Our proprietary platform enables us to ingest multiple sources of data to better characterize individuals (imaging, genetic, phenotypic, molecular and clinical variables).
We are able to rapidly and precisely target subgroups of interest in large, heterogeneous populations.
Perceiv’s digital biomarkers are highly specific and thoroughly validated, making them ready for action in any clinical setting.
Accelerating and improving the quality of clinical trials via prognostic enrichment
Our platform enables our partners to derive unique, actionable insights from their raw data
We improve treatment outcomes by better targeting responders
Patient variability presents a significant problem in Alzheimer’s drug development: about 99.6% of Alzheimer’s disease trials fail. Using our high precision digital biomarkers, we can enrich trials to predict disease progression and identify the subgroups of patients most suitable for Alzheimer’s disease clinical trials, thereby greatly increasing the likelihood of trial success. We can also predict and pre-screen amyloid-beta positive subjects using readily-available modalities.
Clinical trials assessing post-myocardial infarction treatment are particularly challenging; while these trials require subjects that will develop a second cardiovascular event, only 10% of recruited patients do. To demonstrate clinical benefit, this forces trials to require enormous patient sample sizes. To solve this problem, we are developing AI-driven tools to optimize patient selection and predict which patients will 1) develop secondary events and 2) respond to treatment, thereby innovating better, faster, and cheaper ACS trials.
Dr. Dansereau has over a decade of experience doing machine learning research applied to neuroimaging and medical data. Ph.D. in Computer Science from University of Montreal. Master in Biomedical Engineering from McGill University. Bachelor degree in Electrical Engineering.
Dr. Laurent leads the software and machine learning development for Perceiv AI. He is a Deep Learning researcher from MILA Institute. He has extensive experience with medical data and large scale machine learning framework development.
Dr. Tam was a postdoctoral fellow at the National University of Singapore and completed her PhD in neuroscience at McGill University. Expertise in multimodal imaging of neurological diseases.
Dr. Noriega de la Colina's experience is in clinical research focusing in cardiovascular and neurodegenerative disorders. Ph.D. in biomedical aging sciences (Université de Montréal). Doctor in Medicine (M.D.). M.Sc. in Health Economics from the London School of Economics. Specialized training in clinical research from Harvard Medical School.
Mr. Rajchgot has experience in business development, strategic analysis, neuropharmacology research. He earned a Master of Science in Physiology (Georgetown University), an M.Sc. in clinical pharmacology (Université de Montréal), and a Bachelor of Science (McGill University).
Recipient of the Turing Award from the Association for Computing Machinery (ACM). Officer, Order of Canada. Professor, Department of Computer Science and Operations Research, University of Montreal. Canadian Research Chair in Statistical Learning, CIFAR Fellow, NSERC/Ubisoft Industrial Research Chair. Ph.D. in Computer Science, McGill University; Post-Doctorate at MIT and AT&T Bell Labs.
An advocate for translational research and though-tech innovations, Betsabeh's career spans scientific exploration, strategic operation, and early-stage investment. She has played a pivotal operating role at several organizations, most recently as the Managing Director of Global Labs and Health Data at The Commons Project Foundation, focusing on international health data interoperability. As Vice President of Strategy and BD at EquicareHealth she led market positioning and vertical growth across Oncology. At Cerner, she managed corporate strategy and patient predictive analytics in Diabetes and Heart Failure. She has also covered Canada for Borealis Ventures. Betsabeh holds an MBA from the Tuck at Dartmouth, a Master of Engineering from UBC, and Honors Bachelors in both Physics and in Biochemistry from UVic.
Director of the Alzheimer’s Disease Research Unit at McGill University, Montreal, Canada. Professor of Neurology & Neurosurgery, Psychiatry and Medicine at McGill University, Montreal, Canada. Member, Douglas Mental Health University Institute’s Research Center. Membre Associé, Institut Universitaire de Gériatrie, Université de Montréal.
Cardiologist, former president of CAE healthcare, professor of medicine and well-published researcher. An accomplished executive and board member of The Royal College International. Simulation Hall of Fame inductee (2018).
Certified corporate board director with 20+ years of international executive experience in NASDAQ-listed, BioPharma companies (Merck, Novartis, Celgene and Intercept) in the US, Canada and Europe. Extensive global operations and go-to-market medical-marketing expertise across therapeutic areas with several blockbusters and pipeline compounds. Active mentor for several MedTech start-ups. Manon has a master’s in nursing from McGill/University of Montreal, an executive MBA from McGill/HEC, she is a certified corporate board director from Harvard Business School.
Scientific director of the functional imaging unit. Researcher at the CRIUGM, Computer Science and operations research, University of Montreal. Co-lead of the biomarker team of the Canadian Consortium on Neurodegeneration in Aging (CCNA).
Founder and chief scientific officer at KalGene Pharmaceuticals. University and industrial research scientist.
Expertise in financial, health and medical technology sectors. Experienced in startup, growth and governance of companies. Board member of Montreal CHUM hospital.
Headquartered in Montreal’s Innovation District, Perceiv AI is a precision medicine technology company founded in 2018 and dedicated to improving treatment efficacy through refined patient selection. Thanks to multiple partnerships with pharmaceutical companies, hospitals, and research centres, Perceiv AI is developing digital biomarkers to help clinical trials succeed by pairing multimodal biomedical data and proprietary artificial intelligence technology to target the most suitable patients. Our turn-key solutions can be used for prognostic enrichment and for precise targeting of responders to a particular therapeutic intervention. Perceiv AI is helping build the future of precision medicine.
Perceiv is currently developing applications for Alzheimer's disease and cardiovascular disease.