When the Covid-19 pandemic hit, molecular and rapid diagnostics received unprecedented attention and funding. What became essential then for adoption was speed, and speed still matters, but there’s been a shift in the industry. It’s not enough to be scientifically sound. Now, practicality is of utmost importance. This is the priority that anyone involved with investing in and developing diagnostics has to understand in order to be successful, because, as research has shown, diagnostics that are ready for clinical deployment early are the ones that are increasingly favored.
Utility beats novelty
In the past, a scientific breakthrough might have been enough to secure funding. In the present, investors and hospital administrators want lab tests that don’t merely show speculative promise. They want technology that integrates smoothly and immediately into all facets of an operation. There are no regulatory issues. There’s no need for excessive training or retraining. There’s no disruption to how medical records are kept. Bottom line: There’s no lost time or money, making it easier to get funding and being adopted. And most importantly, any test needs to work on the clinical level where clinicians get accurate information and patients are helped and get healthier.
It’s these kinds of diagnostics, designed for early clinical deployment, often described as “clinical first” approaches, which are attracting growing interest. But here’s the challenge for startups. They might have a test that’s backed by strong science – and strong science still counts – but they need to have what investors and clinical partners are requiring, evidence that a diagnostic meaningfully affects care decisions. Having sufficient clinical evidence, essentially, real-world validation early in the process, provides the data that resonates with clinicians and payers, even before large trials are completed.
Watching the economics and access
Another essential consideration for startups is paying attention to the health economics of a technology, specifically, the reimbursement pathways. Diagnostics designed without a clear strategy often struggle to gain traction, regardless of their clinical promise. Whether it’s fee-for-service or valued based models, a reimbursement structure that encourages employee engagement and reduces administrative complexity strongly influences which tests are adopted and how clinicians allocate time and resources.
What’s also attractive and seen as practical is when testing is decentralized. Results are brought closer to the patient and are received more quickly. Decisions can be made faster, and while costs can be reduced, an equally significant upside is that access to care, particularly in underserved areas, can be increased.
Another way to improve both efficiency and access is where multiple readouts can be delivered from a single test sample. Proteomic approaches, the large-scale study of protein in an organism or cell, have especially gained interest for their potential to complement genomic data in complex disease evaluation, where protein-level information may better reflect real-time physiology.
Leveraging the elephant in the room
The ever-present question hovering over any new technology is how to best use artificial intelligence, and it certainly has a role to play. Rather than applying it to unvalidated tests, the focus has shifted toward using AI to enhance established diagnostics. Emerging applications include improving interpretive accuracy, increasing throughput, and streamlining workflows. AI’s most immediate value lies in augmenting, not replacing, clinically proven assays.
It’s a lot of information to process in an ever-changing landscape. One last lesson helps keep things in check. Break development into smaller stages tied to three main markers: validation, pilot deployment, and scale. Nothing guarantees success, but taking these incremental steps minimizes the investment risk, and in doing so, helps encourage investment.
Photo: Andriy Onufriyenko, Getty Images
Dr. Jamie Platt is CEO of Pictor and has more than 20 years of experience in genomics and molecular diagnostics. She has led the development and commercialization of high-complexity diagnostic tests globally and serves on the boards of DxTerity and bioAffinity Technologies. Jamie is a recognized voice in the diagnostics field, focused on advancing clinically meaningful, accessible testing that delivers real-world value for laboratories and health systems.
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