2025-2026 projects will be posted below
The Capstone Design Project proposals listed below are available to undergraduate students in the Department of Bioengineering. Please note that each project is designed for teams of 1 to 4 bioengineering students. Students interested in a specific project are encouraged to express their interest by emailing the project supervisor.
Please note that the deadline for students choosing projects is September 16th, and the deadline for faculty submitting proposals is September 5th.
Supervisors: if you note an error in your posting, please email allen.ehrlicher [at] mcgill.ca
- Roles and Responsibilities of Project Supervisors
- Industrial Sponsorship of Undergraduate Project Courses in Bioengineering: Information for Students, Staff and Industrial Sponsor
Project 1:
Bioinspired Design of a Biodegradable Chitosan-Based Composite as a Sustainable Glass Alternative
Supervisor: Prof. Allen Ehrlicher allen.ehrlicher [at] mcgill.ca , Hardik Singla hardik.singla [at] mail.mcgill.ca
Preferred Team Size: 2 (flexible)
Background and Objectives:
Glass is a cornerstone material in modern life, used in electronics, façades, and packaging. Its unique transparency and hardness make it indispensable, but its brittleness, high energy footprint, and persistence in landfills underscore the urgent need for sustainable alternatives.
This project adopts a bioinspired materials engineering approach to develop a transparent, biodegradable composite based on chitosan (CS), a naturally derived polysaccharide with inherent biocompatibility, biodegradability, and film-forming ability. By integrating bioinspired reinforcement strategies, including chitosan nanocrystals (ChNCs) and glass flakes, the material aims to replicate the strength, toughness, and optical clarity of conventional glass, while addressing its sustainability challenges.
The work also builds on the notable achievement of a nacre-inspired glass composite that successfully combined strength, toughness, and transparency, a key inspiration for our approach. Additionally, the Ehrlicher Lab has already carried out preliminary investigations into chitosan-based film casting, reinforcement strategies (using ChNCs and glass flakes), and initial optical testing, providing an invaluable foundation for this systematic design and optimization effort.
Objectives:
- Engineer a biopolymer nanocomposite that combines chitosan with tailored reinforcements for glass-like performance.
- Explore biomimetic design principles to improve fracture toughness and optical clarity.
- Characterize the structure–property relationships governing mechanical resilience, transparency, and biodegradability.
- Demonstrate a proof-of-concept material that could be applied in green packaging, disposable optics, and sustainable biomedical devices.
Description of Design Component:
The design work will focus on bioinspired fabrication, multiscale characterization, and optimization:
- Bioinspired Composite Fabrication
- Prepare chitosan-based matrices through solution casting and thermal processing.
- Incorporate reinforcements (ChNCs, glass flakes) for hierarchical strengthening.
- Optimize additive and dopant processing to achieve uniform dispersion and optical transparency.
- Multimodal Characterization
- Mechanical: tensile, flexural, and impact testing to assess toughness and modulus.
- Optical: UV-Vis spectroscopy and refractive index measurements for clarity.
- Morphological/Chemical: SEM and Raman to probe microstructure and interfacial bonding.
- Thermal: TGA and DSC to assess thermal stability and transitions.
- Swelling Studies: immersion-based swelling and solvent uptake measurements to evaluate network crosslink density and dimensional stability.
- Sustainability: biodegradation assays (soil burial, enzymatic digestion) to benchmark eco-performance.
- Optimization & Structure–Property Mapping
- Quantify the reinforcement effect of ChNCs vs. glass flakes.
- Establish structure–property correlations between composition, mechanics, and optics.
- Benchmark against traditional soda-lime glass and existing polymer composites.
- Outcome
- A bioinspired, biodegradable “glass-like” composite that demonstrates strong potential for sustainable, circular material systems.
Expectations:
By the end of the project, the team is expected to have:
Completed task 1, made significant progress on task 2, especially in mechanical and optical analyses, and completed task 3, establishing clear correlations between formulation and performance.
Skills students will gain:
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- Design and fabrication of bioinspired polymer composites.
- Techniques for nanomaterials dispersion and interface engineering.
- Multiscale analysis of mechanical, optical, thermal, swelling and sustainability metrics.
- Translating bioinspired design concepts into practical sustainable technologies.
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Project 2:
Bioinspired PMMA–PU Interpenetrating Polymer Networks Reinforced with Glass Flakes for Tough and Transparent Composites
Supervisor: Prof. Allen Ehrlicher allen.ehrlicher [at] mcgill.ca , Hardik Singla hardik.singla [at] mail.mcgill.ca
Preferred Team Size: 1 (flexible)
Background and Objectives:
Glass is widely used in packaging, optics, and structural applications because of its transparency and hardness, but its brittleness and low fracture toughness limit its use in advanced engineering contexts. A key challenge in materials design is to produce transparent composites with improved fracture resistance, toughness, and strength, without sacrificing optical clarity.
This project will explore interpenetrating polymer networks (IPNs) of poly(methyl methacrylate) (PMMA) and polyurethane (PU), reinforced with glass flakes and modified with additives/dopants to optimize optical properties. IPNs are known to combine rigidity (PMMA) with toughness and elasticity (PU), providing a versatile platform for bioinspired material design.
By building on prior nacre-inspired composite strategies, this project aims to replicate the hierarchical toughening mechanisms found in natural materials, producing a composite with superior mechanical resilience and glass-like transparency.
Objectives:
- Develop and optimize a PMMA–PU interpenetrating polymer network reinforced with glass flakes.
- Achieve refractive index matching through dopants to preserve optical clarity.
- Characterize the mechanical, optical, thermal, and swelling performance of the composites.
- Benchmark the composite’s performance against conventional glass and single-network polymers.
Description of Design Component:
- IPN Composite Fabrication
- Prepare PMMA–PU IPNs through controlled polymerization and curing.
- Incorporate glass flakes for reinforcement.
- Introduce dopants and additives to fine-tune refractive index matching and transparency.
- Multimodal Characterization
- Mechanical: tensile, flexural, and impact testing to quantify modulus, toughness, and energy absorption.
- Optical: UV–Vis spectroscopy and refractive index measurements to assess transparency and clarity.
- Morphological/Chemical: SEM and Raman spectroscopy for microstructure and interfacial analysis.
- Thermal: TGA and DSC to assess thermal stability and transitions.
- Optimization & Structure–Property Mapping
- Optimize the PMMA–PU ratio to balance stiffness and toughness.
- Study the effects of glass flake reinforcement and dopants on strength and transparency.
- Establish structure–property correlations between polymer chemistry, reinforcement, and composite performance.
Expectations:
By the end of the project, the student/team is expected to have:
- Completed Task 1 (IPN Composite Fabrication).
- Made significant progress on Task 2 (Multimodal Characterization), especially mechanical, optical, and swelling analyses.
- Completed Task 3 (Optimization & Structure–Property Mapping), with clear correlations between reinforcement strategies and material performance.
Outcome:
A bioinspired IPN composite with glass-like transparency, superior toughness, and tunable performance, providing a pathway toward next-generation transparent structural materials.
Skills Students Will Gain:
- Fabrication of interpenetrating polymer networks and reinforced composites.
- Use of additives and dopants for optical property control.
- Multiscale analysis of mechanical, optical, and thermal properties.
- Application of bioinspired design strategies to engineer high-performance transparent materials.
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Project 3
Development of an open source 3D bioprinter with multi-extrusion capabilities to bioprint miniaturized tissues comprised of multiple cell types
Supervisor: Prof. Darcy Wagner, darcy.wagner [at] mcgill.ca
Preferred Team Size: Any
Background and Objectives:
3D bioprinting has become a disruptive technology due its ability to generate humanized tissues on demand. These tissues are envisioned to one day be transplantable to replace diseased or damaged tissue. While this reality is farther in the future, 3D bioprinting has recently shown immense potential to model normal tissue development as well as diseases in a more physiologic environment and with multiple cell types (e.g. cancer). However, the cost of commercially available 3D printers is generally far more than what an individual lab can purchase for routine usage. Furthermore, the technology remains relatively immature and is rapidly evolving. Therefore, having the ability to readily adapt a printer to diverse research needs is critical to enabling rapid advances within the academic space.
The goal of this project is to advance the previous work in the lab in building a generation 2.0 3D bioprinter that is open source and which has extended capabilities for bioprinting constructs containing more than one cell type. While culturing in physiologic conditions (e.g. matrix composition, mechanical environment or environmental controls like oxygen) have been shown to be critical, the importance of including multiple cell types in 3D tissue models has become apparant. This enables self-assembly of tissues into more physiologic structures (e.g. to overcome inherent limitations of manufacturing) and provides a more biomimetic environment with which to model tissues.
The student design team will be responsible for identifying design criteria for next generation, open source bioprinters to enable manufacture of multicellular, miniaturized tissue constructs. Furthermore, the team will be responsible for developing custom bioreactors to support the maturation of these tissues to assess functionality of the tissue.
Description of design component:
· Identify critical design components needed to support bioprinting multicellular tissues
· Select a miniaturized tissue or disease to model
· Design, manufacture and validate a bioreactor which can support this multicellular construct
Economic and social impact:
Due to the high cost of current 3D bioprinters and high interest in leveraging this technology to make advances in tissue engineering and disease modeling, there is a need for lower cost systems. This project offers commercial/innovation/economic potential across multiple stages of the project: 1) bioprinter design, 2) bioink design and 3) bioreactor design.
Skills requested or to be developed:
Experience in 3D printing, polymer science, mammalian cell culture, microscopy (light or electron based). Students will gain experience in material selection, cytocompatible/non-toxic design principles, mammalian cell culture, work with primary human cells, bioreactors, and cell and molecular biology techniques required to validate tissue function.
Our lab focuses on how the extracellular environment directs stem cell behavior for endogenous and exogenous lung tissue regeneration. We use a multidisciplinary approach using advances in materials science (polymer design and synthesis), manufacturing (e.g. 3D bioprinting), and endogenous and iPSC-derived lung stem cells to construct these new models.
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Project 4
In-vitro (IVT) production of template DNA for mRNA manufacturing.
Supervisor: Prof Amine Kamen, amine.kamen [at] mcgill.ca
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https://amine-kamen.lab.mcgill.ca
Preferred Team Size: 3
Background and Objectives:
Building on the outcomes of prior work, this project will focus on In Vitro DNA Amplification Using Rolling Circle Amplification (RCA) for mRNA manufacturing. Ng/ul DNA can be amplified to ug/ul withing hours. Purpose: To bypass slow and resource-intensive bacterial DNA amplification by implementing isothermal RCA for high-yield, cell-free DNA production suitable for IVT of mRNA
Description of design component:
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• Optimization of Circular plasmid template amplified using phi29 DNA polymerase for maximization of product yield.
• Resulting DNA directly compatible with IVT of mRNA with minimal purification requirements.
This will be optimized through the development of a Digital Twin for the process and validation experiments.
Economic and social impact:
For cost-effective manufacturing of mRNA vaccines and equitable distribution.
Skills requested or to be developed:
Modelling and digitalization of biochemical reactions and Bio-Process optimizations.
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Project 5 (taken)
Development of Soft Robotics for Endoscopic and Percutaneous Spine Interventions
Supervisor: Amir Hooshiar, amir.hooshiar [at] mcgill.ca
Preferred Team Size: 5
Background and Objectives:
Goal is to develop a minimally invasive surgical robot for the spine that aides in the specific reconstruction of spinal bones post-cancer lesions.
Objectives include conceptualizing a spinal robot's early prototype that can be tested in-vitro while addressing user (surgeons) pain points in clinical surgeries.
Description of design component:
This encompasses the following skillsets: biocompatibility and pathological scope; AI in spatial, vision, and classification; surgical robotics in their medical-grade material requirements, programming, and controller logic; mechanics in CAD designs and kinematics; and the actual software interactions, real-time UI, and comms protocols.
Economic and social impact:
Post-cancer lesions in the spinal bones can lead to complications such as paralysis. This project may minimize complications and improve surgical success rates, which can reduce cost of complications and directly improve patient outcomes.
Skills requested or to be developed:
Operating system of a robot, end-to-end conceptualizing the way the surgical robot would operate, clinical translation and feedback from surgeons, and more specifically prototype best practices.
As for technical skillsets, this project would assist the students in applying:
- biocompatible materials for intra-spinal operation
- spinal-compatible cement and tissue interactions
- Real-time computer vision applications for a robot (Python OpenCV)
- Robotics operating system (Python/C++)
- Programming (Java, Python)
- Controller logics & kinematic movements in line with surgical needs
- Research & critical thinking in finding proper metrics for the success of the robot's operation
- soft robotics design
- mechanics and CAD specifications
- cross software integrations to include real-time UI, comms protocols, and controller functions
- stages of readiness
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Project 6 (taken)
Developing a robotic bioprinter for reconstructive esophagectomy procedures
Supervisor: Prof Joseph Kinsella, joseph.kinsella [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives:
This project will develop a hydrogel depositing robot using a 3D continuum printing tool as an in situ 3D bioprinter. This includes designing, building, and modeling a miniature continuum printing tool tip capable of extruding tissue adhesive gels and integrating the tool into a 6 Degree of Freedom (DoF) robotic arm. The primary objective is to develop the instrument for automated image-guided printing by integrating the robotic system with an imaging system. The near-term goal is to evaluate the robotic printer via proof-of-concept experiments that demonstrate regenerative gels precise and reproducible motion and location of the extrusion toolhead. Additionally, developing and modeling the gel flow, designing extrusion systems and tool heads, and integrating the image-guided cameras, image processing, and controls necessary for esophagectomy and depositing regenerative materials at the resection site.
Description of design component:
The design component will focus on developing a robotic arm–based hydrogel printing system that incorporates programmable extrusion controls, rheological characterization, and modular printheads. Students will design and fabricate hardware enclosures, build electronic subsystems for valve and pump actuation, and develop control software (ROS 2, Python, MATLAB) to enable automated bioprinting. The system will be validated using synthesized hydrogels to assess printability, precision, and mechanical integrity.
Economic and social impact:
Economically, this project addresses the need for scalable, cost-effective bioprinting technologies. Societally, it contributes to advancing medical solutions for patients with soft tissue damage, particularly in conditions such as vocal fold scarring, thereby improving quality of life and reducing long-term healthcare costs.
Skills requested or to be developed:
The student team is expected to have programming skills (Python, MATLAB, Arduino) and mechanical skills such as soldering, circuit board assembly, and robotic arm repair. They should also possess basic laboratory skills for hydrogel development including design, synthesis, and characterization. Experience in 3D modeling software (Fusion 360 or SOLIDWORKS) is required. The team is expected to further develop expertise in ROS 2, robotic kinematics, and fluidic simulations (ie., Ansys).
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Project 7 (taken)
Microfluidic Platform for Sequential Integration of Vascular cells and Islet Organoids
Supervisor: Dr. Corinne Hoesli and Dr. David Juncker (Engineering) Yasaman Aghazadeh (Experimental medicine) ; corinne.hoesli [at] mcgill.ca, david.juncker [at] mcgill.ca and yasaman.aghazadeh [at] mcgill.ca
Preferred Team Size: 1
Background and Objectives:
This project aims to design and test a microfluidic device that enables sequential seeding of vascular cells followed by pancreatic islet organoids for disease modeling and studying tissue interactions. In conventional organ-on-a-chip systems, all cells are seeded simultaneously, whereas in native tissues vessel networks first form through vasculogenesis, become perfused, and then support the development of adjacent organs. In peripheral tissues such as pancreatic islets, cells interact mainly with vessels undergoing angiogenesis or stabilized vessels. Because vasculogenesis, angiogenesis, and stabilization are driven by distinct signaling pathways, these stages can differentially influence organoid fate and function. To replicate these processes more accurately, vessel networks should form before islet seeding; however, current devices do not permit sequential cell addition. We propose redesigning the cell chamber of commercial microfluidic devices to allow multiple openings and closings and develop a home-made 3D printable replica. In this system, vascular cells would first be seeded and cultured to establish a perfusable, stable vessel network. After validating perfusion and barrier function, the chamber could be reopened to introduce islet organoids. We hypothesize that pre-establishing a vascular network will enhance islet survival and function while providing a more physiologically relevant platform for diabetes modeling.
Description of design component:
The main design component is a modified cell chamber that can be opened and resealed, enabling sequential cell seeding and manipulation. This chamber will be constructed both with 3D printing, and with PDMS replica of the device, allowing a home-made vascularized islet on a chip platform.
Vascular cells would be introduced first into a central gel channel under flow, giving them time to assemble into a perfusable network that can be tested for barrier integrity. Once vessels are created, the device would allow for placement of islet organoids directly into the vascularized region. Some important considerations for the device include ensuring flow distribution, controlling flow pressure, maintaining sterility and minimizing shear stress during islet seeding to preserve viability and function.
Economic and social impact: Diabetes poses a major health challenge, and new models are needed to better understand the disease and develop effective treatments. A microfluidic system that mimics physiological islet–vascular interactions could provide insights into islet maturation, survival, and function. Such a platform could not only accelerate drug discovery but also allow for disease modeling of diabetes under controlled conditions. It could further support regenerative medicine approaches, for example by testing stem cell–derived islet therapies in a vascularized environment. In the long term, this platform could help translate regenerative medicine strategies into therapies to improve outcomes of patients with diabetes.
Skills requested or to be developed: The student will gain experience in microfluidic design and fabrication, cell culture, and organoid handling, as well as functional assays that will be relevant for design testing such as perfusion and barrier integrity testing. Data analysis, microscopy imaging, and quantitative biology skills will also be developed.
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Project 8 (not currently available)
Development of an Ablation Device for the Treatment of Uterine Fibroids
Supervisor: Prof Stuart Kozlick; stuart.kozlick [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: Uterine fibroids are common growths on the uterus which are typically benign. Some symptoms that can arise from uterine fibroids are heavy menstrual bleeding, pelvic pressure or pain, and longer or more frequent periods. Some uterine fibroids, such as submucosal fibroids, can result in infertility or pregnancy loss. Currently, there is no single best treatment for uterine fibroids; medicines, myomectomies, along with radiofrequency and endometrial ablation, are used to treat uterine fibroids. Current ablation methods can be improved by minimizing the risk of damage to nearby tissues, along with pain, bleeding or infection risk.
To improve the targeting of uterine fibroids during treatment, this project proposes the further optimization of ablation methods. The objective of this project is to develop an ablation device for the treatment of uterine fibroids.
Description of design component:
The project will focus on developing an ablation device to optimize the targeted treatment of uterine fibroids. This will begin with the identification of device component(s) that can be optimized to address and improve targeted treatment delivery. Based on these findings, the projects design components will involve:
- Mechanical design of an ablation device using CAD
- Computational modeling of the uterine tissue response
- Fabrication and assembly of the designed device
- Device testing and validation
Economic and social impact:
While not always diagnosed, some estimate that 20-50% of women at reproductive age have uterine fibroids. Currently, the treatment for uterine fibroids consists of medications for symptom management or highly invasive surgeries such as hysterectomies and myomectomies. Our group aims to utilize and optimize ablation technology to develop a minimally invasive treatment to improve the quality of life for many affected women.
Additionally, current surgeries offered are quite expensive, so our group aims to assemble the device at minimal cost to improve this novel surgical innovation, with the goal of reducing the physical impact and economic expenses for those who need treatment to improve their quality of life.
Skills requested or to be developed:
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- Design of mechanical device components using CAD
- Programming (via Python/MATLAB)
- Computational modelling to predict device performance
- Assembly of a device with multiple electrical and mechanical components
- Characterization of device performance and optimization with in vitro experimental techniques (fabricating and using synthetic tissues to test ablation)
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Project 9
Wearable Hydration Monitor with Haptic Display
Supervisor: Prof Jeremy Cooperstock; jer [at] cim.mcgill.ca
Preferred Team Size: Any
Background and Objectives: Intense physical training, such as carried out by high-performance athletes or soldiers, often requires attention to their hydration level, since dehydration can instantly knock them out of competition. However, glancing at a visual display to check current status can interfere with the individual's performance and may be impractical or even dangerous. Building on our prior work that used haptic feedback patterns to convey patient vital signs (
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https://srl.mcgill.ca/projects#multimodal-monitoring), we are developing a small, wearable prototype haptic feedback system, leveraging input from an off-the-shelf hydration monitor, to provide periodic updates on the wearer's hydration level, alerting them to the need to rehydrate as levels drop. An initial prototype will use a smartwatch haptic actuator, but the intention through the project is to prototype and successfully refine a small microelectronics platform with which we can deliver richer haptic alert patterns. The prototypes will need to be tested under realistic conditions to determine their effectiveness in conveying the information relevant to monitoring one's dynamic hydration level with minimal effort, and prompting the wearer appropriately when re-hydration is needed.
Description of design component: The student(s) will work on haptic pattern design, and potentially, microelectronics design including form factor for the assembly
Economic and social impact: Industrial players are eager to develop the same capabilities to incorporate into their future product line, and prospective end users have expressed strong interest in including such a system in the training of their recruits.
Skills requested or to be developed: Programming ability in Kotlin or Java (for Android watches) or C (for Pebble watches) is necessary. Experience in haptics or audio design, as well as microelectronics, are desirable, but not essential.
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Project 10
AI Digital Nurse Assistant
Supervisor: Prof Jeremy Cooperstock; jer [at] cim.mcgill.ca
Preferred Team Size: Any
Background and Objectives:
Our AI Digital Nurse Avatar is a GPT-driven graphical avatar that interacts with users through speech for medical scenario information gathering and conversation with older adults for long-term psychosocial assessment purposes.
The primary objective of the initial use case, focused on interaction with older adults, is to build such AI-based tools to provide assistance to nurses and other care staff, helping reduce workload by serving as a possible initial point of communication with clients, and triaging communications during periods of overload. The avatars, potentially presenting different on-screen human appearances and voices, as best-suited to the preferences of each client, collect information through natural conversation and video-based interaction. The relevant information would then be conveyed to appropriate staff in an appropriate format, without necessitating travel to every client for every interaction.
The prototype system architecture was pilot-tested with nursing staff and older adults, from which we identified various areas of improvement we now wish to implement, in addition to other pre-existing needs, before carrying out a larger-scale trial deployment.
Research tasks include:
• generating improved metrics of the user’s well-being (psychosocial state), and comparison against baseline models, involving:
• analysis of answers to questions posed by the simulated nurse
• analysis of para-linguistic content such as tone of voice, indicative of affect or mood
• analysis of video of physical movements and facial expression
• conversation flow management:
• customized prompts based on input from nurses as to cognitive/conversational skills of older adult
• visually indicating when ADiNA is “thinking” vs. waiting for user input
• speech handling augmentations:
• detection and discrimination of multiple human speakers, e.g., for group conversations and suppression of background noise
• feature additions:
• expanded access to real-time data sources to support greater range of discussion topics
• integration of image/video input interpretation capabilities for understanding of the user’s environment and the user’s own activity
• integration of on-demand video synthesis capabilities, leveraging AI video creation tools
Description of design component: Significant aspects of interaction design are involved in all aspects of the project, given the centrality of user experience, critical to its success.
Economic and social impact: The ADiNA project serves as the core architecture for a forthcoming series of LLM-supported medical service activities planned with an industrial partner.
Skills requested or to be developed: Software skills, familiarity with Python, React/TypeScript development, and use of the OpenAI API.
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Project 11
Hydrogel Characterization and 3D Bioprinter Design for the use of Tumoroid Production and Therapeutic Modeling
Supervisor: Prof Luc Mongeau; luc.mongeau [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: 3D cell culture systems, particularly organoids and tumoroids, have emerged as powerful tools for modeling human tissues and tumors in vitro, which is an important aspect of cancer treatment research. These models offer improved physiological relevance and increased reliability compared to traditional 2D cell culture systems given their multicellular composition, hierarchical structure, and ability to reproduce cell-cell and cell-extracellular matrix interactions [1]. However, the complexity of current bioprinting systems and the lack of standardized, scalable methods for producing and testing these 3D cultures in high-throughput formats are limiting factors.
Bioprinting technologies enable the precise spatial deposition of biomaterials and cells to create structured 3D tissue models [2]. Commercial bioprinters are typically large, expensive, and not optimized for small-scale, high-throughput applications like 96-well plate formats. Therefore, by designing a low-cost, small-footprint bioprinter tailored for this purpose, we aim to democratize access to 3D culture systems and facilitate rapid, parallel experimentation.
Producing 3D cell cultures involves the use of hydrogels derived from extracellular matrices (ECMs), which provide a biologically active scaffold that supports cell viability, differentiation, and tissue formation [3]. ECM composition and structure significantly influence cellular behavior, and differences between tissue sources can impact porosity, stiffness, and bioactivity – important properties to characterize inn order to optimize hydrogel performance for stem cell growth and tumoroid formation [4].
Description of design component: The bioprinter that we are designing for TissueTinker works by using a mechanism to depress 1 or more syringes loaded with our customizable bioink to be dispensed in a controlled manner into 96-well plates on a print bed. We aim to make the print bed, the dispenser mechanism, or both components move in a controlled manner to change the XYZ position for the bioinks to be dispensed. In terms of crosslinking, a mechanism to dispense crosslinking solution and aspirate the remaining solution after the crosslinking must also move into position in each well and activate in a controlled, steady manner.
The developed TissueTinker bioprinter controller software aims to send instructions to the bioprinter. Allowing the control of the crosslinker disperser, aspiration, and the movement of the bioink disperser. Further, the controller software is responsible for telling the printer what type of well plate is being used, to ensure that the mechanisms properly dispense bioink and crosslinker solution into the wells.
Economic and social impact: In The United States, mice death from research reach over 11 million annually. Despite the ethical concerns with animal models, no alternative has been able to achieve the convenience of animal models. Developing a hydrogel-based model for clinical testing provides a substitute for animal models, which besides the ethical concerns they rise, do not mimic human anatomy perfectly, resulting in longer clinical trials. Additionally, hydrogel-based models provide a high throughput drug screening that can be designed to be patient specific, allowing for more cost effective and accelerated treatment development. Hydrogel-based tumoroids also offer a way to perform mechanobiology studies that explore how mechanical factors may influence cancer mechanics and metastasis. With their affordability, accuracy, and reproducibility, hydrogel-based models open up the doors for more personalized, accessible, and affordable medicine without the ethical concern that animal models raise.
Skills requested or to be developed:
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- CAD design
- 3D Printing
- Fluidics
- Arduino/Raspberry Pi
- Hydrogel Characterization (microscopy, rheometry, mechanical tests, viability assays)
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Project 12
Optimizing porous polymer coating for nanovesicle eluting stents
Supervisor: Professor Rosaire Mongrain, Mechanical Engineering; rosaire.mongrain [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: Drug eluting stents are commonly used to prevent restenosis of arteries after stent insertion. While drug eluting stents show improved patient results compared to bare-metal stents, they still pose some issues, such as preventing proper tissue healing due to drugs interfering with endothelial cell migration and proliferation. This results in drug-eluting stents having positive short-term results but leaving long-term outcomes to be desired.
An alternative to drug-eluting stents is the use of nanovesicles-eluting stents. Extracellular nanovesicles play an active part in the natural healing process, promoting tissue regeneration. Research has found that exosome-eluting stents could improve the growth and migratory behavior of endothelial cells, preventing restenosis in the short-term and aiding artery healing in the long term.
The lab has previously investigated nanovesicle diffusion computationally by modelling particle-coated stents using a parametric approach. In addition, the lab has previously developed a Franz cell set up for drug diffusion.
However, the validity of particle-diffusion models has yet to be confirmed by experimental work. Because of the increased size of nanovesicles (~ 50 nm) compared to small molecule drugs, the diffusion properties may change. Particularly, whether the nanovesicles follow the same diffusion profile as small molecule drugs must be experimentally validated.
The objectives of this project are to design a biocompatible porous polymer coating for nanovesicle release and to characterize the system’s diffusion properties. The project builds upon the previous work in the lab through the design & optimization of a Franz cell device to characterize diffusion properties.
Description of design component: Design of polymer coating for nanovesicles:
- Investigate different polymer materials for desirable biocompatibility, mechanical properties, and nanovesicle loading and release
- Modify polymer coatings using additives to affect pore size and achieve a desired spatiotemporal nanovesicle release
- Test polymer coatings using nanovesicles
Design of Franz cell to test diffusion properties:
- Optimize the previously built Franz cell which uses a hydrogel-based surrogate (Polyvinyl Alcohol)
- Modify the Franz cell to incorporate fluid convection to better simulate arterial flow conditions
- Test Franz cell set up with simple dyes, such as methyl blue and calcium salts
- Characterization of the polymer coating system using the Franz cell
Economic and social impact: This project has the potential to advance a novel alternative to the drug-eluting stent, supporting a more natural healing process which could reduce complications and costs associated with restenosis and repeat procedures, leading to an improved quality of life. Investigating methods to investigate nanovesicle diffusion, such as through Franz cells, has the potential to favor research and adoption of these nanovesicle-eluting stents, opening up a new market for these medical devices. The project will be performed in partnership with a South Korean company, demonstrating that this subject has already garnered commercial interest.
Skills requested or to be developed:
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- Modelling diffusion
- Polymer modification protocols
- Polymer porosity characterization
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Project 13
Cloning of Heard Voices
Supervisor: Jeremy Cooperstock; jer [at] cim.mcgill.ca
Preferred Team Size: Any
Background and Objectives: In the context of a former project involving avatar therapy for psychosis (
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https://srl.mcgill.ca/#mixed-reality-hallucinations-schizophrenia), we developed a framework for voice synthesis (
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https://dl.acm.org/doi/10.1145/3491102.3501871) that achieved impressive results in reproducing desired vocal characteristics. However, several limitations of the system, such as its clustering algorithm for similar voices, and the slow process of manipulating latent parameters, preclude the use of this tool in serious applications.
To support a research study being conducted by colleagues in Computational Linguistics in Zurich on the self-perception of one’s own voice, we seek to implement a number of improvements to the current platform (
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https://psychosis.cim.mcgill.ca/mixing/), and collaborate on the study itself.
On the software side, the student(s)’ tasks will include:
- investigating improved clustering algorithms for voices with similar characteristics
- leveraging GPU acceleration for rapid computation of new voices based on manipulation of multiple latent parameters in parallel
- automatic filtering of non-human-sounding voices, based on analysis of clipping artifacts
support for multiple linguistic characteristics by training on an enlarged voice database
Description of design component: UI elements, optimization, clustering algorithm, audio filtering process design
Economic and social impact: Although the motivation for the present project is purely to support scientific investigation activities, Improvements in the underlying voice synthesis framework could be incorporated into products for avatar therapy or audio forensics applications.
Skills requested or to be developed: Python programming experience. Audio processing and a basic understanding of autoencoders.
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Project 14
Hydrogel Characterization and 3D Bioprinter Design for the use of Tumoroid Production and Therapeutic Modeling
Supervisor: Prof Luc Mongeau, luc.mongeau [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: 3D cell culture systems, particularly organoids and tumoroids, have emerged as powerful tools for modeling human tissues and tumors in vitro, which is an important aspect of cancer treatment research. These models offer improved physiological relevance and increased reliability compared to traditional 2D cell culture systems given their multicellular composition, hierarchical structure, and ability to reproduce cell-cell and cell-extracellular matrix interactions [1]. However, the complexity of current bioprinting systems and the lack of standardized, scalable methods for producing and testing these 3D cultures in high-throughput formats are limiting factors.
Bioprinting technologies enable the precise spatial deposition of biomaterials and cells to create structured 3D tissue models [2]. Commercial bioprinters are typically large, expensive, and not optimized for small-scale, high-throughput applications like 96-well plate formats. Therefore, by designing a low-cost, small-footprint bioprinter tailored for this purpose, we aim to democratize access to 3D culture systems and facilitate rapid, parallel experimentation.
Producing 3D cell cultures involves the use of hydrogels derived from extracellular matrices (ECMs), which provide a biologically active scaffold that supports cell viability, differentiation, and tissue formation [3]. ECM composition and structure significantly influence cellular behavior, and differences between tissue sources can impact porosity, stiffness, and bioactivity – important properties to characterize inn order to optimize hydrogel performance for stem cell growth and tumoroid formation [4].
Description of design component: The bioprinter that we are designing for TissueTinker works by using a mechanism to depress 1 or more syringes loaded with our customizable bioink to be dispensed in a controlled manner into 96-well plates on a print bed. We aim to make the print bed, the dispenser mechanism, or both components move in a controlled manner to change the XYZ position for the bioinks to be dispensed. In terms of crosslinking, a mechanism to dispense crosslinking solution and aspirate the remaining solution after the crosslinking must also move into position in each well and activate in a controlled, steady manner.
The developed TissueTinker bioprinter controller software aims to send instructions to the bioprinter. Allowing the control of the crosslinker disperser, aspiration, and the movement of the bioink disperser. Further, the controller software is responsible for telling the printer what type of well plate is being used, to ensure that the mechanisms properly dispense bioink and crosslinker solution into the wells.
Economic and social impact: In The United States, mice death from research reach over 11 million annually. Despite the ethical concerns with animal models, no alternative has been able to achieve the convenience of animal models. Developing a hydrogel-based model for clinical testing provides a substitute for animal models, which besides the ethical concerns they rise, do not mimic human anatomy perfectly, resulting in longer clinical trials. Additionally, hydrogel-based models provide a high throughput drug screening that can be designed to be patient specific, allowing for more cost effective and accelerated treatment development. Hydrogel-based tumoroids also offer a way to perform mechanobiology studies that explore how mechanical factors may influence cancer mechanics and metastasis. With their affordability, accuracy, and reproducibility, hydrogel-based models open up the doors for more personalized, accessible, and affordable medicine without the ethical concern that animal models raise.
Skills requested or to be developed:
- CAD design
- 3D Printing
- Fluidics
- Arduino/Raspberry Pi
- Hydrogel Characterization (microscopy, rheometry, mechanical tests, viability assays)
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Project 15
Optimizing porous polymer coating for nanovesicle eluting stents
Supervisor: Professor Rosaire Mongrain, Mechanical Engineering, rosaire.mongrain [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: Drug eluting stents are commonly used to prevent restenosis of arteries after stent insertion. While drug eluting stents show improved patient results compared to bare-metal stents, they still pose some issues, such as preventing proper tissue healing due to drugs interfering with endothelial cell migration and proliferation. This results in drug-eluting stents having positive short-term results but leaving long-term outcomes to be desired.
An alternative to drug-eluting stents is the use of nanovesicles-eluting stents. Extracellular nanovesicles play an active part in the natural healing process, promoting tissue regeneration. Research has found that exosome-eluting stents could improve the growth and migratory behavior of endothelial cells, preventing restenosis in the short-term and aiding artery healing in the long term.
The lab has previously investigated nanovesicle diffusion computationally by modelling particle-coated stents using a parametric approach. In addition, the lab has previously developed a Franz cell set up for drug diffusion.
However, the validity of particle-diffusion models has yet to be confirmed by experimental work. Because of the increased size of nanovesicles (~ 50 nm) compared to small molecule drugs, the diffusion properties may change. Particularly, whether the nanovesicles follow the same diffusion profile as small molecule drugs must be experimentally validated.
The objectives of this project are to design a biocompatible porous polymer coating for nanovesicle release and to characterize the system’s diffusion properties. The project builds upon the previous work in the lab through the design & optimization of a Franz cell device to characterize diffusion properties.
Description of design component: Design of polymer coating for nanovesicles:
- Investigate different polymer materials for desirable biocompatibility, mechanical properties, and nanovesicle loading and release
- Modify polymer coatings using additives to affect pore size and achieve a desired spatiotemporal nanovesicle release
- Test polymer coatings using nanovesicles
Design of Franz cell to test diffusion properties:
- Optimize the previously built Franz cell which uses a hydrogel-based surrogate (Polyvinyl Alcohol)
- Modify the Franz cell to incorporate fluid convection to better simulate arterial flow conditions
- Test Franz cell set up with simple dyes, such as methyl blue and calcium salts
- Characterization of the polymer coating system using the Franz cell
Economic and social impact: This project has the potential to advance a novel alternative to the drug-eluting stent, supporting a more natural healing process which could reduce complications and costs associated with restenosis and repeat procedures, leading to an improved quality of life. Investigating methods to investigate nanovesicle diffusion, such as through Franz cells, has the potential to favor research and adoption of these nanovesicle-eluting stents, opening up a new market for these medical devices. The project will be performed in partnership with a South Korean company, demonstrating that this subject has already garnered commercial interest.
Skills requested or to be developed:
- Modelling diffusion
- Polymer modification protocols
- Polymer porosity characterization
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Project 16
Supervisor: Prof. Dan Nicolau, dan.nicolau [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: Many mathematical and real-life problems, e.g., “travel salesman problem” (TSP), protein structure, cryptography, cannot be solved, if reasonably large, by the present computers, which process the information sequentially (albeit with extreme precision and speed). These mathematical problems can be solved if (i) they are translated into a graph; (ii) this graph is translated into a design of a microfluidic network; and (iii) the fabricated microfluidic structure is explored by individual biological agents, e.g., microorganisms, which act as simple CPUs.
Objectives: The project aims to assess the individual and collective ‘computational power’ of individual biological agents in optimally partitioning the available space and taking optimal decisions. The project involves, tentatively, the following modules: (i) translate the problem of interest in a graph; (ii) fabrication of the network equivalent to the graph encoding the mathematical problem; (iii) exploration of the microfluidic network by agents, e.g., bacteria; (iv) readout of the bio-computed solutions.
Description of design component: Design and fabrication of microfluidics networks encoding mathematical problems; fine tuning of these microfluidics according to the biological motility
Economic and social impact: The present fast, but sequential electronic computers are essentially not designed to solve combinatorial problems, as "simple" as scheduling travel for more that 5-6 multi-cities, or finding an optimum schedule of teaching classes. For these problems a new computational paradigm is needed. The project will explore alternative to "classical" electronic computers towards biocomputation.
Skills requested or to be developed: The first major task of the project is to design a microfluidics network which will encode a mathematical problem, such as Travel Salesman’s Problem, with full consideration to fabrication, materials and scaling problems. The second major task of the project is to design the operation of such a computer, as tailored to various biological elements, e.g., bacteria, Euglena, paramecium, etc.
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Project 17
Causes, prevention and treatment of gas embolism
Supervisor: Prof. Dan Nicolau, dan.nicolau [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: One of the important causes of “accidental” death during, or occasioned by, surgery is air embolism, with obscure causes [2]. Importantly, many advanced surgery procedures today rely on catheters and on laparoscopy, which are sources of pressured gas introduced in human body, and conceptually prime causes of gas embolism.
Objectives: The project aims to understand the physical processes involved in gas embolism in a surgery theatre, and to progress in finding better alternatives for the designs of the devices that are the source of pressured gas, e.g., catheters, insufflation devices. The project involves, tentatively, the following modules: (i) articulate the physical phenomena causing air embolism; (ii) analysis of the present designs of devices deploying pressured air in the body; (iii) construct a model, both computational (e.g., CFD) and experimental (e.g., microfluidics mimicking blood vessels), on which gas embolism can be studied in vitro; and (iv) propose alternative, safer designs of catheter and insufflation device heads.
Description of design component: The first major task of the project is to choose the right materials, from the mechanical properties, interface with biological fluids, and fabrication point of view. The second major task of the project is to design the microfluidics structures which would mimic blood vessels to an extent that will allow in vitro experimentation. Finally, the third design task is to optimise “blood vessels on a chip” devices, on which several surgery protocols can be attempted with a focus on avoiding gas embolism.
Economic and social impact: Gas embolism has often devastating outcomes, e.g., a mortality of up to 33%, and severe neurological sequelae of up to 35%. Presently, the causal link between macroscopic conditions, especially iatrogenic, leading to gas embolism, are obscure, making fundamental, physical fact-based studies imperative and possibly overdue.
Skills requested or to be developed: Modelling and simulation, microfabrication, microscopy/imaging, diagnostic devices
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Project 18
Performance enhancement of Saccharomyces cerevisiae strains to produce isoprenoids through integration of in silico and in vivo approaches.
Supervisor: Codruta Ignea and Mario Jardon; codruta.ignea [at] mcgill.ca mario.jardoncontla [at] mcgill.ca
Preferred Team Size: Any
Background and Objectives: Isoprenoids play crucial physiological and structural roles in various biological systems and are key precursors for the synthesis of valuable chemicals. They are produced in microbial systems and higher organisms via the mevalonate (MVA) pathway. Understanding and manipulating this pathway can enable the development of therapeutic interventions for certain metabolic disorders and benefit numerous biotechnological applications.
The overall objective of this project is to generate S. cerevisiae strains able to produce increased levels of isoprenoids based on the application of in silico tools to explain previous observations and to guide further metabolic engineering interventions. In order to achieve this overall objective, the proposed specific objectives are:
1. Become familiar with existing platforms used to model, analyse, and predict metabolic states using genome-scale biochemical networks, such as the COBRA (COnstraint-Based Reconstruction and Analysis) and the GECKO (Genome-scale model to account for Enzyme Constraints, using Kinetics and Omics) toolboxes.
2. Incorporate into the COBRA and the GECKO toolboxes an existing genome scale metabolic model of Saccharomyces cerevisiae from publicly available databases for Flux Balance Analysis (FBA) applications.
3. Analyze, with the use of the above software tools, the interventions made on previously engineered strains to explain the modified metabolic fluxes compared to the wild-type parental strain.
4. Apply the described software tools to propose further improvements to the engineered strains.
5. Test in vivo the most promising interventions recommended by the in silico analysis.
Description of design component: The proposed project corresponds to the first step in the DBTL (Design-Build-Test-Learn) cycle that constitutes the main paradigm of Metabolic Engineering and Synthetic Biology. It will establish the foundation for a systematic interrogation of the metabolic pathways under study that can be used as a solid foundation for the next steps in the DBTL cycle.
Economic and social impact: Overall, isoprenoids are vital for a wide range of physiological functions and have significant applications in health, agriculture, and industry.
Skills requested or to be developed: The students participating in this project will become familiar with the COBRA (COnstraint-Based Reconstruction and Analysis Toolbox) and the GECKO (Genome-scale model to account for Enzyme Constraints, using Kinetics and Omics) toolboxes, Matlab-based platforms used to interrogate and analyse genome scale metabolic models (GEMs). Previous experience with Matlab will be beneficial. Students who have experience with other platforms to analyse GEMs are welcome to apply.
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Project 19
Modeling and economic analysis of process intensification for antibody biotherapeutics.
Supervisor: Mario Jardon, mario.jardoncontla [at] mcgill.ca
Preferred Team Size: Any
Background and Objectives: Biologic products continue to expand our ability to prevent, treat, and even cure medical conditions for which therapeutic options have so far been insufficient or plainly non-existent. Among these products, antibodies have demonstrated commercial success for several decades, and yet they continue to be the most prevalent and profit-generating category of biotherapeutics. Further developments to make these proteins more potent and specific (through the development of bi- or tri-specific antibodies, nanobodies, antibody-drug conjugates, etc.) generate new challenges for their production and purification, requiring parallel advancements in process technology. Such advancements in terms of yield and productivity, while safeguarding quality, can be a means to drive down costs and increase the benefit of these products for the general population.
The overall objective of this project is to design a manufacturing process for a model antibody, and perform an economic analysis of a standard process and an intensified end-to-end continuous manufacturing version, using process modeling tools (Matlab/Simulink and SuperPro Designer). In order to achieve this overall objective, the proposed specific aims are:
1. Design an antibody-based therapeutic molecule and estimate the production required to meet expected market needs.
2. Design a fed-batch process and purification strategy for the proposed molecule using Matlab/Simulink and integrating the process operations using SuperPro Designer, identifying all unit operations (upstream and downstream), relevant process variables and outputs.
3. Propose an intensified end-to-end continuous manufacturing version of the process, including perfusion cultures for the upstream stage and continuous chromatography for the downstream operations.
4. Perform an economic analysis of both versions of the manufacturing process (standard and intensified), including: equipment purchase costs, fixed capital estimate, raw materials costs, and annual operating costs estimate. Based on these results, a product pricing should also be proposed.
5. Develop brief environmental impact and sustainability assessments of the proposed design.
Description of design component: The project is an extensive engineering design exercise, from product design to process implementation and evaluation of alternatives, as it involves an integrated approach that combines knowledge in life sciences and engineering in a creative, open-ended, iterative process, taking into account constraints imposed by the living systems used, the regulatory requirements and overall economic considerations, in order to propose solutions that address a major social need.
Economic and social impact: Therapeutic antibodies are high-value products that have a major impact on health care and overall on society. Execution of the proposed project will involve a complete economic analysis and assessment of social, environmental and sustainability implications.
Skills requested or to be developed: The students participating in this project will develop expertise in the use of modeling tools such as Matlab/Simulink and SuperPro Designer. Previous experience with these software platforms, while helpful, is not required.
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Project 20
Rapid Prototyping and Validation of a Colorimetric Diagnostic Device for Infectious Diseases
Supervisor: Prof Sara Mahshid; sara.mahshid [at] mcgill.ca
Preferred Team Size: 3
Background and Objectives: We have developed a molecular diagnostic platform based on nanoplasmonic amplification integrated into microfluidics, enabling ultrafast and sensitive colorimetric quantification of nucleic acid biomarkers from pathogens. The versatility of QolorEX is demonstrated by detecting respiratory viruses such as SARS-CoV-2 and its variants at the single nucleotide polymorphism level, H1N1 influenza A, as well as bacterial pathogens. The objective of this project is to test the device design, develop rapid prototyping workflows for point-of-care diagnostics, and validate its performance with representative microbial and viral targets. Validation efforts will focus on assessing sensitivity, and reproducibility of the platform in detecting diverse pathogens, establishing benchmark datasets, and demonstrating its potential for clinical translation.
https://www.nature.com/articles/s41565-023-01384-5
Description of design component: The project will involve testing microfluidic cartridge designs, rapid prototyping of device components, integration with the optical readout system, and development of protocols for sample handling and signal interpretation.
Economic and social impact: This project addresses the urgent need for cost-effective, rapid diagnostics to combat antimicrobial resistance and infectious diseases. Economically, it has potential to reduce healthcare costs by enabling faster treatment decisions, while societally, it can improve patient outcomes and reduce the spread of infections.
Skills requested or to be developed:
Background in bioengineering, biomedical engineering, or related fields
Familiarity with microfluidics, biosensors, or diagnostics
Basic skills in CAD design, prototyping, or device testing
Interest in translational research and healthcare innovation
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Project 21
Development and Validation of a Rapid Diagnostic Platform for Antibiotic Susceptibility Testing
Supervisor: Prof Sara Mahshid; sara.mahshid [at] mcgill.ca
Preferred Team Size: 3
Background and Objectives: This technology enables parallel bacterial identification and phenotypic profiling of antibiotic resistance. The objective of this project is to test the design of the modular automated device, develop rapid prototyping workflows, and carry out validation studies with bacterial strains and model clinical samples to demonstrate reliability and robustness.
Description of design component: Students will contribute to the design and testing of microfluidic cassettes, rapid prototyping of device modules, integration with optical readout systems, and validation of parallel bacterial identification and antibiotic susceptibility profiling.
Economic and social impact: Antimicrobial resistance (AMR) is a global health crisis, with current AST workflows taking days to deliver results. Our diagnostic platform can reduce profiling times to minutes, leading to faster treatment decisions and improved patient outcomes. Economically, this technology can lower hospitalization costs, reduce ineffective antibiotic prescriptions, and support public health efforts to curb AMR.
Skills requested or to be developed:
Background in bioengineering, biomedical engineering, microbiology, or related fields
Familiarity with microfluidics, biosensors, or diagnostic devices
Basic skills in CAD design, prototyping, and device/system integration
Interest in antimicrobial resistance and clinical diagnostic technologies
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Project 22
Electrochemical Microfluidic Device for Rapid Antimicrobial Susceptibility Testing
Supervisor: Prof Sara Mahshid; sara.mahshid [at] mcgill.ca
Preferred Team Size: 3
Background and Objectives: In our lab, we have developed a wide range of electrochemical biosensors for pathogen detection and diagnostic applications. We also have extensive expertise in designing and fabricating microfluidic devices tailored for biological assays. This combined background in electrochemistry and microfluidics provides the foundation for advancing next-generation diagnostic platforms. The objective of this project is to refine an electrochemical microfluidic device, optimize fluidic–plasmonic integration, and validate diagnostic performance with representative bacterial species and clinical urine samples.
Description of design component: The project will focus on testing and optimizing microfluidic cartridge architectures for improved fluid handling, reagent mixing, and integration with embedded nanostructured surfaces. Students will prototype chip designs, develop electrochemical interfacing, and establish protocols for coupling signal analysis to the microfluidic outputs. The design emphasis will be on robustness and reproducibility.
Economic and social impact: This project directly addresses the global need for rapid, reliable, and cost-effective diagnostics to tackle antimicrobial resistance. By reducing the turnaround time for both bacterial identification and AST, the technology has the potential to transform infection management in both hospital and outpatient settings. Economically, it can reduce unnecessary antibiotic prescriptions and healthcare expenditures, while societally it can improve patient outcomes and help curb the spread of resistant pathogens.
Skills requested or to be developed:
Background in bioengineering, biomedical engineering, or related fields
Familiarity with microfluidics, biosensors, or electrochemistry
Basic experience in CAD design, device prototyping, or signal analysis
Interest in translational diagnostics and clinical validation workflows
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Project 23
Screening of yeast strains and statistical optimization of fermentation parameters for the production of beta-carotene in shake-flasks and benchtop bioreactors
Supervisor: Prof Codruta Ignea, codruta.ignea [at] mcgill.ca
Preferred Team Size: Any
Background and Objectives: Beta-carotene is a valuable carotenoid used in food, pharmaceutical and nutraceutical industries throughout the world for its role as colorant, pro-vitamin A precursor and antioxidant respectively. The market value has been estimated to be approximately 1.3 billion euros in 2017. Currently, beta-carotene is either extracted from plants or synthesized chemically. Both methods have immense limitations including high production costs, low yields, seasonal variability, and environmental concerns. Microbial production in engineered hosts has emerged as an alternative pathway offering possibility of optimization at various stages. In this research project, the goal is to optimize the production of beta-carotene in various engineered yeast strains using statistical design of experiment approaches. The following are the objectives of the research:
The present study is designed with the following objectives:
1. Strain Screening
To screen eleven different bioengineered yeast strains with carotenoid biosynthetic pathways for their ability to produce beta-carotene under shake-flask culture conditions.
2. Shake-flask Parameter Evaluation
To screen critical fermentation parameters (e.g., carbon source concentration, nitrogen source, pH, temperature, aeration) using Placket-Burman design (PBD) on beta-carotene production in selected yeast strains.
3. Statistical Optimization
To apply statistical experimental designs such as response surface methodology (RSM) for optimization of significant factors influencing beta-carotene yield in controlled benchtop bioreactors and assess the scalability of beta-carotene production.
4. Comparative Analysis
To compare beta-carotene production between different strains and culture systems (shake-flask vs. bioreactor) to establish the most efficient combination for future large-scale production.
Description of design component: The project incorporates an experimental design with four main stages. The first stage is the strain selection. Ignea lab has produced many high producers of beta-carotene strains using various synthetic biology techniques. The next stage in this research is the adaptation of these strains for fermentation at industrial scales. To do this, the main goal is strain screening and fermentation optimization strategies. Therefore, the first step will be the screening of eleven different strains that have been selected due to their high production status in 100 ml shake flasks. These strains will be grown in standard conditions using 250-500 ml shake flasks to assess which one can be used for further evaluation. The next stages will be the evaluation of which culture or nutritional parameters affect most prominently (statistically significant) on beta-carotene production. Once three to five parameters are selected, these parameters will be optimized for high production using RSM. The validation of the model will be conducted at both shake flask and bioreactor levels. Once critical parameters are identified, they will further be optimized in benchtop bioreactors.
Economic and social impact: The microbial production of beta-carotene offers a cost-effective and environment-friendly alternative to plant extraction and chemical synthesis. By using engineered yeasts and fermentation scale up, the cost of production can be lowered while stabilizing supply chain and enabling a year-round production.
Skills requested or to be developed: Use of Statistical Software such as JMP Pro or Minitab
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Project 24
Production of AI-assisted novel terpenoids using docking capabilities with GPCR receptor systems
Supervisor: Prof Codruta Ignea, codruta.ignea [at] mcgill.ca
Preferred Team Size: Any
Background and Objectives: Terpenoids are frequently bioactive compounds usually produced by plants and microbes and have been used for their therapeutic effects. Recently, potent terpenoids have been discovered to play significant roles in the treatment of various diseases including cancer, inflammation, HIV/AIDS, diabetes, and mental health issues. However, these natural compounds often require further chemical derivatization to improve their bioactivity and bioavailability. Therefore, the identification and design of novel pharmaceutical targets within the terpenoid class can provide more options for developing better treatment strategies for these diseases. This project employs various newly developed AI tools to generate ultra-large libraries of novel terpenoids, which can be used to expand the current chemical space for more potent drug targets.
The present study is designed with the following objectives:
1. To generate and analyze novel molecular libraries using AI tools.
2. To analyze the physicochemical and pharmaceutical properties of generated molecules.
3. To employ AI assisted docking programs for the analysis of binding affinity with CB2 receptor.
4. To generate biosynthetic pathways of the generated molecules.
Description of design component: This project consists of four main stages. The first stage is the assessment of various AI tools such as DRAGONFLY, MolAICal and DarkNPS for the generation of novel natural products. Once the best tool is discovered, its model will be trained on various datasets to assess the potential viability of produced compounds. After selecting the final dataset, NPClassifier along with various other physicochemical and pharmacological filters will be applied to select compounds from ultra large library. The third step will be the assessment of docking scores using AI tools such as Deep Docking, HASTEN / ML-boosted workflows, DrugCLIP (Contrastive) or RosettaVS. After virtual screening, top molecules with high docking affinities will be selected for in silico biosynthetic pathway construction.
Economic and social impact: The economic and societal impacts of this project can be immense in terms of production of sustainable novel drugs using biosynthesis. The novel molecules can be tailored for a specific diseases based on its virtual screening hit score. Since the selected molecules are natural products, the discovery of their biosynthetic pathway will be relatively easy which can help in their production via fermentation.
Skills requested or to be developed: Use of Python and Compute Canada.
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Project 25
Web-Based Control, Live Preview, and Results Management for Raspberry Pi Imaging
Supervisor: Prof Sebastian Wachsmann-Hogiu (sebastian.wachsmannhogiu [at] mcgill.ca), Reza Abbasi
Preferred Team Size: 3
Background and Objectives: The lab uses Raspberry Pi (Pi 4/5) and Pi Camera modules for several imaging modes (single image, video, long-exposure stills, long-exposure time-lapse). Today, each mode is launched via separate scripts on the Pi and parameters are edited manually.
This project will deliver a wireless, web-based application (works on iOS, Android, and laptops, no installs) that allows the operator to connect to the Pi, choose an imaging mode, set key parameters, start/stop captures, see a live preview, and browse/download results.
Description of design component:
1. Unified Controller on the Pi: Consolidate existing capture modes behind a simple control service; organize outputs per run with basic metadata (requested/applied settings, timestamps).
2. Web App (PWA): Clean interface to connect over Wi-Fi, select mode (single, video, long-exposure still, long-exposure time-lapse), set parameters, and view live preview.
3. Wireless Operation: System must work over the lab Wi-Fi and also in hotspot mode (the Pi can create its own network when Wi-Fi isn’t available).
4. Results Management: In-app gallery to review, download, and share session results; export a ZIP including images/video and metadata.
Economic and social impact: Improve the usability of Raspberry Pi for biosensing applications. Reduce cost of electrochemiluminescent biosensor devices, applications to point of care/need. Impact on health (via food safety) via Disability Adjusted Life Years.
Skills requested or to be developed:
• System Integrator (Pi lead): sets up the Pi, unifies capture modes, ensures both wireless modes work reliably.
• Web App Lead: builds the browser app with a clear UI for mode selection, parameter entry, live preview, and results gallery.
• Networking/QA Lead: device discovery/pairing, basic security, end-to-end testing (preview smoothness, long-run stability).
• Documentation/PM: user guide, setup notes, test reports; coordinates brief weekly updates.
Must-Have Skills (across the team): comfort with Raspberry Pi/Linux, basic programming to control camera parameters, straightforward web UI work, and structured testing.
• Nice-to-Have: familiarity with imaging concepts (exposure/ISO), simple long-exposure quality steps (e.g., dark-frame capture).
Success Criteria (Design Day)
• From a phone on Wi-Fi or Pi hotspot, operator connects → sees live preview → selects Long-Exposure mode → sets Exposure = 10 s, ISO = 800 (example) → captures → downloads the image and its metadata.
• Demonstration of a long-exposure time-lapse with user-set interval and exposure.
• Clear User Manual (operator) and Setup Notes (lab admin) delivered.
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Project 26
Lensless On-Chip Fluorescence Imaging Device
Supervisor: Prof Sebastian Wachsmann-Hogiu (sebastian.wachsmannhogiu [at] mcgill.ca), Reza Abbasi
Preferred Team Size: 3
Background and Objectives: Lensless fluorescence imaging eliminates bulk optics by placing the sample close to a CMOS sensor and rejecting the strong excitation light with a thin long-pass filter. Literature indicates dye-doped PDMS (and related polymers) can provide this filtering if dye load and thickness are tuned for high UV rejection and high emission transmission.
This project will design and prototype a compact lensless fluorescence imager using a Raspberry Pi–class CMOS sensor and a UV (365–405 nm) LED. A thin, dye-doped PDMS (or alternative) filter will be spin-coated on a removable carrier (glass or microfluidic lid) and integrated over the sensor. The team will: (1) characterize filter spectra, (2) design the opto-mechanical/electronic stack (illumination, baffling, thermal), (3) implement image-processing and calibration, and (4) validate detection on standard fluorophores and fluorescent microspheres.
Description of design component:
1. Spectral Filter Development
• Formulate dye-doped PDMS (and 1–2 alternative matrices) for long-pass behavior; vary dye concentration & thickness.
• Measure transmission/rejection with UV-Vis; target high OD at excitation (365–405 nm) and high transmission in emission band(s) (e.g., 450–600 nm).
• Document finalized spin-coat & cure SOPs.
2. Sensor & Opto-Mechanical Integration
• Use Pi camera (NoIR or lens-removed) with removable filter carrier and precise standoff to the sample (≈100–500 µm).
• Integrate UV LED + driver, heat sinking, and blackened light-traps/baffles in a 3D-printed enclosure.
• Define ESD/dust-control handling for bare sensors.
3. Electronics & Control
• Constant-current LED drive with PWM; synchronization with camera exposure.
• Capture automation (exposure, gain), dark-frame routines.
4. Image Processing & Calibration
• Flat-field correction, background subtraction, denoising.
• Sensitivity benchmarking with fluorescent dyes and 1–10 µm fluorescent beads; produce SNR vs concentration curves.
• (Stretch) Explore lensless reconstruction/contrast-enhancement if beneficial.
5. Validation & Reporting
• Benchtop imaging of standards in a simple microfluidic or gasketed slide.
• (Stretch) Bacteria-mimicking phantoms (e.g., NADH/tryptophan mixes).
• Deliver CAD, BOM, code/scripts, SOPs, spectral data, and a final report with design rationale, test results, and next-step recommendations.
Economic and social impact: Improve the usability of image sensors for biosensing applications. Possibility of applications to the detection of bacteria at the point of care/need. Impact on health via Disability Adjusted Life Years.
Skills requested or to be developed:
• Mech/Mfg: CAD, 3D printing, precision fixturing, enclosure design.
• Materials/Optics: PDMS processing, thin-film spin-coating, spectroscopy, optical baffling.
• ECE/Software: LED drivers, Raspberry Pi control (Python), image acquisition, basic image processing/data analysis.
• (Optional Bioeng): Simple microfluidic design; handling of fluorescent standards.
Success Criteria (Design Day)
• Plots showing OD & transmission meeting the spec at excitation/emission.
• Working prototype capturing fluorescence images of standard targets with quantified LOD and repeatability.
• Full design package (CAD, code, SOPs) handed off to the lab.
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Project 27
Self-Contained Raspberry Pi Imaging Box with 3.5" Touchscreen and Light-Tight Sample Port
Supervisor: Prof Sebastian Wachsmann-Hogiu (sebastian.wachsmannhogiu [at] mcgill.ca), Reza Abbasi
Preferred Team Size: 4
Background and Objectives: The lab uses Raspberry Pi camera systems for lensless and conventional imaging. For day-to-day experiments, a standalone, product-like instrument would speed setup and improve repeatability.
This project will deliver a desktop imaging box that integrates:
• a Raspberry Pi (Pi 4/5),
• a 3.5" touchscreen LCD for local control and preview, and
• a fixed camera mount facing a top-loading sample port, all inside a light-tight enclosure so ambient light cannot reach the sensor.
Description of design component: 1. Touchscreen Integration
• Select and integrate a commercially available 3.5" Pi touchscreen.
• Ensure smooth boot, touch calibration, and on-device preview/control (simple, finger-friendly UI).
2. Opto-Mechanical Module
• Rigid camera mount with defined working distance.
• Top-loading sample port sized for slides/flow-cells, with a light-seal (e.g., labyrinth and/or gasketed lid).
• Internals finished matte-black with baffles to suppress stray light (LCD and vents isolated from the optical chamber).
3. Enclosure & Assembly
• Product-style enclosure (CAD) with clean cable routing, access panels, and safe power entry.
• Thermal management (passive or quiet active) using light-baffled vents to maintain darkness.
• Assembly guide, BOM, and printed/laser-cut parts ready for re-build.
4. Validation & Usability
• Light-tightness test: demonstrate dark frames in a bright room with the port closed (no visible light leakage).
• Basic on-device operation: from the touchscreen, preview and capture an image; save and view results.
• Quick-start user manual (startup, sample loading, capture, shutdown).
Key Requirements (must-meet)
• Touchscreen works smoothly on the Pi: reliable touch, clear UI, and responsive preview.
• Light-tight optical chamber: no ambient light reaches the sensor when the port is closed; show before/after images and a short test report.
• Top-loading sample port: easy to use; closes securely with an effective light seal.
• Product feel: neat exterior, protected edges/cables, stable footprint, and safe power.
• Documentation: CAD, BOM, assembly steps, and user manual delivered.
Economic and social impact: Integrated, user-friendly system for various biosensing applications will have applicability at the point of care/need. Impact on health via Disability Adjusted Life Years.
Skills requested or to be developed:
• Mechanical/Product: CAD, 3D printing/laser cutting, fixture and seal design, basic thermal considerations.
• Electronics/Integration: Raspberry Pi setup, touchscreen hookup/calibration, tidy internal wiring.
• Usability/Testing: light-leak tests, simple on-device UI for preview/capture, clear documentation.
Success Criteria (Design Day demonstration)
• Power on → touchscreen UI appears → live preview visible.
• Load a sample from the top port, close the lid → capture and save an image from the screen.
• Light-tightness demo: in a bright room, with the port closed, dark-frame image shows no visible leakage; open the port to show the contrast.
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Project 28
Spatio-temporal MRI models with video diffusion methods
Supervisor: Prof Tal Arbel, tal.arbel [at] mcgill.ca
Preferred Team Size: 4
Background and Objectives: MRI is central to tracking disease progression and treatment response in conditions such as multiple sclerosis, Alzheimer’s disease, and Parkinson’s disease. Predicting how a patient’s MRI evolves under different therapies could accelerate treatment selection and enable patient-specific disease trajectory modeling, a key step toward personalized medicine. However, most existing approaches are limited to single-step predictions, which makes it difficult to capture the full complexity of disease evolution over time.
In this project, students will explore video diffusion methods to generate complete future trajectories of brain MRI, conditioned on one or more initial scans. This approach offers greater flexibility in modeling patient data and can make better use of the diverse and irregular clinical datasets available. Students will contribute to building and training these models, as well as designing the software pipeline needed to handle MRI trajectory data for generative modeling.
Description of design component: Students will develop pipelines to train modern generative models for predicting the evolution of brain MRIs. In addition, they will implement different baseline methods from the literature and design a testing suite to compare the performance of alternative approaches for spatio-temporal modeling.
Economic and social impact: This work could improve patient outcomes by enabling more personalized treatment decisions, which may reduce the burden of neurodegenerative diseases on patients, families, and caregivers.
Skills requested or to be developed: Students are expected to have strong programming skills and experience working with deep-learning methods. They will gain experience with modern generative modeling methods (e.g. diffusion, flow-matching).
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Project 29
Engineering Substrate Selectivity and Catalytic Activity of Taxadiene 5α-hydroxylase Involved in Early Steps of Taxol Biosynthesis
Supervisor: Profs Codruta Ignea, Yu Xia; codruta.ignea [at] mcgill.ca; brandon.xia [at] mcgill.ca
Preferred Team Size: Any
Background and Objectives: Paclitaxel (trademarked as Taxol), initially obtained from the stem bark of the Pacific yew tree, Taxus brevifolia, is a widely used chemotherapeutic agent known for its significant anticancer activity. However, the traditional production methods of taxol are highly inefficient and unsustainable standing on plant cell cultures or plant extraction combined with organic synthesis. Synthetic biology has emerged as a promising approach for the cost-effective and sustainable production of high value compounds, such as taxol, using in yeast (Saccharomyces cerevisiae) or other microbial platforms. However, the synthetic pathway requires substantial optimization to achieve industrial-scale production. A key challenge lies in the low conversion efficiency of taxadiene-5 alpha-hydroxylase (T5aH) in the early stages of taxol biosynthesis, which limits the supply of precursors for subsequent steps, thereby hindering the introduction of the taxol biosynthetic pathway in yeast.
In this project, students will: (i) review published data on the enzyme's structure and function and propose mechanisms for its redesign with the aim of enhancing productivity; (ii) employing enzymology and protein engineering knowledge, develop simulation pipelines for identifying candidate positions for enzyme mutagenesis; and (iii) rationally design enzyme variants and provide in silico analysis to evaluate their designs. The proposed mutants will then be tested in vivo within an established system in the Ignea lab.
With a current demand of 2.6 tons of taxol annually and prediction of expanded uses, the industrial sector will benefit from production of taxol at lower cost using microbial fermentation. A strong societal impact is anticipated as lowering the cost of drug production will translate into more available treatments per patient.
Description of design component: Students will define the desired outcome in the enzyme function, acquire structural information of the enzyme, and perform structural analysis such as active site analysis, binding pocket identification, and stability analysis. Subsequently, students will set up Molecular Dynamics simulations and analyze the trajectory data from MD simulations to identify key interactions, conformational changes, and regions of the enzyme that are critical for its function. Based on the MD simulation results and biochemistry knowledge, students will identify residues that could be mutated to achieve the desired functional change and perform in silico screening to predict and evaluate the effect of mutations on enzyme structure, stability, and activity. Finally, students will test the most promising enzyme variants in vivo to validate the predicted improvements in function.
Economic and social impact: computer science, biochemistry, molecular biology and microbiology laboratory techniques
Skills requested or to be developed: molecular simulations, protein rational mutagenesis.
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Project 30 (Taken)
Yeast Metabolism Investigation for Fermentation of Non-Alcoholic Beer
Supervisor: Prof Codruta Ignea, codruta.ignea [at] mcgill.ca
Preferred Team Size: 3
Background and Objectives: Exploration of the metabolism of non-alcoholic (NA) yeasts. Fermentation of Saccharomyces cerevisiae is thoroughly investigated for the production of beer, however non-Saccharomyces yeast is a promising alternative to produce NA beer. There are still many gaps in the metabolic pathways for these yeasts and a comprehensive investigation will help better understand their opportunity in the fermented beverage market. Many NA yeasts rely on being low-maltose yeasts which are inefficient at fermenting maltose into ethanol. However, the result is often residual maltose, creating “worty” off-flavors, poor mouthfeel, and higher sugar content. Bioengineering solutions offer a means to reroute sugars away from ethanol and toward desirable compounds (esters, glycerol, acids). The project objective is to characterize NA yeast fermentation products, examine the opportunity for genetic engineering to target deficiencies in current NA beer production, optimize fermentation conditions and other biological and process techniques to enhance the NA production that avoid de-alcoholization.
Objectives:
1. Yeast characterization and engineering: a) Determine key chemical characteristics of non alcoholic beer using analysis techniques and find target compounds for metabolism. b) Evaluate a series of non-conventional yeasts that ferment low alcohol beer. c) Explore the possibility of transforming a target yeast with desired genes to optimize non-alcoholic beer production.
2. Industrial scale up and production of promising non-alcoholic beer: a) Conduct an investigation on the effects of varying fermentation conditions (pH, temperature, wort profile, etc.) at large scale. b) Design a protocol for non-alcoholic beer production using identified yeast and fermentation conditions for the optimal product based on defined characteristics
Description of design component: Current non-alcoholic yeasts vary in their ability to metabolise sugars in wort into desirable beer flavour compounds. The goal of the design is to optimize the metabolic pathways of non-alcoholic yeast for the production of these compounds through genetic manipulations. Furthermore, an investigation into the fermentation conditions at industrial scale will support the design of a full brew protocol in order to refine the beer production.
Economic and social impact: The market for non-alcoholic beverages is predicted to be at $2.9 trillion in 2035 because of recent trends in lower alcohol consumption and health considerations. NA beer is a significant component of this market and current de-alcoholization methods tend to eliminate sought after flavours or are extremely resource intensive. Investigating a biological method to produce low/non-alcoholic beer with robust flavour profiles will allow smaller scale breweries to enter into this market and expand the market of non-alcoholic beverages.
Skills requested or to be developed: Chemical analysis (qualitative and quantitative) of compounds in solution and linking to sensory attributes; Design and running controlled fermentations; Understand the metabolic pathways of novel yeasts and genes related; Yeast genetic manipulation; Understand and design of industrial scale protocols including target process, safety, sanitation, material, equipment, etc.
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Project 31
Portable Soft Robotics Platform for ENT Surgery
Supervisor: Prof. Amir Hooshiar, Prof. Mark Driscoll, amir.hooshiar [at] mcgill.com
Preferred Team Size: 5
Background and Objectives: The Surgical Performance Enhancement and Robotics (SuPER) Center of the McGill University Health Centre has developed a series of prototype soft robotic surgical instruments and integration platforms for applications in the surgical management of head and neck (ENT) cancers. Its flexible continuum design can navigate and operate within very tight and curved spaces, reaching areas traditional rigid instruments cannot. This capstone project will focus on the compilation of design requirements, searching for optimal design parameters as well as the prototyping of a compact, mobile surgical robotic platform which will integrate the soft robotic instruments and controllers for bimanual operation.
SuPER is planning to perform pre-clinical validation studies for usability of the system known as Unicorn. The goal is to build a compact, portable prototype for Unicorn with a hardware-software integrated design for surgical use. Subject matter experts, e.g., surgeons and clinical scientists, will be available over the course of the project to provide feedback and testing to inform the design iterations. The final deliverables will include both a live demonstration and a publication.
Description of design component: The project will involve both mechanical design and software development. The design will include system, module, and components design levels.
1. System Design: at a system level, Unicorn’s current system design will be reviewed, and SuPER’s previous findings will provide guidance on identifying the system pain points.
2. Module Design: the system will include three main modules: mechanical, hardware, and software.
a. Mechanical Module (MM) includes:
i. Chassis unit (CHS)
ii. Instrument Actuation unit (ACT), and
iii. Soft Robotic units (SORO)
b. Hardware Module (HM) includes:
i. Power unit (PU)
ii. Motors and control unit (MCU)
iii. Vision unit (VU)
iv. Communications unit (COMMS)
c. Software Module (SM) includes:
i. Firmware (FW) for low-level motor control
ii. Graphical User Interface (GUI) for real time field visualization and imaging
iii. Central Memory Management (CMM) for thread-safe synchronization and communications between GUI and FW and data logging.
3. Components Design: components listed above in Greek numerals represent the components of interest to design (and some to redesign) in this capstone project. The design process of the MM components entails designing robotic components in CAD software, validating designs through finite element analysis (FEA) and experimental testing, rapid prototyping, assembling and testing new design iterations of the overall robotic system. Also, procurement of off-the-shelf components (especially for the CHS component) will be prioritized as SuPER funding and items availability allows. Also, the design process of HM components may entail selection of off-the-shelf components after rigorous engineering analysis and design. SW components however will be built from scratch leveraging the available code-based at SuPER for Unicorn and the available SDKs from components manufacturers, e.g., Maxon Motors, Switzerland. More specifically for VU, we will deploy an AI-based anatomy tracking system based on Co-Tracker deep neural model to be able to track the target anatomy in real time without fiducial markers. Also, for FW of instruments shape control we may need to develop a data-driven kinematic model for the continuum soft robotic tool, including:
- Collecting kinematic data through experiments
- Designing, testing, and validating multiple model architectures
- Integrating the validated model with the overall control software
- Comparing the performance with traditional kinematic models
4. System Validation: We will enroll our Unicorn Capstone system in Dr. Camille Caron’s SuPER-Unicorn Study (led by Dr. Caron and approved by MUHC IRB). Her study involves a system usability study (SUS) with expert feedback. We will incorporate the experts’ feedback into our design. This validation will be on a “system” level and will evaluate the overall integrated system’s usability.
Economic and social impact: Oropharyngeal tumours are difficult to access, even with state-of-the-art surgical tools. Further, existing surgical systems are expensive. This project may lead to higher surgical performance when dealing with oropharyngeal cancers, as well as increasing the access to surgical management for certain patients.
Skills requested or to be developed: Machine learning/deep learning, computer vision, data-driven modelling, ROS, CAD (SolidWorks), FEA (Ansys), additive & subtractive manufacturing, microprocessors, drafting publications and conference submissions.