matrix ( X transform ) is a linearized form of the original X data set. Features from X t ransform that are predictive of Y can be ranked and selected by ordinary least-squares regression. The best features (rows of X t ransform ) are linear depictions of Y that can be utilized to develop regression models with several machine learning models. The IRCB workflow is first detailed by using a case study of Fourier transform infrared (FTIR) spectroscopy for prepared solutions of a three-component mixture. Next, IRCB is applied and compared to benchmark results for the 2006 "Chimiométrie" near-infrared spectroscopy (NIR) soil composition challenge and Raman measurements of a simulated nuclear waste slurry.

Visceral leishmaniasis (VL), a parasitic, poverty-linked, neglected disease, is endemic across multiple regions of the world and fatal if untreated. There is an urgent need for a better and more affordable treatment for VL. DNDI-6148 is a promising drug candidate being evaluated for the treatment of VL; however, the current process for producing the key intermediate of DNDI-6148, 6-amino-1-hydroxy-2,1-benzoxaborolane, is expensive and difficult to scale up. Herein, we describe two practical approaches to synthesizing 6-amino-1-hydroxy-2,1-benzoxaborolane from inexpensive and readily available raw materials. Starting with 4-tolunitrile, the first approach is a five-step sequence involving a Hofmann rearrangement, resulting in an overall yield of 40%. The second approach utilizes 2-methyl-5-nitroaniline as the starting material and features borylation of aniline and continuous flow hydrogenation as the key steps, with an overall yield of 46%. Both routes bypass the nitration of 1-hydroxy-2,1-benzoxaborolane, which is challenging and expensive to scale. In particular, the second approach is more practical and scalable because of the mild operating conditions and facile isolation process., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

A concise and practical synthesis has been developed to provide the 8-fluoro-5-hydroxy-3,4-diydrocarbostyril ( 8-FDC ) fragment of OPC-167832 in 41% yield and in >99% purity over four steps from 3-amino-4-fluorophenol. The key feature of this process is the development of a telescoped one-pot synthesis of the quinolone via a chemoselective amidation/acid-induced cyclization that allows for simple product isolation without the need for column chromatography., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

A scalable four-step synthesis of molnupiravir from cytidine is described herein. The attractiveness of this approach is its fully chemical nature involving inexpensive reagents and more environmentally friendly solvents such as water, isopropanol, acetonitrile, and acetone. Isolation and purification procedures are improved in comparison to our earlier study as all intermediates can be isolated via recrystallization. The key steps in the synthesis, namely, ester formation, hydroxyamination, and deprotection were carried out on a multigram scale to afford molnupiravir in 36-41% yield with an average purity of 98 wt % by qNMR and 99 area% by HPLC., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

Pyrrolotriazine 1 is an important precursor to remdesivir. Initial results toward an efficient synthesis are disclosed consisting of sequential cyanation, amination, and triazine formation beginning from pyrrole. This route makes use of highly abundant, commoditized raw material inputs. The yield of triazine was doubled from 31% to 59%, and the synthetic step count was reduced from 4 to 2. These efforts help to secure the remdesivir supply chain.

The main aim of this work was to 3D print metformin HCl-loaded PVA (ML-PVA) tablets by fused deposition modeling. A modified solvent diffusion approach was used to improve drug loading. PVA filaments were placed in metformin HCl solution in ethanol containing low water content (10%(v/v)) to enhance the drug's solubility. The physicochemical properties of ML-PVA filaments were characterized before and after printing. Lastly, ML-PVA filaments were printed into channeled tablet designs to increase their surface area available for dissolution. The loading of metformin HCl onto PVA filament has significantly increased from 0.08 ± 0.02% in metformin HCl solution in absolute ethanol to 1.40 ± 0.02% in ethanol-water (9:1). The IR spectra of PVA filament soaked in ethanol-water depicted higher peak intensity at 1138 cm -1 , indicating higher degree of crystallinity. Thermal analysis of the soaked PVA filaments showed higher melting enthalpies yet lower melting temperature (T m ) compared to unprocessed PVA. ML-PVA filaments were successfully printed into round-channeled tablets (10% infill) with higher surface area and area/volume ratios compared with the solid ones. The inclusion of channels in the tablet design modified their printing pattern causing an unexpected increase in their mass. The dissolution profiles of ML-PVA tablets were mainly dependent on their area/mass ratios. Our results show a simple approach to increase metformin HCl loading onto PVA and reveal the significance of tablet design, infill percentage, and printing pattern as they dictate the area, volume, and the mass of the tablet which impact its dissolution rate.

Chromatographic characterization and parameterization studies targeting many solutes require the judicious choice of operating conditions to minimize analysis time without compromising the accuracy of the results. To minimize analysis time, solutes are often grouped into a small number of mixtures; however, this increases the risk of peak overlap. While multivariate curve resolution methods are often able to resolve analyte signals based on their spectral qualities, these methods require that the chromatographically overlapped compounds have dissimilar spectra. In this work, a strategy for grouping compounds into sample mixtures containing solutes with distinct spectral and, optionally, with distinct chromatographic properties, in order to ensure successful solute resolution either chromatographically or with curve resolution methods is proposed. We name this strategy rational design of mixtures (RDM). RDM utilizes multivariate selectivity as a metric for making decisions regarding group membership ( i.e. , whether to add a particular solute to a particular sample). A group of 97 solutes was used to demonstrate this strategy. Utilizing both estimated chromatographic properties and measured spectra to group these 97 analytes, only 12 groups were required to avoid a situation where two or more solutes in the same group could not be resolved either chromatographically (i.e. , they have significantly different retention times) or spectrally (i.e., spectra are different enough to enable resolution by curve resolution methods). When only spectral properties were utilized ( i.e. , the chromatographic properties are unknown ahead of time) the number of groups required to avoid unresolvable overlaps increased to 20. The grouping strategy developed here will improve the time and instrument efficiency of studies that aim to obtain retention data for solutes as a function of operating conditions, whether for method development or determination of the chromatographic parameters of solutes of interest ( e.g. , k w )., (© 2019 The Authors.)

Continuous flow chemistry has the potential to greatly improve efficiency in the synthesis of active pharmaceutical ingredients (APIs); however, the optimization of these processes can be complicated by a large number of variables affecting reaction success. In this work, a screening design of experiments was used to compare computational fluid dynamics (CFD) simulations with experimental results. CFD simulations and experimental results both identified the reactor residence time and reactor temperature as the most significant factors affecting product yield for this reaction within the studied design space. A point-to-point comparison of the results showed absolute differences in product yield as low as 2.4% yield at low residence times and up to 19.1% yield at high residence times with strong correlation between predicted and experimental percent yields. CFD was found to underestimate the product yields at low residence times and overestimate at higher residence times. The correlation in predicted product yield and the agreement in identifying significant factors in reaction performance reveals the utility of CFD as a valuable tool in the design of continuous flow tube reactors with significantly reduced experimentation., (© 2019 The Royal Society of Chemistry.)

Analysis of liquid chromatography-mass spectrometry (LC-MS) data requires the differentiation between a small number of relevant chemical signals and a larger amount of noise. This is often done based, at least partially, on a threshold which assumes that low intensity m/z signals arise from the noise. This eliminates low-intensity fragments, isotopes, and adducts and may exclude relevant low-intensity compounds all together. This work describes the use of multivariate curve resolution-alternating least-squares with an additional sparse regression step using elastic net (MCR-ENALS) to distinguish relevant m/z signals without the use of a harsh thresholding step, thus allowing for discovery of low-intensity m/z signals corresponding to the analytes. This strategy is demonstrated first on a unit mass analysis of amphetamines in which relevant m/z signals are found at as low as a 0.1% intensity relative to the molecular m/z peak. The incorporation of MCR-ENALS into our previously reported data reduction strategy for analysis of high-resolution LC-MS is also demonstrated. Analysis based on only 0.3% of the original data set, while retaining low-intensity isotope peaks, was accomplished without the use of thresholding, allowing for the application of MCR-ENALS to the high-resolution LC-MS data.

Comprehensive two-dimensional liquid chromatography (LC × LC) has been gaining popularity for the analysis of complex samples in a wide range of fields including metabolomics, environmental analysis, and food analysis. While LC × LC can provide greater chromatographic resolution than one-dimensional LC (1D-LC), overlapping peaks are often still present in separations of complex samples, a problem that can be alleviated by chemometric curve resolution techniques such as multivariate curve resolution-alternating least squares (MCR-ALS). MCR-ALS has also been previously shown to assist in the quantitative analysis of LC x LC data by isolating pure analyte signals from background signals which are often present at higher levels in LC x LC compared to 1D-LC. In this work we present the analysis of a dataset from the LC × LC analyses of parsley, parsnip and celery samples for the presence and concentrations of 14 furanocoumarins. Several MCR-ALS implementations are compared for the analysis of LC × LC data. These implementations include analyzing the LC x LC chromatogram alone, analyzing the one-dimensional chromatogram alone, as well as two hybrid approaches that make use of both the first and second dimension chromatograms. Furthermore, we compared manual integration of resolved chromatograms versus a simple summation approach, using the resolved chromatographic peaks in both cases. It is found that manual integration of the resolved LC × LC chromatograms provides the best quantification as measured by the consistency between replicate injections. If the summation approach is desired for automation, the choice of MCR-ALS implementation has a large effect on the precision of the analysis. Based on these results, the concentrations of the 14 furanocoumarins are determined in the three apiaceous vegetable types by analyzing the LC × LC chromatograms with MCR-ALS and manual integration for peak area determination. The concentrations of the analytes are found to vary greatly between samples, even within a single vegetable type., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Methods such as liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) are crucial for differentiating compounds with highly similar masses. This is a necessity when analyzing highly complex samples; however, the size of high-resolution LC-HRMS data sets can cause difficulties when applying advanced data analysis techniques. In this work, LC-HRMS analyses of known amphetamine samples and unknown bacterial lipid samples were carried out, and multivariate curve resolution-alternating least squares (MCR-ALS) was applied to the data to obtain mathematical separation of overlapped analyte signals. In order to minimize computational strain, a novel strategy was developed which minimizes the number of irrelevant masses analyzed at full resolution. To do this, data were first binned to unit mass resolution, and MCR-ALS was performed. This provided mathematical components for each analyte present plus background components. In the resolved spectral profiles of analyte components, masses above a preset intensity threshold were extracted, discarding all other masses, and expanded to successively higher levels of resolution, applying MCR-ALS at each level. These steps were repeated until 0.001 amu resolution was achieved, as dictated by the resolution of the instrument-in this case, a time-of-flight mass spectrometer. This strategy allowed for the accurate recovery of all known amphetamine compounds and select bacterial lipid extracts while minimizing the size of the data, therefore minimizing computational analysis time and data storage requirements. This relatively simple strategy enables the effective coupling of LC-HRMS with MCR-ALS.

Stationary phase gradients on monolithic silica columns have been successfully and reproducibly prepared and characterized with comparisons made to uniformly modified stationary phases. Stationary phase gradients hold great potential for use in liquid chromatography (LC), both in terms of simplifying analysis as well as providing novel selectivity. In this work, we demonstrate the creation of a continuous stationary phase gradient on in-house synthesized monolithic columns by infusing an aminoalkoxysilane solution through the silica monoliths via controlled rate infusion. The presence of amine and its distribution along the length of gradient and uniformly modified columns were assessed via X-ray photoelectron spectroscopy (XPS). XPS showed a clear gradient in surface coverage along the length of the column for the gradient stationary phases while a near uniform distribution on the uniformly modified stationary phases. To demonstrate the application of these gradient stationary phases, the separations of both nucleobases and weak acids/weak bases on these gradient stationary phases have been compared to uniformly modified and unmodified silica columns. Of particular note, the retention characteristics of 11 gradient columns, 5 uniformly modified columns, and 5 unmodified columns have been tested to establish the reproducibility of the synthetic procedures. Standard deviations of the retention factors were in the range from 0.06 to 0.5, depending on the analyte species. We show that selectivity is achieved with the stationary phase gradients that are significantly different from either uniformly modified amine or unmodified columns. These results indicate the significant promise of this strategy for creating novel stationary phases for LC.

Comprehensive two-dimensional liquid chromatography (LC×LC) is rapidly evolving as the preferred method for the analysis of complex biological samples owing to its much greater resolving power compared to conventional one-dimensional (1D-LC). While its enhanced resolving power makes this method appealing, it has been shown that the precision of quantitation in LC×LC is generally not as good as that obtained with 1D-LC. The poorer quantitative performance of LC×LC is due to several factors including but not limited to the undersampling of the first dimension and the dilution of analytes during transit from the first dimension ((1)D) column to the second dimension ((2)D) column, and the larger relative background signals. A new strategy, 2D assisted liquid chromatography (2DALC), is presented here. 2DALC makes use of a diode array detector placed at the end of each column, producing both multivariate (1)D and two-dimensional (2D) chromatograms. The increased resolution of the analytes provided by the addition of a second dimension of separation enables the determination of analyte absorbance spectra from the (2)D detector signal that are relatively pure and can be used to initiate the treatment of data from the first dimension detector using multivariate curve resolution-alternating least squares (MCR-ALS). In this way, the approach leverages the strengths of both separation methods in a single analysis: the (2)D detector data is used to provide relatively pure analyte spectra to the MCR-ALS algorithm, and the final quantitative results are obtained from the resolved (1)D chromatograms, which has a much higher sampling rate and lower background signal than obtained in conventional single detector LC×LC, to obtain accurate and precise quantitative results. It is shown that 2DALC is superior to both single detector selective or comprehensive LC×LC and 1D-LC for quantitation of compounds that appear as severely overlapped peaks in the (1)D chromatogram - this is especially true in the case of untargeted analyses. We also anticipate that 2DALC will provide superior quantitation in targeted analyses in which unknown interfering compounds overlap with the targeted compound(s). When peaks are significantly overlapped in the first dimension, 2DALC can decrease the error of quantitation (i.e., improve the accuracy by up to 14-fold compared to 1D-LC and up to 3.8-fold compared to LC×LC with a single multivariate detector). The degree of improvement in performance varies depending upon the degree of peak overlap in each dimension and the selectivities of the spectra with respect to one another and the background, as well as the extent of analyte dilution prior to the (2)D column., (Copyright © 2014 Elsevier B.V. All rights reserved.)