The Australian healthcare sector is not short of innovation. In a single year, around 10,000 digital health apps will be added to the app store; almost as many pharmaceutical research papers will be published by academic journals; and the Australian medical technology (medtech) industry will gross upwards of ten billion dollars.
But in a bottlenecked and crowded marketplace, only a small percentage of healthcare innovations ever go on to raise venture dollars or make their way into routine clinical practice.
Ahead of Informa’s Innovate Health Conference, several industry experts weigh in on what constitutes an effective healthcare innovation commercialisation strategy.
In the context of healthcare, it is vital that innovators don’t simply come up with solutions they think are good for problems they think exist.
The logic may seem obvious, but the data tells us that a surprising proportion of healthcare innovators do not develop a sound, evidence-based use-case prior to developing their product.
Even before your solution goes through the rigours of a clinical trial, it must first have been validated on a conceptual level. In other words, is the solution valuable; and is it needed?
For this, innovators must consider the varying needs of end-users: whether that’s a more efficient workflow, reduction in costs or better patient outcomes (for healthcare practitioners); or a more convenient, personalised or comfortable service (for patients).
James Dromey of the Murdoch Children’s Research Institute believes success in healthcare innovation is less to do with the technology itself, and more to do with the healthcare problems it intends to solve. “Shift the focus the wrong way and we risk oversupplying or delivering low value products that don’t address the real issues faced by the health system, health practitioners, patients and consumers”, he says.
Bronwyn Le Grice, founder & CEO of Australia’s only dedicated digital health accelerator, ANDHealth adds, “Understanding frontline health issues and defining an area of genuine clinical need is clearly hugely important. But where we see most companies fail is in a lack of understanding of the economic environment in which they are operating.
“Healthcare has complex payment and value flows and simply coming up with a technology that improves patient outcomes or system efficiency, does not, unfortunately, equate to an incentive to pay for it.”
Big Data, machine learning, AI, blockhain are all terms which appear to be taking the healthcare sector by storm; and academics and entrepreneurs have been keen to oblige current demand.
Every day, it would seem, a new research paper is published highlighting the importance of large data sets in healthcare, the performance of a new healthcare machine learning tool or how blockchain will transfer the handling of health data.
But despite the soundness of the literature, the vast majority of these “solutions” are disregarded by investors and the wider healthcare sector. Why?
In the context of AI, Dr. Martin Seneviratne, Digital Health Fellow at Stanford Medical X says, “The most important part of a machine learning algorithm is what a clinician should do with the output. A predictive model without a clear way to intervene for the patient will never make its way into practice”.
He points to a number of existing prognostication algorithms, which are theoretically impressive, but which haven’t established a clear clinical use case.
In contrast, he highlights several quality-assurance algorithms that have been deployed in clinical practice, including one at Stanford which identifies patients in need of a palliative care review and makes that referral.
“The prediction coupled with a distinct clinical action are what forms part of a successful implementation recipe”, he tells us. “To be clinically actionable, you need to have algorithms integrated with the EHR.”
Bronwyn Le Grice add, “The power of digital health is in the shift from health technologies being focused on product/technology push to a service-based model which captures the hearts and minds of healthcare consumers and empowers them through understanding and harnessing consumer behaviour.
“Successful companies are able to reach people wherever they are, can identify when people are at risk, can deliver what they need before they know they need it, and are personalised, sticky and deployed in a timely (and appealing) manner. It’s all about right information, to the right people at the right time to transform prevention, diagnosis, treatment and care.”
In a highly saturated digital health market, both clinical and commercial validation are key for those looking to differentiate, attract venture dollars or make it into mainstream practice. Health economics is critical in this space.
Successful global players in digital and connected health have proven both their clinical and commercial impacts via substantial studies.
WellDoc (US) has undertaken numerous clinical studies in support of its FDA Approval of their Bluestar application for the treatment of Type II diabetes (yes, it’s an app, approved as a medical product. You can get a prescription version or an over the counter version.) But in addition, they have undertaken studies on key health economics outcomes such as healthcare utilisation.
Similarly, Pear Therapeutics undertook cost-effectiveness studies in addition to clinical trials, on their journey to becoming an approved digital therapeutics for substance abuse.
Ms. Le Grice says, “Digital health companies face a vastly different commercialisation pathway to regular medical technology. The types of data required to support clinical and commercial uptake are broader, and there is a significant requirement for health economics studies which support the economies of the business model and empower purchasing decisions. These health economic metrics also differ greatly across different healthcare systems, so there is often no ‘one size fits all’ approach.”
“Coupled with a shifting regulatory environment (both with respect to clinical regulation, but also data ownership, privacy and security), the challenges facing nascent digital health companies are significant and access to people with demonstrable experience in this emerging space can be difficult.”
In a research context, Glenn Begley of Biocurate highlights the crucial importance of experimental validity and says that around 75-90 percent of bioscientific papers he analyses do not meet the necessary criteria for industry acceptance.
He attributes this to factors such as “p-hacking” (the process by which researchers game the system, tirelessly trying out random combinations of variables until a statistically significant result is achieved) and “cherry-picking” (choosing the result that looks the best but which is not truly representative).
Mr. Begley says, “The average investment required to convert a bioscientific research finding into a drug or therapy is $2.6 billion (US). To justify this investment, companies must have absolute confidence that the research findings upon which the therapy development is based are valid and accurate”.
“Part of BioCurate’s mandate has been to replicate and validate existing data to give pharmaceutical firms the confidence to make necessary investments. The industry as a whole is very aware of p-hacking and other factors that contribute to low validity – and appreciates the work we are doing, sifting through experiments to find the ones that we can really believe”.
Differentiation is a key to the success of any business; but in a flooded and highly fragmented marketplace it is critical.
For digital health providers serious about scaling this multi-billion-dollar industry, FDA approval is the gold standard – offering a key way to differentiate from other market players and win investment.
But healthcare innovators should also be asking themselves, does this solution provide better clinical and commercial/economic outcomes than other solutions already available in the marketplace?
In the context of pharmaceuticals, Mr. Begley says, “It’s all very well discovering the importance of a particular molecule in the sensation of pain, for example. But if a therapy targeting that molecule for pain relief is no more effective than, say, aspirin, then the research is practically redundant to industry”.
Mr. Begley instead encourages researchers to maintain a long-sighted view of how their finding may benefit humankind, as opposed to shorter-sighted prospects, such as publication and or a subsequent research grant.
Ms. Le Grice adds, “From a purely commercial view, the best way for patients to benefit from your technology is to ensure that there is a customer for it. Just like biotechnology companies partner with pharmaceutical companies to distribute their products globally, digital health companies need to commercialise effectively – that is, have someone put their technology in the hands of patients on a global scale”.
Ms. Le Grice says, “Most of the companies we see talk about their ‘Voice of Customer’ work and how patients and clinicians wholeheartedly support the need and effectiveness of the product.
“Unfortunately in a complex healthcare payment environment, which is extremely cost-sensitive, many companies fail to differentiate between customers and users.
“For example, whilst patients and clinicians may use your application and associated web or EMR integrated dashboard, they are probably not going to be the people that pay for it.
“US based company Driver, once considered a promising digital health company – having raised US$90m from venture investors – shut its doors just 2 months after its product launch, despite having relationships with the 30 leading cancer hospitals in the world.
“Why? Because it had validated its business model with its users (oncologists), but never actually verified that patients would pay the US$3000 plus $20 per month price tag.
“If your identified customers won’t pay or can’t pay, you don’t have an economic model, and therefore regardless of the patient impact, you can’t sustainably change lives”.
Gaining venture backing requires more than just a great solution to a genuine problem. It requires a sound and scalable business model.
Mr. Dromey says, “Too often great digital health solutions are built to address a problem, but the really hard questions around who pays are left to the end”.
Initiatives like ANDHealth have sought to address this, by providing education, mentoring and accelerator programs which specifically address the business challenges alongside the clinical evidence requirements, from the very first stages of development.
Ms. Le Grice says, “By leveraging a multi-sectoral group of local and international leaders with real world experience in commercialising digital health specifically, we can provide insights to companies that are specific and actionable and which can transform their commercial outcomes. In just 18 months our cohort companies have created 74 jobs, raised over $15m and undertaken 16 clinical studies and over 290 commercial pilots.”
Similarly, incubators, like Cicada MedLab, provide mentor-driven support for early-stage startup entrepreneurs. MedLab’s program is supported by experienced innovators, investors, business builders and domain experts; and provides everything needed to develop and scale a high-growth medtech business.
Cicada’s Alfred Lo says, “Great things come when you bring people together from different skills and experience – strong commercial and strategic thinkers combined with researchers and scientists working on breakthrough technologies – that’s when you see really successful innovation”.
Evidence based digital health technologies require long time frames and patient capital. Most international success stories are at least ten years old before they start to gain commercial traction.
The time to recruit and undertake trials and health economics studies along with slow sales cycles and complex regulatory, reimbursement and procurement pathways mean that, like other medical technologies, founders and investors need to be in it for the long haul.
Ms. Le Grice says, “Selling a short term ‘hockey stick’ revenue story may work in pure technology plays, but the regulatory and evidence requirements in health make these challenging for investors. Underestimating and understating the time and cost of development is a key challenge for many companies.”
Early stage companies are best placed when they take a strategic approach to forming strong partnerships with clinical and commercial partners. Australian adherence company Perx, has partnered with a number of large pharmaceutical companies to pilot its innovative medication adherence solution; and CancerAid established a relationship with Cedar Sinai and participated in their accelerator program to create a clinical partnership.
On the investor side, Ms. Le Grice says, “taking money from an investor is the beginning of a long term relationship. Founders should be cautious of engaging with investors who don’t understand their business or who don’t share their long-term vision of the future. Investors should have applicable skills and networks, and a track record in successfully working with companies like yours. A good investor brings a lot more than cash to the table.”