Artificial intelligence and machine learning (AI/ML) are already transforming many parts of the economy, and the health care sector is no exception. But while the use of AI/ML is proliferating across the industry, it has yet to reach its full potential as a driver of new business opportunities and efficiencies.
In a recent Morgan Stanley Research survey, 94% of health care companies said they employ AI/ML in some capacity. Meanwhile, the industry’s average estimated budget allocation to these technologies is projected to grow from 5.7% in 2022 to 10.5% in 2024.
Specifically, investors should look for AI/ML to create significant opportunities in four areas:
- Biopharma
- Health care services and technology
- Life sciences tools and diagnostics
- Medical technology
1. Development Drives Biopharma Revenue
The biopharma industry is moving to unlock the potential of AI/ML across a range of areas, including drug discovery, clinical development, manufacturing and physician-patient engagement. In 2021, more than 100 drug and biologic applications to the U.S. Food and Drug Administration included AI/ML components, up from 14 in 2020. AI/ML could help to shorten development timelines for drugs, reduce spending on R&D, and increase patients’ probability of success.
“Every 2.5% improvement in preclinical development success rates could lead to an additional 30-plus new drug approvals over 10 years,” says Terence Flynn, Morgan Stanley’s Head of U.S. Biopharma Research. “Doubling that could yield 60 new therapies approved, translating into to an additional $70 billion in value for the biopharma industry.”
Meanwhile, incorporating AI/ML in R&D and manufacturing will better position companies to scale improvements while identifying new areas for automation.
2. Better Delivery of Care
AI/ML offers an opportunity to drive change and efficiency where health care services and technology meet. The tools’ predictive capabilities make it easier for doctors and other health care providers to detect and diagnose disease more quickly. This gives them more time with patients, which could improve patients’ satisfaction as well as their health outcomes.
Some other benefits of AI for providers include more efficient and accurate patient access and allocation, diagnostics, risk coding, claims processing, supply-chain management and predictive modeling.
On the patient side, AI could help individuals access and manage treatment. It could unlock the most effective insurance distribution channels and find local pharmacies with the lowest drug prices, while improving telehealth services, disease detection and 3-D modeling capabilities.
Analysts expect AI to improve inefficiencies in care delivery and coordination, as well as reimbursement, to drive value across the health care ecosystem. They see companies focused on diagnostics, patient care and electronic health records as best positioned to benefit.
3. Harnessing Data for Tools and Diagnostics
Tools that help parse minute biological components and diagnose diseases, conditions and injuries remain at the forefront of applying AI/ML to drive better care and create new business opportunities.
