The number of poorly water-soluble drugs in the pipeline has increased, and they are often not well absorbed by the gastrointestinal tract. Amorphous solid dispersion (ASD) is an emerging strategy to improve drug solubility and absorption. The overall aim is to expand methods used to evaluate the performance of ASD as a strategy to improve water solubility. Firstly, we aimed to develop an in vitro-in vivo correlation (IVIVC) model to predict human pharmacokinetics (PK) of itraconazole tablets with different release rates from dissolution experiments and determine formulation and process parameters that affect in vivo performance. Human PK was successfully predicted from in vitro dissolution experiments, and the IVIVC model created here met internal predictability criteria. Secondly, liquid state proton nuclear magnetic resonance (1HNMR) techniques were used to streamline polymer selection for ASDs in a non-destructive and resource-sparing fashion. For three drug-polymer pairs (i.e. etravirine with each HPMC, HPMCAS-M, and PVP-VA), 1HNMR findings were compared to supersaturation studies. Our hypothesis was that strong molecular interactions between polymer and drug observed in 1HNMR predicted precipitation kinetics in the supersaturation studies. Supersaturation studies agreed with 1HNMR predictions, as HPMC and HPMCAS-M maintained etravirine in solution for a longer time than PVP-VA. Thirdly, a robust, viable, and resource-sparing method to measure partition coefficient P (logP) was developed using reverse-phase high-performance liquid chromatography (RP-HPLC). Highly lipophilic drugs lack reliable, experimentally determined logP values in the literature. The RP-HPLC method reported here can be used for high throughput estimation of logP of commonly used drugs. A larger pool of reliable logP values of commonly used drugs shows promise to improve quality of medicinal chemistry and PK models. Lastly, our goal was to assess, for lipophilic drugs, the impact of logP on human volume distribution at steady state (VDss) predictions using the Oie-Tozer, Rodgers-Rowland, GastroPlus, Korzekwa-Nagar, and TCM-New methods. Sensitivity and prediction error analyses were conducted with a range of logP values and specific logP. TCM-New was shown to be the best method for VDss prediction of highly lipophilic drugs, suggesting blood plasma ratio (BPR) as a favorable surrogate for drug partitioning in the tissues.

Introduction: Parkinson disease (PD) is a neurodegenerative disorder causing disability and loss of independence (LOI), impacting patients and families. The longitudinal patterns of LOI in PD, prognostic factors predicting LOI in different types of activities of daily living (ADLs), and costs associated with functional dependency (FD) in PD remain unclear. Methods: We used 2003-2020 data from a prospective PD cohort at a tertiary neurologic center. Disability with LOI was assessed using the modified Older Americans Resource and Services Daily Function Questionnaire at baseline and follow-up. Patterns of LOI were summarized using EventFlow data visualization software. Cox proportional hazards models identified prognostic factors for LOI on different types of ADLs. Costs borne by patients with PD (PWP) and their families were analyzed using 2018-2019 Financial and Social Impact of Parkinson’s Disease Survey data. We estimated the incremental costs comparing families of PWP with and without FD using generalized linear models. Results: Among 270 early-stage PD patients, 133 (45%) developed LOI on one or more ADL, where 57 regained independence at least once. Housework was the most frequent first ADL requiring help (mean time 4.6 years post-first visit). Longitudinal patterns of loss included transient and persistent loss. Strongest associations were dyskinesia (adjusted hazard ratios [aHR], 1.82; 95% CI, 1.12-2.96) for LOI on any ADL; falls (aHR, 1.72; 95% CI, 1.16-2.55) for basic ADLs (BADLs); gait impairment (aHR, 2.04; 95% CI, 1.43-2.91) and dyskinesia (aHR, 2.09; 95% CI, 1.29-3.37) for instrumental ADLs (IADLs); and dyskinesia (aHR, 1.68; 95% CI, 1.05-2.68) for walking. Compared to families of PWP without FD (n=882), families of PWP with FD (n=476) faced higher direct non-medical costs (adjusted average marginal effect [aAME], $3,438; 95% CI, $1,719-$5,157) and indirect costs (aAME, $11,479; 95% CI, $1,545-$21,413). Conclusion: This study provides novel information about LOI patterns in PD and the fluctuations in patients' functioning in daily tasks. We identified factors (e.g., dyskinesia and gait impairment) with varying impacts on BADLs and IADLs. The study quantifies the financial strain on families of PWP with FD, underscoring the need for interventions to delay or prevent LOI in PD.

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.

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.

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.

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.

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. 

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.

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.

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.