Artificial intelligence could help biopharmaceutical companies reduce costs as well as improve their chances of developing successful new drugs.
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Welcome to Thoughts on the Market. I'm Terence Flynn, Morgan Stanley's Head of U.S. BioPharma Research. Along with my colleagues bringing you a variety of perspectives, today, I'll focus on how artificial intelligence and machine learning can reshape the health care sector. It's Thursday, July 6th at 10 a.m. in New York.
As we've discussed on this podcast, Tech Diffusion is one of the big three themes we at Morgan Stanley Research are following this year. The other two being the Multipolar World and Decarbonization. As a quick reminder, by tech diffusion, we mean the process by which any transformative technology is adopted widely by consumers and industries.
When it comes to the healthcare sector, it's still early but we believe artificial intelligence and machine learning adoption is poised to accelerate significantly. The biopharma industry specifically is moving to unlock the potential of A.I across multiple areas, including drug discovery, clinical development, manufacturing and physician patient engagement.
We see two broad areas where A.I enabled investments in drug development could drive significant value in the biopharma space. One is direct cost savings, so think of improved R&D margins, for example. And two is increased probability of success of pipeline programs. Here we estimate that even small improvements in the probability of success could drive significant value.
Now, let me put some numbers around this. Over the past ten years, the FDA has granted 430 new drug approvals or about 43 per year. We estimate that every two and a half percentage point improvement in early stage development success rates could lead to an additional 30 new drug approvals over the course of ten years, or nearly a 10% boost. Assuming that each incremental approved drug generates over 600 million in peak sales, we estimate that 60 additional therapies approved over a ten year period would translate into an additional 70 billion in drug development and PV for the biopharma industry.
However, biopharma is not the only health care subsector that's poised to benefit from A.I.. Looking at health care services and technology, A.I represents an opportunity to drive meaningful change in efficiency in how care is delivered. A.I tools have predictive capabilities that could be used for early diagnosis and detection of disease, which could lead to improved clinical outcomes and patient experience and reduce the cost of care over time. Many health systems have already begun to migrate data from on premises to the cloud, an important step for capturing the full benefits of A.I.
We will continue to monitor further developments in health care, both near-term and long term, and will provide you with our latest analysis and insights.
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