Chimeric Antigen Receptor (CAR) T-cell therapy has emerged as a promising treatment for certain cancers, but its clinical success is often hindered by the risk of Cytokine Release Syndrome (CRS) — a severe immune response triggered by elevated cytokine levels. Early detection of CRS is critical for effective intervention and patient safety. To address this challenge, this study unveils the development of a digital optical biosensor integrated into a microfluidic chip for real-time, point-of-care monitoring of CAR T-cell therapy. The biosensor is designed to simultaneously quantify CAR T cells and detect key cytokines, such as Interleukin (IL)-6 and Interferon (IFN)-γ, directly from patient blood samples. Functionalized with specific molecular probes, the microfluidic chip enables highly selective biomarker detection through automated optical imaging, ensuring rapid and accurate results. The system’s performance was assessed based on sensitivity, dynamic range, and response time, benchmarking it against gold-standard methods like Enzyme Linked Immunosorbent Assay (ELISA). Results demonstrated a significant reduction in assay time while maintaining high detection efficiency, positioning this biosensor as a strong candidate for point-of-care applications.
By offering a portable, cost-effective, and real-time diagnostic solution, this biosensor has the potential to revolutionize patient monitoring in immunotherapy. Its seamless integration into clinical workflows could enhance clinical decision-making, improve patient outcomes, and lower healthcare costs. Beyond CAR T-cell therapy, this technology sets the foundation for broader applications in personalized medicine, advancing biosensing solutions for precise and accessible healthcare.

Accurate and timely diagnostics are essential for effective disease management. However, existing platforms face a trade-off between centralized accuracy and rapid assay speed. Enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) require washing, labeling, extensive sample preparation, expensive instrumentation, and hours-to-day turnaround times, limiting their adoption in resource-limited settings. This dissertation presents Nanoparticle-Supported Rapid Electronic Detection (NasRED), a biosensing platform that overcomes these challenges by enabling rapid, highly sensitive, and cost-effective biomolecular detection. NasRED utilizes functionalized gold nanoparticles (AuNPs), whose analyte-dependent aggregation modulates solution turbidity, generating an optical signal. Engineered centrifugation and vortex-driven fluidic forces accelerate reaction kinetics, enhancing nanoparticle interactions in a quasi-equilibrium state. A portable (<$30) optoelectronic readout system improves detection sensitivity and reduces reliance on large-scale instrumentation. NasRED was validated across diverse applications: infectious disease detection (SARS-CoV-2), food safety (Shiga toxin, Stx2), agricultural biosecurity (African swine fever virus, ASFV), and cancer prognosis (Thrombospondin-2, THBS2). For SARS-CoV-2 antigen and antibody quantification, NasRED demonstrated a limit of detection (LoD) of ~51 aM (8 fg/mL) in PBS (>3,000 times more sensitive than ELISA), ~71 aM (10 fg/mL) in serum, and ~250 aM (38 fg/mL) in diluted whole blood. It also enabled a competitive neutralization assay to assess human serum potency against SARS-CoV-2 variants, including Gamma and Omicron. For foodborne pathogen detection, NasRED, functionalized with designed ankyrin repeat proteins (DARPins), achieved attomolar sensitivity for Stx2 across biological matrices, distinguishing STX2 subtypes and Shiga toxin-producing E. coli (STEC) variants in 8-hour cultures. In oncology applications, it achieved femtomolar sensitivity for THBS2, spanning five orders of magnitude, differentiating it from CA 19-9 and BSA. In ASFV diagnostics, NasRED detected P72 and P30 antigens and antibodies in porcine serum, supporting early and concurrent detection strategies. With attomolar sensitivity, rapid processing (<30 min), and affordability (<$3/test, <$30 readout system), NasRED is scalable for global health, pandemic prevention, vaccine evaluation, food safety, and disease surveillance. The platform has reached technological maturity for commercialization through ASU’s Skysong Innovations and REDX Diagnostics, demonstrating real-world impact.

Population growth and urban lifestyles have contributed to the increased consumption of industrialized fast food, while sedentary behaviors have fostered metabolic disorders, ultimately leading to premature mortality. Changes in body weight and associated conditions, such as obesity, diabetes, and other related pathologies, necessitate monitoring metabolic changes through biomarkers that effectively indicate health risks. Ketones are established biomarkers of fat oxidation, produced in the liver as a byproduct of lipolysis. They include acetoacetic acid and hydroxybutyric acid in the blood and acetone in our breath and skin. Monitoring ketone production in the body is essential for people who use caloric intake deficit to reduce body weight or use ketogenic diets for wellness or treatments. Current ketone monitoring methods include urine dipsticks, capillary blood monitors, and breath analyzers. However, these existing methods have limitations that hinder their broader application. This work presents the development of a novel acetone sensor designed to detect breath and skin acetone and address the limitations of existing sensing methods. The key component of this sensor is a robust pH-indicator sensing solution capable of measuring acetone using a complementary metal oxide semiconductor (CMOS) chip, coupled with efficient data analysis via a red, green, and blue deconvolution imaging approach. The acetone sensor demonstrated sensitivity in the micromolar concentration range, selectivity for acetone detection in breath, and a stable operational lifetime of at least one month. The sensor’s performance was validated through a human breath sample test using a well-established blood ketone reference method. In addition, a second approach developed in this work was the synthesis and use of the liquid-cored microsphere containing a hydroxylamine/thymol blue sensing probe. Sensors utilizing liquid-core microspheres and polyvinyl alcohol as binding agents were fabricated on a transparent polyethylene terephthalate (PET) substrate and calibrated using simulated breath and skin acetone samples. Furthermore, a custom signal processing algorithm was developed to process sensor signals, enabling the simulation of real-time, continuous monitoring of skin acetone levels. This is the first instance of a colorimetric detection mechanism, allowing continuous measurement of skin acetone. Finally, a fat oxidation model incorporating ketone metrics was developed and correlated with skin acetone levels, establishing a direct link to body fat burning and offering a means to report clinically meaningful personal results for future integration into actionable insights in behavioral health.

Quantifying the interactions of bacteria with external ligands is fundamental to the understanding of pathogenesis, antibiotic resistance, immune evasion, and mechanism of antimicrobial action. Due to inherent cell-to-cell heterogeneity in a microbial population, each bacterium interacts differently with its environment. This large variability is washed out in bulk assays, and there is a need of techniques that can quantify interactions of bacteria with ligands at the single bacterium level. In this work, we present a label-free and real-time plasmonic imaging technique to measure the binding kinetics of ligand interactions with single bacteria, and perform statistical analysis of the heterogeneity. Using the technique, we have studied interactions of antibodies with single Escherichia coli O157:H7 cells and demonstrated a capability of determining the binding kinetic constants of single live bacteria with ligands, and quantify heterogeneity in a microbial population.

Many drugs are effective in the early stage of treatment, but patients develop drug resistance after a certain period of treatment, causing failure of the therapy. An important example is Herceptin, a popular monoclonal antibody drug for breast cancer by specifically targeting human epidermal growth factor receptor 2 (Her2). Here we demonstrate a quantitative binding kinetics analysis of drug-target interactions to investigate the molecular scale origin of drug resistance. Using a surface plasmon resonance imaging, we measured the in situ Herceptin-Her2 binding kinetics in single intact cancer cells for the first time, and observed significantly weakened Herceptin-Her2 interactions in Herceptin-resistant cells, compared to those in Herceptin-sensitive cells. We further showed that the steric hindrance of Mucin-4, a membrane protein, was responsible for the altered drug-receptor binding. This effect of a third molecule on drug-receptor interactions cannot be studied using traditional purified protein methods, demonstrating the importance of the present intact cell-based binding kinetics analysis.

Measuring small molecule interactions with membrane proteins in single cells is critical for understanding many cellular processes and for screening drugs. However, developing such a capability has been a difficult challenge. We show that molecular interactions with membrane proteins induce a mechanical deformation in the cellular membrane, and real-time monitoring of the deformation with subnanometer resolution allows quantitative analysis of small molecule–membrane protein interaction kinetics in single cells. This new strategy provides mechanical amplification of small binding signals, making it possible to detect small molecule interactions with membrane proteins. This capability, together with spatial resolution, also allows the study of the heterogeneous nature of cells by analyzing the interaction kinetics variability between different cells and between different regions of a single cell.