In recent years, healthcare investing has been synonymous with one story – the remarkable rise of GLP-1s*. Originally developed for diabetes, these treatments have become some of the most commercially successful medicines in history, transforming the fortunes of pharmaceutical companies and changing expectations around obesity treatment worldwide.
But while these drugs have dominated headlines, they may represent just the first chapter of a much broader healthcare revolution.
Artificial intelligence (AI), faster regulatory pathways and more efficient drug-development systems are all combining to reshape how modern medicines are discovered, tested and brought to market. For investors, this could open opportunities well beyond today's winners, especially as the IQVIA Institute for Human Data Science forecasts that global spending on medicines is set to reach around $2.3 trillion by 20281, reflecting the continued growth in healthcare demand.
The GLP-1 phenomenon is only the beginning
The success of GLP-1 medicines has demonstrated both the commercial potential of breakthrough healthcare innovation and the scale of unmet medical need.
Analysts at Goldman Sachs estimate that the global obesity drug market could exceed $100 billion annually by 20302, making it one of the largest pharmaceutical markets ever created. With the World Health Organisation (WHO) estimating that obesity rates have tripled worldwide since 1975, demand for these drugs has consistently outstripped supply. Meanwhile, researchers are continuing to investigate the drugs’ potential benefits for conditions including cardiovascular disease, kidney disease and sleep apnoea.
After concerns over patent disputes and legal challenges weighed on sentiment last year, much of that uncertainty is beginning to ease, allowing investors to refocus on the GLP-1 industry's long-term growth potential.
The even bigger opportunity may lie in applying similar levels of innovation across many other therapeutic areas.
Faster approvals could accelerate innovation
One of the most significant recent developments has received far less public attention than weight-loss drugs, and this is that the US regulatory environment has become increasingly supportive of accelerating promising treatments to patients. The US Food and Drug Administration (FDA) has expanded its use of accelerated approval pathways, allowing medicines for serious conditions to reach the market earlier, even as further evidence continues to be gathered.
These programmes are designed to shorten development timelines without abandoning rigorous safety standards. For biotechnology companies, every month saved on bringing a product out can significantly reduce development costs and improve access to funding.
Alongside this, the FDA has increasingly signalled a willingness to use modern scientific tools and real-world evidence to support decision-making, creating a regulatory environment that many industry participants believe is becoming more innovation friendly.
For investors, a faster and more predictable approval process could strengthen the pipeline of commercial opportunities across the biotechnology sector.
AI could transform drug development
Developing a new medicine has traditionally been an extraordinarily arduous and expensive undertaking, with a process that takes 10-15 years on average to develop a new medicine from discovery to approval.
According to research published by the Tufts Centre for the Study of Drug Development, bringing a successful drug to market can cost more than $2.6 billion when factoring in the failures and the cost of capital3.
Now, it increasingly appears that AI will have the potential to reduce those costs at multiple stages.
Machine-learning models can analyse enormous biological datasets, quickly identify promising drug candidates and help researchers predict which compounds are most likely to succeed before the expensive laboratory work begins. AI is also increasingly being used to improve the design of clinical trials, identify suitable participants and analyse trial results more efficiently.
Even relatively modest improvements in success rates could save billions of dollars across the industry while allowing more medicines to be developed.
The decline of animal testing
One particularly important use of AI is to reduce the reliance on animal testing.
Traditional animal studies – generally carried out on rats, dogs and primates – have long been an expensive and imperfect predictor of how medicines will perform in humans. According to FDA analysis, around 90% of drugs that successfully pass animal testing ultimately fail during human clinical trials, highlighting the limitations of the existing system.
Recognising these shortcomings, the FDA has committed to significantly reducing unnecessary animal testing by embracing advanced computer modelling, AI-based simulations and human-cell technologies where appropriate.
The implications extend beyond ethics. Better predictive models could shorten development timelines, reduce research costs and increase the probability that medicines entering clinical trials will ultimately succeed.
Taken together, these could all improve returns on research investment throughout the healthcare sector.
Where do the investment opportunities lie?
The obvious investment strategy is to focus solely on the largest pharmaceutical companies. There is no doubt that these industry leaders remain important, particularly those with established GLP-1 franchises and substantial AI investments.
However, some of the most compelling opportunities may lie elsewhere.
Mid-sized biotechnology companies with late-stage drug pipelines could benefit disproportionately from lower development costs and a more efficient approval process. Companies able to use AI effectively throughout research and clinical development may reach commercialisation faster while requiring less capital than previous generations of biotech businesses.
In addition, those businesses providing enabling technologies, including AI software, laboratory automation, genomic analysis and advanced clinical-trial platforms, could also benefit regardless of which individual medicines ultimately succeed.
For diversified investors, the opportunities could be found beyond today's household pharmaceutical names and in the wider healthcare innovation ecosystem.
The bottom line
Healthcare has always been driven by scientific breakthroughs, but the pace of development appears to be accelerating.
The extraordinary success of GLP-1 drugs has reminded investors how valuable genuine medical innovation can be. Yet advances in AI, more efficient regulation and modern research techniques could prove even more transformative over the coming decade.
While drug development will always carry risks and setbacks, the combination of faster approvals, lower research costs and improved scientific tools has the potential to create a stronger pipeline of new medicines than ever before.
For long-term investors, the next healthcare revolution may not be defined by a single blockbuster drug but by a faster, smarter and more productive innovation system capable of delivering a sustained surge of pharmaceutical breakthroughs.