Antibiotic resistance is a growing global threat. AarogyaAI’s intelligent genomics software aims to identify antibiotic resistance in patients and assist policymakers by predicting future antimicrobial resistance with their AI-powered genomics platform. AarogyaAI has been selected as one of the companies in the 2023 Health Incubator Helsinki program.

In 2018, roughly 23% of the world’s population was infected by the bacteria causing tuberculosis. To treat tuberculosis infection, patients need to undergo up to six months of antibiotic treatments with huge side effects — and because of antimicrobial resistance, it might not even work. But what if a doctor could choose the right combination of the 19 available antibiotics the first time, and save patients months of unnecessary, often debilitating treatment?

Predicting resistance to get the right drugs to the right patients

This is the problem that AarogyaAI set out to solve. Aarogya, meaning “good health” in Sanskrit, was founded in 2019 by Avlokita Tiwari and Praapti Jayaswal. With a PhD focused on tuberculosis studies (Jayaswal) and masters in bioinformatics with research in antimicrobial resistance (Tiwari), they realized they could predict drug resistance using artificial intelligence and DNA sequence information from the bacteria infecting patients. “We list out the drug resistance of a particular pathogen so we can give a complete report to the clinician about which drug not to give the patient” says founder and CTO Tiwari. “Where our solution can make the most difference is in economically weak areas, so patients can get treated quickly and efficiently and their families don’t have to give up all of their savings for long treatments” adds Nidhi Misra, head of PR and communications.

Avlokita Tiwari and Praapti Jayaswal, founders of AarogyaAI.

COVID-19 as a model of infectious disease surveillance

When the company was founded in 2019, founders Tiwari and Jayaswal found that people didn’t immediately understand the usefulness of sequencing the DNA of infectious diseases. But following the COVID-19 pandemic and the massive effort in genomic surveillance of variant strains, “People started to understand what we were talking about” says Tiwari. Besides getting the right drugs to the right patients, information on genetic variants associated with drug resistance are key for policies of the United Nations and World Health Organization, “So they can have an idea of where diseases are spreading. That gives a lot of information about drug distribution, what to target next, and areas of development” says Tiwari. This information is also important for pharmaceutical companies, to know how to better design new drugs that get around antibiotic resistance.

Health Incubator Helsinki opens doors to the Finnish ecosystem

With the pathogen identification process from DNA samples validated and a clinical trial wrapping up at one of the biggest hospitals in India, what is in the future for AarogyaAI? “At the moment we are in the middle of our next fundraising round” says Tiwari. “We are looking at a couple of commercial contracts and global expansion.” When thinking about EU expansion, Finnish resident Tiwari immediately thought of the Finnish investment ecosystem’s open and receptive atmosphere. “If we think of EU, Helsinki needs to be our base!” says Tiwari. “That’s why Health Incubator Helsinki made sense. The team at the incubator is super supportive and helpful in understanding market needs, how to pitch, and particularly the regulatory pathways. When entering a new market as a foreign company, it is important to understand the local ecosystem and its requirements before going to market. Health Incubator Helsinki is actively helping us do that.” If you’re interested in supporting AarogyaAI, joining one of their open positions or collaborating on a clinical study, get in contact with the information below!

AarogyaAI contact: Praapti Jayaswal, praapti@aarogya.ai

Check out all the companies in the Health Incubator Helsinki program.

Text: Lea Urpa, Giuliano Didio

Photos: AarogyaAI, Pixabay