Screening Workflow Research Articles

Toward Standardization and High Reliability: Improved Sepsis Screening in Emergency Department Triage Across an Academic Health System

Sepsis is a life-threatening emergency, and early recognition and treatment in the emergency department (ED) is critical to improving outcomes. The authors implemented an interdisciplinary quality improvement (QI) project to standardize sepsis screening workflow across an academic health system consisting of a large tertiary care urban hospital, one freestanding ED, and two small rural affiliate hospitals (RA-1 and RA-2). The research team used the Institute for Healthcare Improvement Model for Improvement framework, consisting of iterative Plan-Do-Study-Act (PDSA) cycles. The primary outcome was rates of screening for sepsis at each site. Secondary outcomes included sepsis mortality and Centers for Medicare & Medicaid Services (CMS) sepsis bundle (SEP-1) compliance at our main medical center. Primary outcome was assessed using electronic dashboards extracting the ratio of ED encounters with electronic health record (EHR)-documented sepsis screening per total ED encounters. The SEP-1 bundle was assessed as percent compliance, and mortality was calculated as average observed to expected (O:E). Averages were compared from preintervention to after initiating improvements using two-tailed t-tests. This QI project took place from December 2022 to December 2023 across four EDs that experience around 138,000 visits annually. A standardized workflow was established at ED triage with an EHR-based question and an associated nurse and physician defined response. Preintervention (October 2022 to November 2022) triage rates for sepsis were 1.7% (163/9,560), 25.3% (523/2,068), 11.0% (360/3,272), and 36.5% (915/2,506) at our main hospital, freestanding ED, RA-1, and RA-2, respectively. After four PDSA cycles, triage rates rose to 91.9% (4,927/5,360), 97.5% (1,032/1,059), 99.0% (1,845/1,863), and 97.4% (1,328/1,363), respectively (p < 0.005). Sepsis triage rates rose most slowly at the large academic medical center, where progressive PDSA cycles were needed to achieve > 90% screening for sepsis. Mean O:E mortality was 0.99 for the 9 months of available data preintervention and 0.83 in the 17 months postintervention (p = 0.07). CMS sepsis bundle compliance was 28.4% for the 15 months preintervention and 40.5% in the 17 months postintervention, (p = 0.14). An interdisciplinary QI project leveraged EHR optimization to integrate with human workflows over four PDSA cycles to achieve standardized and improved screening for sepsis in the ED. This resulted in lower sepsis mortality and increased sepsis bundle compliance, though results were not statistically significant.

HSADab: A comprehensive database for human serum albumin

Human Serum Albumin (HSA), the most abundant protein in human body fluids, plays a crucial role in the transportation, absorption, metabolism, distribution, and excretion of drugs, significantly influencing their therapeutic efficacy. Despite the importance of HSA as a drug target, the available data on its interactions with external agents, such as drug-like molecules and antibodies, are limited, posing challenges for molecular modeling investigations and the development of empirical scoring functions or machine learning predictors for this target. Furthermore, the reported entries in existing databases often contain major inconsistencies due to varied experiments and conditions, raising concerns about data quality. To address these issues, a pioneering database, HSADab, was established through an extensive review of >30,000 scientific publications published between 1987 and 2023. The database encompasses over 5000 affinity data points at multiple temperatures and >130 crystal structures, including both ligand-bound and apo forms. The current HSADab resource (www.hsadab.cn) serves as a reliable foundation for validating molecular simulation protocols, such as traditional virtual screening workflows using docking, end-point, and al-chemical free energy techniques. Additionally, it provides a valuable data source for the implementation of machine learning predictors, including plasma protein binding models and plasma protein-based drug design models.

Genomic barcoding for clonal diversity monitoring and control in cell-based complex antibody production

Engineered mammalian cells are key for biotechnology by enabling broad applications ranging from in vitro model systems to therapeutic biofactories. Engineered cell lines exist as a population containing sub-lineages of cell clones that exhibit substantial genetic and phenotypic heterogeneity. There is still a limited understanding of the source of this inter-clonal heterogeneity as well as its implications for biotechnological applications. Here, we developed a genomic barcoding strategy for a targeted integration (TI)-based CHO antibody producer cell line development process. This technology provided novel insights about clone diversity during stable cell line selection on pool level, enabled an imaging-independent monoclonality assessment after single cell cloning, and eventually improved hit-picking of antibody producer clones by monitoring of cellular lineages during the cell line development (CLD) process. Specifically, we observed that CHO producer pools generated by TI of two plasmids at a single genomic site displayed a low diversity (< 0.1% RMCE efficiency), which further depends on the expressed molecules, and underwent rapid population skewing towards dominant clones during routine cultivation. Clonal cell lines from one individual TI event demonstrated a significantly lower variance regarding production-relevant and phenotypic parameters as compared to cell lines from distinct TI events. This implies that the observed cellular diversity lies within pre-existing cell-intrinsic factors and that the majority of clonal variation did not develop during the CLD process, especially during single cell cloning. Using cellular barcodes as a proxy for cellular diversity, we improved our CLD screening workflow and enriched diversity of production-relevant parameters substantially. This work, by enabling clonal diversity monitoring and control, paves the way for an economically valuable and data-driven CLD process.

(062) IMPLEMENTING A VALIDATED SEXUAL DYSFUNCTION SCREENING TOOL AT AN INNER-CITY WOMEN’S HEALTH CLINIC

Abstract Introduction The American College of Obstetricians and Gynecologists (ACOG) reports 43% of American women experience sexual health problems, including Female Sexual Interest and Arousal Disorder, Female Orgasmic Disorder, Genito–Pelvic Pain and Penetration Disorder, and Substance or Medication-Induced Sexual Dysfunction. Objective At Women’s Ambulatory Health Services (WAHS), an inner-city clinic associated with Hartford HealthCare, at which UConn Health ObGyn residents work, there is no routine screening in place for sexual dysfunction. This project aimed to implement the Female Sexual Function Index (FSFI) for screening for sexual dysfunction at this clinic to identify patients who may benefit from treatment. Methods We implemented the FSFI-short version, a six-question screening tool for sexual dysfunction that has been validated in English and Spanish and utilized in many countries on July 1st, 2022. Patients presenting for a new gynecologic visit or an annual gynecologic exam were asked to complete the screening tool. Patients who scored equal to or less than 18 on the FSFI-short version were identified as at risk for female sexual dysfunction and were offered referral to a health psychologist specializing in sexual dysfunction. We utilized the RE-AIM framework for implementation science to guide the implementation evaluation. We collected data on patients from July 1 through December 1, 2022. We collected patient demographics and implementation outcomes, including rate of survey completion, candidacy for referral and referral completion. Results 196 surveys were reviewed between July 1st and December 1st of 2022. 44 surveys were excluded for various reasons, including not meeting study inclusion criteria or invalid responses. 152 screening forms were included and 45 patients screened positive. Subjective patient barriers were gathered from comments written directly onto the paper survey as well as quotes documented by their providers in the visit note. These subjective barriers included hesitancy to discuss sexual health and lacking knowledge that the gynecologist provider offers assessment and management for these disorders. Conclusions The introduction of the FSFI-sv at WAHS has both expanded the resources offered to patients, enhanced the environment surrounding topics of women’s health both between staff members as well as within the patient-provider relationship, and has unearthed multiple opportunities for improving the screening process, referral selection and work flow for sexual dysfunction amongst the patient population. Disclosure No.

Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.

The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell development and activation. Dysregulation of LCK signaling has been demonstrated to drive the oncogenesis of T-cell acute lymphoblastic leukemia (T-ALL), thus providing a therapeutic target for leukemia treatment. In this study, we introduced a sophisticated virtual screening strategy combined with biological evaluations to discover potent LCK inhibitors. Our initial approach involved utilizing the PLANET algorithm to assess and contrast various scoring methodologies suitable for LCK inhibitor screening. After effectively evaluating PLANET, we progressed to devise a virtual screening workflow that synergistically combines the strengths of PLANET with the capabilities of Schrödinger's suite. This integrative strategy led to the efficient identification of four potential LCK inhibitors. Among them, compound 1232030-35-1 stood out as the most promising candidate with an IC50 of 0.43 nM. Further in vitro bioassays revealed that 1232030-35-1 exhibited robust antiproliferative effects on T-ALL cells, which was attributed to its ability to suppress the phosphorylations of key molecules in the LCK signaling pathway. More importantly, 1232030-35-1 treatment demonstrated profound in vivo antileukemia efficacy in a human T-ALL xenograft model. In addition, complementary molecular dynamics simulations provided deeper insight into the binding kinetics between 1232030-35-1 and LCK, highlighting the formation of a hydrogen bond with Met319. Collectively, our study established a robust and effective screening strategy that integrates AI-driven and conventional methodologies for the identification of LCK inhibitors, positioning 1232030-35-1 as a highly promising and novel drug-like candidate for potential applications in treating T-ALL.

Implementing Inpatient Social Needs Screening in an Urban Tertiary Care Children's Hospital.

The American Academy of Pediatrics recommends screening for unmet social needs, and the literature on inpatient screening implementation is growing. Our aim was to use quality improvement methods to implement standardized social needs screening in hospitalized pediatric patients. We implemented inpatient social needs screening using the Model for Improvement. An interprofessional team trialed interventions in a cyclical manner using plan-do-study-act cycles. Interventions included a structured screening questionnaire, standardized screening and referrals workflows, electronic health record (EHR) modifications, and house staff education, deliberate practice, and feedback. The primary outcome measure was the percentage of discharged patients screened for social needs. Screening for social needs was defined as a completed EHR screening questionnaire or a full social work evaluation. Process and balancing measures were collected to capture data on screening questionnaire completion and social work consultations. Data were plotted on statistical process control charts and analyzed for special cause variation. The mean monthly percentage of patients screened for social needs improved from 20% at baseline to 51% during the intervention period. Special cause variation was observed for the percentage of patients with completed social needs screening, EHR-documented screening questionnaires, and social work consults. Social needs screening during pediatric hospitalization can be implemented by using quality improvement methods. The next steps should be focused on sustainability and the spread of screening. Interventions with greater involvement of interdisciplinary health care team members will foster process sustainability and allow for the spread of screening interventions to the wider hospitalized pediatric population.

Screening approach by a combination of computational and in vitro experiments: identification of fluvastatin sodium as a potential SIRT2 inhibitor.

Sirtuins (SIRTs) are NAD+-dependent deacetylases that play various roles in numerous pathophysiological processes, holding promise as therapeutic targets worthy of further investigation. Among them, the SIRT2 subtype is closely associated with tumorigenesis and malignancies. Dysregulation of SIRT2 activation can regulate the expression levels of related genes in cancer cells, leading to tumor occurrence and metastasis. In this study, we used computer simulations to screen for novel SIRT2 inhibitors from the FDA database, based on which 10 compounds with high docking scores and good interactions were selected for in vitro anti-pancreatic cancer metastasis testing and enzyme binding inhibition experiments. The results showed that fluvastatin sodium may possess inhibitory activity against SIRT2. Subsequently, fluvastatin sodium was subjected to molecular docking experiments with various SIRT isoforms, and the combined results from Western blotting experiments indicated its potential as a SIRT2 inhibitor. Next, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations were performed, revealing the binding mode of fluvastatin sodium at the SIRT2 active site, further validating the stability and interaction of the ligand-protein complex under physiological conditions. Overall, this study provides a systematic virtual screening workflow for the discovery of SIRT2 activity inhibitors, identifies the potential inhibitory effect of fluvastatin sodium as a lead compound on SIRT2, and opens up a new direction for developing highly active and selectively targeted SIRT2 inhibitors.

Insights into the early-life chemical exposome of Nigerian infants and potential correlations with the developing gut microbiome

Early-life exposure to natural and synthetic chemicals can impact acute and chronic health conditions. Here, a suspect screening workflow anchored on high-resolution mass spectrometry was applied to elucidate xenobiotics in breast milk and matching stool samples collected from Nigerian mother-infant pairs (n = 11) at three time points. Potential correlations between xenobiotic exposure and the developing gut microbiome, as determined by 16S rRNA gene amplicon sequencing, were subsequently explored. Overall, 12,192 and 16,461 features were acquired in the breast milk and stool samples, respectively. Following quality control and suspect screening, 562 and 864 features remained, respectively, with 149 of these features present in both matrices. Taking advantage of 242 authentic reference standards measured for confirmatory purposes of food bio-actives and toxicants, 34 features in breast milk and 68 features in stool were identified and semi-quantified. Moreover, 51 and 78 features were annotated with spectral library matching, as well as 416 and 652 by in silico fragmentation tools in breast milk and stool, respectively. The analytical workflow proved its versatility to simultaneously determine a diverse panel of chemical classes including mycotoxins, endocrine-disrupting chemicals (EDCs), antibiotics, plasticizers, perfluorinated alkylated substances (PFAS), and pesticides, although it was originally optimized for polyphenols. Spearman rank correlation of the identified features revealed significant correlations between chemicals of the same classification such as polyphenols. One-way ANOVA and differential abundance analysis of the data obtained from stool samples revealed that molecules of plant-based origin elevated as complementary foods were introduced to the infants’ diets. Annotated compounds in the stool, such as tricetin, positively correlated with the genus Blautia. Moreover, vulgaxanthin negatively correlated with Escherichia-Shigella. Despite the limited sample size, this exploratory study provides high-quality exposure data of matched biospecimens obtained from mother-infant pairs in sub-Saharan Africa and shows potential correlations between the chemical exposome and the gut microbiome.

Optical redox imaging to screen synthetic hydrogels for stem cell-derived cardiomyocyte differentiation and maturation.

Heart disease is the leading cause of death in the United States, yet research is limited by the inability to culture primary cardiac cells. Cardiomyocytes (CMs) derived from human induced pluripotent stem cells (iPSCs) are a promising solution for drug screening and disease modeling. Induced pluripotent stem cell-derived CM (iPSC-CM) differentiation and maturation studies typically use heterogeneous substrates for growth and destructive verification methods. Reproducible, tunable substrates and touch-free monitoring are needed to identify ideal conditions to produce homogenous, functional CMs. We generated synthetic polyethylene glycol-based hydrogels for iPSC-CM differentiation and maturation. Peptide concentrations, combinations, and gel stiffness were tuned independently. Label-free optical redox imaging (ORI) was performed on a widefield microscope in a 96-well screen of gel formulations. We performed live-cell imaging throughout differentiation and early to late maturation to identify key metabolic shifts. Label-free ORI confirmed the expected metabolic shifts toward oxidative phosphorylation throughout the differentiation and maturation processes of iPSC-CMs on synthetic hydrogels. Furthermore, ORI distinguished high and low differentiation efficiency cell batches in the cardiac progenitor stage. We established a workflow for medium throughput screening of synthetic hydrogel conditions with the ability to perform repeated live-cell measurements and confirm expected metabolic shifts. These methods have implications for reproducible iPSC-CM generation in biomanufacturing.

High-throughput nanopore DNA sequencing of large insert fosmid clones directly from bacterial colonies.

Fosmids and cosmids are vectors frequently used in functional metagenomic studies. With a large insert capacity (around 30 kb) they can encode dozens of cloned genes or in some cases, entire biochemical pathways. Fosmids with cloned inserts can be transferred to heterologous hosts and propagated to enable screening for new enzymes and metabolites. After screening, fosmids from clones with an activity of interest must be de novo sequenced, a critical step toward the identification of the gene(s) of interest. In this work, we present a new approach for rapid and high-throughput fosmid sequencing directly from Escherichia coli colonies without liquid culturing or fosmid purification. Our sample preparation involves fosmid amplification with phi29 polymerase and then direct nanopore sequencing using the Oxford Nanopore Technologies system. We also present a bioinformatics pipeline termed "phiXXer" that facilitates both de novo read assembly and vector trimming to generate a linear sequence of the fosmid insert. Finally, we demonstrate the accurate sequencing of 96 fosmids in a single run and validate the method using two fosmid libraries that contain cloned large insert (~30-40 kb) genomic or metagenomic DNA.IMPORTANCELarge-insert clone (fosmids or cosmids) sequencing is challenging and arguably the most limiting step of functional metagenomic screening workflows. Our study establishes a new method for high-throughput nanopore sequencing of fosmid clones directly from lysed Escherichia coli cells. It also describes a companion bioinformatic pipeline that enables de novo assembly of fosmid DNA insert sequences. The devised method widens the potential of functional metagenomic screening by providing a simple, high-throughput approach to fosmid clone sequencing that dramatically speeds the pace of discovery.

Structure-Based Virtual Screening for Methyltransferase Inhibitors of SARS-CoV-2 nsp14 and nsp16.

The ongoing COVID-19 pandemic still threatens human health around the world. The methyltransferases (MTases) of SARS-CoV-2, specifically nsp14 and nsp16, play crucial roles in the methylation of the N7 and 2'-O positions of viral RNA, making them promising targets for the development of antiviral drugs. In this work, we performed structure-based virtual screening for nsp14 and nsp16 using the screening workflow (HTVS, SP, XP) of Schrödinger 2019 software, and we carried out biochemical assays and molecular dynamics simulation for the identification of potential MTase inhibitors. For nsp14, we screened 239,000 molecules, leading to the identification of three hits A1-A3 showing N7-MTase inhibition rates greater than 60% under a concentration of 50 µM. For the SAM binding and nsp10-16 interface sites of nsp16, the screening of 210,000 and 237,000 molecules, respectively, from ZINC15 led to the discovery of three hit compounds B1-B3 exhibiting more than 45% of 2'-O-MTase inhibition under 50 µM. These six compounds with moderate MTase inhibitory activities could be used as novel candidates for the further development of anti-SARS-CoV-2 drugs.

High resolution mass spectrometry targeted analysis and suspect screening of pesticide residues in fruit samples and assessment of dietary exposure

Fruits consistently hold a prominent position in healthy dietary habits. Pesticides are used to manage plant diseases, achieve sustainable production, and maintain high food standards. This study utilized a comprehensive analytical technique that involved both targeted analysis and suspect screening. Analysis was conducted using Ultra-high-performance liquid chromatography coupled with hybrid Linear Trap Quadrupole (LTQ)/Orbitrap High Resolution Mass Spectrometry (HRMS) to examine pesticide levels in fruits. The matrices chosen comprised fruit commodities that are commonly consumed in Greece, including table grapes, apples, pears, citrus fruits, and strawberries. The QuEChERS approach was effectively validated for 30 specific pesticides. According to the method acceptance criteria established by SANTE, the QuEChERS method have shown exceptional efficiency in extracting the chosen pesticides, with recovery rates ranging from 70% to 120% in three concentration levels (10, 50, 100 μg kg−1). It also exhibited outstanding linearity, with an R2 more than 0.99. The method exhibited exceptional precision, with relative standard deviations (RSDs) below 20%. Additionally, the combined measurement uncertainty (MU%) was found to be acceptable, remaining below 50%The quantification limits were below 10 μg kg−1 for the majority of the analytes, satisfying the Maximum Residue Levels (MRLs) established by the European Commission. Following targeted analysis, a dietary risk assessment was performed, revealing that both acute and chronic hazard quotients (aHQ and cHQ), along with chronic hazard index (cHI) were below 1, which indicated that the studied commodities are safe for human consumption. In addition, a suspect screening workflow was developed based on an in-house database comprising 355 pesticides commonly applied to the relevant commodities and related transformation products (TPs). Overall, through suspect screening, twenty-two additional pesticides and TPs not included in the target list were identified. Hence, this approach is anticipated to function as proactive alert system guaranteeing the long-term viability of agricultural production.

Unravelling psychoactive substances and their metabolites and transformation products: High-Resolution Mass Spectrometry approaches for comprehensive target and suspect screening in wastewater

Untangling the consumption rates of psychiatric drugs and their metabolites/ transformation products-(TPs) through wastewater gains attention lately. However, the potential environmental impact caused by their release remains ambiguous. As it follows, the monitoring of this class of pharmaceuticals as well as the evaluation of their potential toxicity is a matter of high concern. In the light of the above, here, wastewater samples, were collected in a 1-year and a half sampling campaign (2020−2021) and were further subjected to solid phase extraction. A Q Exactive Focus Orbitrap mass analyzer was employed for the analysis of the samples. For the data curation, except of the monitoring of targets, a comprehensive suspect screening workflow was developed and slightly optimized based on a lab made HRMS database for the investigation of legally or illegally prescribed psychiatric drugs and their relevant metabolites/TPs in influents and effluents. Carbamazepine and amisulpride were quantified at the highest mean concentrations 243 and 225 ng/L respectively, in influents. In effluents, the highest mean concentrations were calculated for carbamazepine (180 ng/L) and venlafaxine (117 ng/L). The implementation of suspect screening approach enhanced the comprehensiveness of analysis by detecting 29 compounds not included in the target list. O-Desmethylvenlafaxine was the predominant metabolite in influents presenting a mean concentration equal to 87 ng/L while the same pattern was also noticed in effluents where the mean concentration was up to 91 ng/L. From the group of suspect compounds for which no analytical standards were available, the predominant compounds with detection frequency 100 % were norephedrine and codeine in influents while in effluents, oxazepam was detected in 81 % of the analyzed samples. Finally, in silico and mathematical tools were employed for the assessment of the risk posed to environmental systems. Most of the detected compounds present high risk in all trophic levels.

Development of a high throughput oxidation profiling strategy for monoclonal antibody products

Oxidation is one of the most common degradation pathways of biopharmaceutics, potentially leading to altered product stability, pharmacokinetics, reduced biological activity and/or an increased immunogenicity. However, it is often insufficiently assessed in early development stages, leaving potential molecule liabilities undiscovered. Aim of the present work was the development of a high throughput oxidation profiling strategy, applicable throughout various stages of biopharmaceutical development. The study demonstrates that the combination of multiple stress assays, including peroxide-based, visible light, and metal-catalyzed oxidation (MCO), enables a comprehensive understanding of a mAb's oxidation susceptibility. The most effective parameters to evaluate oxidation in a high-throughput screening workflow are aggregation, tryptophan oxidation and changes in the hydrophobicity profile of the Fc and Fab subunit measured via Size Exclusion Chromatography, Intrinsic Tryptophan Fluorescence Emission spectroscopy and Reversed-Phase Chromatography subunit analysis, respectively. This oxidation profiling approach is valuable tool to systematically characterize the oxidation susceptibility under relevant conditions, time effective and with minimal sample consumption.

Integration of Physiochemical Characterization Techniques in Toxicological Screening of Emerging Contaminants in Food and Environment.

The pervasive presence of emerging contaminants in food and the environment poses a grave threat to human health and ecological stability. Addressing this challenge necessitates a comprehensive approach that integrates physiochemical characterization techniques into toxicological screening protocols. This paper provides an extensive review of the methodologies and advancements in the amalgamation of various physiochemical characterization techniques, including chromatography, spectroscopy, and mass spectrometry, in toxicological screening for emerging contaminants. By synergistically employing these techniques, the identification, quantification, and toxicity assessment of contaminants are significantly enhanced, facilitating a thorough understanding of their implications for human health and environmental integrity. Through case studies and empirical evidence, this paper underscores the pivotal role of integrated physiochemical characterization techniques in ensuring the safety of food and the environment. By integrating these physiochemical characterization techniques into toxicological screening workflows, researchers can elucidate the presence of emerging contaminants, assess their bioavailability and bioaccumulation potential, and evaluate their toxicological profiles. Furthermore, the synergistic application of these techniques facilitates the identification of transformation products and metabolites, enhancing our understanding of contaminant fate and behavior in environmental matrices and food systems DOI: https://doi.org/10.52783/tjjpt.v45.i02.6483

Handling of problematic ion chromatograms with the Automated Target Screening (ATS) workflow for unsupervised analysis of high-resolution mass spectrometry data

Liquid chromatography (LC) or gas chromatography (GC) coupled to high-resolution mass spectrometry (HRMS) is a versatile analytical method for the analysis of thousands of chemical pollutants that can be found in environmental and biological samples. While the tools for handling such complex datasets have improved, there are still no fully automated workflows for targeted screening analysis. Here we present an R-based workflow that is able to cope with challenging data like noisy ion chromatograms, retention time shifts, and multiple peak patterns. The workflow can be applied to batches of HRMS data recorded after GC with electron ionization (GC-EI) and LC coupled to electrospray ionization in both negative and positive mode (LC-ESIneg/LC-ESIpos) to perform peak annotation and quantitation fully unsupervised. We used Orbitrap HRMS data of surface water extracts to compare the Automated Target Screening (ATS) workflow with data evaluations performed with the vendor software TraceFinder and the established semi-automated analysis workflow in the MZmine software. The ATS approach increased the overall evaluation performance of the peak annotation compared to the established MZmine module without the need for any post-hoc corrections. The overall accuracy increased from 0.80 to 0.86 (LC-ESIpos), from 0.77 to 0.83 (LC-ESIneg), and from 0.67 to 0.76 (GC-EI). The mean average percentage errors for quantification of ATS were around 30% compared to the manual quantification with TraceFinder. The ATS workflow enables time-efficient analysis of GC- and LC-HRMS data and accelerates and improves the applicability of target screening in studies with a large number of analytes and sample sizes without the need for manual intervention.Graphical

A phage-displayed disulfide constrained peptide discovery platform yields novel human plasma protein binders.

Disulfide constrained peptides (DCPs) show great potential as templates for drug discovery. They are characterized by conserved cysteine residues that form intramolecular disulfide bonds. Taking advantage of phage display technology, we designed and generated twenty-six DCP phage libraries with enriched molecular diversity to enable the discovery of ligands against disease-causing proteins of interest. The libraries were designed based on five DCP scaffolds, namely Momordica charantia 1 (Mch1), gurmarin, Asteropsin-A, antimicrobial peptide-1 (AMP-1), and potato carboxypeptidase inhibitor (CPI). We also report optimized workflows for screening and producing synthetic and recombinant DCPs. Examples of novel DCP binders identified against various protein targets are presented, including human IgG Fc, serum albumin, vascular endothelial growth factor-A (VEGF-A) and platelet-derived growth factor (PDGF). We identified DCPs against human IgG Fc and serum albumin with sub-micromolar affinity from primary panning campaigns, providing alternative tools for potential half-life extension of peptides and small protein therapeutics. Overall, the molecular diversity of the DCP scaffolds included in the designed libraries, coupled with their distinct biochemical and biophysical properties, enables efficient and robust identification of de novo binders to drug targets of therapeutic relevance.

An Efficient Workflow for Quality Control Marker Screening and Metabolite Discovery in Dietary Herbs by LC-Orbitrap-MS/MS and Chemometric Methods: A Case Study of Chrysanthemum Flowers.

LC-MS is widely utilized in identifying and tracing plant-derived food varieties but quality control markers screening and accurate identification remain challenging. The adulteration and confusion of Chrysanthemum flowers highlight the need for robust quality control markers. This study established an efficient workflow by integrating UHPLC-Orbitrap-MS/MS with Compound Discoverer and chemometrics. This workflow enabled the systematic screening of 21 markers from 10,540 molecular features, which effectively discriminated Chrysanthemum flowers of different species and cultivars. The workflow incorporated targeted and untargeted methods by employing diagnostic product ions, fragmentation patterns, mzCloud, mzVault, and in-house databases to identify 206 compounds in the flowers, including 17 screened markers. This approach improved identification accuracy by reducing false positives, eliminating in-source fragmentation interference, and incorporating partial verification utilizing our established compound bank. Practically, this workflow can be instrumental in quality control, geolocation determination, and varietal tracing of Chrysanthemum flowers, offering prospective use in other plant-derived foods.

Abstract 6787: Evaluation of CAR-T cytotoxicity in solid tumors: A screening workflow using 3D patient-derived tumoroids

Abstract Introduction: Over the last decade, chimeric antigen receptor T cell (CAR-T)-based immunotherapy has achieved unprecedented clinical benefits for the treatment of hematological malignancies. However, application of CAR-T therapy to solid tumors remains challenging, in part due to tumor antigen heterogeneity and microenvironmental complexity present in these tumors. Therefore, selecting physiologically-relevant models is critical for validation of the on-target efficacy and off-target effect of CAR-T therapy. Emerging 3D patient-derived tumoroid models better recapitulate the morphological organization, mutational status, and gene expression levels of patient tumors. Hereby, we propose a screening platform to evaluate mesothelin (MSLN)-targeted CAR-T therapy for solid tumors using patient-derived tumoroids. Methods: T cells were isolated from peripheral blood mononuclear cells of healthy human donors. Meso3 (region III of MSLN) or CD19 CARs (served as control) were knocked-in (KI) to activated T cells using electroporation-based CRISPR/Cas9 system followed by CAR Cassette containing adeno-associated virus (AAV) transduction. T-cell receptor (TCR) knockout (KO) and CAR-KI efficiency were validated by flow cytometry. Patient-derived tumoroids with high and low MSLN expression were co-cultured with various effector-to-target ratios of Meso3 CAR, CD19 CAR and Control (TCR KO without CAR KI) T cells. Cytotoxicity was evaluated by caspase-based live cell imaging. Key cytokine secretion was measured using a multiplexing platform 2-3 days post co-culture. Results: T-cell electroporation of CRISPR/Cas9 yielded a high KO efficiency (&amp;gt;90%) of TCR as well as high AAV-mediated CAR cassette-KI efficiency (&amp;gt;70%). The killing efficiency of Meso3 CAR-T cells with different effector to target ratios was successfully captured in a ratio-dependent manner via live cell imaging and analysis platform in the MSLN-high tumoroids, while minimum killing was observed in MSLN-low tumoroids. As expected, control and CD19 CAR-T cells showed no killing towards MSLN-high or -low tumoroids, which do not express CD19. Moreover, the observed killing ability correlated with secretion of cytokines associated with T cell-mediated cytotoxicity. Conclusion: These findings demonstrated the ability of 3D patient-derived models as a screening platform for validations of CAR-T cell therapy in vitro. This platform has potential advantages over commonly used impedance-based and flow cytometry-based killing assay since it better captures the 3D architecture and microenvironment of the tumor origin and allows real-time quantification. With the ability of accurately detecting on and off-target killing, quick turn-around time, and cost-effectiveness compared to in vivo systems, this platform allows for high-throughput screening workflows for CAR-T cell therapies. Citation Format: Xiaoyu Yang, Maryam Mafreshi, Garrett Wong, Vivek Chandra, Colin Paul, Chris Yankaskas, Brittany Balhouse, Jason Sharp, Matt Dallas, Erik Willems, David Kuninger. Evaluation of CAR-T cytotoxicity in solid tumors: A screening workflow using 3D patient-derived tumoroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6787.

Abstract 4919: AI-enabled hit selection of drug screening on human pancreatic cancer organoids

Abstract Cancer remains one of the leading causes of death in the 21st century. Despite the latest advances in oncology, most cancer patients lack tailored therapeutic approaches with lasting benefit. Measuring the impact of anticancer compounds and their combinations is only possible on ex vivo assays. To this end, patient-derived organoids (PDOs) have been proposed as viable and efficient models for ex vivo testing. PDOs show long-term expansion potential while retaining tumor histopathology as well as cancer gene mutations. However, the translation of organoids in screening applications has so far been hampered by the lack of homogeneity and difficulties in handling and automation. Moreover, organoids are typically randomly distributed across the culture which complicates imaging and images analyses. To overcome these challenges, we set up a compound screening workflow with PDOs using Gri3D platform, comprising plates with micro-cavities suitable for high-throughput and reproducible organoid culture. Based on a standard 96 microtiter plate, each well contains a microwell array patterned in a cell repellent hydrogel. On Gri3D®, organoids are robustly generated in the microwells and are located in the same imaging plane. This greatly facilitates quantitative analyses in high content image-based screens. Furthermore, the pipetting port enables automation of cell seeding, media exchange and compound incubation with liquid-handlers, thus increasing assay reproducibility. In the presented work, we exposed human pancreatic cancer PDOs to a panel of anti-cancer compounds at different doses and followed their response to the drugs using viability dyes Calcein AM (live stain) and Ethidium Homodimer-1 (dead stain) with high-content confocal imaging. Using an AI-based approach, we efficiently detected each single organoid and extracted phenotypic features from all three channels (TL, live stain and dead stain) which correlate with cytotoxicity. The extracted features (more than 100) were first dimensionally reduced to 3 components using either PCA or UMAP, the treatments were then visualized in 3D scatter plots, ranked and clustered using machine learning. The data suggests that the compound treatment Palbociclib 50uM has significant cytotoxicity effects similar to the positive control, which is consistent with the traditional live/dead analysis. The AI approach demonstrates feasibility to perform drug screening in a robust and un-biased data analysis approach. Citation Format: Zhisong Tong, Angeline Lim, Marine Meyer, Maria Clapes, Oksana Sirenko, Nathalie Brandenberg. AI-enabled hit selection of drug screening on human pancreatic cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4919.