In pharma, AI will probably make the big even bigger
Generative AI is fixing to transform the pharmaceutical industry. However, not all adopters will reap rewards in comparable degrees.
That’s because large companies will outspend smaller rivals by a lot. In the process, the dominant will gain an “enduring” competitive advantage over the rest of the field.
The prediction is in a new report from S&P Global.
Commenting on AI’s potential to speed development of new and improved drugs—one of the most hotly anticipated applications of the technology in the sector—the authors note the pace will be difficult to measure.
They point out the cycle from initial discovery to clinical trials to FDA approval to market presence currently takes an average 10 to 15 years. And they predict: Much of that process will not be compressed by AI.
Also of note in the report:
Pharmaceutical companies have good reason to seek to obscure the contribution of AI to their drug development. Accurate information could provide competitors with insight into the success or failure of AI programs, enabling them to direct their own spending more efficiently.
Noting that the global pharmaceutical AI market has been forecast to close in on $22 billion by 2027—up from $1 billion in 2022—the authors state AI’s successful implementation at individual companies “is not assured and will be the result of investment, a willingness to adopt new processes and their ability to manage change.”
S&P expects the greatest benefits from AI projects will accrue to companies that share four traits:
1. Endurance.
AI partnerships and projects are on the rise in pharma. However, initiatives “remain predominantly early stage and characterized by the exploration of the possibilities of generative AI,” the authors write. More:
Pharma AI endeavors will require the development and curation of large datasets and time to improve their precision.
2. Scalability.
AI investment in pharma tends to be narrowly focused and limited in its applications, S&P Global observes. More:
Generative AI will need to address a wider range of diseases and a greater number of activities in order to significantly contribute to health outcomes and create meaningful value for adopters.
3. Integration.
Generative AI for pharma “will have to be combined with existing proprietary systems to optimally and efficiently drive improvements in research and manufacturing.” More:
Companies that prove adept at that integration will reap the greatest competitive advantages.
4. Expertise.
“While we believe that generative AI will improve R&D efficiency, it will not replace fundamental research lead by scientists,” S&P remarks, adding:
Maximum synergies will thus rely on the combination of the technology and specialized human resources that prove capable of working together.
Embracing these four factors, and thus harnessing the potential of AI, will entail “a journey that is just starting for the pharmaceutical sector,” the authors write. “But the potential for improvement to treatments, processes and patients’ lives is already evident, and suggests that AI will have a significant and lasting role at the heart of the pharmaceutical industry.”
The report is available for downloading here.