The industry is in the early stages of using AI and machine learning to drive new revenue and boost efficiency.
Key Takeaways
- AI and machine learning are set to transform the health care sector.
- The industry has yet to fully exploit AI’s potential to drive new revenue and boost efficiency.
- Biopharma; health care services and technology; life sciences tools and diagnostics; and medical technology are at the forefront.
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 US$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 modelling.
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 modelling 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.
Advancements such as adoption of next-generation sequencing (NGS) and the broader move to electronic health records has opened the door to advanced diagnostics by combining genomic data with patient health records, medical imaging and other data. For instance, algorithms could help glean insights into the cause of disease or identify subtle correlations that can’t be parsed through traditional methods of analysis.
AI/ML approaches will become increasingly necessary and highly desirable for companies looking to leverage these complex data sets to build competitive advantage, develop new products and ultimately shift health care toward personalised medicine and improved patient care.
Analysts see diagnostics as a top area for AI/ML investment. By contrast, companies with products and services focused on later-stage, more invasive procedures may experience reduced demand as AI tools identify and treat illness earlier.
Devices Get Smarter
Companies that interact with patients earlier in the care continuum are well positioned to capitalise on AI while avoiding disruption. In addition to diagnostics, monitoring technology stands out as another potential area for investment. For example, medical technology (medtech) that collects data from devices could identify abnormalities and recommend treatment. AI could analyse patients' vital signs and results from preventative screenings to detect, recommend treatments, and continuously monitor glucose levels, or cardiac and neurological health.
In the longer term, smart sensor-equipped hip or knee implants would allow providers to monitor patient recovery.
Medical devices that come into play in the earlier stages of patient interactions, such as continuous glucose monitoring, cardiac monitoring, and neuromonitoring; and diagnostics and robotics are key markets for leveraging AI, analysts believe.
With only 24% of medical devices employing AI/ML technology currently, Morgan Stanley’s Health Care Research team says there remains significant opportunity ahead. They think larger companies look best positioned to collect proprietary data sets at scale and invest in training and implementing AI innovation.
For complete analysis, ask your Morgan Stanley representative or Financial Adviser for the full report, “What’s NEXT – How AI/ML Could Reshape Healthcare,” (June 19, 2023)
