91ÉçÇø

The 6th Annual 91ÉçÇø Clinical Innovation Competition and Awards Ceremony took place on May 11, 2023.

To watch the video recording of the event, .

Congratulations to all of our winners and finalists!  

Winner of the Hakim Family Innovation Prize

PL Signals

Lung fibrosis is a serious chronic and progressive disease with limited treatment options. TGF-beta is a potent pro-fibrotic factor, and its excessive action plays a central role in lung fibrosis. We have developed a novel anti-fibrotic biologic that traps TGF-beta with high specificity and efficiently reduces lung fibrosis in preclinical models and in vitro in patients’ fibrotic cells.

Anie Philip, Department of Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø
Shikha Chawla, Department of Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø
Kenneth Finnson, Department of Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø
Jini John, Department of Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø
Tenzin Kungyal, Department of Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø

Winner of the First Marika Zelenka Roy Innovation Prize

CoreSlicer

CoreSlicer is a cloud-based AI platform that automates the measurement of frailty and body composition from clinically available medical images (CT, MRI, ultrasound). The insights provided by CoreSlicer empower clinicians to individualize the care of vulnerable older patients to prevent postoperative complications, fatal adverse events, and emergency readmissions.

Jonathan Afilalo, MD, MSc, Principal Scientist, Jewish General Hospital, 91ÉçÇø
Philippe Marchandise, Lead Developer
Ding Yi Zhang, Data Scientist & Medical Student
Zara Vajihi, Machine Learning Engineer
Magueye Diagne, Data Engineer
Jeremie Abitbol, Strategic Analyst
Ibrahim Mohamed, Full-Stack Developer
Robert Viengkhou, Interface Designer
Louis Mullie, MD, MSc, Prior Member
Marc Afilalo, MD, Clinical Scientist

Winner of the Second Marika Zelenka Roy Simnovation Prize

PeTIT VR 

PeTIT VR (Pediatric Trauma Innovative Training) is a virtual reality course designed to enhance the skills of healthcare students and providers in pediatric trauma care. By leveraging the immersive and interactive nature of virtual reality technology, PeTIT VR is able to provide a unique and effective training experience that increases the quality of care and safety for pediatric trauma patients.

Fabio Botelho, MD, Experimental Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø
Dan Poenaru, MD, Experimental Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø
Elena Guadagno, MLIS, Division of Pediatric Surgery, Montreal Children's Hospital
Hamed Ranjbar , MSc, Experimental Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø

Winner of the First-Place MI4 Innovation Prize
   & the Bereskin & Parr Innovation Prize

BacPen DIAGNOSTIC

BacPen DIAGNOSTIC is a medical device start-up focused on a real-time point-of-care approach for diagnosing bacterial infections. They have developed a technology using electrochemistry that allows detection and specifically quantification for bacteria and other biological moieties in liquid and solid specimens.

Geraldine Merle, Professor, Biomedical Engineering, Polytechnique
Edward Harvey, Professor, Department of Surgery, Faculty of Medicine and Health Sciences, 91ÉçÇø
Raphael Trouillon, Assistant Professor, Electrical Engineering, Polytechnique

Winner of the Second-Place MI4 Innovation Prize

Curaforge

Curaforge aims to provide a low-cost and innovative solutions to make the stethoscope safer for healthcare workers and ultimately prevent healthcare worker exposure in the form of a medical device.

Sean Seltzer, Medical Resident, Faculty of Medicine and Health Sciences, 91ÉçÇø

Congratulations also to our finalist teams:

CapmAI

CapmAI is a leading provider of AI-based diagnostic solutions for capsule endoscopy. Their goal is to minimize diagnostic errors, increase efficiency for gastroenterologists, and accurately identify the location of disease.

Puja Pachchigar, Faculty of Medicine and Health Sciences student, 91ÉçÇø
Pranay Dixit, Business and Administration, John Molson School of Business, Concordia University
Emile Normand, Software Engineering, École de technologie supérieure 
Xiang Chen Zhu, Computer Sciences, Concordia University

MedTQ

The current standard tourniquet consists of a strip of fabric fastened about a hemorrhaging limb, and a windlass to mechanically augment tightening. However, inappropriate tourniquet application, either in terms of applied pressure or excessive duration, may lead to ischemia, nerve palsy, exsanguination, and possibly amputation. SmartTQ addresses these issues by incorporating a vessel occlusion sensor and timer to monitor these salient parameters, providing key data to soldiers and doctors.

Ludovic Mouttet, Experimental Surgery student, 91ÉçÇø
Romy Philip, Experimental Surgery student, 91ÉçÇø
Lora Tzaneva, Experimental Surgery student, 91ÉçÇø
Gabriella Spacagna, Experimental Surgery student, 91ÉçÇø
Quentin Bodineau, Engineering student, École Technologie Supérieure
Victoria Peuriot, John Molson School of Business student, Concordia University

SPINORT

SPINORT is an algorithm driven smart garment that manages and prevents recurrent mechanical low back pain. The device captures personal motion and muscle activity data and calculates the amount of near-infrared energy needed to stimulate the deep back muscles and correct the spine posture, and as such improve physical movement.

Antonia Arnaert, Associate Professor, Ingram School of Nursing, 91ÉçÇø
Swajan Paul, PhD student, Department of Experimental Surgery, 91ÉçÇø
Zoumanan Debe, Research Associate, Ingram School of Nursing, 91ÉçÇø