Speaker: Dr. Rashmi Mohanty

Title: Extracellular Matrix- A Transport Barrier for Drug Delivery

Abstract: Extracellular Matrix (ECM) determines crucial cellular responses through cell-matrix interactions. Specific qualitative and quantitative changes occur in the ECM during disease and, in part, regulate critical events that determine pathological tissue phenotype. For example, in solid cancers, the extraordinarily dense fibrotic ECM is primarily responsible for the increased interstitial tissue pressure and stiff mechanical properties. The resulting dense stroma impedes the transport of therapeutic anticancer drugs, limiting effective drug delivery and, therefore, the therapeutic potential of drug candidates. To overcome the tumor ECM drug delivery barrier, during my PhD, I leveraged favorable surface physicochemical interactions between the tumor ECM and drug carriers to enhance the delivery and, hence, the therapeutic outcomes of antitumor drugs. I used genetically engineered peptide-presenting phage libraries as a high-throughput approach to screen and identify peptide coatings that would facilitate improved transport through the tumor microenvironment. Interestingly, in contrast to most studies, I found that a positively charged peptide “surface” enhanced penetration, uptake, and retention of particles in tumor tissue when compared to neutrally charged peptides. Next, I conjugated the peptide to immune checkpoint inhibitor antibodies, which, in a murine melanoma tumor environment, recruited a higher number of activated tumor-infiltrating T-cells, resulting in delayed tumor growth.

Having worked with cell culture, ex vivo tissue culture, and animal model development during my Ph.D., I realized there is an unmet gap in developing models that can more easily recapitulate the dynamic and transport features of disease. Believing that the emerging, complex multicellular 3D organoid systems would more accurately reflect the human physiological environment, I joined the Weiss lab for my postdoctoral study to implement synthetic biology tools for organoid design. Currently, I am working on recapitulating the native-like organ architecture in liver organoids by mimicking the honeycomb-like patterns in human livers. Combining synthetic biology, micro-robotics, and machine learning, we deliver biological cues at precise locations to control the differentiation of human-induced pluripotent stem cells (hiPSCs) in a spatiotemporal fashion.

Although organoids have emerged as the next-generation tool for disease modeling and drug screening, the formation of matured organoids remains a challenge, partly because the current models lack the natural context of endogenous cell-governing ECM secretion and assembly formation. In my future research program, I will employ synthetic biology principles to genetically engineer hiPSCs to secrete relevant ECM (as occurs in vivo) for designing tailor-made disease-specific organoids to investigate drug transport and drug delivery with an aim to accelerate the drug development pipeline.

About the speaker: Dr. Rashmi Mohanty is am a postdoctoral associate in the Department of Biological Engineering at the Massachusetts Institute of Technology. My current work focuses on employing synthetic biology tools to control cell fate decisions for the formation of programmable organoids. She has completed Ph.D. in the College of Pharmacy at the University of Texas at Austin (UT). During Ph.D., she worked on developing therapeutic moieties that can overcome the transport barrier of the tumor microenvironment for improved drug delivery. Prior to matriculating at UT, she received my Bachelor of Technology in Chemical Engineering from the National Institute of Technology (NIT) Rourkela and my Master of Technology in Chemical Engineering from the Indian Institute of Technology (IIT) Kanpur. Building from my knowledge and gained experiences with the limitations of current models used to recapitulate stroma-rich disease environments, in the long run, she is interested in designing 3D models that better reflect various disease environments to accelerate the progress of disease diagnostics and drug discovery.