We, at Lightspeed, have been exploring the impact of Generative AI through a series of meetups held in major cities across the globe, including San Francisco, Los Angeles, New York, London, and Berlin. Recently, we brought this event to our Bangalore office in India, for a focused discussion on AI in Healthcare.
At Lightspeed India, we have been investing in innovative healthcare AI startups that are transforming the industry, such as Qure.ai, Triomics, Innovaccer, Emversity, HealthPlix, and Acko. Many of these startups are leveraging AI to improve diagnostics, streamline clinical trials, enhance data analytics, provide personalised learning for medical professionals, simplify healthcare delivery, and make health insurance more accessible.
We had the privilege of hosting Prashant Warier, Co-Founder of Qure.ai; Hrituraj Singh, Co-Founder of Triomics; and Dr. Vibhuti Agarwal, Head of Analytics at Innovaccer for a fireside chat in front of a packed house of leaders from across the healthcare industry, including physicians, heads of hospital chains, pharmaceutical companies, and founders building cutting-edge products to cater to the healthcare ecosystem in the US and India. Dev sat down with the panel to unpack their experiences with AI in Healthcare.
Unlocking Market Expansion
Gen AI solutions are enabling healthcare to scale tasks that were previously bottlenecked by the scarcity of manpower. Qure AI’s models, for example, can analyze radiology images in seconds, a task that traditionally took days due to the limited bandwidth of doctors. This has expanded the use cases for radiology images, particularly X-rays, which can now be used for preliminary screening and deployed in remote areas that previously lacked access to specialized doctors. As a result, the market for imaging has grown exponentially.
Similarly, Triomics can analyze every patient and match them with clinical trials, a process that was earlier constrained by the limited bandwidth of care coordinators.
Differing Value Propositions Across Geographies
In the US, where healthcare spending exceeds $4.5 trillion, AI solutions play a role in automating manual tasks, reducing costs, and improving efficiency. While healthcare providers already collect data, scribes assist them in reducing the manual work involved in the process. Qure’s solutions help them process data faster and with more accuracy.
In resource-crunched environments, such as rural parts of the US, India, and many low-and middle-income countries (LMICs), AI plays the role of the scarce resource and aids in expanding the use cases of existing solutions. For example, Qure has expanded the use case of X-rays, a very accessible solution, in diagnoses that previously required CT scans, which are significantly more expensive and less prevalent. AI also helps collect high-quality data in places where it was not being done earlier.
The Rise of Ambient AI in Healthcare
AI is increasingly taking on an ambient role in many healthcare workflows, from medical scribes assisting doctors with note-taking and filling in EHRs to Qure AI’s incidental pathway solutions that analyze routine radiology images to diagnose across a wider range of disease vectors. This has allowed healthcare providers to continue their daily tasks with significantly increased efficiency, without the need for a steep learning curve or major changes to their workflows.
Specialized AI Solutions vs. Foundational Models
While foundational models are becoming more capable across various tasks, healthcare AI requires specific data that can be accessed through partnerships with hospitals. Moreover, vertical models can perform tasks faster and at a lower cost compared to generic models. For instance, Triomics’ OncoLLM is approximately 35 times cheaper than performing the same task using state-of-the-art foundational models.
Navigating the Go-to-Market Landscape
Selling to large hospital chains often involves lengthy sales cycles and varying testing processes. Companies employ multiple strategies to shorten this cycle, such as catering to smaller hospitals or third-party centers to prove their solutions. Having experienced physicians as advisors on the board can also open doors, as they speak the same language as the customer and add credibility. As companies scale, forging strategic partnerships with marketplaces, conference hosts, and hyperscalers becomes crucial for improving discoverability. Pharmaceutical companies are increasingly collaborating with startups that enhance diagnosis, as it helps expand their top of the funnel, making them valuable go-to-market partners.
Ethical Implications of AI
The session concluded with a thought-provoking discussion on the ethical implications of AI in healthcare. As solutions move from a search-led approach to a feed-led approach, AI can diagnose multiple vectors using the same data points. This raises the question of whether knowing about all their ailments might cause anxiety for customers, especially when some conditions may not be treatable. The panel concluded that AI’s role is to augment physicians and provide them with valuable insights, but ultimately, the physician is best placed to decide how and what to communicate with the patient.
The Future of Healthcare AI
The insights shared by the panel at Generative BLR underscores the immense potential and opportunities in this rapidly evolving space. At Lightspeed, we remain committed to supporting and investing in startups that are pushing the boundaries of what’s possible with AI in healthcare. If you’re a founder building innovative solutions in this domain, we’d love to hear from you and explore how we can help accelerate your growth.
