HeartFlow’s $364m initial public offering (IPO) signals market validation for the use of artificial intelligence (AI) in a medtech company’s product portfolio, an expert says.
Roundly exceeding its $300m expectations for the IPO, the Bain Capital-backed AI-based coronary artery disease (CAD) platform developer debuted with a a $2.2bn valuation on the Nasdaq on 8 August.
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HeartFlow’s current products are HeartFlow Plaque analysis, which aims to provide clinicians with the ability to more accurately assess patients with arterial plaque buildup (atherosclerosis), and HeartFlow FFRCT analyses CT angiogram (CCTA). Typically used alongside Plaque Analysis, FFRCT creates detailed 3D models of the arteries to assess the impact of blockages on blood flow.
Plaque Analysis received US Food and Drug Administration (FDA) clearance in 2022 and is claimed to be the only AI-based plaque quantification tool currently cleared by the agency. FFRCT received FDA clearance in 2014.
To reach the IPO milestone, HeartFlow maintained a focus on testing its product offerings alongside physicians, generating real world evidence, taking on feedback and refining as needed, and ensuring they were truly ready to scale.
HeartFlow also navigated the structural barriers of getting its product to market; again, real-world evidence – with over 3,000 peer-reviewed papers demonstrating its products’ efficacy – spurred the company’s commercialisation efforts.
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By GlobalDataMedtech industry veteran, Brent Ness, CEO of Aclarion, who served as HeartFlow’s chief commercial officer from 2014 to 2015, told Medical Device Network that HeartFlow’s work on the underlying economic factors around its product, including working on contractual relationships with imaging centres to get them on board with the product, pre-reimbursement, have proven a key part of its success.
“Between FDA clearance and reimbursement, lots of technologies can’t make it through that journey because there’s no reimbursement, and therefore there’s no adoption, and they run out of cash,” Ness explained.
“Part of the structural barrier stage of development involves getting the provider economics right and that market access work that needs to take place between the early payors and the key opinion leaders (KOL) advocating for the product. But payors aren’t going to turn it on just because a KOL says so.
“This is why the shining jewel in HeartFlow’s history has been their absolute commitment to leading with evidence.”
AI’s recognition in healthcare and its future
According to Ness, the success of HeartFlow’s IPO reflects the market validation of the overall rationale for using AI in imaging and the deployment of software-as-a-service (SaaS) based products as the “raw material” underpinning the technology’s ability to provide clinically actionable information and improve patient outcomes.
Ness said this model is “here to stay”, having been “completely validated by the market, which has recognised of its value, which obviously translates into revenue, and speaks to the long term success and viability of HeartFlow and the significant potential for other AI-based SaaS imaging developers.”
To learn from HeartFlow’s success, Ness views a critical role for SaaS-based AI software providers as being to try and shorten the timeframe between regulatory approval and reimbursement.
“The faster that new and novel technologies using AI can move through that Death Valley, the better it’s going to be for patients, and the more money we’re going to save as a collective society,” Ness said.
“The ‘muscle’ of these AI tools is proving to be valuable. It’s got to be safe, and it’s got to make sense economically, but we’ve got to figure out how to shorten that part of the journey.”
