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.

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.

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.

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.

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.

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.

Overcoming Biopharmaceutical Interferents for Quantitation of Host Cell DNA Using an Automated, High-Throughput Methodology.

The rapid development of biologics and vaccines in response to the current pandemic has highlighted the need for robust platform assays to characterize diverse biopharmaceuticals. A critical aspect of biopharmaceutical development is achieving a highly pure product, especially with respect to residual host cell material. Specifically, two important host cell impurities of focus within biopharmaceuticals are residual DNA and protein. In this work, a novel high-throughput host cell DNA quantitation assay was developed for rapid screening of complex vaccine drug substance samples. The developed assay utilizes the commercially available, fluorescent-sensitive Picogreen dye within a 96-well plate configuration to allow for a cost effective and rapid analysis. The assay was applied to in-process biopharmaceutical samples with known interferences to the dye, including RNA and protein. An enzymatic digestion pre-treatment was found to overcome these interferences and thus allow this method to be applied to wide-ranging, diverse analyses. In addition, the use of deoxycholate in the digestion treatment allowed for disruption of interactions in a given sample matrix in order to more accurately and selectively quantitate DNA. Critical analytical figures of merit for assay performance, such as precision and spike recovery, were evaluated and successfully demonstrated. This new analytical method can thus be successfully applied to both upstream and downstream process analysis for biologics and vaccines using an innovative and automated high-throughput approach.

Poverty, Comorbidity, and Ethnicity: COVID-19 Outcomes in a Safety Net Health System.

Objective: To determine if race-ethnicity is correlated with case-fatality rates among low-income patients hospitalized for COVID-19. Research Design: Observational cohort study using electronic health record data. Patients: All patients assessed for COVID-19 from March 2020 to January 2021 at one safety net health system. Measures: Patient demographic and clinical characteristics, and hospital care processes and outcomes. Results: Among 25,253 patients assessed for COVID-19, 6,357 (25.2%) were COVID-19 positive: 1,480 (23.3%) hospitalized; 334 (22.6%) required intensive care; and 106 (7.3%) died. More Hispanic patients tested positive (51.8%) than non-Hispanic Black (31.4%) and White patients (16.7%, P<.001]. Hospitalized Hispanic patients were younger, more often uninsured, and less likely to have comorbid conditions. Non-Hispanic Black patients had significantly more diabetes, hypertension, obesity, chronic kidney disease, and asthma (P<.05). Non-Hispanic White patients were older and had more cigarette smoking history, COPD, and cancer. Non-Hispanic White patients were more likely to receive intensive care (29.6% vs 21.1% vs 20.8%, P=.007) and more likely to die (12% vs 7.3% vs 3.5%, P<.001) compared with non-Hispanic Black and Hispanic patients, respectively. Length of stay was similar for all groups. In logistic regression models, Medicaid insurance status independently correlated with hospitalization (OR 3.67, P<.001) while only age (OR 1.076, P<.001) and cerebrovascular disease independently correlated with in-hospital mortality (OR 2.887, P=.002). Conclusions: Observed COVID-19 in-hospital mortality rate was lower than most published rates. Age, but not race-ethnicity, was independently correlated with in-hospital mortality. Safety net health systems are foundational in the care of vulnerable patients suffering from COVID-19, including patients from under-represented and low-income groups.

Care of the Critically Injured Burn Patient.

Care of the critically injured burn patient presents unique challenges to the intensivist. Certified burn centers are rare and geographically sparse, necessitating that much of the initial management of patients with severe burn injuries must happen in the pre-burn center setting. Severe burn injuries often lead to a wide range of complications that extend beyond the loss of skin integrity and require specialized care. As such, medical intensivists are often called on to stabilize these critically injured patients. This focused review outlines the clinical care of these medically complex patients, including airway management, postburn complications, volume resuscitation, nutrition, and end-of-life care.

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.

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.

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.

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.

Process monitoring of polysaccharide deketalization for vaccine bioconjugation development using in situ analytical methodology.

Pneumococcal conjugate vaccines (PCVs) are formed by bioconjugation of a carrier protein to the purified capsular polysaccharide (Ps) from multiple serological strains of Streptococcus pneumoniae. The associated bioconjugation chemistry relies on initial selective modifications to the Ps backbone structure. Among these modifications, removal of a ketal functional group, termed deketalization, is one that is important for pharmaceutical PCV production. Herein, we report a process monitoring investigation into the deketalization of a polysaccharide relevant to PCV process development. We have applied process analytical technology (PAT) for in situ process monitoring to study the deketalization reaction in real time. We find that in situ FTIR spectroscopy elucidates multiple classes of reaction kinetics, one of which correlates strongly with the deketalization reaction of interest. This PAT approach to real time reaction monitoring offers the possibility of improved process monitoring in the pharmaceutical production of PCVs. To our knowledge, this report represents the first PAT investigation into Ps deketalization. Our findings suggest that broader application of PAT to the chemical modifications associated with PCV bioconjugation, as well as other pharmaceutically relevant bioconjugation processes, carries the power to enhance process understanding, control, and efficiency through real time process monitoring.

Utilizing in situ spectroscopic tools to monitor ketal deprotection processes.

The use of protection groups to shield a functional group during a synthesis is employed throughout many reactions and organic syntheses. The role of a protection group can be vital to the success of a reaction, as well as increase reaction yield and selectivity. Although much work has been done to investigate the addition of a protection group, the removal of the protection group is just as important - however, there is a lack of methods employed within the literature for monitoring the removal of a protection group in real time. In this work, the process of removing, or deprotecting, a ketal protecting group is investigated. Process analytical technology tools are incorporated for in situ analysis of the deprotection reaction of a small molecule model compound. Specifically, Raman spectroscopy and Fourier transform infrared spectroscopy show that characteristic bands can be used to track the decrease of the reactant and the increase of the expected products over time. To the best of our knowledge, this is the first report of process analytical technology being used to monitor a ketal deprotection reaction in real time. This information can be capitalized on in the future for understanding and optimizing pharmaceutically-relevant deprotection processes and downstream reactions.

Quantitation and speciation of residual protein within active pharmaceutical ingredients using image analysis with SDS-PAGE.

Recent advances in biocatalysis and directed enzyme evolution has led to a variety of enzymatically-driven, elegant processes for active pharmaceutical ingredient (API) production. For biocatalytic processes, quantitation of any residual protein within a given API is of great importance to ensure process robustness and quality, pure pharmaceutical products. Typical analytical methods for analyzing residual enzymes within an API, such as enzyme-linked immunosorbent assays (ELISA), colorimetric assays, and liquid chromatographic techniques, are limited for determining only the concentration of known proteins and require harsh solvents with high API levels for analysis. For the first time, total residual protein content in a small molecule API was quantitated using image analysis applied to SDS-PAGE. Herein, a proposed methodology for residual protein detection, quantitation, and size-based speciation is presented, in which an orthogonal technique is offered to traditional analysis methods, such as ELISA. Results indicate that our application of the analytical methodology is able to reliably quantitate both protein standards and the total residual protein present within a final API, with good agreement as compared to traditional ELISA results. Further, speciation of the residual protein within the API provides key information concerning the individual residual proteins present, including their molecular weight, which can lead to improved process development efforts for residual protein rejection and control. This analytical methodology thus offers an alternative tool for easily identifying, quantitating, and speciating residual protein content in the presence of small molecule APIs, with potential for wide applicability across industry for biocatalytic or directed enzyme evolution efforts within process development.

Dissolved rubidium to strontium ratio as a conservative tracer for wastewater effluent-sourced contaminant inputs near a major urban wastewater treatment plant.

Municipal wastewater (MWW) effluent discharges can introduce contaminants to receiving waters which may have adverse impacts on local ecosystems and human health. Conservative chemical constituents specific to the MWW effluent stream can be used to quantify and trace wastewater effluent-sourced contaminant inputs. Gadolinium (Gd), a rare earth element used as a contrasting agent in medical magnetic resonance imaging, can be found in urban MWW streams. Dissolved anthropogenic Gd has been shown to be an indicator and potential conservative tracer for MWW effluent in receiving waters. Like other known MWW tracers, it can be difficult and expensive to measure. Dissolved rubidium (Rb) to strontium (Sr) ratio enrichment in biological materials such as blood and urine can lead to enriched Rb/Sr values in MWW effluent relative to natural waters. This ratio is relatively easy and inexpensive to measure and represents a promising additional indicator for MWW effluent in receiving waters in urbanized freshwater systems. In July 2015 and 2016 surface water samples were collected from sites in the tidal-fresh Potomac River in the vicinity of the Blue Plains Advanced Wastewater Treatment Plant (BPAWWTP) outfall near Washington, DC USA along with treated MWW effluent samples from the BPAWWTP. Dissolved Rb/Sr ratios were measured in these waters and compared to dissolved Gd concentrations in order to demonstrate the potential of the dissolved Rb/Sr ratio as a conservative indicator for MWW effluent. Results suggest the dissolved Rb/Sr ratio represents a simple and cost-effective indicator and conservative tracer for MWW effluent. It can be used with, or in place of, other proven tracers to investigate wastewater impacts in highly-urbanized, anthropogenically-impacted freshwater systems like the tidal fresh Potomac River and perhaps in a wider range of geologic settings than previously thought. A case study is presented as an example to demonstrate the potential of using dissolved Rb/Sr ratios to trace MWW-sourced nutrient inputs from a major WWTP like BPAWWTP to the receiving waters of tidal-fresh Potomac River.