Nazanin has a MSc in Physics and a PhD in Medical Biophysics from University of Toronto, located at Sunnybrook Hospital.
Naz leads our Covid-19 pivotal clinical trial and manages research projects in collaboration with the University of Alberta and Baycrest Hospital.
Given her background in biophysics, Naz’s passion aligns with Vielight’s goal of discovering how light energy could be used optimally to positively impact human physiology.
Industry Expertise (4)
Health and Wellness
Advanced Medical Equipment
Medical Equipment / Supplies / Distribution
Areas of Expertise (10)
Medical Device Development
Ultrasound Contrast Agents
University of Toronto: Ph.D., Medical Biophysics 2014
Brock University: M.Sc., Physics 2006
Sharif University of Technology: B.Sc., Physics 2003
- IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society : Member
Media Appearances (1)
Ontario light therapy clinical trial aims to accelerate recovery from COVID-19
Clinical Trials Ontario
The Vielight RX Plus device delivers light therapy to the sternum and the nasal canal. “This device brings a holistic approach to the treatment of COVID-19 patients,” said Nazanin Hosseinkhah, Research Scientist and Physicist at Vielight Inc. “The device stimulates the thymus gland, creates nitric oxide, increases natural killer cells, acts as an anti-inflammatory therapy, and increases cellular energy.”
Near-Infrared Photobiomodulation of Living Cells, Tubulin, and Microtubules In VitroFrontiers in Medical Technology
2022 We report the results of experimental investigations involving photobiomodulation (PBM) of living cells, tubulin, and microtubules in buffer solutions exposed to near-infrared (NIR) light emitted from an 810 nm LED with a power density of 25 mW/cm2 pulsed at a frequency of 10 Hz. In the first group of experiments, we measured changes in the alternating current (AC) ionic conductivity in the 50-100 kHz range of HeLa and U251 cancer cell lines as living cells exposed to PBM for 60 min, and an increased resistance compared to the control cells was observed. In the second group of experiments, we investigated the stability and polymerization of microtubules under exposure to PBM.
Home-use Photobiomodulation Device Treatment Outcomes for COVID-19medRxiv
2022 BACKGROUND There is need for non-pharmaceutical treatments for COVID-19. A home-use photobiomodulation (PBM) device was tested as Treatment in a randomized clinical trial. METHODS 294 patients were randomized with equal allocation to Treatment or Standard of Care (Control). 199 qualified for efficacy analyses. The Treatment group self-treated for 20 minutes twice daily, for the first 5 days, and subsequently once daily for 30 days. A validated respiratory questionnaire was used, and patients were monitored remotely. The primary endpoint was the time-to-recovery (3 consecutive days of no sickness) for general sickness. The Kaplan-Meier method and the Cox Proportional Hazards model were primary methods of analyses.
Modulation of cortical oscillations using 10hz near-infrared transcranial and intranasal photobiomodulation: a randomized sham-controlled crossover studyBrain Stimulation
2021 Objectives: To determine if baseline or changes in CNS metabolites in thebasal ganglia (BG) predict response to taVNS-paired feeding, particularly inIDM exposed to uncontrolled hyperglycemia in utero.Methods: Thirty infants, who had brain injury and were G-tube candi-dates, had daily taVNS-paired feeding treatments for 2 weeks, with pre-and post-treatment MRS scans. LCModel quantiﬁed metabolite concen-trations were compared pre- and post-taVNS (Mean+/-St.Dev, 15 +/- 8days). Oxidative stress was measured by glutathione (GSH). We performedlogistic regression to predict treatment response with gestational age (GA),metabolite concentrations, treatment days, and IDM status as covariates.
Artificial intelligence in outcomes research: a systematic scoping reviewExpert Review of Pharmacoeconomics & Outcomes Research
2021 Introduction: Despite the number of systematic reviews on how artificial intelligence is being used in different areas of medicine, there is no study on the scope of artificial intelligence methods used in outcomes research, the cornerstone of health technology assessment (HTA). This systematic scoping review aims to systematically capture the scope of artificial intelligence methods used in outcomes research to enhance decision-makers’ knowledge and broaden perspectives for health technology assessment and adoption. Areas covered: The review identified 370 studies, consisted of artificial intelligence methods applied to adult patients who underwent any health/medical intervention and reported therapeutic, preventive, or prognostic outcomes.