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.

Recent Submissions

  • The Economic Burden of Chronic Obstructive Pulmonary Disease and Comparative Effectiveness of Maintenance Inhaler Medications in the United States

    Shah, Chintal; Zafari, Zafar (2023)
    Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a highly prevalent condition in the United States (US). Among individuals with moderate to very severe COPD, inhalation therapy is the mainstay of disease management, with the goal to reduce COPD exacerbations. Maintenance medications, especially combinations of long-acting beta2 agonist (LABA)/long-acting muscarinic antagonist (LAMA) or LABA/inhaled corticosteroids (ICS), are commonly used. This dissertation aimed to examine the (i) economic burden of COPD, (ii) comparative effectiveness of LABA/LAMA and LABA/ICS fixed dose combination (FDC) single inhaler therapy across various subgroups, and (iii) comparative effectiveness of LABA/LAMA combinations with different ingredients and inhaler types, vilanterol/umeclidinium (VI/UMEC) and olodaterol/tiotropium (OLO/TIO). Methods: Medical Expenditure Panel Survey data was used to estimate the economic burden of COPD (Aim 1). COPD-specific (adjusted) costs were determined for various service categories using a regression-based weighted two-part model among patients aged 45 years and older. Medicare Chronic Conditions Warehouse data was used for the comparative effectiveness studies (Aim 2, Aim 3). A new user active comparator retrospective cohort study design was utilized, and the outcome of interest was time to first COPD exacerbation. To ensure comparability between groups, they were matched based on their high-dimensional propensity scores. Results: The total COPD-specific direct medical cost was 2018 US $4,322 (Standard Error (SE): US $577) per patient per year with prescription drugs contributing US $1,887 (SE: US $216). The resultant overall annual total COPD-specific cost was US $24.0 billion, with prescription drugs contributing US $10.5 billion. For the interclass comparative effectiveness analysis, the hazard ratio (HR) of time to COPD exacerbation was 0.846 (95% Confidence interval (CI): 0.776-0.923) for LABA/ICS compared to LABA/LAMA initiators. Among LABA/LAMA FDCs, the HR of time to first COPD exacerbation was 0.948 (95% CI: 0.813-1.105) for individuals initiating OLO/TIO versus VI/UMEC. Conclusion: This dissertation found that COPD poses a significant economic burden on the US healthcare system, with prescription drugs being a major contributor. Optimizing therapy can help reduce this burden. While a statistically significant interclass difference was observed between LABA/LAMA and LABA/ICS initiators, no statistically significant intraclass difference was observed between initiators of LABA/LAMA FDCs: VI/UMEC and OLO/TIO.
  • Immunomodulatory Nanoparticles as a Multimodal Approach to Attenuate Immune Dysregulation in Severe Inflammation and Sepsis

    Truong, Nhu; Pearson, Ryan M. (2023)
    Sepsis, a life-threatening condition triggered by an uncontrolled immune response to infection, currently lacks an FDA-approved therapeutic intervention to enhance patient survival. Severe inflammatory conditions can disrupt the balance of histone acetyltransferase (HAT)/histone deacetylase (HDAC) activity, leading to global cellular hypoacetylation. Histone deacetylase inhibitors (HDACi) restore acetylation profiles and reverse transcriptional silencing. Suberoylanilide hydroxamic acid (SAHA), a pan-HDACi, was modified by para-hydroxymethylation (termed SAHA-OH), which resulted in a favourable reduction in SAHA-associated toxicity under inflammatory lipopolysaccharide (LPS) challenge. SAHA-OH was incorporated into immunomodulatory nanoparticles (iNPs), previously developed by our lab, to form iNP-SAHA using a prodrug approach through the covalent modification with poly(lactic-co-glycolic acid) (PLGA). iNP-SAHA treatment significantly reduced proinflammatory cytokines in vitro and in vivo, improved the viability of LPS-stimulated primary macrophages, and enhanced survival of mice in an LPS-induced endotoxemia model. iNP-SAHA treatment did not significantly improved mice survival compared to the iNP treatment alone; however, the synergistic anti-inflammatory properties of iNP-SAHA are potentially promising for future exploration in alternative models of inflammatory disease. We evaluated the efficacy and cellular mechanism of iNP activity using a clinically relevant cecal ligation and puncture (CLP) murine model of polymicrobial sepsis. iNPs, when administered as an adjuvant to antibiotics, significantly improved survival compared to antibiotics alone. Interestingly, iNP treatment marginally affected local and systemic cytokine profiles, despite mitigating organ dysregulation. Minimal effects on immune cell proportions at local sites were observed, but iNP treatment normalized monocyte levels in peripheral blood and alveolar macrophages in lung tissues. Further studies enumerated that iNPs modulated cellular adhesion and migration surface marker expression as well as apoptotic levels on immune cells. These findings highlight the potential of iNPs as an adjunctive therapy for sepsis, particularly when combined with antibiotics, suggesting promising prospects for future clinical translation. Lastly, a high-throughput microfluidic approach for iNP formulation to enable facile scale-up was developed. We optimized the microfluidic method and the impact of polymer and surfactant concentrations, surfactant chemistry, flow rate ratio (FRR), and anti-inflammatory activity. This work demonstrated a controlled and reproducible microfluidic method for iNP formulation, showcasing their inherent anti-inflammatory properties and offering a promising avenue for inflammation management.
  • Conversion of Small-Molecule Inhibitors into Heterobifunctional Compounds in the Discovery of Novel Chemotherapeutics

    Chan, Alexandria; Fletcher, Steven (2023)
    Heterobifunctional polypharmacologic agents are compounds that have individual pharmacophores for at least two separate biological targets. Our work spans two distinct sets of heterobifunctional molecules: 1. Polypharmacologic agents that inhibit two proteins known to contribute to the disease state, and 2. Protein degraders: Proteolysis targeting chimeras (PROTACs) and molecular glues. Both types of protein degraders function through recruiting an E3 ligase to the protein of interest, resulting in a hijacking of the ubiquitin-proteasome system, and the subsequent destruction of the target protein. The use of type 1 compounds is rapidly growing as such polypharmacologic agents are postulated to exhibit distinct advantages over the monovalent, parent drug compounds from which they are constructed, including the ability to increase therapeutic effect, lower effective dosage, and circumvent treatment resistance. Type 2 compounds – the protein degraders – can eliminate a target of interest, requiring the cell to resynthesize the protein to regain its cellular function. These compounds may have a catalytic mechanism of action wherein the compounds are recycled after mediating the degradation of the target protein, thereby requiring non-stoichiometric amounts of drug while also directly countering resistance that manifests through target protein upregulation. Moreover, such degraders retain activity with resistant proteins where traditional, non-covalent small-molecule drugs fail. Due to these advantages, there is increasing enthusiasm that targeted protein degraders may herald a new class of anti-cancer therapeutics. Herein, our efforts towards the discovery of heterobifunctional pharmaceuticals for the treatment of drug-resistant hematological malignancies are described.
  • Utilizing Pharmacometrics to Facilitate Generic Drug Development of Orally Inhaled Products and Optimize Pharmacotherapy of Antifibrinolytics

    Li, Shuhui; Gobburu, Jogarao (2023)
    This thesis has two parts. The first part is related to the pharmacokinetic (PK) batch-to-batch variability of orally inhaled products, which may pose challenges for generic product development. I applied the techniques of pharmacometrics to propose and evaluate alternative PK bioequivalence (BE) study designs using Advair Diskus as an example product, aiming to facilitate generic development. First, population PK models for Advair Diskus were developed and qualified to simulate PK BE study. Next, the effect of batch-to-batch variability on the establishment of BE was evaluated using the developed models. Batch-to-batch variability substantially elevates the probability of reaching a false conclusion in a PK BE study for equivalent and inequivalent comparisons. Therefore, ignoring batch-to-batch variability when presenting will increase the risk of either patients being treated with an inequivalent formulation or pharmaceutical companies not obtaining approval for an equivalent formulation. This calls for alternative PK BE approaches to account for the batch-to-batch variability. I proposed and evaluated a two-phase study framework that uses a pilot study to select reference and test batches for the pivotal BE study. A parallel design with ≥ 12 patients per sequence or a crossover design with ≥ 6 patients per sequence is recommended for the pilot study design. The proposed criteria for selecting batches based on the pilot study results include (1) 0.9 ≤ T/R ≤ 1.11 and (2) higher conditional power. The two-phase study design offers the flexibility to select batches in a PK study to minimize the impact of batch-to-batch variability on the generics development. The two-phase framework might be applied to other products with similar characteristics and high batch-to-batch variability in the reference products. The second part of this thesis used pharmacometrics to optimize the pharmacotherapy of an anti-fibrinolytic, tranexamic acid (TXA), in special patient populations. The PK and pharmacodynamics (PD) of TXA in special populations are understudied; therefore, the PK/PD-driven optimal doses for them are unknown. First, I characterized the PK and PD of TXA in pregnancy and found that pregnant women have up to 30% higher clearance and volume of distribution than the general non-pregnant population. A dose of 650 mg maintains both PK and PD targets for > 1 hour in most patients, which is recommended as the postpartum prophylactic dose for future confirmatory clinical studies. In addition, I evaluated a current dosing regimen for cardiac surgery patients who use cardiopulmonary bypass (CPB) during their surgeries from a PK perspective. This dosing regimen consists of a long infusion of TXA at 100 mg/hr for 5 hours before CPB initiation, a 1 g bolus of TXA at CPB initiation, and another 1 g bolus at the end of CPB. While kidney function affects the clearance of TXA, and the CPB procedure increases the volume of distribution of TXA, the current dosing regimen was confirmed to provide sufficient TXA exposure (15 mg/L) from CPB initiation till 3 hours post-CPB, achieving the therapeutic goal. Both studies contribute to understanding how TXA dosing can be optimized in special patient populations.
  • Development of Mass Spectrometric Methods for Analysis of Sphingolipids and Oligonucleotides

    Tran, Anh Quan; Jones, Jace W., 1978- (2023)
    Mass Spectrometry (MS) is a powerful method for analysis of biomolecules due to its selective and sensitive analytical benchmarks, providing information about their structures and abundance, further enabling their functions to be studied. This thesis focuses on the analysis of sphingolipids and oligonucleotide therapeutics due to knowledge gaps in their MS analysis. Sphingolipids (SPs) are pivotal membrane lipids with very diverse structures, setting the stage for challenging analysis. To enhance analytical performance, lithium was incorporated into the MS workflow, consolidating adducts and simplifying the mass spectrum and proving informative fragmentation patterns. An extraction protocol was developed that integrated a base hydrolysis step for SP enrichment using lithium hydroxide, which effectively hydrolyzed esterified lipids with the added benefit of lithium adduct consolidation. A high throughput screening method was developed with lithium adduct consolidation, resulting in detection enhancement of low abundant SPs. A multidimensional analytical platform was developed to provide higher structural quality of SPs, utilizing off-line liquid chromatograph (LC), ion mobility and high-resolution tandem MS. The off-line LC provided separation and allowed lithium adduction for further analysis while ion mobility and elevated energy tandem MS are used to structurally characterize and resolve SP isomers. Data processing, analysis and visualizations techniques were also developed, tailored to the specific needs of the workflow. A MS imaging method for spatial localization of SPs was developed with lithium adduction and on tissue hydrolysis to enhance SP analysis of intact tissue. OGN (oligonucleotide) therapeutics are becoming increasingly more popular for complex diseases. Despite this, rigorous analytical techniques to monitor biomanufacturing processes and the final formulation product are lacking. A high-throughput screening method was developed to verify the molecular weight and to scan for non-isomeric impurities while minimizing alkali salt contamination that notoriously adduct to OGNs during ionization. LC methods were developed for both analytical and preparative separation while tandem MS was used to confirm their sequence. For isomeric impurities, ion mobility was utilized to interrogate and compare the extremely complicated diastereomeric composition of various OGN drug products.
  • Integration of Quantitative and Qualitative Mass Spectrometric Workflows to Evaluate the Role of Plasmalogen Glycerophosphoethanolamine in Disease Progression

    Morel, Yulemni; Jones, Jace W., 1978- (2023)
    Lipids encompass the major constituent of cellular membranes and are involved in various cellular processes such as membrane integrity, energy storage, and cellular signaling. Due to their structural composition, lipids are vulnerable to disruptions in redox biology, ultimately leading to lipid peroxidation (LPO) and detrimental alterations to membrane dynamics, interactions with membrane proteins, and signal transduction. Several disease states such as traumatic brain injury (TBI) are plagued by oxidative stress and LPO. Thus, an understanding of the lipid molecular targets is crucial for defining the underlying mechanisms driving pathology. Plasmalogen, a unique glycerophospholipid (GP) characterized by a vinyl ether bond at the sn-1 position, is a lipid structure with noteworthy redox-regulating properties. Reports have highlighted dysregulated levels of plasmalogen lipids following TBI-onset, with oxidative degradation products such as lysoglycerophospholipids accumulating. With their established importance, a comprehensive investigation of their oxidative role within TBI is lacking. Furthermore, the structural diversity of the lipidome and the extended lipid complexity due to LPO introduces challenges with the detection, identification, and quantification of these lipid structures. This research describes the development of analytical methodology for the detection, characterization, and quantification of plasmalogen and its oxidized derivatives across biological samples. Herein, a targeted quantitative assay was established to evaluate plasmalogen and its lysoplasmalogen/glycerophospholipid levels, and confirm its role as an early marker of acute brain injury. To investigate the unique oxidative properties of plasmalogen as compared to other lipid classes, liposomal mixtures were prepared, and displayed a significant vulnerability for lipids with the presence of a vinyl ether bond at the sn-1 position, a polyunsaturated fatty acid (PUFA) at the sn-2 position, and an ethanolamine headgroup (PE). After validating their oxidative potential, we further constructed a comprehensive analytical workflow that combined complementary LC separations, tandem mass spectrometry, and drift-tube ion mobility, which significantly improved our ability to tease apart the isomeric complexity of the oxidative lipidome. To establish their impact on the cellular environment, whole cells, purified lysosomes, and samples isolated from a TBI mouse model were investigated and revealed the formation of oxidized PE products that potentially alter organellular function and propagate disease pathology.
  • HDX-MS, Molecular Dynamics, and Modeling: An Integrative Approach to Model Solution Structural Ensembles

    Kihn, Kyle; Deredge, Daniel D.; Wintrode, Patrick L. (2023)
    Probing the structural equilibrium that proteins and protein complexes can adopt in solution is critical in understanding a multitude their biophysical properties. Two common ways to probe these dynamic structures are hydrogen deuterium exchange coupled mass spectrometry (HDX-MS) and molecular dynamics simulations (MD). HDX-MS is a solution-based technique that reports on a system’s secondary and tertiary structure and dynamics at peptide level resolution. Although informative, the typical information obtained through HDX-MS studies remains largely qualitative and is limited by the attainable resolution. On the other hand, MD takes a static starting high resolution structure with a set of model parameters to simulate the system’s motion over time. The resulting trajectory gives an atomistic view of the system from which a multitude of biophysical properties can be derived. However, the timescales accessible to MD simulations are limited and can lead to an under exploration of the conformational landscape. To overcome this, enhanced computational sampling methods have been developed to more efficiently explore a system’s conformational landscape. The ability to integrate experimental HDX-MS data with MD simulations has the potential to increase the utility of both methods. Such integration rests on the ability to predict deuterium exchange from computationally generated ensembles. Thus far, several physics-based models of HDX exchange have been developed and implemented in the calculation of HDX exchange rates from MD simulations. Whereas the value of any single model remains a subject of debate, studies have not focused on the application of such integration to address unanswered biophysical questions. In this project, I aim to demonstrate the applicability of such integrative approach to a variety of biophysical questions. HDX exchange rates will be calculated from MD simulations and compared to the experimentally observed exchange rates for given systems. Further, utilizing a maximum entropy reweighting method, structural ensembles most consistent with in solution HDX-MS data will be extracted for analysis. In this thesis, I apply enhanced sampling MD, experimental HDX rates, and maximum entropy reweighting to generate realistic structural ensembles of protein and protein complexes in-solution to be used in the characterization of in-solution native state ensembles, protein conformational transitions, and protein-small molecule interactions. This is done using three model systems: the Cytoplasmic Heme Binding Protein (PhuS) from Pseudomonas aeruginosa, Human Plasminogen activator inhibitor-1, and ERK2 and its known type I inhibitors. This thesis develops, optimizes, and validates a workflow which can help shift HDX-MS studies from its current qualitative perspective to a quantitative treatment of HDX-MS which leverages computational simulations and extract atomic resolution interpretations.
  • PTGFRN as a Target for Antibody-Drug Conjugate (ADC) Development in Mesothelioma and Medulloblastoma

    Marquez, Jorge; Serrero, Ginette; Kane, Maureen A. (2023)
    Cancer is a disease that afflicts millions of people each year. While there are many drugs available to treat certain subsets of cancer, there still remain many types of cancer that do not have tailored therapy available to treat them. Mesothelioma and Pediatric Medulloblastoma are two such cancers that the NIH classifies as rare and aggressive neoplasms. As such, both cancers display unmet needs, and are the subject of much research to improve the chemotherapy available for treatment. Our laboratory has found that both cancers express a protein called Prostaglandin F2 Receptor Negative, or PTGFRN. PTGFRN is a member of the Tetraspanin family, which are transmembrane proteins. Previously, PTGFRN expression has been found to correlate with a more aggressive phenotype. Additionally, when its expression is inhibited, cellular processes essential for cancer metastasis were also found to be impacted. To better understand how PTGFRN affects cancer progression, we looked at the effects of PTGFRN with various in vitro functional assays to assess phenotypic changes. We also performed a global proteome and pathway analysis using mass spectrometric methods to better understand what pathways were most affected by PTGFRN expression, and identify proteins that are complexed, or in direct interaction, with PTGFRN. In parallel to these studies, we also developed monoclonal antibodies that are capable of binding cell-surface PTGFRN, and inducing endocytosis to the cytoplasm. Conjugation of our prototype antibody, the mouse mAb 33B7, to the ribosome-inactivating protein Saporin results in an Antibody-Drug Conjugate (ADC) of moderate¬ efficacy. Due to the success of this first ADC attempt, we then developed a fully human antibody, denoted as 8C7, and conjugated it to the payload Duocarmycin via a cleavable linker, resulting in our second generation ADC. This new ADC exhibits improved, highly potent in vitro anti-cancer effect, as well as in in vivo models with mice bearing mesothelioma and medulloblastoma tumors. The work detailed here lays the groundwork for a tailored therapy to treat the aforementioned cancers, and expands our knowledge of proteins and protein interactions involved in cancer metastasis.
  • Development of an In-Cell Footprinting Method Coupled with MS for the Study of Proteins in Three-Dimensional Cancer Models

    Shortt, Raquel; Wang, Hongbing; Jones, Lisa M. (2023)
    Fast 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.
  • The Effect of Medication Information Delivery Format on Cognitive Load and Knowledge Retention of Informal Caregivers

    McPherson, Mary Lynn M.; Kulo, Violet A; Cestone, Christina (2023)
    Informal 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. 
  • The Effects of Graded Versus Ungraded Individual Readiness Assurance Tests on Pharmacy Students’ Assessment Performance and Achievement Goals in a Team-Based Learning Classroom

    Noel, Zachary; Cestone, Christina; Gordes, Karen L. (2023)
    Individual 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.
  • Under-ascertainment and underreporting of adverse events in clinical trials

    Hong, Kyungwan; Doshi, Peter (2023)
    Introduction: 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.
  • Determination of Harmful and Potentially Harmful Constituents in E-cigarettes, E-liquids, and Generated Aerosols

    Lee, Angela; Dalby, Richard N. (2023)
    Electronic 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.
  • A Cost-Effectiveness Analysis Model Framework For Treatments Of Early-Stage Huntington’s Disease Patients In The United States

    Patil, Divya; Slejko, Julia JS; Slejko, Julia F. (2023)
    Huntington'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.
  • Evaluation of Evidence in Economic Models Used for Decision-Making: Development of the Data Inputs in Value Economic Evaluations (DIVEE) Checklist

    Desai, Bansri; Perfetto, Eleanor M. (2023)
    Background: 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.
  • Regulation of retinoid homeostasis by cellular retinol-binding protein, type 1

    Zalesak-Kravec, Stephanie; Kane, Maureen A. (2022)
    Retinoic 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.
  • Method Optimization of a New Automated Platform for Proteome-Wide Structural Biology

    Johnson, Dante; Jones, Lisa M. (2022)
    Proteins 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.
  • Effect of Excipients on the Performance of Spray-dried Amorphous Solid Dispersion (ASD) in Tablets

    Yu, Dongyue; Hoag, Stephen W. (2022)
    Amorphous 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.
  • The Regulatory Role of the Cytoplasmic Heme Binding Protein PhuS in Pseudomonas aeruginosa

    Wilson, Tyree; Wilks, Angela (2022)
    Pseudomonas 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.
  • Development of the Lennard-Jones Parameters for the Polarizable Classical Drude Oscillator Force Field

    Chatterjee, Payal; MacKerell, Alexander D., Jr. (2022)
    The 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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