ASDRP Spring 2026 Research Symposium & Expo
Time: 10:00 - 10:30 AM
Location: 103
Keywords: Medicinal Chemistry, Cancer Drug Discovery, Chemical Biology, Organic Synthesis
The molecular complexity engineered by nature has long been a source of interest to chemists and biologists alike in the search for bioactive and therapeutically relevant materials - and yet, the power of organic synthesis in the design of new-to-nature chemistry with unique function opens doors as an enabling tool the development of compounds that impact human health. Grounded in this, the main thrusts of research in our laboratory include synthetic derivatization and asymmetric total synthesis of bioactive natural products to more fully probe structure-activity relationships, development of chemical platforms for introducing fluorinated functionalities into complex chemical scaffolds including natural products and their inspired analogs, and developing creative workflows for benchtop NMR spectroscopy as a real time analytical tool for process development and reaction optimization in multistep and multicomponent organic synthesis. Our laboratory is principally interested in the intersection of chemical biology and organic synthesis, particularly in the context of developing next-generation small molecule therapeutics to treat human disease. Current thrusts of research in our laboratory are primarily centered around small molecule discovery chemistry towards the treatment of solid cancers and of neurodegenerative diseases (ALS, etc.). This is accomplished through developing new chemistries around precision-controlled reactivity of fluorinated building blocks (see Chyu, et al. Spectroscopy J. 2024; Li, et al. Artificial Intelligence Chem. 2024; Gu, et al. Discover Chem. 2025; Chen, et al. ACS Omega 2023; Wang, et al. Can. J. Chem. 2023 for a few representative student-coauthored publications from our laboratory), synthetic derivatization of biologically active natural products (see Lo, et al. ACS Bio & Med Chem Au 2025; Gu, et al. Bioorganic & Medicinal Chem. Lett. 2025; Somani, et al. Disc. Pharm. Sci. 2025; Gutti, et al. Drugs and Drug Cand. 2025, Lu, et al. Nat. Prod. Res. 2024, Thomas, et al. ChemRXiv 2023, and others for a few representative publications in this space); targeted molecular-logic design of medicinal chemistry campaigns (see Gutti, et al. BioRXiv 2025; Chen, et al. Applied Biosci. 2025; Sarkar, et al. US Patent App. WO2024155707A1), and the use of machine learning for drug design and therapeutics development (Chang, et al. J. Exp. Theor. Anal. 2026; Chalasani, et al. ChemRXiv 2025; Li, et al. Art. Int. Chem. 2024) Towards this end, we will share current advances from our group in the chemical synthesis of natural products and their analogs, particularly those bearing bio-orthogonal elements, such as silicon and fluorine, to enable unique chemical and biological functions. In parallel, we will describe how recent advances in benchtop NMR spectrometers have been deployed directly in an organic chemistry laboratory, and how this has enabled broader access to NMR as a real time analytical tool for reaction discovery and development and as both a research and training tool for structural elucidation of complex natural products.
Time: 10:00 - 10:30 AM
Location: 305
Keywords: CRISPR-Cas9, Gene Therapey, Genetic Engineering
Multidrug resistance (MDR) remains a major challenge in both infectious diseases and cancer therapy, often driven by stress-induced genetic mutations that enable rapid adaptation to therapeutic pressure. Although classical models assume that mutations arise randomly, emerging evidence suggests that mutagenesis can be actively promoted under stress through specialized DNA repair pathways. This project investigates mutagenic DNA repair as a therapeutic target to limit adaptive mutation and overcome drug resistance while enabling novel CRISPR-based gene therapy strategies. Using engineered chromosomal systems in Escherichia coli, we demonstrated that mutations preferentially accumulate through error-prone DNA repair mechanisms. The process is regulated by stress-response pathways, including RpoS (σS), recombination proteins RecBCD and RecA, and translesion DNA polymerases such as DinB and UmuCD. Our findings further reveal that transcription-associated R-loops and metabolic signaling pathways contribute to genome instability by promoting DSB formation and mutagenic repair. To enable direct visualization of DNA breakage, we developed a system capable of detecting single DNA double-strand breaks (DSBs) in both bacterial and human cells. This approach utilizes the DNA end–binding protein MuGam, which binds to DSBs and blocks DNA repair. Building on this strategy, we are developing a CRISPR-based system to induce cancer-specific DNA double-strand breaks while using MuGam to inhibit repair at these sites. This combination is designed to prevent proper DNA repair, ultimately triggering mitotic catastrophe and leading to selective cancer cell death.
Time: 10:00 - 10:30 AM
Location: 107
Keywords: Giant Unilamellar Vesicles, Fluoresence Imaging, Lipid Engineering
Giant vesicles (GVs) are cell-sized, bioengineered containers that often serve as fascinating models of the cell plasma membrane. GVs have proven useful for understanding a variety of different biophysical phenomena such as the visualization of "lipid rafts," the quantification of membrane elasticity and stability, the mechanics of membrane budding and fusion, and the complexity of protein-membrane interactions, among others. However, translation of these model systems into functional medicines such as biomimetic drug delivery vehicles, biochemical microreactors, or even "artificial cells" has presented some major engineering challenges, including controlling the size, stability, and encapsulation efficiency of the GVs while maintaining low manufacturing costs. In this work, we present a novel scaffold-supported giant vesicle system (sGV) that overcomes some of these major limitations by providing a cytoskeleton-like environment that maintains the size and stability of the GVs for long periods of time both in vitro and in vivo. We characterize the unique stability and delivery profiles for drugs (ranging from potent chemotherapies to rejuvenating vitamin-based compounds) using several techniques including conventional fluorescence microscopy, high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS), dynamic light scattering (DLS), and spectrophotometry. Finally, demonstrating the power of this new paradigm, we compare our room-temperature stable sGVs to the current gold standard in therapeutics and complex formulation delivery, the lipid nanoparticle (LNP), showcasing their capability to localize and tune the release of drugs across various mouse tissues including liver, pancreas, skin, conjunctiva, and breast, as well as both pig and human skin.
Time: 10:00 - 10:30 AM
Location: 303
Keywords: Materials Science, Nanomaterials
This talk presents highlights of studies conducted at ASDRP. We are investigating the potential of the prediction of mechanical properties across three distinct material systems: nanostructures, bulk copper, and 3D-printed polylactic acid (PLA). For nanostructures, machine learning is used to identify and characterize the morphology. Nanoindentation can be correlated to microhardness to macroscopic strength. Bulk mechanical properties of copper are evaluated through tensile and hardness testing to determine if grain size influences the linear correlation coefficients between hardness and strength. The mechanical behavior of 3D-printed PLA is characterized under two varying parameters—such as print orientation—to determine their effect on stiffness, strength, and failure modes. Comparative analysis across these materials highlights critical relationships between structure and mechanical response, potentially providing predictive insights applicable to materials design and additive manufacturing optimization. The topic of interfacial free energy measurements from dihedral angle of twin boundaries in copper will also be discussed.
Time: 10:00 - 10:30 AM
Location: 302
Keywords: Amphiphiles, Lipid delivery, Biguanide Chemistry
Biguanides are a class of nitrogen-rich compounds with a proven record in medicine, metformin alone is the most prescribed drug on the planet, yet their potential as a scaffold for next-generation therapeutics remains largely untapped due to their unforgiving synthetic challenges. Building on my doctoral work in which biguanide functionalization dramatically enhanced the potency of the antibiotic vancomycin against drug-resistant bacteria and novel targets, our group at ASDRP is systematically exploring how this pharmacophore can be extended across four distinct drug design contexts: tamoxifen–biguanide hybrids for breast cancer oncology, biguanide-linked PROTACs for targeted protein degradation in androgen receptor sensitive cancers, and two biguanide-functionalized lipid architectures via thiol-yne click chemistry and Ugi four-component reactions. Across each, the biguanide motif offers the ability to modulate membrane interactions, engage metal-binding sites, and augment established drug scaffolds in ways that conventional functional groups cannot. Yet realizing this potential is far from straightforward. Biguanide synthesis is notoriously unforgiving: classical condensation routes demand harsh conditions, offer poor selectivity, and tolerate only a narrow range of functional groups, constraints that become acute when working with sensitive scaffolds like lipids or multifunctional PROTAC linkers. Regioselectivity, competing reaction pathways, purification and structural integrity across multi-step sequences remain persistent hurdles that our method development work directly confronts. It is precisely this tension between therapeutic promise and synthetic difficulty that drives our research forward, and we warmly invite you to explore it with us.
Time: 10:00 - 10:30 AM
Location: 322
Keywords: Public Health, Diabetes, Cognitive Decline, Epidemiology
Cognitive decline (CD), encompassing impairments in memory, attention, and executive function, is an emerging public health challenge with significant implications for aging populations. Diabetes, including Type 1 Diabetes, Type 2 Diabetes, and Prediabetes, is a prevalent chronic metabolic disorder characterized by persistent glucose dysregulation and has been increasingly implicated in neurocognitive deterioration through mechanisms such as microvascular damage, insulin resistance, and chronic neuroinflammation. Despite growing clinical evidence linking diabetes to cognitive impairment, population-level analyses capturing real-world associations across diverse demographic groups remain limited. In this study, we use data from the Behavioral Risk Factor Surveillance System (BRFSS) of the Centers for Disease Control and Prevention (CDC) to investigate the association between Diabetes and Cognitive decline. Using weighted descriptive statistics and multivariable logistic regression models, we assess the relationship between diabetes status and cognitive outcomes while adjusting for key sociodemographic, behavioral, and health-related confounders. Additional subgroup and sensitivity analyses are conducted to evaluate the robustness of findings across populations. Our analysis aims to quantify the population-level burden of cognitive decline associated with diabetes and identify high-risk subgroups that may benefit from targeted prevention and intervention strategies. This work contributes to a broader understanding of the intersection between metabolic and cognitive health. It highlights the importance of integrating chronic disease management with cognitive health screening in both clinical and community settings. Furthermore, this research serves as a framework for mentoring students in applied epidemiologic methods, health data analysis, and research translation within a collaborative, education-driven environment.