Sorry, you need to enable JavaScript to visit this website.

In Quest for Building Better Healthcare – Dr Chandrasekhar Nair

Read time: 11 mins
In Quest for Building Better Healthcare – Dr Chandrasekhar Nair

In an exclusive interview with Research Matters, Dr Chandrasekhar Nair, awardee of the Infosys Prize for Engineering and Computer Science 2021, shared the motivation, challenges and breakthroughs during the making of Truenat®, a portable, battery-operated PCR testing platform. He commented that using technology in medicine and healthcare can save many lives. Prof Arvind, chair of the jury for Infosys Prize in Engineering and Computer Science 2021, also present, said that an easily accessible testing facility in small towns and villages could contribute a lot to controlling epidemics and pandemics.

Dr Chandrasekhar Nair has been awarded the Infosys prize for his development and large-scale commercialisation of Truenat®, a new point-of-care testing platform for PCR-based medical diagnostics. Dr Nair’s work has enabled testing for millions of COVID-19 cases across resource-limited settings in India and the diagnosis of many infectious diseases, including tuberculosis, worldwide.

Dr Nair is the  Co-founder & Chief Technology Officer of Molbio Diagnostics, one of India’s leading healthcare companies in the In-Vitro Diagnostics (IVD) segment and the manufacturer of the renowned molecular diagnostic platform Truenat® Real-Time PCR. He is also the founder of Bigtec Labs, a fully-owned subsidiary of Molbio Diagnostics.

Prof Arvind is Johnson Professor of Computer Science and Engineering and the Head of Computer Science Faculty at Schwarzman College of Computing, Massachusetts Institute of Technology. He is a renowned computer scientist whose work has been instrumental in the development of dynamic dataflow architectures and associated parallel programming languages.

Commenting on the achievements of Dr Nair and his team, Prof Arvind notes, “I think sometimes people in India do not appreciate how much engineering is needed to bring something to a usable level or to market. So this was a perfect example for us. You know that there is science. You know you can do it, but that’s a very different story than actually doing it at scale and bringing it to market. It is really truly an international level accomplishment which has special bearing for India.”

Portable Testing Platform - The Beginnings

Dr Nair wanted to make something that could give a very good diagnosis. The first design they had was about very precise blood glucose measurement. But they soon realised that daily variations in blood glucose levels are so much that the accuracy that their method offered was not useful.

Detecting infection was another avenue, especially in India, where one has to go through several infections during one's lifetime. Being able to precisely identify what infection a person has can help them get directed therapy and a very rapid return to wellness. Accurate diagnosis is also very important to prevent the spread of infections.

PCR or polymerase chain reaction is a method to multiply a DNA sample in the laboratory. It can be used to detect a human pathogen. It is highly sensitive because we are amplifying the DNA or targeted DNA segment itself many times. It also has very high specificity because we amplify only the pathogen using the technique. Hence Dr Nair’s team decided to work with PCR.

When Dr Nair was thinking of making a diagnostic solution, PCR tests were costly, and the procedure was complex. “When we conceived this (a PCR testing solution) around the year 2002-3, we had just one PCR machine in a clinical setting in Bangalore,” informed Dr Nair. He wanted to make something easily accessible and affordable.

Collection and handling of the samples for PCR tests pose the hazard of infection. A high level of biosafety is needed to handle a sample. When Dr Nair first thought of making a PCR test platform, India did not have many setups that could operate at the required biosafety levels. Secondly, the pathogen DNA to amplify needs to be separated from the samples collected. Whether it be a blood sample, nasal swab or sputum, it is not a straightforward task to separate the DNA. The chemicals required for the test were expensive, fragile and needed to be stored at -80℃. The PCR machine, on which the amplification is carried out, itself was bulky and extremely costly. “We had bought our first PCR machine for Rs 35 lakhs! That is a lot of money to spend at a point of care,” says Dr Nair. Additionally, the machines needed expert training to operate.

“All these factors made it impossible to have PCR testing available easily at every point of care. To be able to make an affordable, accurate point of care PCR testing machine, we had to rethink the entire thing. When I look back at this, I think we were a bunch of crazy guys to attempt something like this at that point in time, but I think it was good that we did not know much,” said Dr Nair.

An Interdisciplinary Approach

Dr Nair and his team followed a multi-pronged approach to solve the problems at hand. It required expertise in many fields, including biology, chemistry, engineering and computer science.  

One of the unique methods they utilised was using nanofibers to isolate the sample to be tested. They initially used magnetic nanoparticles to isolate the sample, but these nanoparticles needed to be imported, and the costs were prohibitive. Additionally, the method that used nanoparticles was difficult to automate.

Dr Nair’s method extracted 1/10 ml of pure DNA from ½ ml of sample. They needed a microfluidic cartridge in large quantities at a low cost for the commercial product. It called for precision plastic engineering, and it was difficult to get it done at that time. “I think we (Indians) are very happy doing non-precision parts, but when high reproducibility across millions of parts was needed, we failed miserably. Part of our manufacturing ecosystem was very primitive at that time,” he comments. The company used laser welding to bond two pieces of flat plastic to make the part they needed. And now, they have one of the most sophisticated laser welding machines. “I think our ecosystem is catching up now, and I’m super happy that there is an effort being put into improving that ecosystem,” he added.

A PCR machine typically has a block with 96 wells (each to hold about 0.1 ml fluid) to hold 96 samples. The block is a high precision metal alloy that heats and cools uniformly. For Dr Nair’s PCR testing machine, they wanted to be able to run tests as and when the samples came in and not wait for a batch to be completed. Choosing good material for the construction of the well was a challenge. They first thought of silicon, but no foundry in India could make the needed parts with the accuracy and precision required, and importing would make costs prohibitive. They explored glassy substances and finalised ceramic. It could heat and cool uniformly, and they were able to make it at scale. “Temperature artefacts will be one of the biggest reasons why PCR results could go wrong. So you required absolutely identical temperatures,” said Dr Nair.

Stabilising the chemistry so that the tests could run at room temperature was another challenge. Building the support infrastructure for a large number of points of care that would be using the machine was no straightforward task. They needed to make sure that the machines ran continuously without breakdown, had to arrange a network of technical support staff and had to make sure that the machines were easy to use and did not require a whole lot of expertise to operate.

Dr Nair’s team started with making a test for Hepatitis and then expanded the platform to conduct tests for H1N1, tuberculosis and now Covid-19. Their novel methodology allows the use of the same kind of preparation and the same kind of cartridge for all types of tests.

“The beauty of the prep is that our prep does not change. The only thing that changes is the buffer that you collect your sample in, and I think that is a very massive chemistry breakthrough. I don’t think anybody has been able to do that,” exclaims Dr Nair.

The Pandemic, Scaling, and Technology for Healthcare

Just before the first wave of Covid-19 started, Dr Nair’s company had an order of about 1500 machines (meant for TB testing) to be delivered over the year. “Come Covid-19, and suddenly they wanted all these machines and even more, in a month!” shared Dr Nair. Their testing platforms helped expand the PCR testing facilities in India from merely 100 testing centres to more than 1000. “It was an absolute thrill for us to see that something we developed had the ruggedness to be running 24 by 7,” he added.

Dr Nair and Prof Arvind both feel that having an accessible testing facility can make a huge difference in disease management and control. Technology contributes in various ways, may it be novel testing techniques, vaccines or better ways of handling and transporting samples. Though the COVID-19 pandemic is a prominent example,  another one that underlines how technology can benefit healthcare is tuberculosis.

A PCR test for tuberculosis (TB) has made it possible to detect tuberculosis within three weeks of observing symptoms instead of the earlier six-month time frame. Conventionally, the patient’s sputum (saliva and mucus from the respiratory tract) is tested to confirm TB, using a test called smear microscopy. The test has only 50% sensitivity, and the sample needs to have 10000 bacteria per ml, which happens typically only after six months of infection. “During the six months, not only do the patients suffer, but they also spread the infection,” says Dr Nair. A PCR test, on the other hand, can detect TB when there are 100 bacteria per ml, which usually happens in the first three weeks of active infection.

Developing a PCR test for a sputum sample was no easy task. Sputum samples vary a lot. They have different physical and chemical properties from person to person, from location to location and from season to season. The challenge was that such a sample needed to be collected and homogenised in the field for the test. With advanced biotechnology, Dr Nair’s team could make a field PCR test for TB using their portable test platform. 

Prof Arvind expressed that technology will help develop vaccines and affordable detection mechanisms faster. “This COVID vaccine development has had such a huge impact that now people are getting it to a point where they’re ready for next,” he said. Dr Nair added, “I think with more effective vaccines and much early diagnosis, we will be able to take appropriate measures to prevent the spread of disease. It will lead to the prevention of these large-scale disruption of life because of pandemics.”

Artificial Intelligence and Machine Learning in Medicine


A machine learning algorithm (ML) is fed a large amount of data so that it ‘learns’ something about the data. Then the algorithm can predict properties of a new data sample or make decisions related to the data point based on what it has learned. The ability of machines to decide based on continuous learning and improving their decision-making algorithms can be ascribed as artificial intelligence (AI). Prof Arvind suggests that one way to think about machine learning is how to make use of data before drawing better conclusions. So it is much more interesting to use machine learning when we have some knowledge about a system. If we train the machine learning algorithm with those known constraints, we get a lot more accurate results.

The ability to process a huge amount of data helps us cross-check our theories. For example, half a century ago, we had theories and models about atmospheric circulation but no data to prove them. Now we have data, and we can cross-check our theories.

“I think the use of data in refining science is just so fundamental that I just regarded it as an obvious revolution. It doesn’t take anything away from fundamental science. It is just yet another tool for doing science, which makes our lives richer in some sense,” says Prof Arvind

An excellent example is an AI-based solution from Dr Nair’s company, set to be used for a broader screening of tuberculosis across large populations. The digital x-ray machine will capture chest X-rays of people and, powered by AI, predict if a person is likely to have tuberculosis. A PCR test can be conducted on the spot there. A PCR takes maybe 30- 45 minutes to give a result, but a digital X-ray provides the result within minutes. Hundreds of patients can be screened rapidly, and a confirmatory PCR test can be conducted for persons who are likely to be TB positive. .

With an AI that is well trained using large databases of X-rays scanned by expert radiologists, the possibilities of X-rays being screened are relentless. “I think it is revolutionary that you can not only pick up TB but also  pick up other chest abnormalities because the AI will pick up all of those abnormalities, and the reason behind those can be analysed.”

Data plays a crucial role in an AI and ML-based system. Huge data may be available, but it needs to be captured and made available in a structured way. For example, as more and more data is made available to researchers, they can analyse it and suggest better and better diagnostics. Prof Arvind informs that many institutes and governments are now making efforts to make data available to researchers.

Do researchers in India face a problem in accessing data from other countries? Prof Arvind says that while accessing data from other countries is not a problem, for the field of medicine, India itself is rich in data because of the population and the abundance of diseases and their treatment and handling. “It is more important for India to have a system of data collection,” he says.

Dr Nair opines that data is collected in India to an extent, but there is a problem of sharing medical records in a structured way. Collecting the right kind of data or having it validated in the right fashion are really the challenges. “I think it's only a question of evolution. I think we will evolve to a stage where there will be some structure around sharing this information,” he hopes.


Editor's note:  This article was edited to correct a couple of spelling errors. The error is regretted.