08/02 - Maryam's poster won second place at the SURF Symposium. Congratulations!
08/01 - Group alumnus, Shipeng Xu, joins Masters program at Northwestern. Good luck!
07/14 - Dr. Solorio gives talk at Amelia Project
​
08/02 - Maryam's poster won second place at the SURF Symposium. Congratulations!
08/01 - Group alumnus, Shipeng Xu, joins Masters program at Northwestern. Good luck!
07/14 - Dr. Solorio gives talk at Amelia Project
​
08/02 - Maryam's poster won second place at the SURF Symposium. Congratulations!
08/01 - Group alumnus, Shipeng Xu, joins Masters program at Northwestern. Good luck!
07/14 - Dr. Solorio gives talk at Amelia Project
​
08/02 - Maryam's poster won second place at the SURF Symposium. Congratulations!
08/01 - Group alumnus, Shipeng Xu, joins Masters program at Northwestern. Good luck!
08/01 - Anastasiia Vasiukhina joins the lab co-advised by Dr. Solorio and Dr. Vlachos. Welcome!
07/14 - Dr. Solorio gives talk at Amelia Project
​
Tissue
MicroEnvironment & Therapeutics Lab (TMET)
Research Topics
The TMET Lab engineers physiologically-relevant in vitro platforms, scaffolding, and other devices to investigate key cellular events, improve regeneration, or perform precision medicine tests clinically.
Some of our models include:
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A micro-actuating lung model
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A pre-metastatic niche and wound healing mimetic
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Mandible scaffolding for bone regeneration
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Tissue property and physiology characterization
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A tumbling robot for precise movement of payload in patients
These platforms use a variety of matrices, cell types, and tissues to study or improve patient outcomes related to regenerative medicine, drug delivery and cancer progression.
Cancer Research
Using our developed in vitro platforms, we can study how microenvironmental elements act individually and in concert to drive cancer cell responses, including migration, proliferation, and dormancy. Our lab also studies how the tumor microenvironment influences resistance to targeted therapies in HER2+ breast cancer.
Some of our current projects include:
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Understanding how ECM and mechanical changes in the premetastatic niche fuel metastatic cell dormancy and reactivation
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Investigating the role of tissue cross-linking enzymes in antibody-drug conjugate resistance in breast cancer
Controlled Delivery Bone Graft
The current standard of care of periodontal guided bone regeneration is limited by its variability, prolonged patient exposure to potential infection during surgery, as well as tight packing, often leading to diminished bone regeneration as blood vessels may fail to form. Although this method benefits from innate growth factor release, it is often uncontrolled and poorly defined.
We seek to enhance existing methodologies by:
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utilizing 3D printing technology to fabricate a fully biodegradable, patient-specific device with controlled release of growth factors to foster improved vascularization and osteointegration.
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using in silico finite element analysis (FEA) in tandem with in vitro experimentation and optimization of mechanical properties to achieve superior outcomes.
Tissue Physiology and Characterization
We work to develop improved delivery and transport of therapeutics by understanding the effects that local tissue properties have on transport phenomena.
Microrobots and Controlled Release Systems
Microrobots have been shown to have promising capabilities for targeted drug delivery for patients with health conditions. In collaboration with the NIH, our research centers on advancing controlled drug release systems for precise, localized delivery. We also focus on the creation of extended release polymer-based in situ forming implants (ISFI) to treat opiate use disorder.
Our current projects include:
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Creating magnetically actuating microrobots for targeted therapeutic delivery of mesalamine in the colon using techniques such as electrospraying and focused ultrasound systems.
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Developing an extended release polymer-based in situ forming implant (ISFI) that releases buprenorphine over an extended period of time to increase patient compliance
Image Processing
Our lab has developed an image-based algorithm for detection and tracking of cells. Relevant cell feature parameters such as position, diameter, mean intensity, area, and orientation are obtained across a set of images. Our technique achieved a minimum of 92% detection and tracking accuracy, compared to 16% from state of the art methodologies.
Current research efforts focus on improving the robustness of the algorithm by enhancing segmentation of cells alongside feature extraction.
