Ever since the introduction of AI, there have been a number of changes in the world of life sciences. While the pharma industry has evolved a lot, the journey for medicines is still a bit tedious. Makers still rely on slow processes that bring the laboratory research to a patient’s hands. But there’s an interesting startup called Avira Digital that is looking to solve this problem using AI.
At a recent India AI Impact summit, I sat down with Sanjeev Welling, the CEO of Avira Digital, and we discussed how his startup is using AI agents to bridge these gaps. As per him, the company is focused on integrating data across R&D, clinical trials, and medical affairs to bring drugs to market faster and cheaper. Let’s take a look at what Avira Digital is doing and how it is changing the pharma landscape.
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First of all, speaking of what exactly the company does, Sanjeev explained to me that their focus is on the pharma space. While they also deal with financial services industries and sports tech, the pharma industry is where their core products are based on.
He expressed that it can take billions of dollars to bring a drug to market, but the company is looking to solve this by integrating data from 25 different sources to create a solution. They have their own platform, called Medical 360, which uses AI to solve gap prioritisation problems and deliver products more efficiently.
Given how AI has become a buzzword, I also wanted to understand how exactly AI comes into the picture. Sanjeev gave a deep dive into how exactly AI is used and how the company helps drug makers.
First up, he explained about the AI they’re using. He said that they’ve built their own platform called Athena, which includes compliance guardrails and enterprise-grade security. Interestingly, as per him, their platform isn’t tied to one model. He said that their clients have the freedom to use different models like OpenAI and Gemini, based on their preferences.
He then explained that while traditionally, pharma companies spent a lot of money, close to 250,000 dollars or more, to have agencies collect data from conferences and social media to see who was talking about their drugs, which took a lot of time too. But now, using their AI models, companies are able to analyse the open data, using which they can have the present sentiment of the drug and the other important details in much less time.
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