不良研究所

An Innovative Device for Non-Invasive Intervention for TMJ Pain and Bruxism

Assistant Professor Natalie Reznikov, Bioengineering, Assistant Professor Julia Cohen Levy, Orthodontics, Associate Professor Joyce Fung, School of Physical & Occupational Therapy and Dr. Alexei Morozov

Executive Summary

Bruxism is a broad category of jaw muscles activities during sleep or wakefulness. Manifesting as clenching/grinding of teeth or bracing jaws, bruxism may cause irreversible deterioration of dentition and chronic temporomandibular joint (TMJ) disorder and pain. The etiology of bruxism is nebulous, and no etiotropic treatment exists for its root cause. Based on a comprehensive analysis of the TMJ biomechanics, we hypothesize that bruxism motor patterns can be alleviated noninvasively by correcting the basal tone of the muscles involved in the lower jaw movement. We have built a prototype of the oscillating device (patent pending technology) that applies mechanical vibration to masticatory, facial, and neck muscles to reduce their basal hypertonicity. By validating and quantifying the reconditioning effect of vibration on the head and neck musculature, we aim at developing a novel physiotherapy/home treatment for TMJ disorder and bruxism. Firstly, we will test whether the reversal of the jaw-muscle hypertonicity changes the habitual position of the jaw. Secondly, we will test whether the symptoms of TMJ disorders, awake bruxism and/or sleep bruxism diminish as a result of muscle reconditioning. Finally, we will evaluate the longevity of the therapeutic result and will develop a treatment protocol. The insight obtained in this study will help further assess the commercialization potential of the invention.

Sleep Staging with Intra-Oral EOG Monitoring Wearable

Associate Professor Sharmistha Bhadra and Han Cat Nguyen, PhD Student, both from Electrical and Computer Engineering

Executive Summary

According to the international classification of sleep disorders (ICSD-II) criteria, 84 different sleep disorders are defined. Depending on the type of sleep disorder, treatments are prescribed for patients. Sleep disorders are diagnosed by assessing sleep quality which is usually determined by sleep staging. Typically sleep specialists manually identify sleep stages (wake, N1, N2, N3, and REM) based on polysomnography (PSG) signals acquired in sleep labs or with home sleep test kits. The manual annotation process is time consuming, prone to human errors and requires experts. Automatic sleep staging based on either electroencephalogram (EEG) or electrooculogram (EOG) signals is gradually increasing. Currently, there are EEG or EOG based sleep monitoring wearables in the forms of headbands, sleep masks and in-ear devices used at home or in research. However, most of these wearables as well as home test kit are uncomfortable to wear and tend to get displaced during sleep, which results in wrong measurements. These days, affordable intra-oral wearables such as mouthguards and mandibular advanced devices (MADs) are already worn comfortably by many people during sleep to reduce bruxism (teeth grinding), snoring, and sleep apnea. These intra-oral devices do not get displaced during sleep. In these contexts, we have developed the first prototype of a low cost intra-oral EOG monitoring wearable with application to automatic sleep staging. People who are susceptible to sleep disorders and are already using some kind of intraoral wearables will be the first adopter of the technology. Since the publication of our papers and recent meetings with potential investors, it is evident that our solution addresses an invaluable asset for comfortable EOG monitoring wearable that enables the next generation of sleep staging. With the WRSA we will fabricate more intra-oral EOG monitoring wearables and collect sleep EOG data from volunteers to further test the effective operation of the wearable.

PreFab AI Photonics

Professor Odile Liboiron-Ladouceur and Dr. Dusan Gostimirovic, Postdoctoral Fellow, both from Electrical and Computer Engineering

Executive Summary

The semiconductor industry can now integrate light on a chip, leading to higher data capacity in communications and many emerging applicationssuch as sensors, optical quantum computing, and optical neuromorphic computing. Light, however, is more susceptible to fabrication process deviations than its electronic counterpart. Our invention uses machine learning (ML) to predict and correct deviations in the design of photonic (optical) integrated circuits prior to nanofabrication, saving on cost, time, and energy. Since the publication of our paper and recent discussions with potential customers at an international conference earlier in November, it is evident that our solution addresses an invaluable need for better design tools that enable the next generation of photonics. Indeed, our technology is the first ML-based solution to correct design prior to fabrication, which will have considerable impact in the industry. The WRSA grant will enable us to deploy our next minimum viable product to gather feedback and validate its performance with a target group of users.

BleedBloc: Next-Generation Hemostatic Technology to Stop Hemorrhage

Assistant Professor and Canada Research Chair Jianyu Li and Shiyu Liu, PhD Candidate, both from Mechanical Engineering

Executive Summary

Uncontrolled bleeding or hemorrhage remains an unmet clinical challenge, which causes ever-increasing socio economic burdens due to the aging population, increasing trauma injuries, limited supply of blood transfusion and conflicts around the world. Despite the significance and growing market of hemostatic agents, existing solutions cannot meet the clinical needs due to the limited mechanical performance and the lack of hemostatic efficacy. To address the clinical needs and save lives from hemorrhage, we have invented a paradigm-shifting hemostatic technology, called Liquid-Infused Microstructured Bioadhesive (LIMB). The LIMB can stop various bleeding conditions, including the most challenging non-compressible hemorrhage, in seconds, while exhibiting excellent biocompatibility and biodegradability. With its performance validated in vitro and in vivo, the LIMB overperforms clinically used hemostatic agents in terms of hemostatic efficacy and biosafety.

SALIVERA: A FULLY AUTOMATED MOLECULAR TESTING DEVICE FOR RAPID DETECTION OF VIRAL RNA

Professor Sara Mahshid and Dr. Roozbeh Siavash Moakhar, research associate, Bioengineering

Executive Summary

This technology consists of a device for very rapid diagnostic and serological testing in response to urgent needs in the COVID-19 pandemic. The portable and automated electrical acquisition can be coupled to a smartphone, using a smartphone application that can receive the electrical data and interpret the data into reading signals for a digital display. Our approach is cost-effective and does not require skilled operators. The William and Rhea Seath Award (WRSA) will support the fabrication cost of one unit of industrial design of SALIVERA with the aim of testing the device in a hospital -the last critical step before regulatory approval and commercialization.

PATTERN BASED CONTRACTILITY SCREENING IN DRUG DISCOVERY

Pictured Professor Allen Ehrlicher and Ajinkya Ghagre, PhD Candidate, both from Bioengineering; Dr. Ali Amini, postdoctoral fellow, Johanan Idicula (Forces Canada) and Professor Ramaswamy Krishnan (Harvard Medical School)

Executive Summary

Cells exert contractile forces, and defects therein are fundamental to diverse pathologies including cardiomyopathies, skeletal myopathies, vasospasm, bronchospasm, and cancer migration, invasion and metastasis. In each of these disease contexts, novel drugs with the potential to modulate cellular contractile forces that ameliorate disease symptoms or progression are urgently sought. Nevertheless, there are no pre-clinical, clinical, or industrial methods for quantifying the forces exerted by cells. To bridge this gap, we have created a simple and efficient methodology of contractile quantification which we call Pattern-based Contractile Screening (PaCS). We are commercializing PaCS as a new screening technology that uses cell contractility to identify and characterize novel potential therapeutic compounds while eliminating false positives early in the drug process, thus potentially saving billions of dollars, years of effort, and human lives associated with defective drug candidates. With the William and Rhea Seath Award, we hope to complete the translation of our proven lab method into a successful product.

A PARADIGM SHIFT IN WATER TREATMENT: REENGINEERING WITH LOW-COST, SUSTAINABLE AND RECOVERED WASTES

Professor Nathalie Tufenkji and Dr. Mathieu Lapointe, postdoctoral fellow, Chemical Engineering

Executive Summary

With an annual global market of $18 billion, coagulants and flocculants are critical to water treatment but carry an economic and environmental burden. For wastewater alone, these chemicals generate ~8 million tons of metal-containing sludge waste annually. To simultaneously deal with the issues of process sustainability, cost, and efficiency, we have developed new materials notably reengineered using recovered waste from treatment plants; namely, cellulose, polyester, cotton, and keratin fibers. These advanced materials (functionalized fibers and microspheres) drastically improve removal of conventional and emerging contaminants during settling by increasing floc size and density. Moreover, we developed a three-in-one bridging/ballasting/adsorbing cellulose-based material (flake) that can simultaneously adsorb contaminants, bridge colloids, and ballast flocs, whilst reducing chemical usage. The unprecedented size of flocs produced using flakes enables easy floc removal by screening, eliminating the need for a settling tank, a large and costly process unit. These reusable materials combined with separation via screening will allow global water treatment facilities to reduce their capital and operating costs as well as their environmental footprint. Because of their relatively low cost and unprecedented performance, we expect that our products will be commercialized globally. In fact, our materials would be notably used during aggregation-settling, a technology used by more than 70% of the water treatments plants in the world. This award will be used for salary support and the fabrication of a portable pilot unit to test the materials for different market applications as we drive the technology to commercialization. This award will significantly accelerate our market entry by enabling us to demonstrate the performance of our disruptive technology at a larger scale and over a wider range of operating conditions (i.e., for several industrial sectors requiring water treatment).

POWER-EFFICIENT听AI-PROCESSOR WITH DIRECT RAW CAMERA-SENSOR DATA PROCESSING

Pavel Sinha, PhD Student, Professors Ioannis Psaromiligkos and Zeljko Zilic, all Electrical and Computer Engineering

Executive Summary

Artificial Intelligence (AI) is an emerging technology that is slowly making its way into our day-to-day life. Currently, AI is mostly in the cloud computing space, but in the future, AI will be present in every electronic device. Like the microprocessors penetrating every electronic component since the early 1990s, in the future, dedicated AI computation circuitry will be into every electronic device regardless of shape and size. Companies trying to build such computing devices are presently concentrating on the hardware component, which has been the traditional approach. We believe that the optimal approach is to simultaneously optimize the algorithm, hardware platform, and the overall system, resulting in a scalable and highly cost-optimized solution. We have a patent-pending AI-Processor hardware architecture that is best in its class for power consumption. The technology enables running on battery power for over a year without needing a battery replacement. We have a patent-pending technology to integrate our AI-Processor in most existing systems without the need for hardware re-spin, unlike our competition.

Further, we differentiate ourselves with patent-pending technology that enables the application of optimized AI algorithms directly on raw camera sensor data, reducing the need for expensive image signal processing hardware, thus lowering cost and power consumption. Finally, our integrated software development platform enables developers to effortlessly integrate AI algorithms from any of the popular Python/Matlab environments to our AI-Processor. We have demonstrated several attractive applications such as real-time object detection and classification and automatic lip-to-audio synthesis. We are currently in talks with potential customers that have expressed sincere interest in our technology and are in an engineering collaboration with one of them. We are currently developing the integrated circuit (IC) in an industry-academic partnership with 不良研究所 and CMC. We intend to use the WRSA funds to pay the salary and stipend for interns and pay for material costs for the AI-Processor development and testing.

Professor Amine Kamen (Bioengineering) for 鈥淎dvanced process for scalable production of viral vectors for gene and cell therapy鈥�

Executive summary:

There is a revolution happening in medicine with the recent regulatory approval of novel cell and gene therapy treatments against so far incurable diseases, such as blood cancer and some types of rare genetic diseases. As a result, researchers in the field are moving toward the development of new promising approaches with application to other unmet medical needs. However, the complex manufacturing process behind these treatments is slowing down the research translation. Preclinical experiments as well as clinical trials require large quantities of high quality viral vectors and, to date, manufacturing centers are overburdened. Academic research laboratories and early stage companies do not have the infrastructure to develop and manufacture the needed biological material. We will exploit our integrated process for a high yield and scalable production of viral vectors (lentivirus and adeno associated virus) using our suspension technology platform instead of the ancient and difficult to scale adherent cell system. Our production process and capability can have a significant impact to support the increasing demand of these vectors and bridging the existing gap between research and clinic. With this award, we want to support end user validation in the form of salary and consumables towards commercialization.

Professor Pascal Hubert (Mechanical Engineering) for 鈥淒evelopment of an innovative composite prepreg recycling system鈥�

Executive summary:

Carbon fibre prepregs are the most widely used raw material for making high-performance composite structures. They consist of dry fibre impregnated with a partially cured polymeric resin and they represent a very significant portion of the total manufacturing cost of a given structure. The carbon fiber prepreg market is expected to grow

from USD 7.0 billion in 2019 to USD 11.5 billion by 2024. Current manufacturing practices, however, generate large quantities of prepreg waste, which poses both a financial burden on the manufacturer and a negative environmental impact. Several recycling solutions are being studied at the lab scale, but none have reached the level of maturity necessary for industrial implementation. This project aims at deploying a commercially viable recycling tool that transforms prepreg waste collected directly from an aerospace manufacturer into a high-performance compression moulding compound. The successful scale-up of this technology would lead to an unprecedented improvement in composites manufacturing sustainability within the aerospace industry. Estimated saving of USD 2-3 billion per year could be achieved with this technology developed at 不良研究所 as 30-50% of the carbon fibre prepreg purchased end up in the landfill. Furthermore, it would facilitate the adoption of composites within other major sectors, such as automotive, marine, recreational sporting goods, etc.

Presented by Associate Dean, Research and Innovation Benoit Boulet

(left to right) Professor Vivian Yargeau (Chemical Engineering), Professor Thomas Szkopek and Ibrahim Fakih, PhD candidate (both Electrical and Computer Engineering) for 鈥淣ext-Generation Hydrological Sensor Technology for Water Quality Monitoring鈥�

Executive summary:

Water is a natural resource essential to the global biosphere, and no less important to the well-being of a nation's citizens. Despite its importance, water quality is insufficiently measured in space and time due to cost, practicality and overall feasibility. Deficiencies in water quality monitoring can be overcome by increasing the accessibility of ion sensing tools. We have developed inexpensive graphene ion sensing field effect transistors (ISFETs) with very low detection limits that can measure water quality in real-time. Our invention can potentially fill an important void in water quality monitoring technology. With this award we will validate graphene ISFETs by testing them in the field and integrating them with the Internet of Things (IoT).

(left to right) Hamed Rafezi, PhD candidate and Professor Ferri Hassani (both Mining and Materials Engineering) for 鈥淭ricone Bit Wear Monitoring and Failure Prediction鈥�

Executive summary:

The mining industry is moving toward automation and autonomous machinery for increasing the efficiency and precision in production. A successful automated blasthole drilling condition monitoring is a necessary component of this journey. Drilling and blasting (Appendix 鈥� figure 1 and 2) are two preliminary tasks in large surface mining operations and constitute more than 15% of the total operational costs. Bit wear and subsequent bit failure create remarkable delays and costs. The detached bit parts after the failure must be removed from the hole to avoid damage to the rock crusher equipment. In addition, fully autonomous drilling would not be achievable without a machine sensing system for recognizing when the drill bit is worn and requires replacing. Our patent-pending system, offers a solution to monitor the bit wear level in real-time and to predict the catastrophic failure. The system relies on signals analysis and an artificial intelligence model trained by full-scale drilling data gathered in mining operations in the past phases. The proposed application aims to cover the costs to build a stand-alone prototype of our system.

Professor Brett Meyer and Professor Warren Gross (both Electrical and Computer Engineering) for 鈥淓ffortless AI Makes Artificial Intelligence Easy鈥�.

Executive summary:

While AI is clearly the future, most developers lack the expertise to build such systems. Effortless AI, by automating the design and optimization of machine learning systems, makes it possible to bring efficient AI to more devices, faster. Though we are not the first or only to automate the design of machine learning algorithms (e.g., Google鈥檚 AutoML, NYTimes) we are unique in our approach: by explicitly considering issues that matter for mobile/IoT systems (e.g., the time or energy required to perform facial recognition), we produce the best systems possible for these platforms. The WRSA will offer critical support at a key time as we work to prepare our prototype for customer validation and early contracts, and ultimately to raise seed funding.

Professor Showan Nazhat (Materials Engineering) and his team comprised of Professor Anie Philip (Surgery, not present) and PhD student Gabriele Griffanti (Materials Engineering) for 鈥淩apid high through-put 3D-printed in vitro skin models for drug discovery and screening鈥�

Executive summary:

This proposal aims to advance a world unique 3D printing technology developed at 不良研究所 that is based on a recently granted U.S patent (9,764,060). Our breakthrough development is the 3D bioprinting of tissue structures with varying architectures based on a platform bioink system with a novel printing method. By using naturally derived bioink hydrogels with incorporated cells, the printed tissue structures can be tailored to mimic collagen fibril density and alignment, as well as cell loading and density according to the intended use. This novel approach will overcome current challenges in the bioprinting of tissues such as maintaining cell viability and spatial control in 3D microenvironments during processing. In this WRSA proposal, we intend to reduce to practice this technology by focusing on the 3D bioprinting of in vitro skin models to investigate a novel therapeutic in the treatment of fibrosis and cancer.

William Lepry, PhD student, Professor Showan Nazhat, both Materials Engineering and Professor Faleh Tamimi (Faculty of Dentistry), for their 鈥淩emineralizing Toothpaste for Treatment of Tooth Hypersensitivity鈥� project.

Executive summary:

It is estimated that more than half of the adult population suffer from dentine hypersensitivity; a common clinical condition that results in sharp bouts of pain generating from the mouth when teeth are exposed to external stimuli. Treatment methods include desensitizing agents in mouthwashes or chewing gums, but more recently there has been a drive towards the addition of mineralizing agents, such as bioactive glass, in toothpastes. However, the slow dissolution rate of the current glass formulations is far from ideal for dental applications, often requiring days for dissolution. At 不良研究所, we have developed sol-gel derived borate glasses that have demonstrated remarkable rates of conversion to the mineral present in dentine (and bone); hydroxycarbonated apatite. In this application, we intend to exploit this mineralizing capacity by combining the novel glass formulation with toothpaste, to provide rapid dentine hypersensitivity relief. This award will prove vital in the progression of this technology by providing critical funds to carry out in vitro testing using human dentin models.

Professor Marta Cerruti, Materials Engineering, and her team Dr.Simon Tran (Dentistry, not present), Dr. Faleh Tamimi (Dentistry), Dr. Reza Farivar (Medicine, not present), Dr. Monzur Murshed (Dentistry, not present) for their 鈥淧olymer Coating Technology for Biomedical Applications鈥� project.

Executive summary:

Synthetic polymeric materials are used in cell culturing and tissue engineering as platforms to enhance cell attachment, proliferation and activity, and to promote healing of injured or missing tissues. Despite being biocompatible, most synthetic polymers do not allow easy integration with cells or tissues. Thus, the surface of a polymer needs to be modified prior to any biomedical application. Current technologies result in layers that are unstable, inhomogeneous, and often degrade the polymer, in addition to being expensive and not applicable on complex geometries. We have developed a simple technology to modify polymer surfaces to promote cell adhesion and improve in-vivo performance. With the WRSA funds, we will be able to move on to commercialization.

Professor Subhasis Ghoshal (not present) and Dr. Sourjya Bhattacharjee, post-doctoral fellow, both Civil Engineering and Applied Mechanics, for their 鈥淪cale Up of Novel Biphasic Treatment Process for the Treatment of Chlorinated Solvents with Reactive Iron Nanoparticles鈥� project.

Executive summary:

Extensive industrial use and improper disposal in the past have resulted in the widespread contamination of groundwater aquifers and soils with neurotoxic, carcinogenic chlorinated solvents such as tetrachloroethylene (PCE) and trichloroethylene (TCE). A significant fraction of the TCE and PCE are present as non-aqueous phase liquids (NAPLs) in contaminated aquifers because of their slow solubilization, leading to persistent and extensive contamination. We have developed a novel, cost effective, nanotechnology-based non-aqueous phase treatment process that rapidly transforms PCE and TCE into non-toxic gases, ethene and ethane, and chloride ions, which can be recovered and reused. The limited amounts of reagents required and the generation of commercially relevant end products make this a lower environmental footprint system than existing alternatives. Through this award, we propose to scale up and demonstrate the successful treatment of PCE and TCE in a 20 L pilot scale reactor with maximized material recycle and recovery.

Professor Nathalie Tufenkji and Dr. Vimal Maisuria, postdoctoral fellow, both Chemical Engineering, for their 鈥淢aple Syrup Extract to Reduce Antibiotic Resistance鈥� project.

Executive summary:

They have showed that an extract from maple syrup can make disease-causing bacteria more susceptible to common antibiotics. This is a simple and effective approach for significantly reducing antibiotic usage (up to 97%), thus slowing the spread of antibiotic-resistance. The extract also acts synergistically with antibiotics in destroying resistant bacterial communities known as biofilms. The proposed synergism-based treatment may expand the spectrum of existing antimicrobials, prevent the emergence of resistant strains, and minimize potential cytotoxicity due to high antibiotic doses. They envision the extract being incorporated, for example, into antibiotic capsules or creams as an antibiotic-boosting agent. The award will be used to conduct necessary in vitro and in vivo experiments with maple syrup extracts to confirm the efficacy of this non-obvious and potentially disruptive technology.

Dr. Mehrdad Mahoutian, postdoctoral fellow, and Professor Yixin Shao, both Civil Engineering and Applied Mechanics, for their 鈥淕reen, Carbon-Negative Construction Materials鈥� project.

Executive summary:

They have developed a carbonation technology that produces construction materials using steel slag as binder and carbon dioxide (CO2) as activator. A specific example is a standard construction block, which are traditionally made from Portland cement. The method developed uses the carbonation activation technique to make steel slag a primary binder for block applications. This will eliminate the use of Portland cement, reduce carbon dioxide emissions, convert steel industry waste into value-added products, sequester carbon dioxide into stable carbonates, and consume zero virgin materials. These construction blocks have equivalent mechanical properties compared to commercial cement-based concrete blocks. As well, the production cost of the green blocks is approximately 25% lower than the commercial standard. The well-established block market suggests a great business opportunity for this new product. The award will allow the team to further generate commercially-relevant data and de-risk the technology for future investment.

Farshad Mirshafiei, PhD student Civil Engineering and Applied Mechanics and Dr. Mehrdad Mir Shafiei, Postdoctoral fellow, Electrical and Computer Engineering, for their 鈥淣ovel Three-Dimensional Seismic Assessment Method (3D-SAM) for Structures based on Sensing Tests鈥� project.

Executive summary:

In the world we live in, earthquakes often cause damage to structures, pose threats to human lives and result in huge economic losses. Existing earthquake assessment solutions start with visual inspection of the structure and subsequently more detailed earthquake evaluation may be planned. Detailed assessment is based on theoretical models that require detailed engineering plans, is both complex and time consuming with an accuracy that depends on the engineer. To address the shortcomings of the current methods, the team invented a new three-dimensional seismic assessment method, 3D-SAM, based on real data recorded by sensors. They established Sensequake to commercialize the idea in September 2015. The award will help to enhance the technology and also to purchase required sensors.

Professor Damiano Pasini, Mechanical Engineering, Dr. Sajad Arabnejad, Mechanical Engineering, Dr. Michael Tanzer, MD, Department of Surgery, and Burnett Johnston, Mechanical Engineering for their 鈥淔ully Porous Hip Replacement Implant Capable of Eliminating Bone Resorption鈥� project.

Executive summary:

Their novel implant uses a fully porous structural biomaterial that avoids bone resorption by seamlessly matching the properties of the local host bone tissue. In addition, the new design can be adopted with no modifications to existing surgical technique and hospital infrastructure. Existing hip replacement procedures often require follow-up surgery that can increase the risk of complications and even death. Current hip implants in the market are incapable of preventing long-term stress-related bone loss, which is a risk factor for the success of revision hip surgery. The award is contributing to the cost of the animal studies.

Professor Milica Popovic, Electrical and Computer Engineering, for her 鈥淓arly Breast Cancer Screening with Low-Power Microwaves鈥� project.

Executive summary:

It is under further development promises inexpensive, comfortable and safe monitoring of breast tissue and early detection of malign lesions. Detection of early stage breast tumors is critically important. Each of the current modalities, such as mammography, ultrasound and MRI, has downsides, often resulting in late tumor detection and, consequently, a lower success rate in post鈥恠urgical treatment. Low鈥恜ower microwave鈥恇ased screening is an emerging field that promises inexpensive, comfortable and safe monitoring of breast tissue, to enable early detection of malignant lesions. The 不良研究所 research team is among only a few in the world that has evaluated the underlying technology (ultra-wide-band (UWB) microwave detection) for monitoring breast tissue in human subjects. The award is providing funds to help build a more compact and portable second-generation prototype for use in ongoing feasibility studies.

James McGoff and Charles A. Vincent, both undergraduate students in Mining and Materials Engineering for their 鈥淣ovel Insulation Inserts for Improving Large-Scale BioPharma Logistics Operations鈥�.

Executive summary:

LIFEPACK, the company that James and Charles co-founded, is commercializing a novel insulation product for companies seeking to improve their large scale cold chain operations without disrupting their current shipping logistics. Adopting the LIFEPACK product is the quickest and easiest way for companies to improve their cold chain packaging by 40% to 80%. The product鈥檚 development was heavily based on a continuous dialogue with key partners in the biopharma industry. These industrial partners included pharmaceutical developers, centralized laboratory services, contract research organizations (CRO鈥檚), blood banks, hospitals, and third party logistics providers (3PL). The award will go towards scaling and sustaining the growth of the company.

Professor Andrew Kirk, Electrical and Computer Engineering, Dr. Philip Roche of the Lady Davis Institute for Medical Research, and Professor Mark Trifiro, 不良研究所 Department of Medicine and Chief of Endocrinology at the Jewish General Hospital, for their 鈥淢ultiplex Measurement of PCR Reactions by a Label Free Plasmonic Thermocycler鈥�.

Executive summary:

This new, better, cheaper, and faster method in the performance of the polymerase chain reaction (PCR) has been demonstrated and patented at 不良研究所. PCR is an essential tool in molecular biological investigations and dominates the field of molecular diagnostics, providing DNA fingerprinting for crime scene analysis as well as identification of disease processes (cancer resistance and susceptibility, hereditary illness and microbial infection). The award will meet the specific aim of delivering the prototype of a miniaturized, multiplex, energy efficient, and rapid real-time PCR platform that outperforms market leaders.

Toufic Azar, PhD student Mechanical Engineering and his multidisciplinary team comprised of Dr. Renzo Cecere (cardiac surgeon at MUHC) and Professors Jorge Angeles, Josef Kovecses, and Rosaire Mongrain (Mechanical Engineering) for their 鈥淣ovel Percutaneous Mitral Valve Repair System鈥�.

This system gives those suffering from mitral valve regurgitation disease the opportunity to undergo a more effective and less invasive technique to reduce risks and trauma associated with conventional open-heart surgery.

Ahmad Haidar, PhD student in Electrical and Computer Engineering and Professor Benoit Boulet (Electrical and Computer Engineering) for their 鈥淓xternal Artificial Pancreas for Patients with Type 1 Diabetes鈥�.

This system gives those suffering from Type 1 diabetes the opportunity to access more effective, portable, automated treatment of their disease.