How Indian engineering colleges are revamping medical R&D with new-age tech

Using tools such as AI, ML, data science and 3D printing, they are making breakthroughs in fields such as oncology, neurology, liver disease and premature deliveries

Sometime in May 2021, IIT Madras announced the development, in collaboration with the Massachusetts Institute of Technology, of human brain tissues called ‘organoids’ with the help of a 3D-printed bioreactor. The aim of the project was to observe these tissues as they grow in vitro, and develop a technology to potentially accelerate therapeutic discoveries for diseases such as cancer and neurological disorders like Alzheimer’s and Parkinson’s.

Explaining the technology, Ikram Khan SI, IIT Madras Alumnus and CEO of ISMO Bio-Photonics, an IIT Madras-incubated startup, told Business Standard that the invention eliminates the need to physically transfer cells from the incubation chamber to the imaging chamber, as is the case in existing cell culture protocols. This enables them to grow uninterruptedly, thereby delivering more accurate results and eliminating contamination. 

So one could, for instance, create hundreds of copies of Alzheimer's cells and map them to a hundred different drugs in order to arrive at the medication most suited to a particular patient, given that different patients react differently to different drugs for the same ailment.

In May again, researchers from the Indian Institute of Technology, Mandi elucidated a part of the structure of a key protein in the Covid-19 virus, which helps in understanding its mode of action, its role in the spread and severity of the disease and development of antiviral therapeutics.

Later, in June, a team led by Dr Prosenjit Mondal, Associate Professor, School of Basic Sciences at IIT Mandi used complementary experimental approaches using mice models to establish the underlying biochemical link between consumption of excessive sugar and fatty liver disease, a disorder that impacts a third of the Indian population. The study established that consumption of excess sugar and carbohydrates causes the liver to convert them into fat in a process called hepatic de novo lipogenesis or DNL, which leads to fat accumulation in the liver, and eventually to cirrhosis if not addressed in a timely manner. 

A team led by Dr Himanshu Sinha, Associate Professor, Department of Biotechnology, IIT Madras, collaborated with Dr Shinjini Bhatnagar, Translational Health Science and Technology Institute, Faridabad, to predict and mitigate preterm births in 8,000 women in Gurugram, Haryana. The subjects were enrolled and tracked from their first trimester--the first three months of pregnancy--till six months after delivery using medical data such as ultrasound, obstetric and clinical reports, along with socio-economic parameters such as family size and income, and nutritional levels tocreate a model based on data science and ML. This model would identify women at risk of delivering prematurely much more accurately than the conventional ultrasound at the typical maternity hospital, and would provide guidance on delaying the date of delivery. 

The group recently published a report describing the development of an Indian population-specific first-trimester gestational age model, which is more accurate in classifying preterm birth compared to the conventional model.

The examples above are just the tip of the loads of medical research that the IITs and other engineering institutes, such as the Indian Institute of Science Education and Research (IISER) Bhopal have been into. 

Researchers at IISER have, in fact, invented a new technology that can deliver active molecules to specific sections of proteins. The innovation--an outcome of studies on the ‘engineering’ of protein molecules over the past few years--has gained a detailed insight into the chemical features of these molecular machines. With this understanding, they have designed the first-ever modular platform for the precision engineering of proteins.

What gives? How come India's engineering colleges are stepping into territory that has been regarded as the preserve of large institutions such as the Indian Council of Medical Research (ICMR) and the host of large hospitals such as CMC Vellore, AIIMS, Mumbai's KEM and several private health care set-ups?

Sinha says medical research presents the most challenging data and provides a fertile ground for the application of new-age technologies such as AI, machine learning and IoT. "Clinical research institutes generate a great deal of data but are not able to do justice to the depth of that data. This is where technologies such as AI and ML algorithms come in to identify patterns that conventional techniques find it difficult to," he adds.

To substantiate his point, he cites the example of the pre-term birth project in which each of the 8,000 subjects was mapped on 1,300 parameters, to give more than 10 million data points. ML is being used to identify patterns using these combinations and segregate them into normal patterns bereft of any medical complications, and sub-normal patterns that required medical intervention. "This is something conventional technology is incapable of handling," says Sinha.

Funding and monetisation

Sinha says quite a few medical researchers receive funding from the Central government. The preterm project, for instance, has been financially supported by the Department of Biotechnology, Government of India, and has been named as one of the five Atal Jai Anusandhan Biotech Missions--UNaTI (Undertaking Nationally Relevant Technology Innovation). The models developed under this programme can be considered for monetisation once they are validated.

Khan, who graduated from IIT Madras last year, says his project on human brain tissues was supported by Kris Gopalakrishnan, Co-Founder, Infosys, through funds for the Centre for Computational Brain Research (CCBR) at IIT Madras. A great deal of financial support also came from MIT towards validation of results. The project, which kick-started in 2019, was completed in early 2020. 

As far as monetisation is concerned, Khan says his approach is to first take the technology abroad, and once it is commercially established there, he would consider bringing it to India. However, there is some level of engagement with another IIT--the one at Mandi. He added that he is already in talks with the University of Buffalo and a few others, whose names he was unable to share due to the existence of non-disclosure agreements.