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Sarul Malik

CURRENT PEOPLE

Lab Manager

Postdoctoral Fellows

Graduate Students

Saurabh Singh (co-supervised with Dr. Ravi K. Elangovan and Dr. Vivek Perumal)

Vikas Pandey (co-supervised with Dr. Ravi K. Elangovan)
Pragya Swami

Meenakshi Singh (co-supervised with Dr. Gaurav Goel)
Rukmini Sarma

B.Tech. Students

Divya Choudhary

Satyam Anand

Prashant Jhalani

Project Interns

Abhirup Basu

Ayush Sharma

Undergraduates

Our Collaborators

Saruk Malik   sarulmalik@gmail.comsarulmalik@gmail.com

Sarul Malik is a Ph.D. student in the Center for Biomedical Engineering (CBME) at IIT Delhi under Dr. Sneha Anand jointly co-supervised by Dr. Shalini Gupta. Her graduate research topic is ‘Non-invasive detection of fasting blood glucose levels using saliva’. Diabetes mellitus is a systemic metabolic disease with a global burden of around 387 million at present that is expected to rise to 592 million by 2035. Handheld electrochemical glucometers are the most popular way to check blood glucose levels at home as they are convenient, however, their major drawback is the invasive way in which the blood is drawn from a patient via a finger prick. At times, the requirement for the number of sample withdrawals can increase up to 6 to 8 times a day making the whole process substantially cumbersome and frightful for the user.

There has been a surge of activity in the last two decades to find alternative strategies that can measure blood glucose levels non-invasively in alternate biofluids such as tears, sweat, saliva etc. Since the last 4 years, Sarul has been working on demonstrating saliva as a potential diagnostic biofluid to  painlessly and rapidly measure blood glucose levels. Her results show that the electrochemical properties of saliva such as pH, conductivity, redox potential and ionic concentrations (Na+, K+, Ca2+) and a person’s age can be collectively used to predict the body’s fasting blood glucose level with a significantly high accuracy of 87.62 ± 15 % and a coefficient of determination 0.76. For implementing this approach, Sarul has developed a single platform with five integrated sensors interfaced with a laptop through a microcontroller and applied several machine learning algorithms to predict the fasting blood glucose concentration after training them on 175 volunteers. The results from saliva can be determined within a couple of minutes.

Her current efforts are now directed toward developing a miniaturized point-of-care device that can be used as simply as a handheld glucometer but without any pain or invasion.

References:

  1. A non-invasive platform to estimate fasting blood glucose levels from salivary electrochemical parameters, Under review
  2. Malik S., Khadgawat R., Anand S. and Gupta S., ‘Non-invasive Detection of Fasting Blood Glucose Level via Electrochemical Measurement of Saliva’ SpringerPlus 5:701 (2016)