We are noticing a once-in-a-generation information technology, Generative AI (Gen AI) surging into a centuries-old industry - Healthcare. All segments of Gen AI - Foundation models, Large Language Models (LLMs), and Gen AI Applications have captured the attention of providers, bio-pharma companies, payers, and investors over the past year. Initial news coming from the trenches portray that Generative AI could drive major productivity gains, improve patient and provider experience, and ultimately lead to better clinical outcomes. It has the promise of making healthcare delivery more efficient, innovative, and effective i.e. it could lower Healthcare administrative costs, speed medical research and drug development, improve claims management, and help develop next-generation diagnostic equipment. It is true that traditional, data and analytical AI has been used in healthcare for many years. But Generative AI is different in its ability to create new content, summarize and translate existing content, and, ultimately, to reason and plan a set of actions. This has never been done till today. Big IT vendors are partnering with healthcare players at a rapid pace to apply Gen AI, while VCs are deploying capital in nascent startups to build modern AI tools.
Gen AI + Healthcare Opportunities
Healthcare IT vendors are at the forefront of using generative AI, marrying the technology with their extensive networks of providers and users. We think, as foundation models, computer vision, and other areas continue to mature, all types of healthcare organizations will find opportunities to apply Gen AI to support operations across the value chain such as supply chain management and back-office activities as well. Ultimately, generative AI may reshape healthcare institutions’ core functional areas, presenting an opportunity for investors to serve changing markets and adjust operations within existing portfolio companies. Here are some areas where the technology has potential:
Care Providers and Delivery
It promises to cut the time spent on documenting patient visits and reimbursement-related communications, which would reduce clinician/doctor burnout and lower administrative costs. HCA Healthcare is pursuing such initiatives via partnerships with Google because patients themselves are already using off-the-shelf tools to understand and inform their interactions with clinicians. Microsoft and Epic have teamed up to reduce the time clinicians spend documenting or replying to patient messages.
Biomedical Research and Drug Development
Generative AI is speeding innovation, as evidenced by the strategic alliance between Sanofi and BioMap, - Sanofi will use BioMap’s AI platform to optimize the process of drug discovery. Molecular biology specific LLMs are also supporting predictive modeling of protein structure and target-binding affinity, in addition to the creation of therapeutic candidates.
Healthcare Insurance
Insurers and other payers are using AI in data analytics, claims management automation and adjudication, and quality and risk management. Now, they are implementing generative AI for member navigation, an example being UnitedHealth’s virtual assistant for patient communication. IBM is working with Microsoft Azure to analyze complex medical records.
Medical Devices
Medtech companies, meanwhile, are focusing their investments on next-generation diagnostic equipment to detect diseases via AI-enabled HW, surgical robots with AI-powered systems, or smart remote-monitoring devices. Philips is partnering with Amazon Web Services (AWS) to develop generative AI to advance the company’s PACS image processing and enhance radiology workflows, as part of its broader AI efforts in diagnosis and treatment, connected care, and personal health. Google is working with Bayer to automate drafting of clinical trial communications in multiple languages and is partnering with iCad to integrate AI tools in the company’s devices to detect breast cancer.
Venture Capital and Growth Equity Investments
Venture Capital (VC) and Growth Equity (GE) investors have deployed capital in startups built around generative AI as a core competency. For example, Hippocratic AI, a healthcare-focused LLM company, raised $50M in a Seed round co-led by General Catalyst and Andreessen Horowitz. Genesis Therapeutics, a drug discovery platform that uses Gen AI to pinpoint novel drug candidates, closed a $200M Series B round, with participation from Andreessen Horowitz, Fidelity, and BlackRock.
Private Equity Investments
To get ahead of the rapidly evolving AI sector, PE investors are carefully considering the impact of Gen AI on their portfolio companies in Healthcare by assessing the exposure of their portfolio companies’ markets to Gen AI disruption, both the magnitude and timing of potential threats or opportunities. Private Equity (PE) backed companies are investing in LLMs to drive operational improvement in various areas including better clinician or patient engagement and lower cost structures. For example, Syneos Health, taken private by Elliott, Patient Square, and Veritas, entered into a multi year deal with Microsoft to leverage OpenAI’s ChatGPT in clinical trials and commercial programs. Advent backed Iodine Software has partnered with OpenAI to infuse LLMs into its AwareCDI product suite to improve the software’s accuracy and efficiency.
Long-term Potential of Gen AI in Healthcare
Given the complexity and uniqueness of patient/provider/payer situations, much of the work in healthcare requires human labor and judgment. Even areas where less discretion is needed, such as coding, charting, and registry extracts, have seen limited impact from AI models due to relatively small data sets available to train the algorithms.
We believe in Generative AI’s disruptive potential and new startups, and have identified several opportunities to take advantage of the technology. Generative AI promises to address some of the above mentioned challenges, and experiments will likely proliferate in the year ahead. We remain aware of several key dynamics while investing in Gen AI based Healthcare startups:
Implications of Gen AI disruption risks vs the potential to unlock value
Opportunities for startups to leverage commercially available Gen AI tools with less upfront capital commitment
Building proprietary Gen AI SW where there is a clear opportunity to establish competitive differentiation
Defining Gen AI governance on health data to ensure its proper use and data security
Gen AI could disrupt processes such as creative content generation, labor-intensive administrative processes and call center work, and text-writing and summarization. Business process outsourcing that employ low-skilled labor to generate communication for medical claims and denials may be areas where Gen AI can automate or accelerate the processes. On the other hand, areas that rely on expert guidance, such as physicians providing clinical recommendations, Gen AI may add less value directly, but instead may enable to democratize access and improve quality. These efforts are early use cases and can have the potential to trigger strong labor efficiency gains - addressing the financial pressures on organizations, improving the patient and provider experience, and leading to better clinical outcomes. We expect progress over the next 1-3 years to come in select and focused use cases. Over a longer time frame, the breadth and depth of Gen AI’s impact on healthcare may well be transformative across workflows, applications, and ways of working. We are thoughtful about Gen AI’s impact and potential investments will be able to harness this technological change to generate superior returns while accelerating the transformation of the overall healthcare sector.
/Service Ventures Team
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