Moderate coffee consumption may be associated with a reduced risk of mental health disorders, according to new research published in the Journal of Affective Disorders.

The study found that drinking two to three cups of coffee a day was linked to a lower likelihood of developing conditions such as anxiety and depression. However, higher intake — particularly five or more cups daily — was associated with an increased risk, suggesting that balance is key.

Researchers analysed data from more than 460,000 participants enrolled in the UK Biobank, a large long-term study tracking individuals aged between 40 and 69. Participants provided detailed information about their coffee habits, including the type of coffee consumed, such as instant, ground, or decaffeinated. They were followed for an average of 13.4 years.

The findings revealed what scientists described as a “J-shaped” relationship. People who consumed moderate amounts of coffee appeared to benefit the most, while those who drank little or excessive amounts did not experience the same protective effect. The association between coffee intake and reduced risk of mood disorders was found to be more pronounced in men.

The researchers noted that growing attention is being paid to the role of diet in mental health. With mental disorders affecting more than one billion people globally, the World Health Organization has identified conditions such as depression and anxiety as leading causes of long-term disability.

The study suggests that certain compounds found in coffee may help explain the observed link. Coffee contains a wide range of bioactive substances, including caffeine, polyphenols, melanoidins and diterpenes. These compounds are believed to have anti-inflammatory and neuroprotective properties.

According to the authors, caffeine may influence brain function through multiple pathways. It can activate receptors associated with improved mood while blocking others linked to stress-related neural dysfunction. These mechanisms may contribute to a lower risk of mental health conditions among moderate coffee drinkers.

Previous research has also connected coffee consumption with slower cognitive decline and a reduced risk of neurological disorders, adding to interest in its potential health benefits.

Despite the findings, researchers caution that coffee consumption alone should not be seen as a solution to mental health challenges. They stress the importance of broader lifestyle and medical approaches, while highlighting the need for further studies to better understand how dietary habits influence mental well-being.

The results add to a growing body of evidence suggesting that everyday dietary choices may play a role in long-term mental health outcomes.

Danish pharmaceutical giant Novo Nordisk has announced a new partnership with OpenAI aimed at integrating artificial intelligence across its drug development and business operations.

The collaboration, revealed on Tuesday, is expected to help the company identify new treatments more quickly and improve how medicines are developed, produced and delivered to patients. Novo Nordisk said the use of advanced AI tools will allow it to analyse vast and complex datasets, uncover patterns that were previously difficult to detect, and shorten the timeline from research to patient access.

Chief executive Mike Doustdar said the agreement marks an important step in positioning the company for the future of healthcare. He noted that millions of people living with chronic conditions such as obesity and diabetes still require better treatment options, adding that new therapies remain to be discovered.

Novo Nordisk is widely known for its leading treatments in these areas, including Ozempic and Wegovy, which have seen strong global demand in recent years. The company said integrating AI into daily workflows will allow its teams to test ideas more rapidly and bring innovations to market at a faster pace.

The partnership will not be limited to research and development. Both companies plan to apply AI tools to manufacturing processes, supply chains and commercial operations, with pilot programmes already set to begin. Full integration is expected by the end of the year.

Sam Altman said artificial intelligence is transforming industries and has the potential to significantly improve outcomes in life sciences. He added that the collaboration would support faster scientific discovery and more efficient global operations, helping to shape the future of patient care.

The move comes as pharmaceutical companies increasingly turn to AI to gain an edge in drug discovery. Novo Nordisk has already invested in innovation through initiatives such as the Danish Centre for AI Innovation, developed in partnership with Nvidia and Denmark’s export and investment fund.

Competition in the sector is intensifying. US-based Eli Lilly, a key rival in the weight-loss drug market, recently announced its own AI-focused collaboration with Insilico Medicine to develop new treatments. The agreement, valued at up to $2.75 billion, highlights the growing role of AI in reshaping pharmaceutical research.

Industry analysts say such partnerships reflect a broader shift toward data-driven innovation in healthcare, where the ability to process and interpret large volumes of information is becoming increasingly important.

For Novo Nordisk, the partnership with OpenAI signals a commitment to staying at the forefront of this transformation, as companies race to harness technology in the search for new and more effective treatments.

A new study has found that artificial intelligence language models still struggle with one of the most critical aspects of medical care, raising concerns about their use without human oversight.

Researchers from Mass General Brigham reported that AI systems failed to produce an appropriate early diagnosis more than 80 per cent of the time. The findings, published in JAMA Network Open, highlight ongoing limitations in how these systems reason through complex clinical scenarios.

The study examined 21 large language models, including systems developed by OpenAI, Google and xAI. Among those tested were versions of GPT, Gemini, Claude, Grok and DeepSeek.

Researchers used a structured evaluation tool known as PrIME-LLM to assess how well the models handled different stages of clinical reasoning. These stages included forming an initial diagnosis, ordering tests, reaching a final diagnosis and planning treatment. The models were tested using 29 standardised clinical scenarios, with information introduced gradually to mirror real-life patient cases.

While the systems showed relatively strong performance when identifying a final diagnosis, their ability to generate a differential diagnosis — a key step in distinguishing between conditions with similar symptoms — remained limited. This early-stage reasoning is widely regarded as essential in medical decision-making.

Marc Succi, a co-author of the study, said current models are not ready for independent clinical use. He noted that differential diagnosis represents a core part of medical practice that AI has yet to replicate effectively.

Another researcher, Arya Rao, said the findings show that AI performs best when given complete information but struggles when cases are still developing. She explained that the models are less reliable in situations where doctors must make judgments based on limited or uncertain data.

Despite these shortcomings, the study identified a group of higher-performing systems, including advanced versions of GPT, Gemini, Claude and Grok. These models achieved final diagnosis success rates ranging from around 60 per cent to over 90 per cent when provided with detailed clinical data such as lab results and imaging.

Experts not involved in the research also stressed the importance of caution. Susana Manso García said the findings reinforce that AI should not replace professional medical judgement. She advised that patients continue to seek guidance from qualified healthcare providers when dealing with health concerns.

The study concludes that while AI has made progress, it still requires close human supervision in clinical settings. Researchers say the technology shows promise as a support tool, but its current limitations mean it cannot yet be trusted to make independent medical decisions.