Pharmaceutical giant Eli Lilly and biotech firm Fauna Bio yesterday (21 December) announced a partnership deal to search for new anti-obesity drugs by examining the hibernation of animals, including the 13-lined ground squirrel.

The deal is worth up to $494m plus royalties and allows Lilly to utilise Fauna’s Convergence artificial intelligence (AI) platform, which holds biometric data from over 450 mammal species.

Obesity drugs have reshaped the pharmaceutical landscape, from a successful but relatively small Danish diabetes specialist into the second-largest drug company by market cap. Lilly is the largest, and its anti-obesity drug Zepbound has proven more effective in clinical trials than Novo’s Wegovy.

Lilly clearly isn’t satisfied, though. By partnering with Fauna, the company aims to discover the secrets of hibernating mammals that are of normal in the case of the 13-lined ground squirrel, .

Ideally, understanding the animal’s ability to manipulate its metabolism will help to explain how the metabolic processes of humans are affected by genetics and how to alter these to induce weight loss.

Lilly is increasingly focused on anti-obesity and diabetes drugs, as demonstrated by the rising number of mentions of 'obesity' in its company filings, per GlobalData analytics. This year, it has become the second most mentioned keyword behind 'revenue'. GlobalData is the parent company of ³Ô¹ÏºÚÁÏÍø Network.

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Lilly is not the only company spending big to get access to potential new obesity treatments. Earlier this month and its pipeline of GLP-1RA drugs, and in November with oral GLP-1RA developer Eccogene.

It is also not the only company exploring genetics as a potential route to weight loss. US biotech Fractyl health is developing a GLP-1RA gene therapy that has already .

Though there is a long way to go before any of these drugs make it to patients, the sheer diversity of treatments and companies developing them makes it likely that new and improved weight loss drugs will enter the market in the coming years.

Our signals coverage is powered by , which tags millions of data items across six alternative datasets — patents, jobs, deals, company filings, social media mentions and news — to themes, sectors and companies. These signals enhance our predictive capabilities, helping us to identify the most disruptive threats across each of the sectors we cover and the companies best placed to succeed.

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