A kinase-cGAS cascade to synthesize a therapeutic STING activator.

The introduction of molecular complexity in an atom- and step-efficient manner remains an outstanding goal in modern synthetic chemistry. Artificial biosynthetic pathways are uniquely able to address this challenge by using enzymes to carry out multiple synthetic steps simultaneously or in a one-pot sequence1-3. Conducting biosynthesis ex vivo further broadens its applicability by avoiding cross-talk with cellular metabolism and enabling the redesign of key biosynthetic pathways through the use of non-natural cofactors and synthetic reagents4,5. Here we describe the discovery and construction of an enzymatic cascade to MK-1454, a highly potent stimulator of interferon genes (STING) activator under study as an immuno-oncology therapeutic6,7 (ClinicalTrials.gov study NCT04220866 ). From two non-natural nucleotide monothiophosphates, MK-1454 is assembled diastereoselectively in a one-pot cascade, in which two thiotriphosphate nucleotides are simultaneously generated biocatalytically, followed by coupling and cyclization catalysed by an engineered animal cyclic guanosine-adenosine synthase (cGAS). For the thiotriphosphate synthesis, three kinase enzymes were engineered to develop a non-natural cofactor recycling system in which one thiotriphosphate serves as a cofactor in its own synthesis. This study demonstrates the substantial capacity that currently exists to use biosynthetic approaches to discover and manufacture complex, non-natural molecules.

Altered hepatic and intestinal homeostasis in a neonatal murine model of short-term total parenteral nutrition and antibiotics.

Parenteral nutrition (PN) prevents starvation and supports metabolic requirements intravenously when patients are unable to be fed enterally. Clinically, infants are frequently provided PN in intensive care settings along with exposure to antibiotics (ABX) to minimize infection during care. Unfortunately, neonates experience extremely high rates of hepatic complications. Adult rodent and piglet models of PN are well-established but neonatal models capable of leveraging the considerable transgenic potential of the mouse remain underdeveloped. Utilizing our newly established neonatal murine PN mouse model, we administered ABX or controlled drinking water to timed pregnant dams to disrupt the maternal microbiome. We randomized mouse pups to PN or sham surgery controls +/- ABX exposure. ABX or short-term PN decreased liver and brain organ weights, intestinal length, and mucosal architecture (vs. controls). PN significantly elevated evidence of hepatic proinflammatory markers, neutrophils and macrophage counts, bacterial colony-forming units, and evidence of cholestasis risk, which was blocked by ABX. However, ABX uniquely elevated metabolic regulatory genes resulting in accumulation of hepatocyte lipids, triglycerides, and elevated tauro-chenoxycholic acid (TCDCA) in serum. Within the gut, PN elevated the relative abundance of Akkermansia, Enterococcus, and Suterella with decreased Anaerostipes and Lactobacillus compared with controls, whereas ABX enriched Proteobacteria. We conclude that short-term PN elevates hepatic inflammatory stress and risk of cholestasis in early life. Although concurrent ABX exposure protects against hepatic immune activation during PN, the dual exposure modulates metabolism and may contribute toward early steatosis phenotype, sometimes observed in infants unable to wean from PN.NEW & NOTEWORTHY This study successfully established a translationally relevant, murine neonatal parenteral nutrition (PN) model. Short-term PN is sufficient to induce hepatitis-associated cholestasis in a neonatal murine model that can be used to understand disease in early life. The administration of antibiotics during PN protects animals from bacterial translocation and proinflammatory responses but induces unique metabolic shifts that may predispose the liver toward early steatosis.

Machine Learning for Prediction, Classification, and Identification of Immobilized Enzymes for Biocatalysis.

BACKGROUND: Enzyme immobilization is a beneficial component involved in biocatalytic strategies. Understanding and evaluating the enzyme immobilization system plays an important role in the successful development and implementation of the biocatalysis route. Ensuring the implementation of a successful enzyme immobilization process is vital for realizing a highly functioning and well suited biocatalytic process within pharmaceutical development. AIM: To develop a method which can accurately and objectively identify and classify differences within enzyme immobilization systems, sample preparation methods, and data collection parameters. METHODS: Raman hyperspectral imaging was used to obtain a total of eight spectral data sets from enzyme immobilization samples. Partial least squares discriminant analysis (PLS-DA) was used to classify and identify the samples based on their differences. RESULTS: Several two-class, four-class, and eight-class PLS-DA models were built to classify the different sample data sets. All models reached between 92-100% accuracy after cross-validation and external validation, illustrating great success of the models for identifying differences between the samples. CONCLUSION: Raman hyperspectral imaging with machine learning can be used to investigate, interpret, and classify different data collection parameters, sample preparation methods, and enzyme immobilization supports, providing crucial insight into enzyme immobilization process development.

Holistic analytical characterization and risk assessment of residual host cell protein impurities in an active pharmaceutical ingredient synthesized by biocatalysts.

Host cell proteins (HCPs) are a significant class of process-related impurities commonly associated with the manufacturing of biopharmaceuticals. However, due to the increased use of crude enzymes as biocatalysts for modern organic synthesis, HCPs can also be introduced as a new class of impurities in chemical drugs. In both cases, residual HCPs need to be adequately controlled to ensure product purity, quality, and patient safety. Although a lot of attentions have been focused on defining a universally acceptable limit for such impurities, the risks associated with residual HCPs on product quality, safety, and efficacy often need to be determined on a case-by-case basis taking into consideration the residual HCP profile in the product, the dose, dosage form, administration route, and so forth. Here we describe the unique challenges for residual HCP control presented by the biocatalytic synthesis of an investigational stimulator of interferon genes protein agonist, MK-1454, which is a cyclic dinucleotide synthesized using Escherichia coli cell lysate overexpressing cyclic GMP-AMP synthase as a biocatalyst. In this study, a holistic characterization of residual protein impurities using a variety of analytical tools including nanoscale liquid chromatography coupled to tandem mass spectrometry, together with in silico immunogenicity prediction of identified proteins, facilitated risk assessment and guided process development to achieve adequate removal of residual protein impurities in MK-1454 active pharmaceutical ingredient.

In situ real time monitoring of emulsification and homogenization processes for vaccine adjuvants.

Adjuvants are commonly employed to enhance the efficacy of a vaccine and thereby increase the resulting immune response in a patient. The activity and effectiveness of emulsion-based adjuvants has been heavily studied throughout pharmaceuticals; however, there exists a lack in research which monitors the formation of a stable emulsion in real time. Process analytical technology (PAT) provides a solution to meet this need. PAT involves the collection of in situ data, thereby providing real time information about the monitored process as well as increasing understanding of that process. Here, three separate PAT tools - optical particle imaging, in situ particle analysis, and Raman spectroscopy - were used to monitor two key steps involved in the formation of a stable emulsion product, emulsification and homogenization, as well as perform a stability assessment. The obtained results provided new insights-particle size decreases during emulsification and homogenization, and molecular changes do not occur during either the emulsification or homogenization steps. Further, the stability assessment indicated that the coarse emulsion product obtained from the emulsification step is stable over the course of 24 hours when mixed. To the best of our knowledge, this is the first report of an analytical methodology for in situ, real time analysis of emulsification and homogenization processes for vaccine adjuvants. Using our proposed analytical methodology, an improved understanding of emulsion-based vaccine adjuvants can now be achieved, ultimately impacting the ability to develop and deliver successful pharmaceuticals.

Machine Learning and Chemical Imaging to Elucidate Enzyme Immobilization for Biocatalysis.

Biocatalysis has rapidly become an essential tool in the scientific and industrial communities for the development of efficient, safe, and sustainable chemical syntheses. Immobilization of the biocatalyst, typically an engineered enzyme, offers significant advantages, including increased enzyme stability and control, resistance to environmental change, and enhanced reusability. Determination and optimization of the spatial and chemical distribution of immobilized enzymes are critical for proper functionality; however, analytical methods currently employed for doing so are frequently inadequate. Machine learning, in the form of multivariate curve resolution, with Raman hyperspectral imaging is presented herein as a potential method for investigating the spatial and chemical distribution of evolved pantothenate kinase immobilized onto two diverse, microporous resins. An exhaustive analysis indicates that this method can successfully resolve, both spatially and spectrally, all chemical species involved in enzyme immobilization, including the enzyme, both resins, and other key components. Quantitation of the spatial coverage of immobilized enzymes, a key parameter used for process development, was accomplished. Optimal analytical parameters were determined by the evaluation of different excitation wavelengths. Exploratory chemometric approaches, including principal component analysis, were utilized to investigate the chemical species embedded within the data sets and their relationships. The totality of this information can be utilized for an enhanced understanding of enzyme immobilization processes and can allow for the further implementation of biocatalysis within the scientific and pharmaceutical communities.

Raman hyperspectral imaging with multivariate analysis for investigating enzyme immobilization.

Directed enzyme evolution has led to significant application of biocatalysis for improved chemical transformations throughout the scientific and industrial communities. Biocatalytic reactions utilizing evolved enzymes immobilized within microporous supports have realized unique advantages, including notably higher enzyme stability, higher enzyme load, enzyme reusability, and efficient product-enzyme separation. To date, limited analytical methodology is available to discern the spatial and chemical distribution of immobilized enzymes, in which techniques for surface visualization, enzyme stability, or activity are instead employed. New analytical tools to investigate enzyme immobilization are therefore needed. In this work, development, application, and evaluation of an analytical methodology to study enzyme immobilization is presented. Specifically, Raman hyperspectral imaging with principal component analysis, a multivariate method, is demonstrated for the first time to investigate evolved enzymes immobilized onto microporous supports for biocatalysis. Herein we demonstrate the ability to spatially and spectrally resolve evolved pantothenate kinase (PanK) immobilized onto two commercially-available, chemically-diverse porous resins. This analytical methodology is able to chemically distinguish evolved enzyme, resin, and chemical species pertinent to immobilization. As such, a new analytical approach to study immobilized biocatalysts is demonstrated, offering potential wide application for analysis of protein or biomolecule immobilization.

A novel multivariate curve resolution-alternating least squares (MCR-ALS) methodology for application in hyperspectral Raman imaging analysis.

Multivariate curve resolution-alternating least squares (MCR-ALS) applied to hyperspectral Raman imaging is extensively used to spatially and spectrally resolve the individual, pure chemical species within complex, heterogeneous samples. A critical aspect of performing MCR-ALS with hyperspectral Raman imaging is the selection of the number of chemical components within the experimental data. Several methods have previously been proposed to determine the number of chemical components, but it remains a challenging task that if done incorrectly, can lead to the loss of chemical information. In this work, we show that the choice of 'optimal' number of factors in the MCR-ALS model may vary depending on the relative contribution of the targeted species to the overall spectral intensity. In a data set consisting of 27 hyperspectral Raman images of TiO2 polymorphs, it was observed that the more dominant species were best resolved with a parsimonious model. However, species with intensities near the noise level often needed more factors to be resolved than was predicted by standard methods. Based on the observations in this data set, we propose a new method that employs approximate reference spectra for determining optimal model complexity for identifying minor constituents with MCR-ALS.

In situ analytical characterization and chemical imaging of tablet coatings using laser induced breakdown spectroscopy (LIBS).

Laser induced breakdown spectroscopy (LIBS) has emerged as an innovative tool for quantitative and qualitative elemental analysis in pharmaceutical research. Herein, the potential use of LIBS for rapid characterization of tablet coatings is illustrated, including the investigation of coating thickness, coating uniformity and localized coating contamination. The laser shot number required for penetrating the coating correlates well with coating thickness determined from traditional scanning electron microscopy measurements. Each laser shot represents a 2.58 µm coating thickness. The inter-tablet coating uniformity was directly visualized using LIBS-based 3D chemical imaging, and the intra-tablet coating uniformity was quantitatively investigated. To our knowledge, this is the first report of 3D LIBS-based chemical imaging being utilized for quantitative analysis of pharmaceutical tablet coatings. In addition to elemental information, the accurate location of contaminants on the tablet coating was rapidly identified using 2D imaging. These results pave the way for LIBS to be a valuable technique for the analysis of pharmaceutical tablet coatings.

Spatial and spectral resolution of carbonaceous material from hematite (α-Fe2O3) using multivariate curve resolution-alternating least squares (MCR-ALS) with Raman microspectroscopic mapping: implications for the search for life on Mars.

The search for evidence of extant or past life on Mars is a primary objective of both the upcoming Mars 2020 rover (NASA) and ExoMars 2020 rover (ESA/Roscosmos) missions. This search will involve the detection and identification of organic molecules and/or carbonaceous material within the Martian surface environment. For the first time on a mission to Mars, the scientific payload for each rover will include a Raman spectrometer, an instrument well-suited for this search. Hematite (α-Fe2O3) is a widespread mineral on the Martian surface. The 2LO Raman band of hematite and the Raman D-band of carbonaceous material show spectral overlap, leading to the potential misidentification of hematite as carbonaceous material. Here we report the ability to spatially and spectrally differentiate carbonaceous material from hematite using multivariate curve resolution-alternating least squares (MCR-ALS) applied to Raman microspectroscopic mapping under both 532 nm and 785 nm excitation. For this study, a sample comprised of hematite, carbonaceous material, and substrate-adhesive epoxy in spatially distinct domains was constructed. Principal component analysis (PCA) reveals that both 532 nm and 785 nm excitation produce representative three-phase systems of hematite, carbonaceous material, and substrate-adhesive epoxy in the analyzed sample. MCR-ALS with Raman microspectroscopic mapping using both 532 nm and 785 nm excitation was able to resolve hematite, carbonaceous material, and substrate-adhesive epoxy by generating spatially-resolved chemical maps and corresponding Raman spectra of these spatially distinct chemical species. Moreover, MCR-ALS applied to the combinatorial data sets of 532 nm and 785 nm excitation, which contain hematite and carbonaceous material within the same locations, was able to resolve hematite, carbonaceous material, and substrate-adhesive epoxy. Using multivariate analysis with Raman microspectroscopic mapping, 785 nm excitation more effectively resolved hematite, carbonaceous material, and substrate-adhesive epoxy as compared to 532 nm excitation. To our knowledge, this is the first report of multivariate analysis methods, namely MCR-ALS, with Raman microspectroscopic mapping being employed to differentiate carbonaceous material from hematite. We have therefore provided an analytical methodology useful for the search for extant or past life on the surface of Mars.

Medically-Derived (131)I as a Tool for Investigating the Fate of Wastewater Nitrogen in Aquatic Environments.

Medically derived (131)I (t1/2 = 8.04 d) is discharged from water pollution control plants (WPCPs) in sewage effluent. Iodine's nutrient-like behavior and the source-specificity of (131)I make this radionuclide a potentially valuable tracer in wastewater nitrogen studies. Iodine-131 was measured in Potomac River water and sediments in the vicinity of the Blue Plains WPCP, Washington, DC, USA. Dissolved (131)I showed a strong, positive correlation with δ(15)N values of nitrate (δ(15)NO3(-)) in the river, the latter being a traditional indicator of nutrient inputs and recycling. Surface water δ(15)NO3(-) values ranged from 8.7 to 33.4‰; NO3(-) + NO2(-) concentrations were 0.39-2.79 mg N L(-1) (26-186 µM). Sediment profiles of particulate (131)I and δ(15)N indicate rapid mixing or sedimentation and in many cases remineralization of a heavy nitrogen source consistent with wastewater nitrogen. Values of δ(15)N in sediments ranged from 4.7 to 9.3‰. This work introduces (131)I as a tool to investigate the short-term fate of wastewater nitrogen in the Potomac River and demonstrates the general utility of (131)I in aquatic research.

Temperature-Dependence of Lipid A Acyl Structure in Psychrobacter cryohalolentis and Arctic Isolates of Colwellia hornerae and Colwellia piezophila.

Lipid A is a fundamental Gram-negative outer membrane component and the essential element of lipopolysaccharide (endotoxin), a potent immunostimulatory molecule. This work describes the metabolic adaptation of the lipid A acyl structure by Psychrobacter cryohalolentis at various temperatures in its facultative psychrophilic growth range, as characterized by MALDI-TOF MS and FAME GC-MS. It also presents the first elucidation of lipid A structure from the Colwellia genus, describing lipid A from strains of Colwellia hornerae and Colwellia piezophila, which were isolated as primary cultures from Arctic fast sea ice and identified by 16S rDNA sequencing. The Colwellia strains are obligate psychrophiles, with a growth range restricted to 15 °C or less. As such, these organisms have less need for fluidity adaptation in the acyl moiety of the outer membrane, and they do not display alterations in lipid A based on growth temperature. Both Psychrobacter and Colwellia make use of extensive single-methylene variation in the size of their lipid A molecules. Such single-carbon variations in acyl size were thought to be restricted to psychrotolerant (facultative) species, but its presence in these Colwellia species shows that odd-chain acyl units and a single-carbon variation in lipid A structure are present in obligate psychrophiles, as well.

In situ process analytical technology for real time viable cell density and cell viability during live-virus vaccine production.

Viable cell density (VCD) and cell viability (CV) are key performance indicators of cell culture processes in biopharmaceutical production of biologics and vaccines. Traditional methods for monitoring VCD and CV involve offline cell counting assays that are both labor intensive and prone to high variability, resulting in sparse sampling and uncertainty in the obtained data. Process analytical technology (PAT) approaches offer a means to address these challenges. Specifically, in situ probe-based measurements of dielectric spectroscopy (also commonly known as capacitance) can characterize VCD and CV continuously in real time throughout an entire process, enabling robust process characterization. In this work, we propose in situ dielectric spectroscopy as a PAT tool for real time analysis of live-virus vaccine (LVV) production. Dielectric spectroscopy was collected across 25 discreet frequencies, offering a thorough evaluation of the proposed technology. Correlation of this PAT methodology to traditional offline cell counting assays was performed, in which VCD and CV were both successfully predicted using dielectric spectroscopy. Both univariate and multivariate data analysis approaches were evaluated for their potential to establish correlation between the in situ dielectric spectroscopy and offline measurements. Univariate analysis strategies are presented for optimal single frequency selection. Multivariate analysis, in the form of partial least squares (PLS) regression, produced significantly higher correlations between dielectric spectroscopy and offline VCD and CV data, as compared to univariate analysis. Specifically, by leveraging multivariate analysis of dielectric information from all 25 spectroscopic frequencies measured, PLS models performed significantly better than univariate models. This is particularly evident during cell death, where tracking VCD and CV have historically presented the greatest challenge. The results of this work demonstrate the potential of both single and multiple frequency dielectric spectroscopy measurements for enabling robust LVV process characterization, suggesting that broader application of in situ dielectric spectroscopy as a PAT tool in LVV processes can provide significantly improved process understanding. To the best of our knowledge, this is the first report of in situ dielectric spectroscopy with multivariate analysis to successfully predict VCD and CV in real time during live virus-based vaccine production.

"A friendly reminder" - Improving workflow and efficiency in a pulmonary fellows' outpatient continuity clinic.

BACKGROUND: Seeing patients in an ambulatory clinic generates electronic medical record (EMR) inbox tasks. Little is known about the standard baseline message turnaround time to EMR inbox task completion and whether electronic reminders improve turnaround time. OBJECTIVE: 1) Obtain baseline message type and mean message turnaround time (MTT) to EMR inbox task completion data, 2) Standardize EMR workflow education, 3) Disseminate bi-weekly electronic reminders to fellows in their continuity clinic and measure MTT. METHODS: Prospective, non-randomized, unblinded, cross-over pre- and post-intervention pilot study in an ambulatory pulmonary clinic at a large, urban, academic referral health system. Sixteen pulmonary and critical care fellows affiliated with the Indiana University School of Medicine Pulmonary and Critical Care Fellowship were divided equally into two groups, with the study period from October of 2021 to May of 2022, and were given bi-weekly calendar reminders in Microsoft Outlook with measurement of EMR messages and MTT. RESULTS: 2554 messages were acknowledged with result notes (n = 1676, 59.16 %) being the most common. There was a 40 % decrease in overall MTT from the pre- to the post-intervention period (MTT = 33 days in pre-intervention period for whole cohort, MTT = 19 days in post-intervention period). CONCLUSIONS: MTT for EMR inbox tasks at a large, academic center with fellowship trainees is roughly 2.5 weeks. These findings should prompt other institutions to investigate their own trainees' inbox handling habits and validates the benefit of EMR training and reminders on fellowship trainee's in-basket task turnaround time.

Analyzing atomic force microscopy images of virus-like particles by expectation-maximization.

Analysis of virus-like particles (VLPs) is an essential task in optimizing their implementation as vaccine antigens for virus-initiated diseases. Interrogating VLP collections for elasticity by probing with a rigid atomic force microscopy (AFM) tip is a potential method for determining VLP morphological changes. During VLP morphological change, it is not expected that all VLPs would be in the same state. This leads to the open question of whether VLPs may change in a continuous or stepwise fashion. For continuous change, the statistical distribution of observed VLP properties would be expected as a single distribution, while stepwise change would lead to a multimodal distribution of properties. This study presents the application of a Gaussian mixture model (GMM), fit by the Expectation-Maximization (EM) algorithm, to identify different states of VLP morphological change observed by AFM imaging.

Process analytical technology and its recent applications for asymmetric synthesis.

The development of a safe and effective active pharmaceutical ingredient (API) to be used for addressing a disease is of the utmost importance in the pharmaceutical industry. Oftentimes, the synthetic pathway required for API development involves the genesis of a chiral compound. Asymmetric syntheses are popular routes for generating these kinds of compounds; these reaction routes require a high level of attention for efficient and successful syntheses. Process analytical technology (PAT) provides significant advantages for monitoring, controlling, and assessing synthetic processes directly and in real time. In this review, PAT applications for investigating and improving asymmetric synthetic reactions are discussed. The totality of this effort provides a comprehensive and thorough repository of recent work which has advanced the pharmaceutical field for generating chiral compounds for industrial applications.

Modernized Machine Learning Approach to Illuminate Enzyme Immobilization for Biocatalysis.

Biocatalysis is an established technology with significant application in the pharmaceutical industry. Immobilization of enzymes offers significant benefits for commercial and practical purposes to enhance the stability and recyclability of biocatalysts. Determination of the spatial and chemical distributions of immobilized enzymes on solid support materials is essential for an optimal catalytic performance. However, current analytical methodologies often fall short of rapidly identifying and characterizing immobilized enzyme systems. Herein, we present a new analytical methodology that combines non-negative matrix factorization (NMF)-an unsupervised machine learning tool-with Raman hyperspectral imaging to simultaneously resolve the spatial and spectral characteristics of all individual species involved in enzyme immobilization. Our novel approach facilitates the determination of the optimal NMF model using new data-driven, quantitative selection criteria that fully resolve all chemical species present, offering a robust methodology for analyzing immobilized enzymes. Specifically, we demonstrate the ability of NMF with Raman hyperspectral imaging to resolve the spatial and spectral profiles of an engineered pantothenate kinase immobilized on two different commercial microporous resins. Our results demonstrate that this approach can accurately identify and spatially resolve all species within this enzyme immobilization process. To the best of our knowledge, this is the first report of NMF within hyperspectral imaging for enzyme immobilization analysis, and as such, our methodology can now provide a new powerful tool to streamline biocatalytic process development within the pharmaceutical industry.

Structure Determination of Lipid A with Multiple Glycosylation Sites by Tandem MS of Lithium-Adducted Negative Ions.

FLATn is a tandem mass spectrometric technique that can be used to rapidly generate spectral information applicable for structural elucidation of lipids like lipid A from Gram-negative bacterial species from a single bacterial colony. In this study, we extend the scope and capability of FLATn by tandem MS fragmentation of lithium-adducted molecular lipid A anions and fragments (FLATn-Li) that provides additional structural and diagnostic data from FLATn samples allowing for the discrimination of terminal phosphate modifications in a variety of pathogenic and environmental species. Using FLATn-Li, we elucidated the lipid A structure from several bacterial species, including novel structures from arctic bacterioplankton of the Duganella and Massilia genera that favor 4-amino-4-deoxy-l-arabinopyranose (Ara4N) modification at the 1-phosphate position and that demonstrate double glycosylation with Ara4N at the 1 and 4' phosphate positions simultaneously. The structures characterized in this work demonstrate that some environmental psychrophilic species make extensive use of this structural lipid A modification previously characterized as a pathogenic adaptation and the structural basis of resistance to cationic antimicrobial peptides. This observation extends the role of phosphate modification(s) in environmental species adaptation and suggests that Ara4N modification can functionally replace the positive charge of the phosphoethanolamine modification that is more typically found attached to the 1-phosphate position of modified lipid A.

Real-time in situ monitoring of CRM-197 and polysaccharide conjugation reaction by fluorescence spectroscopy.

Aims: Process analytical technology (PAT) is increasingly being adopted within the pharmaceutical industry to build quality into a process. Development of PAT that provides real-time in situ analysis of critical quality attributes are highly desirable for rapid, improved process development. Conjugation of CRM-197 with pneumococcal polysaccharides to produce a desired pneumococcal conjugate vaccine is a significantly intricate process that can tremendously benefit from real-time process monitoring. Methods: In this work, a fluorescence-based PAT methodology is described to elucidate CRM-197-polysacharide conjugation kinetics in real time. Results & conclusion: In this work, a fluorescence-based PAT methodology is described to elucidate CRM-197-polysacharide conjugation kinetics in real time.

In situ Raman spectroscopy for real time detection of cysteine.

Cysteine serves a wide range of important biological and chemical functions and may have an association to neurodegenerative disease and cancer. Rapid, accurate analytical methods for cysteine detection are thus highly desirable. In this work, we report an investigation into the utility of in situ Raman spectroscopy as a Process Analytical Technology (PAT) for real time monitoring of cysteine. Cysteine concentrations are tracked in real time using Raman spectroscopy across a range of pharmaceutically-relevant concentrations, demonstrating the capability of Raman spectroscopy detection for in situ cysteine monitoring. The concentration range over which this analytical methodology can be applied is successfully established. As such, the results herein serve as a proof-of-principle investigation to demonstrate and evaluate the capabilities of a real time Raman spectroscopic approach for in situ cysteine detection, thus informing the range of important chemical and biological processes to which this approach can be applied. To the best of our knowledge, this is the first report of in situ Raman spectroscopy for real time monitoring of dynamically changing cysteine process concentrations.