An ideal diagnostic imaging technique would be safe, inexpensive, and provide both molecular and spatial information to the physician. Current diagnostic imaging technologies are expensive, time consuming and/or lack molecular information to aid in the diagnosis. My research focuses on developing novel, inexpensive, and convenient (for improved compliance) optical diagnostic agents to detect inflammatory diseases such as rheumatoid arthritis and monitor treatment response.
The tumor microenvironment is abnormal and complex. Unorganized and hyperpermeable tumor vasculature leads to uneven drug distribution and less effective treatment. I am investigating the use of combination therapies to modulate the tumor vasculature to increase efficacy. Understanding the temporal dependence of combination therapy can elucidate optimal windows of delivery to improve current and future cancer therapies.
Antibody-drug conjugates can stimulate immune system via interaction between FcRs and Fcs. Previous research has proved that the payloads (drug) also have the potential to encourage immune response. I'm making a head to head comparison of different payloads on their abilities to stimulate dendritic cells which, due to their antigen-presenting mechanism, are important in the entire process of immune response. I'm also using pharmacokinetic model and will be using a hybrid angent-based model to do some simulation.
Co-advised by Prof. Jennifer Linderman
Antibody-drug conjugates (ADC) have the advantage of targeting tumor cells and directly delivering payloads (drugs) into them. However, we often confront the challenges of the uneven distribution of ADC and less efficient penetration. Analyzing the transport properties of ADC as well as understanding its interaction with the immune system is significant for improving the drug efficacy. I am working on the characterization of antibody-drug conjugates for enhanced distribution in the cancer cells and immune responses.
Using agent-based modeling, I will be studying the relationship between antibody drug conjugates and immune cells for cancer therapies. This model will be able to predict the impact of ADC drug distribution in tumors and capture improved responses with increased tissue penetration.
Co-advised by Prof. Jennifer Linderman
A number of antibody-drug conjugates (ADCs) have been approved by the FDA and more are in early clinical trials and preclinical development. An important aspect about ADCs is their ability to combine the potency of small molecules and the targeting of antibodies. I am studying the characteristics of ADCs and the factors within the tumor microenvironment that affect and influence their efficacy as anti-cancer agents.
I am working on protein engineering and antibody drug conjugates.
Co-advised by Prof. Peter Tessier
I am working on the protease-activated T-Cell Engager that cross-link tumor cells with T-Cells via a bispecific protein therapeutic. A working system pharmacology model will be developed to capture the systemic distribution of it and to validate uptake and distribution in a mouse xenograft model.
Dr. Bruna Menezes/Scheuher, Ph.D 2020, now at Applied Biomath
Dr. Eshita Khera, Ph.D 2020, now at Novartis
Yinuo Chen, Masters 2020
Dr. Lydia Atangcho, Ph.D 2020, now at BCG
Dr. Tejas Navaratna, Ph.D 2020, now a post-doc at UCSB
Dr. Mukesh Mahajan, Postdoctoral researcher (2019)
Dr. Cornelius Cilliers, Ph.D 2018, now at Mirati Therapeutics
Dr. Sumit Bhatnagar, Ph.D 2018, now at AbbVie
Dr. Liang Zhang, Ph.D 2017, now at AbbVie
Emily Deschenes, Masters 2016
Dr. Kirti Dhingra, Postdoctoral Fellow (2013-2014)