Theses and Dissertations School of Pharmacy
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Full text for dissertations and theses included in this collection dates back to 2011. For older dissertations, check the library’s catalog CatalogUSMAI or Dissertations and Theses database.
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Development of an In-Cell Footprinting Method Coupled with MS for the Study of Proteins in Three-Dimensional Cancer ModelsFast photochemical oxidation of proteins (FPOP) is a powerful, mass spectrometry (MS)-based, biophysical method used to probe protein structure, interactions, and conformations. FPOP was recently extended into cells (IC-FPOP) and can modify thousands of proteins in a single experiment, enabling proteome-wide structural biology. Although IC-FPOP can reveal critical structural information in 2D cell culture, the conditions do not emulate an in-vivo environment. To address this, we propose to develop a mass spectrometry-based protein footprinting method that assesses the varying protein heterogeneity in 3D cell culture; Spheroid-FPOP. IC-FPOP on intact spheroids was performed using a patented PIXY platform which brought automation to IC-FPOP. Spheroid-FPOP coupled with serial trypsinization to obtain spatial resolution, revealed modifications in three distinct spheroid regions; the outer inner and core. Native oncogenic pathways were interrogated through this study showing its value in disease pathogenesis and treatment. Though progressive for FPOP, the extension into 3D model systems generated three times the samples and data compared to typical IC- or IV-FPOP experiments. This shed light to FPOP workflow limitations. The research herein responds to those challenges by developing an automated sample preparation workflow by coupling a sample handling robot with Thermo’s sample preparation kit. These modifications robustly improve the workflow by significantly reducing the manual labor, execution time, and variability of samples processed and data acquired. After workflow optimization FPOP, we apply the optimized method more complex biological sample. In our case, 3D bioprinted Huh-7 liver organoids were generated for IC-FPOP. To obtain spatial resolution within the model, we integrated cryosectioning of the top, middle and bottom layers of the organoid. Peptide level analysis revealed differences in the extent of modification for peptides identified in each region of the organoid, which confirms the acquisition of structural information. However further optimization was required to increase proteome depth. By coupling the organoid model with IC-FPOP we aim further validate its implementation for complex proteome-wide structural studies. In all, this research is focused on advancing the applications and processing workflows for IC-FPOP.
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The Effect of Medication Information Delivery Format on Cognitive Load and Knowledge Retention of Informal CaregiversInformal caregivers (IFCs) are tasked with many responsibilities in patient care, including medication management. Many IFCs feel ill-prepared for this responsibility, and it is incumbent on health care professionals to provide education and ensure IFCs competence in medication management. One common strategy is to provide a medication information leaflet to the IFC to prepare them for this role. Designing medication information leaflets using sound educational principles, such as an infographic designed according to the cognitive theory of multimedia learning (CTML), may optimize knowledge retention and decrease cognitive load for IFCs. The purpose of this randomized, experimental study was to investigate the impact of medication information delivery format on immediate retention of medication information and cognitive load of IFCs of patients with a serious illness. Using purposive sampling, 120 IFCs who have provided some element of medication management for patients diagnosed with a serious illness, including patients who may have been receiving hospice or palliative care services were recruited. Study participants were randomly assigned in either the experimental group or the control group. The experimental group viewed an infographic on the medication hydromorphone, followed by a knowledge quiz, and a self-assessment of cognitive load. This was followed by a second infographic on hydroxyzine, the quiz, and cognitive load assessment. The control group went through the same steps but viewed a text-only medication leaflet. Statistical analyses included descriptive statistics, independent samples t-test, one-way analysis of variance, and one-way multivariate analysis of variance. Statistically significantly higher quiz scores were observed among those who viewed the infographics than those who viewed text-only medication leaflets, indicating better immediate knowledge retention of medication information. Those who viewed the infographic also had statistically significantly lower intrinsic and extraneous cognitive load, and higher germane cognitive load. These findings are consistent with the hypothesis that infographics prepared using the CTML result in better and more efficient learning. Limitations of this research include use of nonprobability sampling, examining only two medications that are commonly used in serious illness, and lack of systematic randomization. Additional research is needed to continue determining best practices for instructing and supporting IFCs in medication management.
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The Effects of Graded Versus Ungraded Individual Readiness Assurance Tests on Pharmacy Students’ Assessment Performance and Achievement Goals in a Team-Based Learning ClassroomIndividual readiness assurance tests (iRATs) are frequently graded in team-based learning (TBL) classrooms, with the goal of incentivizing individual pre-class preparation. The purpose of this study was to determine whether shifting to an ungraded iRAT process affects student preparation and learning, as measured using assessment scores, and whether this is accompanied by a change in achievement goals. Using a crossover design in a required second-year Doctor of Pharmacy pharmacotherapy course, students were assigned to one of two iRAT grading sequences: graded/ungraded (G/UG) or ungraded/graded (UG/G). In the G condition iRATs were graded based on correctness and in the UG condition based on completion. Each period consisted of four iRATs and one examination. Students completed the Achievement Goal Questionnaire at the conclusion of each period. A one-way repeated measures multivariate analysis of variance (MANOVA) was used to test within-subject differences of mean iRAT and examination scores across grading conditions. A separate one-way repeated measures MANOVA was used to analyze differences in achievement goal scores. A total of 91 doctor of pharmacy students were included in the study. There was a statistically significant main effect for iRAT grading condition on assessment scores, F(2,88) = 3.851, Wilks’ Λ = .992, p = .025. Univariate testing using one-way analysis of variance with Bonferroni correction demonstrated a significant difference only in iRAT scores, with the mean score higher in the G condition (72.51% versus 67.99%; p = .011). Examination scores were similar in the G and UG conditions (81.07% versus 80.32%, p = .397). There was not a statistically significant difference in achievement goals based on iRAT grading condition, F(4,85) = 1.109, η2 =.050, p = .358. In conclusion, a modest reduction in iRAT performance was observed when shifting from a graded to ungraded iRAT; however, this had no effect on examination performance. Achievement goals were unaffected by the change in iRAT grading condition.
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Under-ascertainment and underreporting of adverse events in clinical trialsIntroduction: Clinical trials are widely regarded as the “gold standard” for evaluating different interventions’ adverse events (AEs). However, numerous cases have suggested that AEs are underreported in clinical trials due to inadequate data collection methodology and inconsistent reporting criteria. This study examined 1) the AE ascertainment methodologies used for the marketing approval of new drugs and 2) the diversity and consistency of AE reporting criteria used in trial reports. Methods: We screened drugs approved by the US Food and Drug Administration (FDA) in 2018-2019 and collected publicly available trial documents for all pivotal trials. From these documents, we examined ascertainment methods of adverse events of special interest (AESIs) and newly signaled post-marketing AEs. We also assessed the association between trial characteristics and the AE ascertainment approach using binary logistic regression. Additionally, from the obtained reports, we examined the characteristics of reported AEs and the usage of AE reporting criteria. Then, we assessed the consistency of the number of reported AE types and reporting criteria used across trial publications and other important sources of trial results. Results: 322 AESIs were identified from trial documents for 64 trials reporting 31 drugs approved in 2018-2019. 71% were systematically ascertained, mainly using diagnostic measurement tools and laboratory assessments. 10% were non-systematically ascertained. The ascertainment method of 19% was unclear. The regression analysis did not reveal statistically significant associations between trial characteristics and the use of a systematic ascertainment approach for AESIs. Of the six examined newly signaled post-marketing AEs, one was systematically ascertained. The examined sources utilized various criteria to report both serious and non-serious AEs. Frequency criteria were the most commonly used AE reporting criteria. Furthermore, the examined sources inconsistently reported serious AEs and inconsistently utilized reporting criteria. Conclusions: We were unable to identify the ascertainment methodology for some AEs, even with access to underlying trial documents. Additionally, trial reports applied various criteria that potentially resulted in only a subset of AEs recorded during the trial being reported. The study suggests room for improvement in AE data collection and reporting to aid unbiased harm-benefit assessments of study interventions and informed treatment decisions.
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Determination of Harmful and Potentially Harmful Constituents in E-cigarettes, E-liquids, and Generated AerosolsElectronic nicotine delivery systems (ENDS), including e-cigarettes, are battery-operated devices which are vaped with the intent of delivering nicotine to the user. As these devices have become more prevalent on the market, so has the need to quantify different harmful and potentially harmful constituents (HPHCs) from those e-cigarettes. The FDA CTP has an established list of HPHCs, but my focus in collaboration with other labs was metals and volatile organic compounds (VOCs). Throughout this work, both the unaerosolized e-liquids and generated aerosols were characterized for metals and VOCs. Commercial disposable e-cigarettes were purchased, their e-liquids were extracted, and those e-liquids were analyzed for metal content. Across different batches and lots of the same products, metal levels varied greatly. An early focus of the work was determining where the metals in the e-liquid come from, which necessitated x-raying and deconstructing products to determine where e-liquid contacts materials of construction. To further inform on the metals that may be present in e-cigarette aerosols, we developed and constructed an ENDS aerosolization machine to vape e-cigarette products. The ENDS aerosolization machine is sufficiently adaptable for use in aerosolizing commercially available ENDS products, as well as refillable products, with the aerosol collectable in a variety of manners to permit analysis of metal content, VOCs, and cellular effects. Using this machine, we have determined that metals, such as copper, chromium, nickel, and lead, are transferred from e-liquids into aerosols at different efficiencies depending on the e-liquid carrier vehicle and the type of metal in the starting e-liquid. Similarly, we have developed an effective approach for the characterization of VOCs produced by aerosolization. This necessitated capturing volatile and non-volatile components of the aerosol. Our methodology uses real-time derivatization of the VOCs, namely formaldehyde, acetaldehyde, acrolein, acetone, propionaldehyde, crotonaldehyde and 2-butanone, followed by extraction, and analysis via mass spectrometry. From this body of research, we have developed validated methods to analyze unaerosolized e-liquids and generated aerosols from e-cigarettes in order to better understand the harmful and potentially harmful constituents within.
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A Cost-Effectiveness Analysis Model Framework For Treatments Of Early-Stage Huntington’s Disease Patients In The United StatesHuntington's disease (HD) is a rare neurodegenerative condition caused by a mutation in the huntingtin gene. The emergence of drugs such as Tominersen and AMT-130, which have the potential to treat HD highlights the importance of evaluating their cost-effectiveness. This study aims to fill this gap and evaluate the incremental cost-effectiveness of these treatments compared with the current standard of care for HD. A health state transition Markov model was developed to estimate the costs and benefits of each treatment over a lifetime time horizon from a societal perspective. Our findings showed that Tominersen and AMT-130 were associated with higher costs but also provided greater benefits than the standard of care. AMT-130 was found to be a cost-effective option compared to the standard of care and Tominersen, considering the willingness to pay threshold. This study provides valuable insights into the economic impact of HD which can inform healthcare policy and treatment decisions.
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Evaluation of Evidence in Economic Models Used for Decision-Making: Development of the Data Inputs in Value Economic Evaluations (DIVEE) ChecklistBackground: Value or health technology assessment (V/HTA) is a structured approach for evaluating health interventions to inform coverage and reimbursement decisions. V/HTAs often include model-based economic evaluations (economic models) to gauge economic value. Economic models formally examine costs and consequences of interventions versus alternatives. Data sources and inputs (DSIs) used to populate economic models influence the findings, and inappropriate DSIs can result in misleading economic value appraisals. Thus, it is important health care decision-makers (HCDMs) assess the appropriateness of DSIs used to populate key economic-model parameters to understand whether the model is suitable for use in their decision-making. But many HCDMs lack economic training and may be ill-prepared for assessing DSIs. A tool is needed to help HCDMs efficiently and confidently assess DSIs used in economic models to support informed decision-making. Objective: Create a user-friendly checklist that supports HCDMs in assessing, in a standardized, clear, and consistent manner, the appropriateness of DSIs used in model-based V/HTA economic evaluations. Methods: A checklist was developed in three stages: 1. Need for a checklist was established through assessment of DSIs used in published V/HTA economic model reports and a search for existing guidance on identifying, selecting, or reporting DSIs for economic evaluations. 2. Stakeholder perspectives on evaluation of DSIs were obtained through interviews and applied, along with findings from the previous stage, to create, test, and refine a checklist. 3. HCDM views on the new checklist and its potential use in decision-making were elicited through case reviews and interviews. Findings: The Data Inputs in Value Economic Evaluations (DIVEE) Checklist is comprised of eleven items organized into four domains (transparency, relevance, credibility, and model robustness). HCDMs report the Checklist to be comprehensive, easy to understand, and a useful aid for evaluating economic models. HCDMs support use of the Checklist, but recognize barriers exist to full adoption in current decision-making processes. Conclusions: The DIVEE Checklist is a user-friendly decision-maker aid that facilitates transparent, systematic, and consistent assessment of DSIs used in economic models and, ultimately, better-informed coverage and reimbursement decisions. Further testing in larger groups of HCDMs is needed along with training and educational support.
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Regulation of retinoid homeostasis by cellular retinol-binding protein, type 1Retinoic acid (RA) is the main active metabolite of Vitamin A, an essential diet-derived nutrient. RA signaling regulates cell differentiation, proliferation and apoptosis. RA levels are tightly regulated throughout the body via the expression and activity of catabolic and biosynthetic enzymes, and chaperone proteins, including cellular retinol binding protein, type 1 (CRBP1). CRBP1 binds to retinol and retinal, protecting them from non-specific oxidation, and facilitating their delivery to the appropriate enzymes for RA biosynthesis. CRBP1 has been shown to be decreased in disease states that display dysfunctional proliferation and differentiation, including cancers. Reduction of CRBP1 levels directly correlates with reduction in RA and restoration of CRBP1 expression has been shown to increase RA levels and positively impact RA-dependent outcomes. Research on the role of CRBP1 in disease has been limited because of its low abundance and poor immunogenicity. We have developed a targeted, bottom-up proteomics approach for absolute CRBP1 quantitation in complex biological matrices and have utilized this assay to answer important biological questions regarding the role of CRBP1 in regulating RA and RA-mediated signaling. While proper RA homeostasis is essential for biological processes throughout the body, the research in this thesis has focused on its role in the small intestine, heart, and lung. In the small intestine, RA plays an essential role in regulating the gut immune response. In instances of cellular stress in the intestine, RA levels are decreased. We have employed our CRBP1 quantitative assay, along with retinoid metabolite quantitation and quantitative gene expression, to systemically probe the mechanism of disrupted retinoid signaling in intestinal disease via an in vitro model of the small intestine. Proper RA levels are also necessary for growth and development, including heart and lung morphogenesis, and have also been shown to be disrupted in many diseases, such as heart failure and lung cancer. Using a global CRBP1 knock-out mouse model, we have also explored the in vivo effect of loss of CRBP1 on retinoid signaling via multi-omics analysis. Together these studies will help further our understanding of the mechanisms and impact of CRBP1 loss in diseases of the intestine, heart, and lungs.
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Method Optimization of a New Automated Platform for Proteome-Wide Structural BiologyProteins adopt different higher-order structures (HOS) to enable their unique biological functions. Understanding the complexities of protein HOS and dynamics requires integrated approaches, including mass spectrometry (MS), which has evolved into an indispensable tool for proteomics research. One approach readily integrated with MS is protein footprinting. In-cell fast photochemical oxidation of proteins (IC-FPOP) is a protein footprinting method that utilizes hydroxyl radicals to oxidatively modify the side chains of solvent accessible amino acids. Liquid chromatography coupled to mass spectrometry is used to both identify modified amino acids and quantify the levels of labeling. Owing to solvent accessibility changing upon binding or changes in conformations, IC-FPOP can be used to identify protein-ligand and protein-protein interaction sites and regions of conformational change. The method can modify thousands of proteins in a single experiment leading to structural information across the proteome. IC-FPOP modifies proteins on the microsecond timescale making the method suitable to study fast biological processes. However, the single cell flow system developed for initial IC-FPOP experiments had temporal limitations motivating the design for a higher throughput platform. My research describes the development of a new platform for IC-FPOP entitled Platform Incubator with XY Movement (PIXY). PIXY permits IC-FPOP to occur in a sterile system using a temperature-controlled stage top incubator, peristaltic pumps for chemical transport, mirrors for laser beam guidance, and a mobile stage for XY movement. Automated communication amongst the entire PIXY system was made possible using LabVIEW software which allows the analysis of one sample in only 20 seconds. Well over 2000 proteins in HEK cells can be oxidatively modified by IC-FPOP in PIXY. This allows for a greater amount of structural information to be obtained. The capabilities of this high throughput platform permit other cell based experimental applications including fluorescent imaging and time-dependent solution transfer. PIXY’s ability to accommodate automated time points and subsequent changes over time make it a powerful tool for probing protein biochemistry in the native cellular environment.
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Effect of Excipients on the Performance of Spray-dried Amorphous Solid Dispersion (ASD) in TabletsAmorphous solid dispersions (ASD) are a proven method of improving the solubility and bioavailability of poorly soluble drugs. Immediate-release tablets are frequently used as the final dosage form for ASDs. The selection of polymers and excipients is critical for the manufacturability and bioavailability of ASD tablets. ASDs were prepared by spray drying; ASD tablets were then generated using a compaction simulator. We first studied the impact of polymer types and drug-polymer ratios on bulk powder properties, morphologies, and compaction behaviors of ASDs. Itraconazole (ITZ) and indomethacin (IND) were used as model drugs, and two polymers were used: hydroxypropyl methylcellulose acetate succinate (HPMCAS) and polyvinylpyrrolidone (PVP). The results indicated that the tabletability increased with decreasing drug loadings, except for ITZ-PVP ASDs. Multivariate analysis revealed that particle surface area was the most significant factor influencing the tensile strength of ASD tablets. Secondly, the contact angle and surface free energy of ITZ ASD tablets containing different HPMCAS grades and drug loadings were evaluated using a Drop Shape Analyzer. A larger contact angle was correlated with a higher dissolution rate, suggesting that contact angle could be a high throughput tool for screening ASDs formulations. Lastly, we investigated the influence of fillers such as microcrystalline cellulose, lactose, mannitol, and starch on drug release and stability of ITZ-HPMCAS ASDs. We discovered that the dissolution performance and physical stability of tablets were influenced by the choice of filler. The results and inferences drawn from this research will provide valuable insights into ASD formulation development downstream tablet production.
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The Regulatory Role of the Cytoplasmic Heme Binding Protein PhuS in Pseudomonas aeruginosaPseudomonas aeruginosa is an opportunistic pathogen that requires iron for its survival and virulence. P. aeruginosa can acquire iron from heme via the nonredundant heme assimilation system and Pseudomonas heme uptake (Phu) systems. Heme transported by either system is eventually sequestered by the cytoplasmic protein PhuS, which specifically shuttles heme to the iron-regulated heme oxygenase HemO. Furthermore, a conformational rearrangement upon heme binding is necessary for the protein-protein interaction with HemO and a ligand switch between the heme coordinating ligands (His209 and His212) was proposed ot be required for translocation of heme to HemO. As the PhuS homolog ShuS from Shigella dysenteriae was observed to bind DNA as a function of its heme status, we sought to further determine if PhuS, in addition to its role in regulating heme flux through HemO, functions as a DNA-binding protein. Herein, through a combination of chromatin immunoprecipation-PCR, EMSA, and fluorescence anisotropy, we show that apo-PhuS but not holo-PhuS binds upstream of the tandem iron- responsive sRNAs prrF1, F2. Previous studies have shown the PrrF sRNAs are required for sparing iron for essential proteins during iron starvation. Furthermore, under certain conditions, a heme-dependent read through of the prrF1 terminator yields the longer PrrH transcript. Quantitative PCR analysis of P. aeruginosa WT and ΔphuS strains shows that loss of PhuS abrogates the heme-dependent regulation of PrrF and PrrH levels. Taken together, our data show that PhuS, in addition to its role in extracellular heme metabolism, can also modulate PrrF and PrrH levels in response to heme. The dual function of PhuS is central to integrating extracellular heme utilization into the PrrF/PrrH sRNA regulatory network that is critical for P. aeruginosa adaptation and virulence within the host. Additional biophysical, genetic and metabolic approaches have been conducted to determine the role of the PhuS heme coordinating residues regulate the mutual exclusivity of heme and DNA binding and the resulting effects on PrrF and PrrH expression.
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Development of the Lennard-Jones Parameters for the Polarizable Classical Drude Oscillator Force FieldThe quality of Force Fields (FF) determines accuracy of observations made through molecular simulations. Accuracy of such simulations may be achieved by explicit inclusion of electronic polarization, such as via the implementation of the Drude harmonic oscillator, as in Drude Polarizable FF. Although the Drude Polarizable FF spans a large range of biomolecules including proteins, nucleic acids, lipids and carbohydrates, an expansion of its small molecule FF is essential, given the vastness of chemical space. Such an expansion must be accompanied by the optimization of van der Waals (vdW) interactions, in the context of the Lennard-Jones (LJ) formalism. Optimization of the LJ parameters is a multivariate and multi-objective problem and is one of the most challenging aspects of FF optimization. Through this thesis, we have developed a method that utilizes the sampling power of Latin Hypercube Design (LHD) and learning abilities of Deep Neural Network (DNN) to overcome some of these challenges. The model is trained on empirical pure solvent/crystal properties of a selected set of “training set” compounds, where the final selection is based on the quality of both gas phase and condensed phase properties. The optimized LJ parameters are validated for transferability on “validation set” compounds, while their ability to reproduce other experimental thermodynamic properties such as hydration free energy and dielectric constants, are also verified. Chapter 1 of this thesis presents an introduction to underlying concepts of FFs, with a major focus on polarizable FFs. Chapter 2 details development of the method, using four different chemical classes, i.e., alkenes, 3 and 4 membered rings and nitriles. Chapter 3 updates the method developed in chapter 2, addressing the challenge of parameter correlation. Chapter 4 applies the updated method to another chemical class (alkynes), while Chapter 5 concludes the thesis and is a discussion of the challenges associated with empirical FF development with a focus on LJ parameters. Overall, the method developed through this thesis addresses the most challenging aspect of FF development, i.e., LJ parameter development, implemented in a manner that could be utilized in context of development of both additive and polarizable FF.
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Design, Development, and Characterization of Gallium (III) Salophen Metallotherapeutics Targeting Heme Sensing and Iron Acquisition Pathways in Pseudomonas aeruginosaThe development of new antibiotics is outpaced by the rise in multi-drug resistant (MDR) bacteria, creating a global health problem. Pseudomonas aeruginosa, one such bacterium, is labeled as a “critical priority” pathogen by the WHO for its resistance to treatment and prevalence in hospital-acquired infections and immunocompromised patients where it is often life threatening. Adding to this problem, most new discoveries are derivatives of existing antibiotic classes rather than new strategies. Newer approaches targeting bacterial pathways critical to infection but not survival outside the host are expected to exert less selective pressure and slow resistance onset. One such strategy is interfering with bacterial iron uptake and utilization, as iron is a key micronutrient with several iron-regulated virulence traits used to counter iron-sequestering defense mechanisms of the host. P. aeruginosa can shift between the acquisition of labile iron stores and the more abundant heme-bound iron at various stages of infection, so inhibitors targeting these pathways must account for this adaptability. One such approach to targeting iron utilization in several forms is the use of gallium, which mimics ferric iron in ionic size and charge but cannot undergo critical redox processes, thus causing toxicity in the bacteria that acquire it under the guise of iron. This work describes the synthesis and characterization of Gallium Salophen (GaSal) and subsequent analogs targeting heme and iron acquisition pathways in P. aeruginosa. In this characterization, GaSal binds to a hemophore, HasAp, secreted by P. aeruginosa, and inhibits an extra-cytoplasmic function (ECF) signaling cascade with the outer-membrane receptor HasR, which is critical for sensing and adapting to host heme levels. GaSal is simultaneously a substrate for uptake, independent of its effect on HasAp. Using a combination of cell-based assays as well as in vitro target characterization and finally preliminary animal infection studies, GaSal and subsequent derivatives are shown to be promising new developments targeting several points in the iron uptake and utilization pathways of P. aeruginosa. Continued developments aim to retain such activity and include several routes towards further optimization and development as a therapeutic.
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Impact of Undertreatment of Depression on Suicide and Suicide Attempt among Children and Adolescents: A Simulation Study with Microsimulation and Agent-Based ModelsBackground: Depression is a strong risk factor for suicide, but undertreatment of depression is common among children and adolescents. The impact of undertreatment of depression on suicidal behaviors in this population is largely unknown due to the limitations of conventional data sources and methods. This dissertation research aims to overcome these challenges by using simulation models to answer two questions: 1) Is undertreatment of depression associated with increased risk of suicidal behaviors? 2) Do interventions that reduce undertreatment of depression lower the risk of suicidal behaviors? Methods: A microsimulation model simulated the 1-year suicide rate and suicide attempt risk with 12-, 36-, 52-week antidepressant treatment and no treatment in children and adolescents with depression. Modified Poisson regression estimated the suicide rate ratios and suicide attempt risk ratios for 12-, 36- and 52-week treatment compared with no treatment. An agent-based model simulated the potential impact of the following interventions in preventing suicide and suicide attempt in a synthetic population of children and adolescents: 1) depression screening (i.e. reducing untreated depression); 2) reducing attrition during depression treatment (i.e., increasing the proportion who complete the first 12 weeks of treatment); 3) suicide intervention (i.e., screen and treat individuals who need suicide care) among depressed individuals; 4) universal suicide intervention in medical settings. Results: Compared with no treatment, 12-, 36- and 52-week antidepressant treatment was significantly associated with decreased suicide rate and risk of suicide attempt. Depression screening could reduce the risk of suicide attempt (-0.64% (95% Credible Interval (CI): -1.13%, -0.11%)) only when 80% untreated depression was reduced. Universal suicide intervention showed a significant decrease in the risk of suicide attempt, which increased with the screened proportion (20%: -0.68% (95% CI: -0.87%, -0.55%), 50%: -1.47% (95% CI: -1.61%, -1.77%), 80%: -2.89% (95% CI: -4.57%, -2.31%). The other interventions did not show a significant effect in reducing the risk of suicide attempt in the population. Conclusion: Antidepressant treatment for at least 12 weeks may reduce risk of suicidal behaviors. Universal suicide intervention in medical care settings may be more effective in reducing suicidal behaviors compared with interventions that reduce undertreatment of depression.
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The Role of CAR and Nrf2 Dual Activation in doxorubicin/cyclophosphamide-based treatment of triple negative breast cancerTriple negative breast cancer (TNBC) affects 10-20% of all breast cancer cases and is associated with suboptimal outcomes due to drug resistance and/or intolerable side effects. The absence of targetable sites leaves cytotoxic chemotherapy the standard of care. Cyclophosphamide (CPA) and doxorubicin (DOX) are among the most used chemotherapeutic agents for TNBC. CPA, an alkylating prodrug, requires hepatic metabolic conversion to the rate-limiting metabolite, 4-hydroxy-cyclophosphamide (4-OH-CPA), primarily via cytochrome P450 (CYP) 2B6. Additionally, a portion of CPA is metabolized by CYP3A4 leading to a neurotoxic byproduct, chloroacetaldehyde, and an inactive byproduct, dechloroethyl-CPA. The constitutive androstane receptor (CAR, NR1I3), a nuclear receptor, regulates the expression of CYP2B6. Therefore, activation of CAR leads to preferential induction of CYP2B6 and subsequent bioactivation of CPA. On the other hand, DOX is often associated with dose-limiting cardiotoxicity. Mounting evidence suggests that this cardiotoxicity is in part attributed to the production of oxidative stress. It has been demonstrated that the activation of the nuclear factor erythroid 2-related factor (Nrf2) acts as a mediator in the protection against DOX-induced cardiotoxicity. Nrf2 regulates various antioxidant proteins and genes, such as heme-oxygenase 1 (HO-1), by binding to cis-acting antioxidant response elements in the promoter region of target genes, protecting against oxidative stress and inflammation. Our hypothesis was that dual activation of CAR and Nrf2 enhances the bioactivation of CPA while reducing DOX-mediated cardiotoxicity and improving the efficacy:toxicity ratio of CPA/DOX-based treatment for TNBC. CN06 was identified as a novel CAR and Nrf2 dual activator via high throughput screening and a chemical modification approach. Utilizing a multicellular co-culture model incorporating human primary hepatocytes, TNBC cells, and cardiomyocytes, we demonstrated that CN06 increased CPA/DOX-mediated TNBC cell death via CAR-dependent CYP2B6 induction and subsequent conversion of CPA to its active metabolite 4-hydroxy-CPA, while protecting against DOX-induced cardiotoxicity by selectively activating Nrf2-antioxidant signaling in cardiomyocytes but not in TNBC cells. Overall, these results indicate CAR and Nrf2 as a promising therapeutic strategy to improve the therapeutic index of CPA/DOX in the treatment of TNBC.
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Biorelevant In Vitro Dissolution Models to Evaluate Poorly Soluble DrugsBiorelevant media have been devised to mimic the composition of fluids present in the stomach and intestine in fasted and fed states. They are increasingly being used in pharmaceutical product development and to predict in vivo drug dissolution. Since biorelevant media are more complex, their fabrication has been described as challenging and much remains to be understood about the mechanisms by which they are able to enhance dissolution of poorly soluble drugs. The first aim of this work was to assess the repeatability and reproducibility of current biorelevant media and determine the sources of variability when biorelevant media are used to perform dissolution across different study conditions for two model poorly soluble drugs (i.e., ibuprofen and ketoconazole). The effect of volume on small-volume dissolution using biorelevant media was also predicted. Results indicated favorable interday repeatability, favorable interanalyst repeatability, and favorable interlaboratory reproducibility. Commercial media showed greater interlaboratory reproducibility than “from scratch” media. From a nested and then crossed statistical analysis of variance (ANOVA), the rank-order importance of sources of variation overall were location > operator (nested in location) > day > fabrication method > residual. An algorithm to predict the effect of volume on biorelevant media dissolution in high, intermediate, and low solubility scenarios proved to be accurate in 13 of 16 cases. The second aim of this work was to predict dissolution into fasted and fed state biorelevant media and further devise a new model to predict the food effects on dissolution. Solubility studies, intrinsic dissolution studies, particle size analysis, and high-performance liquid chromatography (HPLC) were used to predict dissolution rate as well as dissolution and solubility enhancement of three model poorly soluble drugs (i.e., griseofulvin, ketoconazole, and ibuprofen) in fasted and fed state gastric and intestinal media over their surfactant-free counterparts. Drug dissolution rate into fed state biorelevant media was attenuated relative to drug solubility enhancement due to low colloid diffusivity. Dissolution enhancement in fasted state media was about as much as solubility enhancement due to minimal incorporation of drug into the mixed micelles. A model was also devised to predict the food effect on dissolution by considering the rate of dissolution in fed state biorelevant media over the rate of dissolution in fasted state biorelevant media and the diffusivity of colloids in each. The resulting model allowed for the prediction of a food effect on dissolution and agreed with food effects observed in vivo for the three model drugs
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Predictors and subsequent healthcare utilization associated with CDC-guideline opioid thresholds among commercially insured new chronic opioid usersBackground: The receipt and subsequent healthcare utilization surrounding new chronic opioid users (NCOUs) is multifactorial and includes clinical, demographic, and state-level factors. This study evaluated i) predictors for receipt of chronic opioid therapy informed by CDC-guideline morphine milligram equivalent (MME)/day recommendations and the short-term healthcare utilization measured by ii) total healthcare costs and iii) all-cause hospitalization after new chronic opioid use. Methods: We conducted a retrospective cohort study using IQVIA PharMetrics® Plus for Academics commercial claims with NCOUs identified between January 2014 through March 2015. NCOUs were defined as having at least 60-days coverage of opioids within a 90-day period with at least a 30-day opioid-free period prior to the date of the first qualifying opioid prescription. The short-term healthcare observation period began the 91st day or the day after last day coverage of the chronic opioid period, whichever is sooner. We placed NCOUs in one of three-tiered risk-based opioid thresholds categories: low (> 0 to < 50 MME/day), medium (≥ 50 to < 90 MME/day), and high (≥ 90 MME/day). A multinomial logistic regression was used to evaluate the impact of prescription drug monitoring program (PDMP) rigor on the receipt of respective opioid thresholds. A generalized linear model and multivariable logistic regression was utilized to evaluate the incremental total healthcare costs (ITHC) and odds of incurring a hospitalization between the thresholds, respectively. Results: A total of 16,684 NCOUs were identified. Among the NCOUs, a state with high PDMP robustness had lower odds of receiving medium (0.74; 0.62-0.90) and high (0.74; 0.59-0.92) thresholds when compared to low. When compared to low, medium and high were found to have higher ITHC, (US$, 95% Confidence Interval [CI]) $1,429 (947-1,911) and $1,775 (1,183-2,368), respectively. When compared to medium, the ITHC for high $267 (-310-844) was non-significant. When evaluating odds of all-cause hospitalization (adjusted odds; 95% CI), when compared to low, no difference was identified with medium (1.01; 0.94-1.28) or high (1.01; 0.84-1.22). Conclusion: Among NCOUs, PDMP robustness was found to decrease the odds of subsequent receipt of higher thresholds. However, short-term healthcare costs and all-cause hospitalization did not differ among the thresholds.
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Lessons Learned from the Characterization of CPSF30 – A Zinc Finger Protein Containing an Unexpected 2Fe-2S ClusterZinc Finger (ZF) proteins utilize zinc as a structural co-factor. ZFs are classed based upon the amino acid ligands that coordinate Zn. One class of ZFs is the CCCH class, which uses three cysteine and one histidine as zinc coordinating ligands. These proteins regulate RNA via a ZF/RNA binding interaction. One member of the CCCH class of ZFs is cleavage and polyadenylation specificity factor 30 (CPSF30) which contains 5 CCCH domains. In addition, CPSF30 has a ‘CCHC’ or zinc knuckle domain. CPSF30 regulates pre-mRNA processing. Experiments to determine the RNA recognition properties of CPSF30 and the role of an unusual Fe-S co-factor have been performed. A construct of CPSF30 that contains the 5 CCCH domains binds to an RNA sequence – AAUAAA – which is also called the polyadenylation signal (PAS) and present in a majority of pre-mRNA. I determined that mutations to the PAS, including some associated with human diseases, result in binding affinity changes to CPSF30 suggesting a connection between RNA binding and disease states. I isolated and characterized full length CPSF30, which contains the CCHC domain along with the 5 CCCH domains, for the first time. A major finding was that the CCHC zinc knuckle domain binds polyU RNA. Thus, CPSF30 appears to have bipartite RNA recognition. I determined that RNA recognition to these two distinct RNA sequences by CPSF30 is a competitive event and proposed a model of CPSF30/RNA binding related to alternative polyadenylation or cytoplasmic polyadenylation. The Fe-S cluster of CPSF30 was characterized. Mössbaauer and XAS spectroscopy data support a 2Fe-2S cluster with a CCCH ligand set. Reduction with dithionite followed by UV-visible and EPR spectroscopies demonstrated that the protein is redox active. Metal coupled protein oxidation/mass spectrometry indicate that ZF2 of CPSF30 is the site of the Fe-S co-factor.
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Evaluation of In Vitro-In Vivo Correlations in Topical and Transdermal Drug Delivery Systems by In Vitro Permeation Testing and Pharmacokinetic Studies for Bioavailability/Bioequivalence and Heat Effect AssessmentIn vitro-in vivo correlation (IVIVC) has gained great attention in the biopharmaceutical field because of its potential ability to predict drug performance in vivo, eliminating costly and time-consuming clinical trials. However, the regulatory guidance on IVIVC has only been established for extended-release oral dosage forms, and not for topical and transdermal formulations. An in vitro model is necessary to establish IVIVC. The present work showed that the in vitro permeation test (IVPT) using excised human skin can quantify and distinguish bioavailability (BA)/bioequivalence (BE) between a brand-name topical metronidazole gel, a bioequivalent generic gel, and a non-bioequivalent generic cream. A harmonized pharmacokinetic (PK) study in healthy human subjects was conducted to evaluate IVIVC. The scaled average bioequivalence approach was used to establish BE between the gels and distinguish the cream from the gels. The metronidazole PK study didn’t provide reproducible serum levels; therefore, IVIVC’s predictability was weak. The present work also showed IVPT’s ability to predict BA for two rivastigmine TDS under transient heat exposure. A harmonized PK study was conducted. A Level C and a Level A IVIVC were established under baseline temperature (32.0°C). IVPT demonstrated significantly increased maximum flux for both TDS with a comparable fold enhancement. However, the PK study didn’t demonstrate a consistent heat effect on maximum serum concentrations of rivastigmine under elevated temperature (42.0 °C). The IVIVC’s predictability for the heat effect was therefore weak. Encouragingly, findings suggested that IVPT is useful in assessing BE for topical drug products. For hydrophilic drugs, such as metronidazole, it is possible that IVPT may have limited predictability in vivo if significant absorption of the drug occurs via the shunt route, and/or if significant reproducible systemic absorption can’t be quantified from dosing the semisolid over a large surface area. In conclusion, IVPT was able to quantify the magnitude of heat effect on the absorption from rivastigmine TDS, and data also suggested that under baseline temperature, IVPT will likely show good predictability of TDS performance in vivo. However, experimental conditions should be further altered to validate IVPT’s usefulness in the prediction of TDS BA in vivo under the heat exposure.
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In Vitro Dissolution, Supersaturation, and Permeation to Predict In Vivo Oral Drug AbsorptionMost new drug candidates are poorly water soluble, and as such have limited absorption and bioavailability. The current research focuses on two major aspects of oral drug absorption research (i) characterization of spray dried dispersions (SDDs) of a poorly soluble drug to elucidate the factors that impact overall formulation performance and absorption, and (ii) development and utilization of an in vitro dissolution-permeation model to predict in vivo human absorption and performance of various drugs representing different Biopharmaceutic Classification System (BCS) classes. The first aim was to characterize itraconazole (ITZ) SDDs from three grades (L, M and, H) of hydroxypropyl methylcellulose acetate succinate (HPMCAS) polymer based on supersaturation kinetics and molecular interactions that contributed to the overall SDD performance and drug absorption. A combination of in vitro and solution state drug-polymer interaction studies was used. Results indicated that a high supersaturating concentration, and rate and extent of supersaturation caused the largest increase in absorption. We concluded that such stronger hydrophobic interactions between drug and polymer were relative detriment to ITZ absorption for ITZ and HPMCAS SDDs. Conventional dissolution testing has been modified in terms of in vitro design and medium composition. Biorelevant media closely simulate the composition of human gastrointestinal fluids but are challenging to prepare and contain multiple components. The second aim was to assess the similarity of dissolution profiles from biorelevant media. Results indicated favorable interday repeatability, interanalyst repeatability, and interlaboratory reproducibility suggesting this approach could be incorporated into clinically relevant dissolution models. An in vitro model that can capture the dynamic interplay between dissolution and permeation is sought for poorly soluble drugs, with potential to guide the drug development process and product life cycle management. The third aim was to characterize and utilize a dissolution-hollow fiber membrane (D-HFM) system to correlate in vitro and in vivo parameters for several BCS classes drugs. Model predictions and experimental D-HFM system studies were performed using drug solutions and drug products. Results indicated close agreement between predicted and observed drug permeation profiles, and between the D-HFM system derived in vitro and in vivo permeation constants and absorption profiles.