Diabetes and obesity are two chronic medical conditions that share similar physiologies. They also present significant health burdens with serious societal and economic impact as hundreds of millions of patients suffer from these conditions with combined treatment costs reaching trillions of dollars worldwide. A class of metabolic hormones known as incretins, specifically glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) have been shown to play critical roles in both conditions. These developments have made incretins attractive targets for both diabetes and obesity therapies. The current presentation explores the historical background of incretins and their roles in diabetes and obesity and the evolution of incretins as therapeutic targets. The presentation will conclude with an overview of the manufacturing process Tirzepatide, which is the active pharmaceutical ingredient of both Mounjaro® and Zepbound®. These therapeutics, marketed by Eli Lilly & Co., are GIP/GLP-1 dual agonists indicated for the treatment of type 2 diabetes and obesity, respectively.

The therapeutic landscape is transitioning from small-molecule drugs to biologics-based therapeutics, including peptides, proteins, antibodies, and nucleic acids, due to their greater target specificity and lower toxicity. However, the delivery of these biologics remains a significant challenge. They are vulnerable to degradation, must overcome biological barriers, and require targeted delivery to specific cells and tissues. We devise new chemical strategies to address these issues at the intersection of basic science and translational research. Specifically, we are developing small molecule probes with modular scaffolds that enable: (i) reversible protein surface remodeling for in vivo protein delivery, (ii) multimodal fluorogenic nanoparticles for visualizing cellular uptake of biologics, and (iii) trifunctional activity-based probes for cell surface labeling. We envision that a combination of modular chemical tools and high-throughput techniques will enable a bottom-up approach to addressing fundamental challenges in drug delivery.

The demand for next-generation battery chemistries continues to grow with advances in portable electronics, mobile robotics, and large-scale energy storage for data centers. Solid-state batteries employing Li metal anodes offer improved safety and higher energy density compared to conventional Li-ion systems. Despite these advantages, they face challenges related to dendrite growth and short-circuit failure, which limit fast cycling while maintaining accessible capacity. These issues arise from coupled kinetic and thermodynamic phenomena at the Li anode/solid-electrolyte interface.

In this lecture, I present a multiscale, physics-grounded framework that begins with atomistic simulations to elucidate lithium transport along microstructural defects in Li metal. This mechanistic understanding is used to predict the rate capability of polycrystalline Li anodes and to construct diffusion and creep deformation mechanism maps under various cycling conditions. Atomistic-informed models are further leveraged to assess cell-level capacity and to analyze void formation and annihilation at the Li/solid-electrolyte interface. Finally, I outline a research vision toward inverse modeling enabled by physics-informed AI/ML approaches, where transport properties of solid electrolytes are inferred from operando spatio-temporal field data within a physics-based modeling framework.

Gene delivery has become an essential method for biological research and offers promises for therapeutic applications. Adeno-associated viruses (AAVs) are among the most preferred gene delivery vectors due to their low toxicity and high engineering potential. However, their poor efficacy and target specificity remain critical limitations, often raising serious safety concerns in clinical trials. My research focuses on engineering these viral vectors, enabling efficient and targeted gene delivery to the central and peripheral nervous systems through minimally invasive routes. To achieve this goal, we have developed high-throughput platforms for engineering and screening the genetic variant libraries of AAV capsids and genomes by adapting cutting-edge directed evolution and spatial omics technologies. Through these technical innovations, we have invented a series of engineered AAVs that are, for instance, capable of penetrating the protective blood-brain barrier, preferentially transducing specific brain cell types, or avoiding the liver when intravenously administered. Our platform technologies have successfully been expanded across species, including rodents and non-human primates, proving the exciting potential for advancing therapeutic gene delivery tools. In my lab at UIUC Bioengineering, we aim to advance the precision of gene delivery by better understanding the genetic and epigenetic programs of brain functions and disorders and by using the obtained knowledge to develop programmable gene delivery vectors to target brain cell types and states. We are tackling this challenge at the intersection of synthetic biology, single-cell/spatial omics, and machine learning, advancing deliver precision, programmable, and personalized genetic medicine for complex neurological and mental disorders.