A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond.

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

Wastewater surveillance monitoring of SARS-CoV-2 variants of concern and dynamics of transmission and community burden of COVID-19.

Wastewater-based surveillance is a valuable approach for monitoring COVID-19 at community level. Monitoring SARS-CoV-2 variants of concern (VOC) in wastewater has become increasingly relevant when clinical testing capacity and case-based surveillance are limited. In this study, we ascertained the turnover of six VOC in Alberta wastewater from May 2020 to May 2022. Wastewater samples from nine wastewater treatment plants across Alberta were analysed using VOC-specific RT-qPCR assays. The performance of the RT-qPCR assays in identifying VOC in wastewater was evaluated against next generation sequencing. The relative abundance of each VOC in wastewater was compared to positivity rate in COVID-19 testing. VOC-specific RT-qPCR assays performed comparatively well against next generation sequencing; concordance rates ranged from 89% to 98% for detection of Alpha, Beta, Gamma, Omicron BA.1 and Omicron BA.2, with a slightly lower rate of 85% for Delta (p < 0.01). Elevated relative abundance of Alpha, Delta, Omicron BA.1 and BA.2 were each associated with increased COVID-19 positivity rate. Alpha, Delta and Omicron BA.2 reached 90% relative abundance in wastewater within 80, 111 and 62 days after their initial detection, respectively. Omicron BA.1 increased more rapidly, reaching a 90% relative abundance in wastewater after 35 days. Our results from VOC surveillance in wastewater correspond with clinical observations that Omicron is the VOC with highest disease burden over the shortest period in Alberta to date. The findings suggest that changes in relative abundance of a VOC in wastewater can be used as a supplementary indicator to track and perhaps predict COVID-19 burden in a population.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism.

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Small-Molecule Disruptors of Mutant Huntingtin-Calmodulin Protein-Protein Interaction Attenuate Deleterious Effects of Mutant Huntingtin.

Huntington's disease is a progressive and lethal neurodegenerative disease caused by an increased CAG repeat mutation in exon 1 of the huntingtin gene (mutant huntingtin). Current drug treatments provide only limited symptomatic relief without impacting disease progression. Previous studies in our lab and others identified the abnormal binding of mutant huntingtin protein with calmodulin, a key regulator of calcium signaling. Disrupting the abnormal binding of mutant huntingtin to calmodulin reduces perturbations caused by mutant huntingtin in cell and mouse models of Huntington's disease and importantly normalizes receptor-stimulated calcium release. Using a series of high-throughput in vitro and cell-based screening assays, we identified numerous small-molecule hits that disrupt the binding of mutant huntingtin to calmodulin and demonstrate protective effects. Iterative optimization of one hit resulted in nontoxic, selective compounds that are protective against mutant huntingtin cytotoxicity and normalized receptor-stimulated intracellular calcium release in PC12 cell models of Huntington's disease. Importantly, the compounds do not work by reducing the levels of mutant huntingtin, allowing this strategy to complement future molecular approaches to reduce mutant huntingtin expression. Our novel scaffold will serve as a prototype for further drug development in Huntington's disease. These studies indicate that the development of small-molecule compounds that disrupt the binding of mutant huntingtin to calmodulin is a promising approach for the advancement of therapeutics to treat Huntington's disease.

Tracking Emergence and Spread of SARS-CoV-2 Omicron Variant in Large and Small Communities by Wastewater Monitoring in Alberta, Canada.

Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.

Discovery and Optimization of Pyrrolopyrimidine Derivatives as Selective Disruptors of the Perinucleolar Compartment, a Marker of Tumor Progression toward Metastasis.

The perinucleolar compartment (PNC) is a dynamic subnuclear body found at the periphery of the nucleolus. The PNC is enriched with RNA transcripts and RNA-binding proteins, reflecting different states of genome organization. PNC prevalence positively correlates with cancer progression and metastatic capacity, making it a useful marker for metastatic cancer progression. A high-throughput, high-content assay was developed to identify novel small molecules that selectively reduce PNC prevalence in cancer cells. We identified and further optimized a pyrrolopyrimidine series able to reduce PNC prevalence in PC3M cancer cells at submicromolar concentrations without affecting cell viability. Structure-activity relationship exploration of the structural elements necessary for activity resulted in the discovery of several potent compounds. Analysis of in vitro drug-like properties led to the discovery of the bioavailable analogue, metarrestin, which has shown potent antimetastatic activity with improved survival in rodent models and is currently being evaluated in a first-in-human phase 1 clinical trial.

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population.

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

Use of AD Informer Set compounds to explore validity of novel targets in Alzheimer's disease pathology.

Introduction: A chemogenomic set of small molecules with annotated activities and implicated roles in Alzheimer's disease (AD) called the AD Informer Set was recently developed and made available to the AD research community: https://treatad.org/data-tools/ad-informer-set/. Methods: Small subsets of AD Informer Set compounds were selected for AD-relevant profiling. Nine compounds targeting proteins expressed by six AD-implicated genes prioritized for study by Target Enablement to Accelerate Therapy Development for Alzheimer's Disease (TREAT-AD) teams were selected for G-protein coupled receptor (GPCR), amyloid beta (Aß) and tau, and pharmacokinetic (PK) studies. Four non-overlapping compounds were analyzed in microglial cytotoxicity and phagocytosis assays. Results: The nine compounds targeting CAPN2, EPHX2, MDK, MerTK/FLT3, or SYK proteins were profiled in 46 to 47 primary GPCR binding assays. Human induced pluripotent stem cell (iPSC)-derived neurons were treated with the same nine compounds and secretion of Aß peptides (Aß40 and Aß42) as well as levels of phosphophorylated tau (p-tau, Thr231) and total tau (t-tau) peptides measured at two concentrations and two timepoints. Finally, CD1 mice were dosed intravenously to determine preliminary PK and/or brain-specific penetrance values for these compounds. As a final cell-based study, a non-overlapping subset of four compounds was selected based on single-concentration screening for analysis of both cytotoxicity and phagocytosis in murine and human microglia cells. Discussion: We have demonstrated the utility of the AD Informer Set in the validation of novel AD hypotheses using biochemical, cellular (primary and immortalized), and in vivo studies. The selectivity for their primary targets versus essential GPCRs in the brain was established for our compounds. Statistical changes in tau, p-tau, Aß40, and/or Aß42 and blood-brain barrier penetrance were observed, solidifying the utility of specific compounds for AD. Single-concentration phagocytosis results were validated as predictive of dose-response findings. These studies established workflows, validated assays, and illuminated next steps for protein targets and compounds.

Advances in Sulfonamide Kappa Opioid Receptor Antagonists: Structural Refinement and Evaluation of CNS Clearance.

Focused modification of a sulfonamide-based kappa opioid receptor (KOR) antagonist series previously reported by this laboratory was investigated. A total of 32 analogues were prepared to explore linker replacement, constraint manipulation, and aryl group or amine substitution. All analogues were assayed for KOR antagonist activity, and the initial lead compound was assessed for in vivo CNS penetration. The most improved analogue possessed a 4-fold increase of potency (IC50 = 18.9 ± 4.4 nM) compared with the lead compound (IC50 = 83.5 ± 20 nM) from an earlier work. The initial lead compound was found to attain suitable brain levels and to possess a shorter clearance time than canonical KOR antagonists such as JDTic.

AD Informer Set: Chemical tools to facilitate Alzheimer's disease drug discovery.

Introduction: The portfolio of novel targets to treat Alzheimer's disease (AD) has been enriched by the Accelerating Medicines Partnership Program for Alzheimer's Disease (AMP AD) program. Methods: Publicly available resources, such as literature and databases, enabled a data-driven effort to identify existing small molecule modulators for many protein products expressed by the genes nominated by AMP AD and suitable positive control compounds to be included in the set. Compounds contained within the set were manually selected and annotated with associated published, predicted, and/or experimental data. Results: We built an annotated set of 171 small molecule modulators targeting 98 unique proteins that have been nominated by AMP AD consortium members as novel targets for the treatment of AD. The majority of compounds included in the set are inhibitors. These small molecules vary in their quality and should be considered chemical tools that can be used in efforts to validate therapeutic hypotheses, but which will require further optimization. A physical copy of the AD Informer Set can be requested on the Target Enablement to Accelerate Therapy Development for Alzheimer's Disease (TREAT-AD) website. Discussion: Small molecules that enable target validation are important tools for the translation of novel hypotheses into viable therapeutic strategies for AD.

Divergent Electrochemical Carboamidation of Cyclic Amines.

We developed an electrochemical carboamidation sequence that affords either cyclic ß-amidoamine products via direct functionalization or linear hydroxybisamide products via a ring opening pathway. The reaction pathway was dependent on the nature of the N-acyl activating group, with carbamate groups favoring direct isocyanide addition to the N-acyliminium ion intermediate and the benzoyl activating group favoring the ring opening-functionalization pathway. Both protocols are one-pot reaction sequences, have general applicability, and lead to peptide-like products of greatly increased molecular complexity.

A multicenter study investigating SARS-CoV-2 in tertiary-care hospital wastewater. viral burden correlates with increasing hospitalized cases as well as hospital-associated transmissions and outbreaks.

SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling > 2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r = 0.679, P < 0.0001, Pearson's r = 0.799, P < 0.0001, respectively). Despite increasing hospitalizations through the study period, nosocomial-acquired cases of COVID-19 (Pearson's r = 0.389, P < 0.001) and unit-specific outbreaks were discernable with significant increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P < 0.0001). Wastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute- care medical facilities.

Development of pyrimidone D1 dopamine receptor positive allosteric modulators.

MLS1082 is a structurally novel pyrimidone-based D1-like dopamine receptor positive allosteric modulator. Potentiation of D1 dopamine receptor (D1R) signaling is a therapeutic strategy for treating neurocognitive disorders. Here, we investigate the relationship between D1R potentiation and two prominent structural features of MLS1082, namely the pendant N-aryl and C-alkyl groups on the pyrimidone ring. To this end, we synthesized 24 new analogues and characterized their ability to potentiate dopamine signaling at the D1R and the closely related D5R. We identified structure-activity relationship trends for both aryl and alkyl modifications and our efforts afforded several analogues with improvements in activity. The most effective analogues demonstrated an approximately 8-fold amplification of dopamine-mediated D1R signaling. These findings advance the understanding of structural moieties underlying the activity of pyrimidone-based D1R positive allosteric modulators.

Fluoxazolevir inhibits hepatitis C virus infection in humanized chimeric mice by blocking viral membrane fusion.

Fluoxazolevir is an aryloxazole-based entry inhibitor of hepatitis C virus (HCV). We show that fluoxazolevir inhibits fusion of HCV with hepatic cells by binding HCV envelope protein 1 to prevent fusion. Nine of ten fluoxazolevir resistance-associated substitutions are in envelope protein 1, and four are in a putative fusion peptide. Pharmacokinetic studies in mice, rats and dogs revealed that fluoxazolevir localizes to the liver. A 4-week intraperitoneal regimen of fluoxazolevir in humanized chimeric mice infected with HCV genotypes 1b, 2a or 3 resulted in a 2-log reduction in viraemia, without evidence of drug resistance. In comparison, daclatasvir, an approved HCV drug, suppressed more than 3 log of viraemia but is associated with the emergence of resistance-associated substitutions in mice. Combination therapy using fluoxazolevir and daclatasvir cleared HCV genotypes 1b and 3 in mice. Fluoxazolevir combined with glecaprevir and pibrentasvir was also effective in clearing multidrug-resistant HCV replication in mice. Fluoxazolevir may be promising as the next generation of combination drug cocktails for HCV treatment.

Discovery, Optimization, and Characterization of ML417: A Novel and Highly Selective D3 Dopamine Receptor Agonist.

To identify novel D3 dopamine receptor (D3R) agonists, we conducted a high-throughput screen using a ß-arrestin recruitment assay. Counterscreening of the hit compounds provided an assessment of their selectivity, efficacy, and potency. The most promising scaffold was optimized through medicinal chemistry resulting in enhanced potency and selectivity. The optimized compound, ML417 (20), potently promotes D3R-mediated ß-arrestin translocation, G protein activation, and ERK1/2 phosphorylation (pERK) while lacking activity at other dopamine receptors. Screening of ML417 against multiple G protein-coupled receptors revealed exceptional global selectivity. Molecular modeling suggests that ML417 interacts with the D3R in a unique manner, possibly explaining its remarkable selectivity. ML417 was also found to protect against neurodegeneration of dopaminergic neurons derived from iPSCs. Together with promising pharmacokinetics and toxicology profiles, these results suggest that ML417 is a novel and uniquely selective D3R agonist that may serve as both a research tool and a therapeutic lead for the treatment of neuropsychiatric disorders.

Discovery of sultam-containing small-molecule disruptors of the huntingtin-calmodulin protein-protein interaction.

The aberrant protein-protein interaction between calmodulin and mutant huntingtin protein in Huntington's disease patients has been found to contribute to Huntington's disease progression. A high-throughput screen for small molecules capable of disrupting this interaction revealed a sultam series as potent small-molecule disruptors. Diversification of the sultam scaffold afforded a set of 24 analogs or further evaluation. Several structure-activity trends within the analog set were found, most notably a negligible effect of absolute stereochemistry and a strong beneficial correlation with electron-withdrawing aromatic substituents. The most promising analogs were profiled for off-target effects at relevant kinases and, ultimately, one candidate molecule was evaluated for neuroprotection in a neuronal cell model of Huntington's disease.

Pharmacokinetic evaluation of the PNC disassembler metarrestin in wild-type and Pdx1-Cre;LSL-KrasG12D/+;Tp53R172H/+ (KPC) mice, a genetically engineered model of pancreatic cancer.

PURPOSE: Metarrestin is a first-in-class small molecule clinical candidate capable of disrupting the perinucleolar compartment, a subnuclear structure unique to metastatic cancer cells. This study aims to define the pharmacokinetic (PK) profile of metarrestin and the pharmacokinetic/pharmacodynamic relationship of metarrestin-regulated markers. METHODS: PK studies included the administration of single or multiple dose of metarrestin at 3, 10, or 25 mg/kg via intravenous (IV) injection, gavage (PO) or with chow to wild-type C57BL/6 mice and KPC mice bearing autochthonous pancreatic tumors. Metarrestin concentrations were analyzed by UPLC-MS/MS. Pharmacodynamic assays included mRNA expression profiling by RNA-seq and qRT-PCR for KPC mice. RESULTS: Metarrestin had a moderate plasma clearance of 48 mL/min/kg and a large volume of distribution of 17 L/kg at 3 mg/kg IV in C57BL/6 mice. The oral bioavailability after single-dose (SD) treatment was > 80%. In KPC mice treated with SD 25 mg/kg PO, plasma AUC0-∞ of 14400 ng h/mL, Cmax of 810 ng/mL and half-life (t1/2) of 8.5 h were observed. At 24 h after SD of 25 mg/kg PO, the intratumor concentration of metarrestin was high with a mean value of 6.2 µg/g tissue (or 13 µM), well above the cell-based IC50 of 0.4 µM. At multiple dose (MD) 25 mg/kg/day PO in KPC mice, mean tissue/plasma AUC0-24h ratio for tumor, spleen and liver was 37, 30 and 31, respectively. There was a good linear relationship of dosage to AUC0-24h and C24h. AUC0-24h MD to AUC0-24h SD ratios ranged from two for liver to five for tumor indicating additional accumulation in tumors. Dose-dependent normalization of FOXA1 and FOXO6 mRNA expression was observed in KPC tumors. CONCLUSIONS: Metarrestin is an effective therapeutic candidate with a favorable PK profile achieving excellent intratumor tissue levels in a disease with known poor drug delivery.