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[Tech50] This duo aims to help doctors give accurate prescriptions to treat drug-resistant diseases

YourStory's Tech50 2021 startup AarogyaAI has built a SaaS platform that analyses the DNA sequence from the bacteria and comes up with a patient's comprehensive drug susceptibility status to help doctors prescribe more potent antibiotics.

[Tech50] This duo aims to help doctors give accurate prescriptions to treat drug-resistant diseases

Monday December 20, 2021 , 7 min Read

Every year, nearly ten million people are diagnosed with the second most deadliest disease, after Covid-19, — Tuberculosis (TB), killing over a million people. Yet the standard of treatment for this infectious disease remains prolonged and painful, including a daily regime of multiple antibiotics which go on for about a year.


This regime of “not so accurate antibiotics” is not restricted to TB. A growing number of infections – such as pneumonia, gonorrhoea, and salmonellosis – are becoming harder to treat as the antibiotics used to treat them become less effective (drug resistance). This long painful treatment with a cocktail of complex drugs has not changed for decades, placing a huge physical, mental and economical burden on patients.


Is it possible to have an accurate prescription of antibiotics for patients with drug-resistant diseases? Bengaluru-based startup AarogyaAI Innovations, which is among YourStory's Tech50 list of most promising early stage startups, believes it is, by addressing the issue with genomics and Artificial Intelligence (AI). Helming the startup, Dr Praapti Jayaswal and Avlokita Tiwari propose genome sequencing-based AI-powered diagnosis of drug resistant diseases such as TB; the diagnosis can be provided in a few hours.


The duo has built a SaaS (software-as-a-service) platform where the DNA sequence from the bacteria, also known as the genome sequencing infecting a patient can be uploaded, which is then analysed using a machine learning (ML) algorithm and AI to generate a report showing the patient’s comprehensive drug susceptibility status. This includes a list of drugs and their combinations that will and will not work for the patient.

This report can then be used by doctors to prescribe a more potent combination of antibiotics, significantly bringing down the duration of the treatment to less than six months.


The software has been validated internally and has reached its external validation and pilot testing stage. It is expected to be rolled out for commercial use by mid-2022.

Healthtech startup AarogyaAI

Scientists-turned-entrepreneurs

AarogyaAI CEO and Co-founder Praapti has over a decade’s experience as a researcher at premier institutions such as the All Indian Institute of Medical Sciences (AIIMS). Hailing from a family of (medical) doctors, she holds a PhD in tuberculosis research from the Translational Health Science and Technology Institute (THSTI), New Delhi.


Praapti’s co-founder Avlokita acts as the bridge between “the biology” and “the technology” in the company. She holds an MS in Bioinformatics from the University of Turku, Finland, and has expertise in computational biology and genomic data.


The duo’s association goes back to their research days at AIIMS, around 2013. After pursuing their respective career paths, they met each other again in 2019 in Bengaluru over a “friendly cup of coffee”.


At this time, Praapti had started building on the idea of using AI and bioinformatics for modern healthcare and Antimicrobial Resistance (AMR) predictions for patients. She was visiting Bengaluru for a “find a co-founder” meet as a part of her six-month long UK-based Entrepreneur First programme. Serendipitously, her search ended with Avlokita, an expert in bioinformatics, who was actually planning to move back to Finland for work. She was invited to join the startup and translate the literature into a commercial product.


Together, they pitched the idea to the investment committee of Entrepreneur First and managed to bag their first round of pre-seed funding to develop the platform.

A precise prescription

There are 19 anti-TB drugs, and patients have to go through a gruelling regime of trial and error before the right combination of antibiotics can be prescribed to them. According to the founder duo, an AI-based diagnostic solution in a matter of hours can help start suitable treatment at the very onset of the disease.


“What happens in antimicrobial resistance is that if you are infected with a pathogen, a doctor wouldn’t know exactly what antibiotic to give you. Many times, you will find yourself taking antibiotics during flu, which is completely unnecessary as it is a viral infection at first place. This unnecessary usage of antibiotics gives rise to antimicrobial resistance,” explains Avlokita.

The idea is to just look at the genomic sequence of the pathogen infecting the patient and be able to tell the most potent antibiotics out of a long list. AI enables tracking and predicting emerging drug resistance as the algorithm evolves with increasing samples.


“Our solution is not restricted to TB and is replicable to all other disease models, especially infectious pathogens causing sepsis, pneumonia and HIV. We started with TB because it is one of the biggest problems across the globe and is very hard, on ground, for doctors to treat the patients with a precise combination of antibiotics,” she adds.

Business model

Backed by Entrepreneur First, AarogyaAI was accelerated at Illumina Accelerator San Francisco, USA. It raised a bridge round through the accelerator in 2020.


Operating on a B2B2C (business-business-to-consumer) model, its customers include diagnostic labs and hospitals, and pharmaceuticals in the long run as it accumulates more data to provide insights about antibiotic development.

The startup will either charge service fees per diagnostic test or build a subscription-based revenue model. “We aim to keep the product as affordable as possible. The prices can be brought down with volumes. Drug susceptibility testing (DST) costs about Rs 20,000 in the private sector. We will definately be below this price range,” says Avlokita.


Currently, pre-deployment in Bengaluru and Jodhpur, the startup is still in a pre-revenue stage.


There are a lot of research tools, especially international, that are able to do what AarogyaAI does. However, they are yet to be validated and packaged into a product. There are a couple of companies in France and the US like GeneXpert and GenoScreen, but the technology used by many of them is either not available in India yet or are not specifically focused on TB.


The startup is also focussing on building dashboard analytics that showcase disease demographics, spread of drug resistance, and the patterns of emerging drug resistance. It plans to monetise this service on subscription basis, catering to health organisations, hospitals, pharmaceutical companies and research organisations.

Staying one step ahead

The startup is working on its long-term goal to expand the product to solve other infectious diseases beyond TB. It has recently closed a seed funding round of $700,000 from Info Edge (India) Ltd-backed Redstart Labs (India) Ltd, Avaana Capital (Seed Program), and existing investors--Entrepreneur First and First In Ventures. It aims to scale pan-India through five to seven public and three to four private chains by 2022 and expand to other countries that are grappling with TB.


“We are doing R&D (research and development) for other diseases as well and building proof of concept for them.”


AarogyaAI’s diagnostic solution aims to address a big gap in the healthcare space. Using modern technology and whole genome sequencing, this innovation could help the medical fraternity stay one step ahead as far as combatting potential disease spread is concerned. Think about the COVID-19 pandemic for instance, it took us months to figure out the impact, its spread, mutations, precautions etc. Genome sequencing of pathogens and technology is expected to help make predictions easy and quick.

“We already know that superbugs and drug-resistant pathogens are already here and spreading. There are no means to immediately predict how they will affect. We need a way to predict the nature of these pathogens and make predictions and drugs that can cut them off before the harm they do. The idea is to stay one step ahead.”

Edited by Ramarko Sengupta