SENIOR DESIGN

The senior design is a project all students in SCU’s College of Engineering complete their senior year to apply the skills they’ve learned to a hands-on project with a real-world impact. Here are some of the bioengineering projects students have completed!

Poly(ADR-ribose) Polymerase 14-specific Inhibitor
for Hepatocellular Carcinoma

by Clarissa Silvers, Colin Sim, Ian Carter-O'Connell, Bill Lu

When Poly(ADP-ribose) 14 (PARP14) Polymerase is overexpressed in liver cells, they tend to be cancerous. Currently, there are no PARP14-specific inhibitors. Our Senior Design project aims to create a PARP14-specific small-molecule inhibitor via click chemistry techniques.

Engineering Stealthy Exosomes for Drug Delivery

by Chris Olson, Mika Domingo,
Bill Lu

This project evaluates the potential of two anti-phagocytic markers, CD24 and CD47, as exosomal surface modifications to create an immunoevasive drug delivery platform. Over-expression of these markers on the exosomal surface would allow these modified exosomes to evade destruction by macrophages and increase their survival in the body.

Immuno-anti-infective Drug Design using BioAI

by Vivian Zhang, Cathy Chen, Zhiwen (Jonathan) Zhang

Staphylococcus aureus bacteria invade mammalian cells by activating its extracellular receptor called Sortase A. Our project involves identifying a critical activating molecule of Sortase A using bioAI. Then, the inhibitor of the activating molecule is tested as a potential anti-infective drug to combat bacterial infection and antibiotic resistance.

Hydrogel Therapeutics for Protein Drug Delivery

by Francesca Briggs, Daryn Browne, Prashanth Asuri

Hydrogels are water-based polymers with the potential to act as efficient and non-invasive drug delivery systems. Throughout our experiment, we investigate different hydrogel properties that can affect drug release rates as well as how crosslinking hydrogels can potentially improve therapeutic protein delivery systems.

Wearable Health Sensor Platform

by Kelley McCarroll, George Kouretas, Unyoung (Ashley) Kim

This project aims to develop a wearable, open-source, and low-cost health sensing platform that accurately analyzes relevant biometric signals to identify early stages of illness. This will help prevent hospitalizations and severe cases of COVID-19 or other related diseases by promoting early diagnosis among significantly impacted populations.

Gastrointestinal Myoelectric Phantom (G-MAP) for Benchtop Testing

by Laura Apolloni, Takumi Simon, Vindhya Mullapudi, Prashanth Asuri, Emre Araci

Our Gastrointestinal Myoelectric Phantom (G-MAP) is a benchtop testing tool that will be used in G-Tech Medical’s preclinical studies to simulate the clinical data collected through in vivo models. This phantom allows G-tech to test the efficacy of their product in reading EMG signals produced from the gastrointestinal tract.

Minimally Invasive Continuous Glucose Monitor

by Eduardo Quintero, Justin Wong, Unyoung (Ashley) Kim

Our project revolves around increasing the resolution of our microneedle arrays as a minimally invasive continuous glucose monitoring system. It is designed to be able to penetrate the dermal layer of the skin where it will measure glucose concentration in interstitial fluid.

Shear Detection of Microencapsulated Cells for Monoclonal Antibody Production Scaleup

by Dwight Johnson, Kendall Defelippi, Maryam Mobed-Miremadi

Scale the reported hydrodynamic shear values in industrial bioreactors for monoclonal antibody production to the shear stress measured in our custom microneedle prototype by extruding microencapsulated CHO cells. A correlation between the number of extrusion loops to reduction in cell viability enables a scalable screening method for bioprocessing efficiency.

EncIDE: Encellin Implant Delivery System

by John DePalo, James Peterman, Isabelle Vidamo, Unyoung (Ashley) Kim, Verna Rodriguez

We set out to develop a minimally invasive subdermal implant delivery system to deposit Encellin's therapeutic device for the treatment of Type 1 diabetes. Following an initial incision in the forearm, our tool dispenses the implant at a standardized depth and orientation in an effort to reduce procedural variability and associated patient risks.

Non-Ribosomal In Vivo Protein Ligation

by Sarah Desautel, Victorino Miguel Francisco, Kenneth Joseph, Zhiwen (Jonathan) Zhang

Protein ligation is an integral yet inefficient process in the development of drugs and diagnostic assays. Our Senior Design project aims to improve upon current industry standards by creating a new protein ligation method that relies on a single enzyme, Sortase A, rather than tedious and error-prone in vitro techniques.

EView: High Throughput and On-Chip Characterization of Single Engineered Extracellular Vesicles

by Brendan Johnson, Jiayi Zhang, Bill Lu

Engineering extracellular vesicles (EVs) with transmembrane scaffolds holds great promise for targeted drug delivery, but EV heterogeneity imposes a significant challenge on fully understanding engineered EVs and engineering efficiency. This project aims to analyze individual engineered EVs for their biological and functional characteristics and reveal distinct capabilities of various scaffolds.

X-Messenger Molecule

by Julianna Bernardo, Jiacheng Tan, Zhiwen (Jonathan) Zhang

Knowing the fact that antibiotic-resistant Gram-positive bacteria are emerging and effective therapeutics are lacking, we will focus our engineering efforts on discovering and developing potential anti-infective therapeutics against Sortase A's messenger molecule that will not impose the risk of further antibiotic resistance and yet can effectively eliminate the pathogenic bacteria.

Artificial Lumbar Spinal Disc Implant

by Sara Layton, Nikhil Pai, Michael Rueckert, Bill Lu, Maryam Mobed-Miremadi

We are designing an Artificial Lumbar Spinal Disc Implant to counter degenerative disc disease within patients as well as alleviate back pain. Our goal is to create a long lasting restorative disc with an emphasis on revise-ability for patients in the case of repeat surgeries.

Flow Visualization of Bolus Microcapsule Delivery through 3D Printed Microneedles

by Lexi Enstrom, Sophie Quisling, Leana Vestal, Maryam Mobed-Miremadi

Microneedles enable painless delivery and withdrawal of biologicals through the dermis. Operating within the therapeutic range, flow and microcapsule trajectory through the custom 3D printed device were simulated pre-puncture. Using the validated model, multiple failure modes of the 3D printed artifacts were tested to determine their effect on flow profiles.

Skin Phantoms for Biowearable Testing

by Brooke Fitzwilson, Ruby Karimjee, Jordan Spice, Emre Araci, Prashanth Asuri

The biowearable device industry is in need of a model that can accurately mimic the properties of skin. Our project design includes a skin phantom and corresponding COMSOL simulation, which emulates the perspiration and impedance spectrum behavior of human skin.

G-MAP: Gastrointestinal Myoelectric Activity Phantom

by Kei Castleberry, Sarah King, Edie O’Connor, Prashanth Asuri, Shoba Krishnan

This project aims to develop a phantom that can accurately emulate the myoelectric activity of the stomach, small intestine, and colon. The phantom will meet the biowearable industry’s need for a synthetic platform to test devices that non-invasively measure the motility of the gastrointestinal tract.

Minimally Invasive 3D Printed Microneedles for Glucose Monitoring

by Daniel Bermudez, Josephine Semaan, Amanda Yaung, Unyoung (Ashley) Kim

With the purpose of making patient care for diabetics more affordable, accessible, and reliable, our project aims to create a minimally invasive glucose monitoring system through the use of 3D printed microneedles. This system would have extensive applications in helping improve patient care for diabetics.

Microfluidic Barcode Device for Human Movement Data Storage

by Justin Culpepper, Gianna Gathman, Katie Neighbors, Emre Araci

We have developed a computer model of a novel wearable microfluidic strain sensor to support human physical therapy. Our microfluidic pump design uses the skin strain produced by movement to create a fluidic pattern that resembles a barcode. This device will provide patients and clinicians information to bridge inter-appointment gaps.

Classification of Breast Cancer Using Deep Learning and Mammogram Images

by Travis Kay, Derrick Nguyen, Lashan Wijayawickrama, Yuling Yan

Using an open-source mammography dataset, we examined several pre-trained convolutional neural network (CNN) models to find the best model for classifying breast masses and cysts. This CNN model can be used to assist radiologists in rapid screening of breast cancer and improving the diagnostic accuracy.

MilkGuard: Predictive Modeling and Mobile App Development

by Beau Hsia, Emma McCurry, Unyoung (Ashley) Kim, Maryam Mobed-Miremadi

MilkGuard aims to produce a sensitive, low-cost, and environmentally friendly biosensor that can detect the presence of E. Coli in donated human breast milk. This year, we focus on building 1) a dynamic CAD model of our colorimetric assay and 2) a user-friendly mobile app that interfaces with our sensor.

Classifying Brainwaves for Brain-Computer Interface Technology

This project's aim is to utilize pre-trained image classification networks to develop a deep learning (DL) model for signals recorded via electroencephalography (EEG). We focused on the classification of motor imagery tasks, which is useful for the development of brain-computer interfaces (BCIs).

Predictive Model for Design of a 3D Developmental Neurotoxicity Platform

We worked on developing a predictive model, based on literature review and statistical analysis, to test developmental toxicity on early neuronal differentiation in three-dimensional cell culture. Such models may be useful for clinical and pharmaceutical research.

Optical Strain Sensor for Physical Activity Assessment

by Michael Cromie, Kristen Mosher, Emre Araci

Our objective is to design a wearable optical strain sensor to track the physical activities of the upper extremities. Activity sensors currently on the market lack sensitivity, directionality, and electromagnetic immunity. Our optical sensor will provide wavelength-multiplexed spatial data with a single input/output, hence enabling simpler human-wearable device interfacing.

A Microfluidic SMILE: Sensor for Mental Illness Evaluation

by Keala Johnson, Nicole Keller, Shriya Syal, Emre Araci

We develop wearable microfluidic sensors to monitor human emotions. The skin deforms with changing facial expressions, causing strain on our sensors. This strain is converted to the displacement of ionic liquids and measured electrically or optically. The technology can be used in the management and diagnosis of mental health disorders.

Power Generation by Genetically Modified Bacteria in a Microbial Fuel Cell

by David Bengford, Sarah Khoilian, Ann McMonigal, Maryam Mobed-Miremadi

Our project aims to examine the potential of fourth-generation biofuels (genetically engineered bacteria) in a microbial fuel cell (MFC). Our primary research objective is to improve the consistency of the system's power generation over time. Our work will contribute to the fields of bioengineering, materials, and sustainable energy.

Microfluidic Multi-Complication Cancer Test

by Brendan Heap, Samuel Nichols, Anthony Ramirez Guerrero, Emre Araci

Circulating tumor cells (CTCs) are cells shed into the vasculature from a tumor and can metastasize to other organs. Our objective is the development of microfluidic and microfabrication technologies for label-free detection and isolation of CTCs and CTC clusters.

CERVIS: Cervical Cancer Early Response Visual Identification System

by Kira Palazzo, Lauren Serfas, Juliana Trujillo, Lauren Cherrey, Will Nelson, Prashanth Asuri, Michele Parker, Craig Stephens

The aim of CERVIS is to develop a low-cost, minimally invasive, highly specific screening device to detect cervical cancer in low-resource settings, mainly Uganda. The device will indicate the presence of fusobacteria, one that is highly correlated to cervical cancer diagnosis.

Predicting Depression Progression Rates in Radiotherapy Patients

by Ardella Phoa, Joshua Vincent, Shani Williams, Yuling Yan

Depression affects more than 10% of cancer patients worldwide and lowers the efficacy of radiotherapy treatments. Recent research shows that PET scans capture depression biomarkers in the brain. We use these images to train a convolutional neural network to identify these biomarkers and classify depression progression rates in radiotherapy patients.

Brainwave Distinguishing Network for EEG Control

by Brent Baculi, Stu Cansdale, Yuling Yan

Creating a neural network trained on EEG data that differentiates between focused and relaxed states in the brain. The goal of this network is to provide an alternative control method for people with motor disabilities.

Milkguard from Assay to Kit: Sensor Geometry Optimization

by Emily Brogan, Ariana Haddad, Bridget Woody, Ashley Kim, Maryam Mobed-Miremadi

MilkGuard, a hydrogel-based sensor, utilizes enzymatic reactions to produce colorimetric change when E. coli is present in donated human breast milk. By optimizing extraction processes, accounting for the variability of conditions, and comparing strains of bacteria, our project lowers the limit of detection of the sensor and verifies robust data collection.

Engineering a Switchable Nanosystem for Customizable Therapeutics

by Hanzhe Chen, David Diebold, Bill Lu

We are attempting to engineer an exosome with a switchable protein system that can be used for a variety of therapeutic purposes. Our engineered exosome binds to a specific peptide neo-epitope (PNE) which can then be fused with other antibodies to specifically target various surface proteins.

Novel Cancer Treatment Using Engineered Exosomes to Disrupt Cancer’s Immune Escape

by Abena Boateng, Carley Fowler, Maritza Soria, Bill Lu

Our project is to engineer exosomes to create a novel cancer treatment. This immunotherapy treatment would use exosomes to promote the eradication of cancer by disrupting the PD-1 and PD-L1 immune-escape pathway exploited by cancer cells. Immune-escape pathway disruption would allow killer T-cells to eliminate the diseased cells.

Identification of Messenger Molecule Between Mammalian and Bacterial Cells

by Anna Fraser-Philbin, Alexander Heiler, Zhiwen (Jonathan) Zhang

The messenger molecule between bacterial and mammalian cells is identified by using chemical cross-linking techniques to capture and mass spectrometry to analyze the ligands. The molecules will serve as novel drug targets for the development of anti-infective immunotherapeutics.

Engineering a Synthetic Antibody for Pancreatic Cancer Detection

by Madison Beary, Kyle Carter, Nathaniel Girma, Zhiwen (Jonathan) Zhang

We aim to purify a synthetic antibody that incorporates the unnatural amino acid L-DOPA to take advantage of sugar binding interactions between antibody and antigen, with strength comparable to a monoclonal antibody. This will greatly improve upon the potential diagnostic and therapeutic applications for this disease.

CERVIS: Cervical Cancer Early Response Visual Identification System

by Claire Hultquist, Julia Lanoha, Rosie McDonagh, Hallie McNamara, Prashanth Asuri, Michele Parker, Craig Stephens

Our project aims to address the high rates of cervical cancer in the developing world. We are trying to develop a low-cost, minimally invasive, visual identification device that tests for bacterial changes in the vaginal microbiome as an indication of cervical cancer.

Noninvasive Screening of a Fecal Biomarker for Human Necrotizing Enterocolitis (NEC)

by Daniela Campa, Kyle Sullivan, Zhiwen (Jonathan) Zhang, Guo-Zhong Tao

Our project is discovering a biomarker for NEC, an often-fatal disease affecting approximately 10% of premature neonates. Currently, diagnosis of NEC is based on relatively nonspecific clinical and radiographic markers. The biomarker of interest would ultimately facilitate early diagnosis through a definitive diagnostic test, and consequently increase survival rate.

Anti-infective Mechanism-Based Drug Discovery by Targeting Sortase A

by Huong Chau, Leepakshi Johar, Alice Matsuda, Zhiwen (Jonathan) Zhang

The objective of our senior design project is to confirm that Vitamin B12 will act as the single most efficient drug candidate in vitro to identify virulence factors from gram-positive bacteria. Ultimately, the main long-term goal of this project is to develop more effective drugs to treat MRSA.

Personalized Protein Corona

by Karl Baumgartner, Madeline Eiken, Prashanth Asuri, Korin Wheeler

Engineered nanoparticles have broad applicability in drug delivery, bioimaging, and medical devices. However, applications are limited by incomplete understanding of how binding of plasma proteins to nanoparticles affects their interactions in the body. We intend to explore the impact of varied protein modifications on nanoparticle biochemistry and toxicity.

High-Throughput, Portable Microfluidic Aptamer Assay

by Matthew Curtin, Atticus McCoy, Emre Araci, Steven Suljak

We aim to develop a microfluidic assay platform capable of high-throughput aptamer-based analysis. We intend to perform all steps of the assay on chip. Therefore, the assay will utilize normally closed valves so the chip can be transported without external pneumatic pressure.

Microfluidic Chip for High Efficiency Microinjection of C. elegans

by Delaney Gray, Alex Hadsell, Jessica Talamantes, Emre Araci, Leilani Miller, Don Riccomini

Our microfluidic chip conducts high efficiency microinjection of C. elegans. Traditional microinjection is a tedious and error-prone procedure requiring an expert. Our chip seeks to increase microinjection efficiency, consistency, and accessibility to researchers of all experience levels in order to advance genetics research and genetic engineering technology in C. elegans.

Nebu-Flask: Advancing Usability of Nebulizers to Increase Patient Compliance

by Murray Bartho, Michael Breshock, Megan Nolte, Prashanth Asuri

Nebulizers on the market today do not address the needs of patients as they are difficult to travel with and uncomfortable to use in public. Inspired by a local pediatrician, our design looks to improve on current issues in portability, usability, and social stigma associated with existing nebulizers.

Assessment of Hand Gestures Using Wearable Sensors and Fuzzy Logic

by Angel Cardenas, Ryan Messersmith, Will Newcomb, Emre Araci, Prashanth Asuri

In modern motion sensing of upper extremity motions for rehabilitation, there exists a lack of justification for the selected adhesives and interfacing methods. Our team’s objective is to identify a specific combination of sensor placement and adhesion that enables us to distinguish motion patterns using the fewest number of sensors.