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	<title>Aimée Mugisha, Author at Verhaert Masters in Innovation</title>
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		<title>The impact of decentralization on IVD engineering</title>
		<link>https://verhaert.com/insights/blog/pi/ivd-engineering-decentralization-trends/</link>
		
		<dc:creator><![CDATA[Aimée Mugisha]]></dc:creator>
		<pubDate>Thu, 07 May 2026 14:34:37 +0000</pubDate>
				<category><![CDATA[Life sciences]]></category>
		<guid isPermaLink="false">https://verhaert.com/?p=42946</guid>

					<description><![CDATA[<p>Learn how key trends are making companies rethink IVD diagnostics as end-to-end platforms, and what you can learn from other industries.</p>
<p>The post <a rel="nofollow" href="https://verhaert.com/insights/blog/pi/ivd-engineering-decentralization-trends/">The impact of decentralization on IVD engineering</a> appeared first on <a rel="nofollow" href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
<p>The post <a href="https://verhaert.com/insights/blog/pi/ivd-engineering-decentralization-trends/">The impact of decentralization on IVD engineering</a> appeared first on <a href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
]]></description>
										<content:encoded><![CDATA[<section id="intro"><strong>In-vitro diagnostics (IVD) is moving past the era of &#8216;better specs&#8217; and into the era of &#8216;systemic integration’. While decentralization and connectivity have been discussed for years, we have reached a fundamental inflection point: the convergence of stricter global regulations and the &#8216;retailization&#8217; of healthcare. For R&amp;D and leadership, this requires a total rethink of the product lifecycle, moving from designing isolated technologies to building scalable, connected ecosystems. Let’s explore the key trends driving this change, what they mean in practice and what we can learn from other industries.</strong></section>
<p><img fetchpriority="high" decoding="async" style="margin-bottom: 15px;" src="https://verhaert.com/wp-content/uploads/2026-Blog-IVD.png" alt="IVD engineering for decentralized point-of-care testing systems" width="800" height="400" /></p>
<section id="big picture">
<h2>Big-picture context</h2>
<p>IVD success is no longer a purely biological challenge. While companies remain strongly rooted in scientific excellence, many are hitting a capability ceiling: their expertise in assay performance hasn&#8217;t yet been matched by the specialized systems engineering required for decentralized adoption. Diagnostics now need to function across fragmented healthcare settings, from central labs to point-of-care environments and even patient-facing use cases. That means <strong>usability, connectivity and workflow integration are just as critical</strong> as analytical accuracy. On top of that, regulatory expectations around traceability and real-world performance have intensified, while cost and operational pressures continue to grow. These combined pressures are redefining success in diagnostics, shifting the focus from isolated analytical performance to end-to-end ecosystem effectiveness in complex healthcare environments.</p>
</section>
<p>&nbsp;</p>
<section id="trend 1">
<h2>Trend 1: Decentralized testing needs robust usability</h2>
<p>In vitro diagnostics have always been designed for trained lab techs working in controlled lab environments. That model doesn’t really work anymore. Testing is steadily <strong>shifting out of central labs</strong> and into clinics, hospital wards, pharmacies, and even patients’ homes. That means what used to be a very technical process now has to be simple, intuitive and robust in real-world conditions.</p>
<p>For IVD system design, this shift is profound: <strong>Usability now effectively defines the product.</strong> Devices must be small enough to fit into constrained clinical spaces, but also simple enough that there is only one way to run the test: the correct one. Every extra step increases the risk of error. At the same time, workflows need to be managed and streamlined end-to-end, including how patients register, how samples are collected, and where results are integrated.</p>
<p>Cartridge and consumable design are also changing, since tests are no longer performed in clean lab environments. <strong>Contamination risks must be engineered out</strong> at the design stage. All of this must be achieved while using lower-cost materials and supporting less specialized users, without compromising reliability or consistency.</p>
</section>
<p>&nbsp;</p>
<section id="trend 2">
<h2>Trend 2: Connected traceability changes system architecture</h2>
<p>With stricter frameworks such as <a href="https://ec.europa.eu/tools/eudamed/#/screen/home" target="_blank" rel="noopener">EUDAMED</a> and tighter post-market surveillance rules, manufacturers are now expected to <strong>continuously generate, structure and report performance data</strong> across the entire product lifecycle. The old model of building a device and releasing it is giving way to one of ongoing accountability.</p>
<p>This shift matters more than ever because diagnostics are <strong>moving into higher-stakes clinical areas.</strong> Tests that once supported relatively simple decisions, such as pregnancy confirmation, are now being used in complex and sensitive domains like neurodegenerative diseases and long-term condition management. As clinical impact increases, so does the demand for traceable, reliable and auditable data.</p>
<p>Connectivity enables this transition, turning what was once sporadic data collection into a continuous flow of structured information. Yet, it also <strong>changes the fundamentals of system design.</strong> Devices must now be built as data-generating platforms from the outset, with storage, parameters and data streams considered at the architecture level, rather than added later.</p>
<p>The consequences for existing offline systems are significant. Companies must either <strong>re-engineer legacy products or phase them out,</strong> both of which can divert valuable engineering capacity from new innovation. This shift is particularly challenging for mid-sized and niche players, because larger companies are more likely to leverage existing software capabilities across business units. As a result, regulatory compliance demands strong in-house expertise to ensure systems are registered and data streams are correctly structured and maintained.</p>
</section>
<p>&nbsp;</p>
<section id="trend 3">
<h2>Trend 3: Scalability starts earlier, in cartridge and platform design</h2>
<p>Scalability in IVD is often treated as a manufacturing or supply chain challenge, but in reality, it starts much earlier, in the architecture of cartridges, consumables and platforms. As diagnostics move closer to patients and away from centralized labs, manufacturers are being pushed toward <strong>smaller, simpler devices that can operate in clinics, pharmacies and other decentralized settings.</strong> Paradoxically, this miniaturization often increases technical complexity inside the system.</p>
<p>In the past, devices were developed primarily for trained laboratory professionals, which reduced the pressure around usability, volume scaling and cost sensitivity. Today, that is no longer the case. Products must be designed from the outset for <strong>high-volume use and non-expert users,</strong> making early design decisions far more consequential. Usability considerations just can’t be postponed without risking expensive redesigns later in the cycle.</p>
<p>Cost of goods has also become a defining constraint. Unlike central labs, which can absorb higher per-test costs, <strong>general practitioners and point-of-care settings operate under tighter budgets.</strong> This forces manufacturers to make manufacturability and cost trade-offs much earlier in development. At the same time, they need to shift toward<strong> system-level thinking and modular platform designs</strong> capable of running multiple tests on a single system, rather than single-disease instruments. Many R&amp;D teams are still adapting to this way of working.</p>
</section>
<p>&nbsp;</p>
<p><img decoding="async" style="margin-bottom: 15px;" src="https://verhaert.com/wp-content/uploads/AdobeStock_1932473299-scaled.jpeg" alt="IVD engineering" width="800" height="400" /></p>
<section id="other industries">
<h2>What you can learn from other industries</h2>
<p>Luckily, IVD’s current transformation is not happening in isolation. <strong>FMCG and aerospace,</strong> in particular, offer clear lessons in how to design for miniaturization, modularity, and tight system integration without losing control over cost and complexity. In FMCG, high-volume product development has long depended on breaking systems into modular, interchangeable parts that can be rapidly iterated and optimized. Aerospace and space applications, on the other hand, have pushed miniaturization and reliability under extreme constraints, where every gram, component choice, and interface matters.</p>
<p>In practice, this translates into a <strong>more structured cost-down approach early in development,</strong> screening architectures faster and eliminating non-viable options before heavy R&amp;D investment. In some of our projects, such as for Hippo Diagnostics and Fujirebio, applying this discipline helped reduce bill of materials costs by up to 50%, mainly by simplifying subsystem choices and improving component alignment.</p>
<p>Another transferable capability is <strong>holistic gap assessment:</strong> mapping the current system state, identifying regulatory and technical gaps, and translating them into a clear product roadmap. While we don’t replace regulatory expertise, this approach helps you turn complex requirements into actionable engineering decisions.</p>
<p>Finally, FMCG and industrial sectors also provide <strong>mature models for cybersecurity and system robustness,</strong> including proven approaches to risk management, layered security architecture, and continuous monitoring. These practices are increasingly relevant as IVD platforms become more connected, data-driven, and exposed to external systems and networks.</p>
</section>
<p>&nbsp;</p>
<section id="conclusion">
<h2>What you can learn from other industries</h2>
<footer>IVD is no longer defined by what happens in the lab, but by how intelligently systems perform in the real world. As usability, connectivity, and scalability converge, the winners will be those who <strong>rethink diagnostics as end-to-end platforms.</strong> Beyond this, AI is set to become a defining force in IVD, <a href="https://edition.cnn.com/2026/02/09/tech/ai-replacing-jobs-concerns-radiology" target="_blank" rel="noopener">much like in radiology,</a> where algorithms already support detection and workflow efficiency. It will augment decision-making, improve consistency, and unlock new levels of diagnostic insight across connected platforms.If you want to know more about how we can support your R&amp;D and product development, <strong><a href="https://verhaert.com/contact-us/product-innovation/" target="_blank" rel="noopener">make sure to reach out!</a></strong></footer>
</section>
<p>The post <a rel="nofollow" href="https://verhaert.com/insights/blog/pi/ivd-engineering-decentralization-trends/">The impact of decentralization on IVD engineering</a> appeared first on <a rel="nofollow" href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
<p>The post <a href="https://verhaert.com/insights/blog/pi/ivd-engineering-decentralization-trends/">The impact of decentralization on IVD engineering</a> appeared first on <a href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
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		<title>The economics of scale: Solving the cell therapy manufacturing bottleneck</title>
		<link>https://verhaert.com/insights/blog/pi/the-economics-of-scale-solving-the-cell-therapy-manufacturing-bottleneck/</link>
		
		<dc:creator><![CDATA[Aimée Mugisha]]></dc:creator>
		<pubDate>Tue, 03 Mar 2026 15:05:25 +0000</pubDate>
				<category><![CDATA[Product innovation]]></category>
		<guid isPermaLink="false">https://verhaert.com/?p=41915</guid>

					<description><![CDATA[<p>See how automated, user-centric systems are enabling cell therapies to move from bespoke lab success to industrial market victory.</p>
<p>The post <a rel="nofollow" href="https://verhaert.com/insights/blog/pi/the-economics-of-scale-solving-the-cell-therapy-manufacturing-bottleneck/">The economics of scale: Solving the cell therapy manufacturing bottleneck</a> appeared first on <a rel="nofollow" href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
<p>The post <a href="https://verhaert.com/insights/blog/pi/the-economics-of-scale-solving-the-cell-therapy-manufacturing-bottleneck/">The economics of scale: Solving the cell therapy manufacturing bottleneck</a> appeared first on <a href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
]]></description>
										<content:encoded><![CDATA[<p><strong>Cell-based therapies, especially Chimeric Antigen Receptor (CAR) T-cell therapies, have evolved from scientific advances to established pillars of oncology. By re-engineering immune cells to target specific cancer markers, these &#8220;living drugs&#8221; offer curative potential where traditional treatments fail. However, in 2026, the strategic challenge has shifted: the industry must now move from &#8220;bespoke&#8221; clinical success to high-volume, predictable manufacturing.</strong></p>
<p><img decoding="async" style="margin-bottom: 15px;" src="https://verhaert.com/wp-content/uploads/2026-Verhaert-Product-Innovation-Blog-The-economics-of-scale.png" alt="Chip-on-Board the future of embedded intelligence" /></p>
<h2 style="margin-top: 30px;">The state of things: The $475,000 ceiling</h2>
<p><span style="font-weight: 400;">In 2026, extreme reimbursement pressure defines the economic landscape. Established therapies like Novartis’s Kymriah list at about <a href="https://bioinformant.com/car-t-cell-therapy-products/#:~:text=Kymriah%20carries%20a%20U.S.%20price,and%20%24278%20million%20in%202019" target="_blank" rel="noopener"><span style="text-decoration: underline;"><strong>$475,000 (USA price)</strong></span></a>, but total care costs, including ICU monitoring and complex logistics, often exceed <strong>$1.2 million</strong>.</span></p>
<p><span style="font-weight: 400;">Outcome-based reimbursement now ties payments to long-term patient survival. For developers, a failed batch or process delay is not just a lost product but a direct financial and regulatory liability. Reducing Cost of Goods Sold (COGS) via smarter equipment architecture is essential for commercial sustainability.</span></p>
<h2 style="margin-top: 30px;">The challenges: overcoming the scaling barrier</h2>
<p>Despite commercial success by leaders like Kite Pharma and Legend Biotech, manufacturing costs remain high. These challenges fall into three main categories:</p>
<h3 style="margin-top: 20px;"><strong>1. The human variable (labor &amp; expertise)</strong></h3>
<p>Manufacturing remains heavily dependent on manual intervention. Our analysis¹ of 2026 industry benchmarks shows that labor accounts for <strong>45-50% of total COGS</strong>.<br />
<img decoding="async" class="alignnone" style="margin-bottom: 15px; margin-top: 15px;" src="https://verhaert.com/wp-content/uploads/2026-Verhaert-Product-Innovation-Blog-The-economics-of-scale-Graph3-scaled.png" alt="Chip-on-Board the future of embedded intelligence" width="1215" height="474" /></p>
<h3 style="margin-top: 0px;"><strong>2. The facility footprint</strong></h3>
<p>Manual processes require &#8220;open&#8221; systems and Grade B cleanrooms, which are significantly more expensive to build and operate than lower-grade environments due to strict HVAC, gowning, and monitoring requirements.</p>
<h3 style="margin-top: 20px;"><strong>3. The &#8216;comparability trap&#8217;</strong></h3>
<p>Many innovators rely on manual, &#8216;open&#8217; processes during phase 1, ‘Proof-of-Concept’, to reach the clinic quickly. However, by the time they reach phase 2b or 3 clinical trials, the transition to automated platforms often alters the cellular product’s phenotype or potency. This triggers a mandatory <strong>comparability study</strong>, a major regulatory hurdle that can lead to years of delay or even a Complete Response Letter (CRL) from the FDA. Success in 2026 requires an<strong> &#8216;automation-by-design&#8217; strategy</strong> that integrates scalable equipment architecture before the first patient is even dosed.</p>
<h2 style="margin-top: 30px;">Insights for COGS reduction: A technological roadmap</h2>
<p>The path to reducing COGS lies in how equipment is designed to handle the biological journey. We see three main areas where technical intervention yields the highest ROI:</p>
<h3 style="margin-top: 20px;"><strong>1. Transitioning to functionally closed systems</strong></h3>
<p>The primary goal is to encapsulate the process – from activation to harvest – within a sterile, operator-independent environment.</p>
<p>Moving to functionally closed systems enables manufacturers to operate in less costly Grade C or D cleanrooms instead of expensive Grade B environments, reducing facility overhead by an estimated 20-30%.</p>
<p>Achieving this shift requires more than a closed loop. It demands <strong>precision-engineered single-use fluidic manifolds</strong> optimized for laminar flow and low shear stress. We emphasize integrating <strong>non-invasive sensor arrays</strong> using optical and ultrasonic technologies directly into the flow path. By sensing through manifold walls or using gamma-sterilized inline components, sterility is maintained while providing a <strong>digital orchestration layer</strong>. This not only monitors the process but creates a self-documenting, high-integrity environment that replaces manual QC with hardware-level validation.</p>
<h3 style="margin-top: 20px;"><strong>2. Future-proofing scale: From modularity to multi-batch</strong></h3>
<p>While scaling out (parallel modularity) is the current industry standard, the roadmap toward 2030 points to <strong>process intensification</strong>.</p>
<p>Not every enterprise is ready to adopt multi-batch platforms today. The immediate opportunity is to design modular systems that improve efficiency through shared subsystems.</p>
<p>For those ready to scale further, <strong>analyzing concurrent multi-batch platforms</strong> – where one system processes multiple patient batches in isolated parallel lanes – can maximize throughput per square meter of cleanroom and significantly reduce depreciation costs per patient.</p>
<h3 style="margin-top: 20px;"><strong>3. The &#8216;comparability trap&#8217;</strong></h3>
<p>In 2026, relying on end-of-process testing is a high-risk strategy.</p>
<p>Incorporating real-time metabolic sensors (glucose, lactate, pH) directly into equipment provides immediate process visibility. In practice, teams increasingly <strong>combine optical and electrochemical sensing</strong> (e.g., spectroscopy/imaging plus pH/DO/glucose/lactate) to reduce manual sampling and detect drift earlier. The other half of the equation is <strong>software built for auditability</strong>: data integrity, traceability, and cybersecurity by design, so process intelligence can credibly support release decisions and tech transfer, not just R&amp;D experiments.</p>
<p>Using <strong>digital twins</strong> to simulate thermal and fluidic behavior enables automated ‘corrective adjustments’. When implemented effectively, this reduces late-stage surprises and recovers time lost to manual QC and deviation handling.</p>
<h2 style="margin-top: 30px;">The state of things: The $475,000 ceiling</h2>
<p>In 2026, science is often proven; commercial sustainability depends on industrial execution. Accelerating growth through the industrial development of medical equipment constitutes a critical strategic differentiator. The most durable COGS gains come from reducing operator-dependent variability, designing for functional closure, and shortening feedback loops between process signals and decisions.</p>
<p>Two questions help teams focus quickly: (1) Is your main constraint <strong>QC lead time</strong>,<strong> facility utilization</strong>, or <strong>batch failure risk</strong>? (2) Which unit operation still relies on ‘expert operators’ rather than defined control limits? Clear answers usually identify the next best investment in automation, analytics, or GMP-ready architecture.</p>
<h2 style="margin-top: 30px;">The science is proven. Is your industrial execution ready?</h2>
<p><span data-path-to-node="6,2,2"><span class="citation-600">If you are struggling to move from a manual &#8216;hands-on&#8217; process to a predictable, high-volume system, you need a partner who understands the full innovation journey</span></span><span data-path-to-node="6,2,4">. Our team specializes in co-creating life sciences products that are built for the market from day one. <span class="citation-598">We help you integrate </span><b data-path-to-node="6,3,5" data-index-in-node="22"><span class="citation-598">connected IoT devices</span></b><span class="citation-598">, </span><b data-path-to-node="6,3,5" data-index-in-node="45"><span class="citation-598">user-centric hardware</span></b><span class="citation-598">, and </span><b data-path-to-node="6,3,5" data-index-in-node="72"><span class="citation-598">scalable architectures</span></b><span class="citation-598"> to ensure your &#8216;living drug&#8217; is as commercially viable as it is scientifically ground-breaking</span>. </span></p>
<p><span class="citation-674">Ready to turn your scientific breakthrough into a sustainable commercial success? </span><a href="https://verhaert.com/contact-us/"><b data-path-to-node="6,0,1" data-index-in-node="83"><span class="citation-674">Get in touch with our Product Innovation team</span></b></a><span class="citation-674"> to boost your R&amp;D capacity and co-create the systems you need to win in the market.</span></p>
<p>&nbsp;<br />
<a href="https://verhaert.com/wp-content/uploads/PI-ATMP.pdf" target="_blank" rel="noopener"><strong>Download the one-page guide to solving cell therapy bottlenecks</strong></a><br />
&nbsp;</p>
<p>(1) These figures are a synthesis of data from:<br />
Lab Practices Committee &#8211; International Society for Cell &amp; Gene Therapy. (n.d.). Higher Logic, LLC. <a href="https://www.isctglobal.org/about/isct-committees/lpc" target="_blank" rel="noopener">https://www.isctglobal.org/about/isct-committees/lpc</a><br />
Mordor Intelligence. (n.d.). <i>Manufacturing services research reports and market analysis</i>. <a href="https://www.mordorintelligence.com/market-analysis/manufacturing-services" target="_blank" rel="noopener"><span class="url">https://www.mordorintelligence.com/market-analysis/manufacturing-services</span></a><br />
PricewaterhouseCoopers. (n.d.). <i>Cell and gene therapy: how to overcome manufacturing challenges</i>. PwC. <a href="https://www.pwc.be/en/news-publications/2023/how-to-overcome-manufacturing-challenges.html" target="_blank" rel="noopener"><span class="url">https://www.pwc.be/en/news-publications/2023/how-to-overcome-manufacturing-challenges.html</span></a></p>
<p>The post <a rel="nofollow" href="https://verhaert.com/insights/blog/pi/the-economics-of-scale-solving-the-cell-therapy-manufacturing-bottleneck/">The economics of scale: Solving the cell therapy manufacturing bottleneck</a> appeared first on <a rel="nofollow" href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
<p>The post <a href="https://verhaert.com/insights/blog/pi/the-economics-of-scale-solving-the-cell-therapy-manufacturing-bottleneck/">The economics of scale: Solving the cell therapy manufacturing bottleneck</a> appeared first on <a href="https://verhaert.com">Verhaert Masters in Innovation</a>.</p>
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