Your 3-Step Process For Innovation In Precision Medicine
By Colin Enderlein, DeciBio Consulting
While scientific innovation is propelling healthcare into the future, there remains a distinct gap between technologies that make it to market and those that are relegated to early-stage failures. Those innovations that never make it to patients are sometimes the most promising, so why didn’t they make it? The transition of early-stage ideas to widespread adoption is where promising technologies often fall short. Failing to account for commercial challenges, fickle market pressures, and the rapidly evolving healthcare landscape prior to developing a new product can be deadly.
Scientific advances are exciting, but not every discovery translates well into the clinic. Why is that? And how can companies successfully position themselves for market success? Understanding the market, distinct value proposition, business model, and clinical actionability of a product is essential to bridging the gap between early-stage ideas and commercialized successes.
1. Identify A Market Need
A common trap is pursuing an innovation out of novelty rather than market need. Believe it or not, it is common for companies to launch a technology just because they can. Scientific feasibility is not the only factor determining innovations’ long-term success. Focusing on applications that afford a technology a meaningful and compelling value differentiation is essential.
Critical to avoiding an early-stage death is identifying the application within a market where the technology fits best and taking stock of existing products on the market. Some markets may not be sexy but are still very necessary. It is easy to be drawn to the biggest and trendiest applications, whether or not they best serve the emerging technology. For example, billions of dollars have been funneled into early cancer detection, making it an attractive target for innovation. However, this application is very expensive and crowded, making it incredibly difficult to competitively enter this market without a billion-dollar checkbook cosigning the venture. Creatively positioning a technology within a saturated market can take different shapes. Pitching a technology to be used in conjunction with an existing product that already has market share is a great way to establish credibility and leverage existing commercial infrastructure for emerging technologies (e.g., cancer monitoring tests building on genomic therapy selection assay workflows or adding risk factor testing to routine annual bloodwork). Perhaps a more traditional approach is positioning a technology to be an attractive acquisition target by selecting an application that is somehow enabling to existing tech.
An example of a technology that failed because of launching without understanding market needs is high-plex gene expression profiling (GEP) for routine companion diagnostic (CDx) testing. While compelling, GEP was far too expensive and complex for regular clinical use in the early days of immuno-oncology approvals, and thus it experienced significant challenges in widespread commercial adoption.
It does not have to be sexy; it just needs to have a competitive advantage over anything else out there because that is what will drive industries to adopt a promising technology.
2. Understand That Not All Business Models Are Alike
A business model compatible with a technology’s target markets and intended commercialization plan is critical. The required workflows and models that will be appropriate for a technology will vary depending on the chosen application. Some technologies are fit for the clinic, whereas others are fit for R&D. Some need to be centralized whereas others can be distributed.
For example, non-invasive prenatal testing (NIPT) has become one of the fastest-spreading genetic technologies around the world. Clinical implementation has been affected by many commercial and national factors such as the structure of the healthcare system, the presence of a prenatal testing program and of public funding, as well as the cultural and political context in which these tests are administered. Despite the science being fairly consistent, clinical testing models must be flexible and adapt to changing market needs as NIPT grows to become a first-tier screening test; otherwise, its growth and adoption will be hampered.
3. Determine Clinical Actionability – The Pinch Hitter
Clinical actionability is precisely what it sounds like – the determination of whether clinical action should be taken based on information generated by the referenced data. As computational capabilities evolve, the issue increasingly becomes interpreting the data output in a way that informs meaningful action. Genomics and other high-plex technologies are great examples of incredibly powerful tools that are limited by their complexity and the challenge of translating data into clinical action. Multi-parameter readouts make result interpretation incredibly difficult and limit these technologies’ ability to inform decision-making about clinical intervention without sophisticated software and experienced clinical staff.
While computational capabilities might be compelling, if the resulting data is not clinically meaningful, it significantly limits the product’s market penetration within healthcare.
Historically, direct-to-consumer technologies have difficulty finding relevance in the clinic. 23&Me and wearables fall into this category. While pharma has recognized the potential of these applications and has stepped in to start mining some of these data, the direct relevance to the clinic is still murky.
Another example is AI-guided clinical decision support, where a computer prompts treatment suggestions based on patient history, biomarkers, and initial therapeutic response. This technology is still in development but is currently very limited in utility. It is anticipated that these technologies will also likely face significant hurdles in gaining physician trust and the eventual regulatory approval. While these ideas remain “cool,” they are not expected to be centrally used to inform clinical decision-making without clinician oversight for many more years.
Ultimately, the key to clinical actionability is being able to answer the question, “Does this data inform patient care?” Market success in clinical spaces depends on sufficient coverage by payers, and if the technology does not directly inform the treatment of a patient, reimbursement is typically a huge challenge and presents significant hurdles to widespread adoption. Payers are beginning to associate reimbursement with efficacy, so innovations must be able to prove not only that they work, but that they are either better or cheaper than the competition. While cost certainly plays a role in adoption, cost by itself is rarely the only barrier. It almost always comes down to a value-based calculation of what you are getting for the cost.
Promising Days Ahead
While the challenges of successfully bringing a new technology to market are many, so are the opportunities. The fluid nature of innovation in healthcare means that there will always be room for emerging technologies to try their hand at market success. Having a promising technology is only half the battle. Commercial considerations at the early stages of technology development are vital to ensuring the long-term success and eventual integration into existing healthcare systems. Identifying target market segments and compatible business models and understanding the clinical actionability of an innovation are essential for it to survive the arduous road to commercialization.
About The Author:
Colin Enderlein is a senior project leader with DeciBio Consulting, where he specializes in research related to oncology therapies and their associated biomarkers, spanning both the pharmaceutical and genomic tools markets. He has been active in precision medicine innovation and CDx commercialization at multiple phases of the R&D value chain in both the public and private sectors. Following the completion of his graduate work at The Karolinska Institute, Enderlein worked with the business development team at Seattle Children's Research Institute to establish industry partnerships with a focus on curing childhood diseases. From there, he joined the business development team at NanoString, where activities focused on CDx partnering and execution, and technology due diligence.