Two-Dimensional SEC-SEC-UV-MALS-dRI Workflow for Streamlined Analysis and Characterization of Biopharmaceuticals.

The emergence of complex biological modalities in the biopharmaceutical industry entails a significant expansion of the current analytical toolbox to address the need to deploy meaningful and reliable assays at an unprecedented pace. Size exclusion chromatography (SEC) is an industry standard technique for protein separation and analysis. Some constraints of traditional SEC stem from its restricted ability to resolve complex mixtures and notoriously long run times while also requiring multiple offline separation conditions on different pore size columns to cover a wider molecular size distribution. Two-dimensional liquid chromatography (2D-LC) is becoming an important tool not only to increase peak capacity but also to tune selectivity in a single online method. Herein, an online 2D-LC framework in which both dimensions utilize SEC columns with different pore sizes is introduced with a goal to increase throughput for biomolecule separation and characterization. In addition to improving the separation of closely related species, this online 2D SEC-SEC approach also facilitated the rapid analysis of protein-based mixtures of a wide molecular size range in a single online experimental run bypassing time-consuming deployment of different offline SEC methods. By coupling the second dimension with multiangle light scattering (MALS) and differential refractive index (dRI) detectors, absolute molecular weights of the separated species were obtained without the use of calibration curves. As illustrated in this report for protein mixtures and vaccine processes, this workflow can be used in scenarios where rapid development and deployment of SEC assays are warranted, enabling bioprocess monitoring, purity assessment, and characterization.

An improved workflow for the development of MS-compatible liquid chromatography assay purity and purification methods by using automated LC Screening instrumentation and in silico modeling.

The development of liquid chromatography UV and mass spectrometry (LC-UV-MS) assays in pharmaceutical analysis is pivotal to improve quality control by providing critical information about drug purity, stability, and presence and identity of byproducts and impurities. Analytical method development of these assays is time-consuming, which often causes it to become a bottle neck in drug development and poses a challenge for process chemists to quickly improve the chemistry. In this study, a systematic and efficient workflow was designed to develop purity assay and purification methods for a wide range of compounds including peptides, proteins, and small molecules with MS-compatible mobile phases (MP) by using automated LC screening instrumentation and in silico modeling tools. Initial LC MPs and chromatography column screening experiments enabled quick identification of conditions which provided the best resolution in the vicinity of the target compounds, which is further optimized using computer-assisted modeling (LC Simulator from ACD/Labs). The experimental retention times were in good agreement with the predicted retention times from LC Simulator (ΔtR < 7%). This workflow presents a practical workflow to significantly expedite the time needed to develop optimized LC-UV-MS methods, allowing for a facile, automatic method optimization and reducing the amount of manual work involved in developing new methods during drug development.

In Silico Method Development of Achiral and Chiral Tandem Column Reversed-phase Liquid Chromatography for Multicomponent Pharmaceutical Mixtures.

Tandem column liquid chromatography (LC) is a convenient, cost-effective approach to resolve multicomponent mixtures by serially coupling columns on readily available one-dimensional separation systems without specialized user training. Yet, adoption of this technique remains limited, mainly due to the difficulty in identifying optimal selectivity out of many possible tandem column combinations. At this point, method development and optimization require laborious "hit-or-miss" experimentation and "blind" screening when investigating different column selectivity without standard analytes. As a result, many chromatography practitioners end up combining two columns of similar selectivity, limiting the scope and potential of tandem column LC as a mainstay for industrial applications. To circumvent this challenge, we herein introduce a straightforward in silico multifactorial approach as a framework to expediently map the separation landscape across multiple tandem columns (achiral and chiral) and eluent combinations (isocratic and gradient elution) under reversed-phase LC conditions. Retention models were built using commercially available LC simulator software showcasing less than 2% difference between experimental and simulated retention times for analytes of interest in multicomponent pharmaceutical mixtures (e.g., metabolites and cyclic peptides).

Deuterated Modifiers in Sub/Supercritical Fluid Chromatography for Streamlined NMR Structure Elucidation.

Isolation and chemical characterization of target components in fast-paced pharmaceutical laboratories can often be challenging, especially when dealing with mixtures of closely related, possibly unstable species. Traditionally, this process involves intense labor and manual intervention including chromatographic method development and optimization, fraction collection, and drying processes prior to NMR analyses for unambiguous structure elucidation. To circumvent these challenges, a foundational framework for the proper utilization of supercritical carbon dioxide (scCO2) and deuterated modifiers (CD3OD) in sub/supercritical fluid chromatography (SFC) is herein introduced. This facilitates a streamlined multicomponent isolation with minimized protic residues, further enabling immediate NMR analysis. In addition to bypassing tedious drying processes and minimizing analyte degradation, this approach (complementary to traditional reversed-phase liquid chromatography, RPLC) delivers highly efficient separations and automated fraction collection using readily available analytical/midscale SFC instrumentation. A series of diverse analytes across a wide spectrum of chemical properties (acid, basic, and neutral), combined with different stationary-phase columns in SFC are investigated using both a protic organic modifier (CH3OH) and its deuterated counterpart (CD3OD). The power of this framework is demonstrated with pharmaceutically relevant applications in the context of target characterization and analysis of complex multicomponent reaction mixtures from modern synthetic chemistry, demonstrating high isolation yields while reducing both the environmental footprint and manual intervention. This workflow enables unambiguous fast-paced structure elucidation on the analytical scale, providing results that are comparable to traditional, but time-consuming, RPLC purification approaches.

Enantioselective UHPLC Screening Combined with In Silico Modeling for Streamlined Development of Ultrafast Enantiopurity Assays.

Enantioselective chromatography has been the preferred technique for the determination of enantiomeric excess across academia and industry. Although sequential multicolumn enantioselective supercritical fluid chromatography screenings are widespread, access to automated ultra-high-performance liquid chromatography (UHPLC) platforms using state-of-the-art small particle size chiral stationary phases (CSPs) is an underdeveloped area. Herein, we introduce a multicolumn UHPLC screening workflow capable of combining 14 columns (packed with sub-2 µm fully porous and sub-3 µm superficially porous particles) with nine mobile phase eluent choices. This automated setup operates under a vast selection of reversed-phase liquid chromatography, hydrophilic interaction liquid chromatography, polar-organic mode, and polar-ionic mode conditions with minimal manual intervention and high success rate. Examples of highly efficient enantioseparations are illustrated from the integration of chiral screening conditions and computer-assisted modeling. Furthermore, we describe the nuances of in silico method development for chiral separations via second-degree polynomial regression fit using LC simulator (ACD/Labs) software. The retention models were found to be very accurate for chiral resolution of single and multicomponent mixtures of enantiomeric species across different types of CSPs, with differences between experimental and simulated retention times of less than 0.5%. Finally, we illustrate how this approach lays the foundation for a streamlined development of ultrafast enantioseparations applied to high-throughput enantiopurity analysis and its use in the second dimension of two-dimensional liquid chromatography experiments.

Automated Hydrophobic Interaction Chromatography Screening Combined with In Silico Optimization as a Framework for Nondenaturing Analysis and Purification of Biopharmaceuticals.

The mounting complexity of new modalities in the biopharmaceutical industry entails a commensurate level of analytical innovations to enable the rapid discovery and development of novel therapeutics and vaccines. Hydrophobic interaction chromatography (HIC) has become one of the widely preferred separation techniques for the analysis and purification of biopharmaceuticals under nondenaturing conditions. Inarguably, HIC method development remains very challenging and labor-intensive owing to the numerous factors that are typically optimized by a "hit-or-miss" strategy (e.g., the nature of the salt, stationary phase chemistry, temperature, mobile phase additive, and ionic strength). Herein, we introduce a new HIC method development framework composed of a fully automated multicolumn and multieluent platform coupled with in silico multifactorial simulation and integrated fraction collection for streamlined method screening, optimization, and analytical-scale purification of biopharmaceutical targets. The power and versatility of this workflow are showcased by a wide range of applications including trivial proteins, monoclonal antibodies (mAbs), antibody-drug conjugates (ADCs), oxidation variants, and denatured proteins. We also illustrate convenient and rapid HIC method development outcomes from the effective combination of this screening setup with computer-assisted simulations. HIC retention models were built using readily available LC simulator software outlining less than a 5% difference between experimental and simulated retention times with a correlation coefficient of >0.99 for pharmaceutically relevant multicomponent mixtures. In addition, we demonstrate how this approach paves the path for a straightforward identification of first-dimension HIC conditions that are combined with mass spectrometry (MS)-friendly reversed-phase liquid chromatography (RPLC) detection in the second dimension (heart-cutting two-dimensional (2D)-HIC-RPLC-diode array detector (DAD)-MS), enabling the analysis and purification of biopharmaceutical targets.

Automated ion exchange chromatography screening combined with in silico multifactorial simulation for efficient method development and purification of biopharmaceutical targets.

Bioprocess development of increasingly challenging therapeutics and vaccines requires a commensurate level of analytical innovation to deliver critical assays across functional areas. Chromatography hyphenated to numerous choices of detection has undeniably been the preferred analytical tool in the pharmaceutical industry for decades to analyze and isolate targets (e.g., APIs, intermediates, and byproducts) from multicomponent mixtures. Among many techniques, ion exchange chromatography (IEX) is widely used for the analysis and purification of biopharmaceuticals due to its unique selectivity that delivers distinctive chromatographic profiles compared to other separation modes (e.g., RPLC, HILIC, and SFC) without denaturing protein targets upon isolation process. However, IEX method development is still considered one of the most challenging and laborious approaches due to the many variables involved such as elution mechanism (via salt, pH, or salt-mediated-pH gradients), stationary phase's properties (positively or negatively charged; strong or weak ion exchanger), buffer type and ionic strength as well as pH choices. Herein, we introduce a new framework consisting of a multicolumn IEX screening in conjunction with computer-assisted simulation for efficient method development and purification of biopharmaceuticals. The screening component integrates a total of 12 different columns and 24 mobile phases that are sequentially operated in a straightforward automated fashion for both cation and anion exchange modes (CEX and AEX, respectively). Optimal and robust operating conditions are achieved via computer-assisted simulation using readily available software (ACD Laboratories/LC Simulator), showcasing differences between experimental and simulated retention times of less than 0.5%. In addition, automated fraction collection is also incorporated into this framework, illustrating the practicality and ease of use in the context of separation, analysis, and purification of nucleotides, peptides, and proteins. Finally, we provide examples of the use of this IEX screening as a framework to identify efficient first dimension (1D) conditions that are combined with MS-friendly RPLC conditions in the second dimension (2D) for two-dimensional liquid chromatography experiments enabling purity analysis and identification of pharmaceutical targets.

Dual-Gradient Unified Chromatography: A New Paradigm for Versatility in Simultaneous Multicomponent Analysis.

Generality in analytical chemistry can be manifested in impactful platforms that can streamline modern organic synthesis and biopharmaceutical processes. We herein introduce a hybrid separation technique named Dual-Gradient Unified Chromatography (DGUC), which is built upon an automated dynamic modulation of CO2 , organic modifier, and water blends with various buffers. This concept enables simultaneous multicomponent analysis of both small and large molecules across a wide polarity range in single experimental runs. After a careful investigation of its fundamental aspects, a DGUC-DAD-MS screening workflow that combines multiple orthogonal column and mobile phase choices across a far-reaching universal elution profile is also reported. The power of this framework is demonstrated with new analytical applications guiding academic and industrial laboratories in the development of new (bio)pharmaceutical targets (e.g. synthetic intermediates, nucleosides, cyclic and linear peptides, proteins, antibody drug conjugates).

Trapping-Enrichment Multi-dimensional Liquid Chromatography with On-Line Deuterated Solvent Exchange for Streamlined Structure Elucidation at the Microgram Scale.

At the forefront of chemistry and biology research, development timelines are fast-paced and large quantities of pure targets are rarely available. Herein, we introduce a new framework, which is built upon an automated, online trapping-enrichment multi-dimensional liquid chromatography platform (TE-Dt-mDLC) that enables: 1) highly efficient separation of complex mixtures in a first dimension (1 D-UV); 2) automated peak trapping-enrichment and buffer removal achieved through a sequence of H2 O and D2 O washes using an independent pump setup; and 3) a second dimension separation (2 D-UV-MS) with fully deuterated mobile phases and fraction collection to minimize protic residues for immediate NMR analysis while bypassing tedious drying processes and minimizing analyte degradation. Diverse examples of target isolation and characterization from organic synthesis and natural product chemistry laboratories are illustrated, demonstrating recoveries above 90 % using as little as a few micrograms of material.

In Silico Multifactorial Modeling for Streamlined Development and Optimization of Two-Dimensional Liquid Chromatography.

Continued adoption of two-dimensional liquid chromatography (2D-LC) in industrial laboratories will depend on the development of approaches to make method development for 2D-LC more systematic, less tedious, and less reliant on user expertise. In this paper, we build on previous efforts in these directions by describing the use of multifactorial modeling software that can help streamline and simplify the method development process for 2D-LC. Specifically, we have focused on building retention models for second dimension (2D) separations involving variables including gradient time, temperature, organic modifier blending, and buffer concentration using LC simulator (ACD/Labs) software. Multifactorial retention modeling outcomes are illustrated as resolution map planes or cubes that enable straightforward location of 2D conditions that maximize resolution while minimizing analysis time. We also illustrate the practicality of this approach by identifying conditions that yield baseline separation of all compounds co-eluting from a first dimension (1D) separation using a single combination of 2D stationary phase and elution conditions. The multifactorial retention models were found to be very accurate for both the 1D and 2D separations, with differences between experimental and simulated retention times of less than 0.5%. Pharmaceutical applications of this approach for multiple heartcutting 2D-LC were demonstrated using IEC-IEC or achiral RPLC-chiral RPLC for 2D separations of multicomponent mixtures. The framework outlined here should help make 2D-LC method development more systematic and streamline development and optimization for a variety of 2D-LC applications in both industry and academia.

Mapping the Separation Landscape in Two-Dimensional Liquid Chromatography: Blueprints for Efficient Analysis and Purification of Pharmaceuticals Enabled by Computer-Assisted Modeling.

Recent developments in two-dimensional liquid chromatography (2D-LC) now make separation and analysis of very complex mixtures achievable. Despite being such a powerful chromatographic tool, current 2D-LC technology requires a series of arduous method development activities poorly suited for a fast-paced industrial environment. Recent introductions of new technologies including active solvent modulation and a support for multicolumn 2D-LC are helping to overcome this stigma. However, many chromatography practitioners believe that the lack of a systematic way to effectively optimize 2D-LC separations is a missing link in securing the viability of 2D-LC as a mainstay for industrial applications. In this work, a computer-assisted modeling approach that dramatically simplifies both offline and online 2D-LC method developments is introduced. Our methodology is based on mapping the separation landscape of pharmaceutically relevant mixtures across both first (1D) and second (2D) dimensions using LC Simulator (ACD/Labs) software. Retention models for 1D and 2D conditions were built using a minimal number of multifactorial modeling experiments (2 × 2 or 3 × 3 parameters: gradient slope, column temperature, and different column and mobile phase combinations). The approach was first applied to online 2D-LC analysis involving achiral and chiral separations of complex mixtures of enantiomeric species. In these experiments, the retention models proved to be quite accurate for both the 1D and 2D separations, with retention time differences between experiments and simulations of less than 3.5%. This software-based concept was also demonstrated for offline 2D-LC purification of drug substances.

Introducing Multifactorial Peak Crossover in Analytical and Preparative Chromatography via Computer-Assisted Modeling.

Modern pharmaceutical processes can often lead to multicomponent mixtures of closely related species that are difficult to resolve under chromatographic conditions, and even worse in preparative scale settings. Despite recent improvements in column technology and instrumentation, there remains an urgent need for creating innovative approaches that address challenging coelutions of critical pair and poor chromatographic productivity of purification methods. Herein, we overcome these challenges by introducing a simple and practical technique named multifactorial peak crossover (MPC) via computer-assisted chromatographic modeling. The approach outlined here focuses on mapping the separation landscape of pharmaceutical mixtures to quickly identify spaces of peak coelution crossings which enables one to conveniently switch the elution order of target analytes. Diverse examples of MPC diagrams as a function of column temperature, mobile phase gradient or a multifactorial combination in reversed phase and ion exchange chromatography (RPLC and IEC) modes are generated using ACD Laboratories/LC Simulator software and corroborated with experimental data match (overall retention time differences of less than 1%). This powerful MPC technique allows us to gain massive productivity increases (shorter cycle time and higher sample loading) for purification of pharmaceuticals by selectively switching the elution order of target components away from undesired tailing peaks and coelution spaces. MPC chromatography dramatically reduces the time spent developing productive analytical and preparative scale separations. In addition, we illustrate how this new MPC concept can be used to gain substantial improvements of the signal-to-noise ratio, enabling straightforward ppb detection of low-level target components with direct impact in the quantitation of metabolites and potential genotoxic impurities (PGIs). These innovations are of paramount importance in order to facilitate efficient isolation, characterization, and quantitation of drug substances in the development of new medicines.

The Emergence of Universal Chromatographic Methods in the Research and Development of New Drug Substances.

Manufacturing process development of new drug substances in the pharmaceutical industry combines numerous chemical challenges beyond the efficient synthesis of complex molecules. Optimization of a synthetic route involves the screening of multiple reaction variables with a desired outcome that not only depends on an increased product yield but is also highly influenced by the removal efficacy of residual chemicals and reaction byproducts during the subsequent synthetic route. Consequently, organic chemists must survey a wide array of synthetic variables to develop a highly productive, green, and cost-effective manufacturing process. The time constraints of developing robust quantitative methods prior to each processing step can easily lead to sample analysis becoming a bottleneck in synthetic route development. In this regard, conventional "on demand" analytical method development and optimization approaches, traditionally used for guiding synthetic chemistry efforts, become unsustainable. This Account introduces recent efforts to address the aforementioned challenges through the development and implementation of generic or more universal chromatographic methods that can cover a broad spectrum of targeted compound classes. Such generic methods require significant resolving power to enable baseline resolution of multicomponent mixtures in a single experimental run without additional method customization but must be simple enough to allow for routine use by chemists, chemical engineers and other researchers with little experience in chromatographic method development. These powerful analytical methodologies are often employed to minimize the time spent developing new analytical assays, while also facilitating method transfer to manufacturing facilities and application in regulatory settings. Diverse examples of universal and fit-for-purpose analytical procedures are presented herein, illustrating the power of modern readily available analytical technology for streamlining the development of new drug substances in organic chemistry laboratories across both academic and industrial sectors. With recent advances in analytical instrumentation and column technologies, universal chromatographic methods are quickly becoming a proactive and effective strategy to accelerate the discovery and implementation of new synthetic methodologies, especially but not limited to laboratories where the synthetic process route is undergoing rapid change and optimization. Targets of these generic methods include analysis of organic solvents, acid and basic additives, nucleotide species, palladium scavengers, impurity mapping, enantiopurity, synthetic intermediates, active pharmaceutical ingredients and their counterions, dehalogenation byproducts, and mixtures of organohalogenated pharmaceuticals, among other chemicals used or formed in process chemistry reactions.

Comprehensive online multicolumn two-dimensional liquid chromatography-diode array detection-mass spectrometry workflow as a framework for chromatographic screening and analysis of new drug substances.

The analysis of complex mixtures of closely related species is quickly becoming a bottleneck in the development of new drug substances, reflecting the ever-increasing complexity of both fundamental biology and the therapeutics used to treat disease. Two-dimensional liquid chromatography (2D-LC) is emerging as a powerful tool to achieve substantial improvements in peak capacity and selectivity. However, 2D-LC suffers from several limitations, including the lack of automated multicolumn setups capable of combining multiple columns in both dimensions. Herein, we report an investigation into the development and implementation of a customized online comprehensive multicolumn 2D-LC-DAD-MS setup for screening and method development purposes, as well as analysis of multicomponent biopharmaceutical mixtures. In this study, excellent chromatographic performance in terms of selectivity, peak shape, and reproducibility were achieved by combining reversed-phase (RP), strong cation exchange (SCX), strong anion exchange (SAX), and size exclusion chromatography (SEC) using sub-2-µm columns in the first dimension in conjunction with several 3.0 mm × 50 mm RP columns packed with sub-3-µm fully porous particles in the second dimension. Multiple combinations of separation modes coupled to UV and MS detection are applied to the LC × LC analysis of a protein standard mixture, intended to be representative of protein drug substances. The results reported in this study demonstrate that our automated online multicolumn 2D-LC-DAD-MS workflow can be a powerful tool for comprehensive chromatographic column screening that enables the semi-automated development of 2D-LC methods, offering the ability to streamline full visualization of sample composition for an unknown complex mixture while maximizing chromatographic orthogonality. Graphical Abstract.

Bioactive peptides and proteins as alternative antiplatelet drugs.

Antiplatelet drugs reduce the risks associated with atherothrombotic events and show various applications in diverse cardiovascular diseases including myocardial infarctions. Efficacy of the current antiplatelet medicines including aspirin, clopidogrel, prasugrel and ticagrelor, and the glycoprotein IIb/IIIa antagonists, are limited due to their increased risks of bleeding, and antiplatelet drug resistance. Hence, it is important to develop new effective antiplatelet drugs, with fewer side-effects. The vast repertoire of natural peptides can be explored towards this goal. Proteins and peptides derived from snake venoms and plants represent exciting candidates for the development of novel and potent antiplatelet agents. Consequently, this review discusses multiple peptides that have displayed antiplatelet aggregation activity in preclinical drug development stages. This review also describes the antiplatelet mechanisms of the peptides, emphasizing the signaling pathways intervened by them. Also, the hurdles encountered during the development of peptides into antiplatelet drugs have been listed. Finally, hitherto unexplored peptides with the potential to prevent platelet aggregation are explored.

Chaotropic Effects in Sub/Supercritical Fluid Chromatography via Ammonium Hydroxide in Water-Rich Modifiers: Enabling Separation of Peptides and Highly Polar Pharmaceuticals at the Preparative Scale.

Chromatographic separation, analysis and characterization of complex highly polar analyte mixtures can often be very challenging using conventional separation approaches. Analysis and purification of hydrophilic compounds have been dominated by liquid chromatography (LC) and ion-exchange chromatography (IC), with sub/supercritical fluid chromatography (SFC) moving toward these new applications beyond traditional chiral separations. However, the low polarity of supercritical carbon dioxide (CO2) has limited the use of SFC for separation and purification in the bioanalytical space, especially at the preparative scale. Reaction mixtures of highly polar species are strongly retained even using polar additives in alcohol modifier/CO2 based eluents. Herein, we overcome these problems by introducing chaotropic effects in SFC separations using a nontraditional mobile phase mixture consisting of ammonium hydroxide combined with high water concentration in the alcohol modifier and carbon dioxide. The separation mechanism was here elucidated based on extensive IC-CD (IC couple to conductivity detection) analysis of cyclic peptides subjected to the SFC conditions, indicating the in situ formation of a bicarbonate counterion (HCO3-). In contrast to other salts, HCO3- was found to play a crucial role acting as a chaotropic agent that disrupts undesired H-bonding interactions, which was demonstrated by size-exclusion chromatography coupled with differential hydrogen-deuterium exchange-mass spectrometry experiments (SEC-HDX-MS). In addition, the use of NH4OH in water-rich MeOH modifiers was compared to other commonly used basic additives (diethylamine, triethylamine, and isobutylamine) showing unmatched chromatographic and MS detection performance in terms of peak shape, retention, selectivity, and ionization as well as a completely different selectivity and retention behavior. Moreover, relative to ammonium formate and ammonium acetate in water-rich methanol modifier, the ammonium hydroxide in water additive showed better chromatographic performance with enhanced sensitivity. Further optimization of NH4OH and H2O levels in conjunction with MeOH/CO2 served to furnish a generic modifier (0.2% NH4OH, 5% H2O in MeOH) that enables the widespread transition of SFC to domains that were previously considered out of its scope. This approach is extensively applied to the separation, analysis, and purification of multicomponent reaction mixtures of closely related polar pharmaceuticals using readily available SFC instrumentation. The examples described here cover a broad spectrum of bioanalytical and pharmaceutical applications including analytical and preparative chromatography of organohalogenated species, nucleobases, nucleosides, nucleotides, sulfonamides, and cyclic peptides among other highly polar species.

Multi-column ultra-high performance liquid chromatography screening with chaotropic agents and computer-assisted separation modeling enables process development of new drug substances.

Modern process research and development can often be hampered by the tedious method development required to chromatographically resolve mixtures of chemical species with very similar physical properties. Herein, we describe a simple approach for the development and implementation of an efficient ultra-high performance liquid chromatography (UHPLC) assay that is extensively applied to the separation and analysis of multicomponent reaction mixtures of closely related pharmaceutical intermediates and impurities. Methods are optimized using multi-column and multi-solvent UHPLC screening in conjunction with chromatography simulation software (ACD Labs/LC Simulator). This approach is implemented to enable the separation, identification, mapping and control of impurities formed within the process chemistry optimization of the dimeric catalyst used in the synthesis of new drug substances. The final method utilized a sub-2 µm C18 stationary phase (2.1 mm I.D. × 50 mm length, 1.7 µm particle size ACQUITY UPLC BEH C18) with a non-conventional chaotropic mobile phase buffer (35 mM potassium hexafluorophosphate in 0.1% phosphoric acid/acetonitrile) in order to achieve baseline separation of all reaction components. The chromatographic simulation and modeling strategy served to generate 3D resolution maps with robust separation conditions that match the outcome of subsequent experimental data (overall ΔtR < 0.35%). Our multi-column UHPLC screening with computer-assisted chromatographic modeling is a great addition to the toolbox of synthetic chemists and can be a powerful tool for streamlining process chemistry optimization in organic chemistry laboratories across both academic and industrial sectors.

Determining the Chemical-Heterogeneity-Corrected Molar Mass Averages and Distribution of Poly(styrene-co-t-butyl methacrylate) Using SEC/MALS/UV/DRI.

Chemical heterogeneity, defined as the change (or lack thereof) across the molar mass distribution (MMD) in the monomeric ratio of a copolymer, can influence processing and end-use properties such as solubility, gas permeation, conductivity, and the energy of interfacial fracture. Given that each parent homopolymer of the copolymer monomeric components has a different specific refractive index increment (∂n/∂c) from the other component, chemical heterogeneity translates into ∂n/∂c heterogeneity. The latter, in turn, affects the accuracy of the molar mass (M) averages and distributions of the copolymers in question. Here, employing size-exclusion chromatography coupled on-line to multi-angle static light scattering, ultraviolet absorption spectroscopy, and differential refractometry detection, the chemical heterogeneity (given as mass percent styrene) was determined for a poly(styrene-co-t-butyl methacrylate) copolymer. Also determined were the chemical-heterogeneity-corrected M averages and MMD of the copolymer. In the present case, the error in molar mass incurred by ignoring the effects of chemical heterogeneity in the M calculations is seen to reach as high as 53,000 g mol-1 at the high end of the MMD. This error could be much higher, however, in copolymers with higher M or with larger difference among component ∂n/∂c values, as compared to the current analyte.

Low Serum Vitamin D: A Surrogate Marker for Advanced Colon Adenoma?

AIMS: To examine the association between low 25-OH Vitamin D levels and prevalence of advanced adenomas (AAs) in screening/surveillance colonoscopy patients. RATIONALE: Low serum 25-OH Vitamin D has been associated with an increased risk for colon cancer. In the Adenoma-Carcinoma pathway, a subset of colon polyps (AA) have been regarded as high-risk precursor lesions. We used a retrospective case-control design to examine the association between Vitamin D deficiency and the prevalence of AA in a high-risk population. MATERIALS AND METHODS: We examined a total of 354 patients who presented for initial screening or surveillance colonoscopy at our Colon Cancer Prevention Program. Our main exposure variable was serum Vitamin D levels and the outcome was AAs defined as those adenomas that were large (≥1 cm) or had advanced pathology (>25% villous components or high-grade dysplasia). Known risk factors were also collected from the patients' charts including gender, age, smoking, and family history. Bivariate and multivariate analyses were performed to examine the relationship between serum 25-OH Vitamin D levels and AAs. A total of 354 patients [(males, 188; females, 166); average age, 61 y] charts were reviewed. Vitamin D levels ranged between 4 and 70 ng/mL, with a mean of 25 ng/mL (clinical laboratory normal>30 ng/mL). There was no significant association between serum levels and time of the year of blood draw. Risk for tubular adenoma and AA increased as Vitamin D levels decreased to <30 ng/mL (P=0.002). In total, 80% of AAs were detected in patients whose levels were below this value (odds ratio, 3.36; 95% confidence interval, 1.40-8.03; P=0.007). Bivariate analysis also showed a positive association between smokers with AA as well as those with a family history of colon cancer (P=0.011) and low Vitamin D levels (P=0.001). A multivariate analysis using quintiles of Vitamin D levels demonstrated an increased risk of AAs for patients with levels in the second quintile (33 ng/mL) (odds ratio, 4.3; P=0.01) MAIN CONCLUSIONS:: Most patients presenting in our Colon Cancer Prevention Program have low levels of serum 25-OH Vitamin D. Analysis of the results of both screening and surveillance colonoscopies demonstrated an inverse relation between serum 25-OH Vitamin D level and AAs.

In vitro-in silico pharmacology and chemistry of Stercularin, isolated from Sterculia diversifolia.

Stercularin is a coumarin, isolated from the ethyl acetate fraction of stem bark and leaves of S. diversifolia. Pharmacologically it is active against cancer, diabetes, and inflammation etc. The molecule is further screened for in vitro pharmacological activities. In addition, a detailed description on its drug likeness and pharmacokinetic profile has been established to further explore its fate as a drug candidate. Stercularin exhibited antiglycation, immunomodulatory, and leishmanicidal activity in three different in vitro models. The IC50 values obtained in these three assays were 80.22 ± 0.46 mg/ml, 12.8 ± 1.6 µg/ml, and 8.32 ± 0.42 µg/ml, respectively. In case of drug likeness evaluation, Stercularin has acceptable physicochemical properties and compliant with major drug likeness descriptors i.e., Lipinski rule, Pfizer rule, GSK rule, and "golden triangle". Accepting Lipinski rule implies the oral drug development of Stercularin. Pharmacokinetically, Stercularin is permeable to Caco-2 and MDCK cell lines. 'Boiled-egg' plot suggest intestinal route of absorption, blood brain barrier nonpermeating, and not affected by p-glycoprotein. Stercularin has high plasma protein binding with low free fraction circulating in the plasma. Stercularin proved to be the substrate and/or inhibitor of CYP 450 system with a moderate half-life and clearance rate to allow flexible dosing regimen. Finally, slight risk of toxicity exists for Stercularin, but not being limiting factors of drug knock out. A nature isolated Stercularin possess pharmacological activities and is predicted to have acceptable pharmacokinetic profile. Further drug development and in vivo studies are desirable for optimization.