AI startup Research Grid secures $6.5 mn to make clinical trials faster

thedigitalfit.com
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UK-based artificial intelligence (AI) startup Research Grid, which helps medical research institutions automate back-office admin for clinical trials, has raised a $6.5 million seed funding led by Fuel Ventures.

The company said it will use the fresh investment to double down on its “mission of making clinical trials faster and more successful”.

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The funding round also saw participation from Arve Capital, Ada Ventures, Morgan Stanley Inclusive Ventures Lab, Araya Ventures, Ascension Ventures, Plug and Play Ventures, and Atomico Angels.

“Our vision is to make the back office of health research admin-free for the first time in history” said Dr Amber Hill, Founder & CEO of Research Grid.

Hill founded the startup in London in 2020.

The startup also mentioned that it will use the funding to invest in R&D, developing more AI automations and building out its engineering teams.

It also plans to grow its marketing and sales functions as it expands its presence in the US and Asian markets.

“While AI is making significant waves in drug discovery, clinical trials are still the main barrier to medicine reaching the people who need it, and Research Grid is strategically placed to exploit the urgent demand of automating clinical trials at scale,” said Shiv Patel, Partner at Fuel Ventures.

He also mentioned that Research Grid’s rapid growth has shown that the market is largely green-field, with validation from across the industry in the US and Europe, including big pharma, contract research organisations and sites.

Clinical trial delays are costly, reaching up to $400 million annually per Phase 3 trial in administrative expenses.

Also Read: Healthtech startup Healthify raises $20 mn to foray into US market

Research Grid addresses this with two products: Inclusive and TrialEngine, which streamline the entire clinical trial life cycle, according to the company.

Powered by AI algorithms, these tools automate administrative and data management tasks, reducing repetitive work and allowing medical researchers to focus on higher-value activities.

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