Private sector needs to translate AI productivity gains into cost savings for patients, experts say<\/p>\n
[SINGAPORE] Artificial intelligence innovations are attracting growing interest from private healthcare players and investors, but translating them into commercially viable applications within the sector can be more difficult.<\/p>\n
A deep talent pool and strong government support within the ecosystem has seen Singapore\u2019s medtech<\/a> and biotech<\/a> sectors grow considerably in recent years, with an increasing number of startups finding success developing AI tools for clinical use.<\/p>\n For example, an AI-powered wound care scanner by local startup KroniKare has found its way into hospitals around the island, reducing wound assessment time by up to 70 per cent.<\/p>\n Still, only a small minority of healthcare AI algorithms developed eventually make it into real-world clinical settings while remaining commercially sustainable, said Associate Professor Daniel Ting, director of the SingHealth AI Office in an interview with The Business Times.<\/p>\n The biomedical sciences industry has seen its fair share of high-profile failures<\/a> and funding winters<\/a> over the years as investors turned towards lower-risk sectors.<\/p>\n Singapore\u2019s AI ambitions in healthcare<\/p>\n For the Republic, fostering robust and competitive innovation<\/a> within the healthcare industry is increasingly becoming a national priority.<\/p>\n Singapore has keenly backed AI technology through strategic investments as part of its National AI Strategy 2.0, positioning the country as a prominent hotspot for private enterprises deploying AI across various sectors from software to manufacturing.<\/p>\n The healthcare sector, Prof Ting believes, is among the most well-positioned to benefit from this national AI push.<\/p>\n As part of the Research, Innovation and Enterprise (RIE) 2030 five-year strategy, the Ministry of Health will emphasise AI compute capabilities and health data to build the Republic\u2019s medical research capacity.<\/p>\n The latest tranche of RIE 2030 has earmarked S$37 billion<\/a> for research and innovation to address key national needs \u2013 including healthcare for a rapidly ageing population.<\/p>\n In July, the Republic launched the Singapore Medical Foundation AI Model (Simfoni), an initiative which will integrate AI models tailored specifically for Singaporean patients and medical practices into public healthcare systems.<\/p>\n Private healthcare systems are distinct from public healthcare in their for-profit objectives, but Prof Ting noted that both have different yet complementary roles in driving the sector\u2019s technological transformation as AI adoption accelerates.<\/p>\n Private players are increasingly deploying AI tools across operational and medical processes.<\/p>\n Fullerton Health has selectively implemented<\/a> AI into its operations, with use-cases from reading X-rays to writing code, while SGX-listed integrated healthcare group IHH Healthcare has introduced AI tools for nurse rostering and fee estimation processes.<\/p>\n But industry leaders believe AI\u2019s biggest commercial opportunities extend well beyond improving hospital operations.<\/p>\n Drug discovery, for instance, could potentially see major transformation as AI augments the development process<\/a>.<\/p>\n Prof Ting explained that traditional timelines in drug development are often long, generally taking ten to 15 years from identifying a biological target to regulatory approval, while failure rates remain high.<\/p>\n These development challenges are why drug prices remain high, as drugmakers often seek to recover costs from both the successful development process and other pipelines that failed to discover viable drugs.<\/p>\n \u201cThe costs can be a few billion dollars,\u201d Prof Ting added.<\/p>\n He said AI could shorten the medical product life cycle by helping researchers identify promising molecules, recruit suitable patients for clinical trials and reduce costly failures.<\/p>\n \u201cWith AI, you can potentially cut the cost by 50 per cent throughout the total medical product life cycle,\u201d he said.<\/p>\n Global pharmaceutical giants such as Pfizer and Elil Lilly are investing heavily in AI tools that could accelerate timelines rapidly, while local players like biotech startup Nanyang Biologics<\/a> are betting on the technology to drive long-term growth.<\/p>\n Meanwhile, the rapid development of agentic AI systems could transform how healthcare is provided. Within hospitals, such tools could drive efficiency in triage, medical screenings, diagnosis and prescription of care, he noted.<\/p>\n The opportunities for deploying AI agents extend beyond hospitals. \u201cIf you look holistically at healthcare, medical care is just one of the big pillars \u2013 there is still nutrition, mental wellness, counselling and education,\u201d Prof Ting added.<\/p>\n But scientific breakthroughs alone are not enough to guarantee commercial success, he noted. Rather, what matters more is how these innovations can be applied to drive productivity and revenue within the private sector.<\/p>\n \u201cIf the innovation is scientifically robust and clinically applicable, the technology will remain,\u201d said Prof Ting. \u201cThen it comes down to the business model, the go-to-market strategy, and how financially sustainable it is.\u201d<\/p>\n He acknowledged that profitability remains critical in sustaining private healthcare, as revenue-generating providers can attract better technology and purchase better equipment.<\/p>\n Reducing patient cost<\/p>\n