The COVID-19 pandemic has demonstrated that rapid and widespread molecular diagnostics are crucial for controlling the spread of pathogens. Traditionally, epidemiological surveillance has relied on centralised laboratories and reporting systems, with inevitable delays. Today, technological advances are enabling a paradigm shift: networks of cloud-connected point-of-care devices can act as distributed 'sensors', sending real-time data to a national analysis centre. According to the World Health Organisation [1], point-of-care testing not only improves access to rapid diagnosis, but also offers the potential to enhance disease surveillance. Similarly, the European Centre for Disease Prevention and Control (ECDC [2]) supports the use of decentralised rapid testing for the purposes of surveillance, prevention and control of infectious diseases.

In this context, Helyx Industries S.p.A., through its Hyris Division, offers a distributed PCR approach based on the Hyris System™ (bCUBE™ portable device and bAPP™ cloud platform). Each molecular test performed 'in the field' – for example, in a nursing home or school – generates a result that is immediately available in the cloud, where it can be aggregated with other data, anonymised and displayed on geographical and temporal dashboards. The strategic objective is twofold: on the one hand, to make diagnosis more proactive and widespread (not just faster), and on the other, to transform each test result into actionable data for the healthcare system, capable of providing early warning of epidemiological trends. "The future of diagnostics is not only faster, but smarter and more distributed. Every test performed in the field generates data that helps the entire healthcare system react better and sooner," says Stefano Lo Priore, President of Helyx Industries. This vision reflects a cultural shift: diagnosis becomes a continuous, data-driven process rather than an isolated event.

The core of distributed surveillance is the collection and aggregation of data from devices in the field. Helyx Industries' bAPP™ platform acts as a central hub in the cloud: each connected bCUBE automatically transmits test results (e.g., positivity for a certain pathogen, Ct value, etc.) along with metadata such as timestamps and test geolocation. This data flows into geotemporal dashboards updated in real time, accessible to epidemiologists and authorised public decision-makers. This provides a dynamic map of cases emerging in different areas, with the option to filter by time interval, type of infection, context (e.g., school vs. nursing home), etc. For example, an abnormal increase in positive flu tests in a specific school district will appear on the dashboard as a highlighted cluster, triggering automatic AI notifications (e.g., an alert of a possible outbreak).

Thanks to the artificial intelligence integrated into bAPP™, it is possible to perform advanced analyses on aggregated data: trend analysis algorithms and predictive models can identify anomalous patterns (e.g., a certain viral strain increasing in an area compared to the seasonal baseline) and thus support crisis units in scaling their response. The literature highlights that surveillance systems based on real-time dashboards significantly improve the speed of outbreak detection compared to traditional methods. During the pandemic, we saw the emergence of public epidemiological dashboards (e.g., COVID maps) – Helyx Industries' approach extends this concept to any pathogen that can be tested via PCR and brings it to the local level. Every facility equipped with a bCUBE™ becomes an active detection node within a national 'digital nervous system' for public health. [7]

From a technical point of view, data security and quality are guaranteed through rigorous protocols: each test is uniquely identified, results are encrypted as they travel from the device to the cloud, and automatic quality control systems validate the results before making them available. Any associated personal data (e.g. patient ID) is anonymised in accordance with privacy regulations, retaining only information relevant to surveillance (age, geographical area, etc.). In bAPP™, data is normalised and structured in a uniform manner so that it can be combined with other sources (e.g. centralised hospital laboratory data) to provide a complete epidemiological picture. The result is a solid information base for generating key performance indicators (KPIs) such as positivity rates by area, case doubling times, heat maps of outbreaks, etc.

In order for distributed PCR to reach its full potential, interoperability with existing health information systems is essential. Helyx Industries has designed bAPP™ with an open API architecture and compatibility with health standards to ensure seamless integration with public Laboratory Information Systems (LIS) and other e-health platforms. This means, for example, that a positive meningococcal swab test performed in a peripheral clinic can be simultaneously sent to the regional meningitis surveillance platform (if one exists) or to the local Department of Prevention's information system. In Italy, many regions have their own organisational models for surveillance (e.g. infectious disease registries, regional epidemiological observatories): a system such as bAPP™ can automatically feed these channels with up-to-date data, avoiding duplication of entry and delays.

At the international level, the platform is designed to interact with initiatives such as those promoted by the ECDC. Just think of the European surveillance networks for influenza or invasive infections: traditionally, they rely on sentinel laboratories that report aggregated data on a weekly basis. With distributed diagnostics, sentinel laboratories can multiply (each local device acts as a mini-laboratory) and the data flow can become continuous. In 2022, the ECDC conducted a mapping exercise [2] on the use of POCT in Europe, highlighting that in at least seven countries, rapid test results are already being used for infectious disease surveillance. Furthermore, the COVID experience has led the European Union to invest in the integrated digitalisation of surveillance (as indicated in the ECDC 2021–2027 strategy), recognising the value of collecting data even from decentralised contexts. "The goal is not to create new silos, but to connect each new device to a unified information ecosystem," Lo Priore emphasises. "That's why we focus on interoperability by design: each bCUBE is designed to communicate with hospital LISs, national repositories and any global disease surveillance platforms."

From an organisational perspective, implementing a distributed PCR network requires collaboration between public and private entities. One possible model is the creation of public-private partnerships: companies provide the technology (instruments, cloud, maintenance) as a service, while institutions guarantee the regulatory framework, staff training and the use of data for public health measures. This model, in line with the emerging concept of Diagnostics-as-a-Service (DaaS), is sustainable and scalable: it allows public bodies to quickly activate diagnostic points across the territory without having to purchase expensive equipment, paying instead for a subscription or per-test service. For their part, technology providers can monetise the cloud (e.g. advanced data analysis modules, integration with health records) and generate recurring revenues, as already discussed in previous articles [3]. The key is to define shared standards and clear interoperability protocols: for example, a COVID test result from bCUBE can generate an HL7 message that is automatically received by the Ministry of Health's COVID surveillance system, ensuring that no critical results 'slip through the cracks' of the authorities' radar.

The distributed PCR approach can be applied in many contexts. Nursing homes and retirement homes are high-risk environments: here, an outbreak of influenza or COVID-19 can have serious consequences. Equipping these facilities with portable PCR devices means that residents or staff with symptoms can be tested immediately, identifying the pathogen in a matter of minutes and isolating positive cases. A recent study conducted in Canada in a number of nursing homes showed that the introduction of point-of-care PCR platforms for respiratory viruses reduced the time to diagnosis by 36 hours [6] compared to external laboratories and shortened the time to officially declare an outbreak in the facility. In practice, the nursing home management was able to activate containment measures (cohorting of positive cases, limiting visits, antiviral prophylaxis if indicated) earlier, limiting the number of infections and, consequently, reducing hospital admissions among frail elderly people.

In remote or rural areas, far from large hospitals, devices such as bCUBE™ represent a vital diagnostic bridge. An example comes from Australia: in remote Aboriginal communities, the implementation of decentralised PCR platforms (e.g. decentralised PCR platforms) for COVID-19 has made it possible to overcome geographical barriers and offer timely testing, integrated into a successful local response model. The authors of that study (published in The Lancet Infectious Diseases) recommend considering the implementation of decentralised testing models in vulnerable and underserved communities globally. Similarly, in mountainous areas or on smaller Italian islands, a network of portable PCR devices could ensure widespread diagnostic coverage, preventing patients from having to travel and, above all, ensuring that any dangerous agents (e.g., a case of resistant tuberculosis or imported dengue fever) are detected immediately on site. [4]

Temporary clinics and mobile hubs are further scenarios of use: think of mobile screening units that move around during vaccination campaigns or health emergencies. A van equipped with bCUBE™ could perform multiplex PCR tests (e.g. Influenza+RSV respiratory panels) in neighbourhoods during the winter, bringing the test directly to where citizens live. In emergency situations (earthquakes, large mass events), where the risk of epidemics may increase due to crowds or precarious conditions, having a portable PCR laboratory on site means that any pathogens (cholera, norovirus, etc.) can be detected immediately and clusters prevented from developing. This operational flexibility – testing anyone, anywhere – is an essential part of what is called field epidemiology 2.0. As highlighted in Nature by Okeke and Ihekweazu, thanks to new molecular technologies, 'even in resource-limited settings, it is possible to obtain rapid and agile diagnoses, allowing for a timely response to new threats'. The authors report concrete cases: in Nigeria, the use of portable PCRs made it possible to identify outbreaks of Ebola and yellow fever several weeks earlier than with traditional methods, providing crucial information to guide the health response. Furthermore, in Bangladesh, molecular testing of meningitis samples tripled the rate of agent identification compared to conventional techniques, retrospectively discovering a Chikungunya outbreak that had escaped standard systems. These international examples confirm that decentralised diagnostics is not just theory, but a reality capable of changing the course of an epidemic in its infancy. [5]

One of the major strategic benefits of distributed PCR is the quantum leap in preparedness and active prevention. Preparedness means having the tools ready before an emergency strikes: for infectious diseases, this means having a sensitive and widespread surveillance network capable of picking up early warning signs. Investing in such networks is highly cost-effective [8]: a 2025 OECD report estimates that upfront investments in prevention and response yield significant returns by reducing the costs of future health crises. COVID-19, for example, caused enormous economic losses (over 3% of global GDP in 2020) precisely because many systems were unprepared. Conversely, equipping ourselves now with local diagnostic infrastructure can avert much more costly interventions tomorrow. In the specific context of local outbreaks, detecting even a few days before the start of an epidemic curve makes all the difference: mathematical models [9] show that early detection of a tuberculosis cluster and initiation of contact tracing significantly reduces the total number of cases and is cost-effective, with costs per life year gained that are entirely sustainable for the healthcare system.

Active prevention is achieved when we do not simply react to cases, but continuously monitor the environment to prevent them. One example is active surveillance in nursing homes: by regularly testing (e.g. weekly) a sample of residents and staff for respiratory pathogens during the flu season, it is possible to anticipate a flu alert in that facility by several days, activating measures (such as prophylaxis with antivirals or isolation of at-risk individuals) before a full-blown outbreak occurs. Similarly, in a large company or military barracks, a periodic molecular screening programme (perhaps targeting new recruits or sensitive departments) allows a high level of vigilance to be maintained and avoids costly downtime caused by internal epidemics.

It should be emphasised that these systems also increase the speed of action in the broadest sense: not only do they detect quickly, but they also facilitate response. In fact, having clear and localised data allows authorities to activate targeted interventions within a few hours: sending health task forces to a certain area, allocating stocks of vaccines or antibiotics where they are needed, and sending targeted communications to the affected population. During an emergency, every hour counts. Having a real-time epidemiological picture (rather than waiting for weekly bulletins) means that more proportionate and timely public health measures can be implemented, reducing the impact on the economy and society. Ultimately, distributed molecular diagnostics become a multiplier of health resilience.

In order to successfully implement distributed PCR in surveillance, appropriate organisational models must be put in place. An effective scenario involves the designation of a centralised control room (e.g. at the National Institute of Health or Regional Public Health Agencies) to monitor dashboards and coordinate responses, and a network of peripheral actors (local health authorities, mobile laboratories, sentinel doctors) equipped with shared tools and protocols. Staff training is crucial: non-specialist operators (e.g. school nurses, general practitioners) will need to be trained in the use of bCUBE and in compliance with quality procedures (PCR requires rigour to avoid contamination, even though modern systems are greatly simplified). At the same time, communication flows must be established: for example, in the event of a positive result for a notifiable disease, bAPP could automatically send an alert to the competent public health doctor and enter the case in the surveillance database. This requires institutional agreements and an update of notification regulations to recognise point-of-care as an official source of epidemiological data.

Interoperability, as already mentioned, also has a technical-standard aspect: there are standards [10] designed for multi-vendor integration of point-of-care devices. Adopting open standards avoids technological lock-in and allows, for example, a device from another manufacturer to still send data to the national platform, or for bAPP™ data to be read by third-party software for independent analysis. In this regard, Helyx Industries adheres to the main international standards and provides documented APIs to facilitate integration projects. In an ideal ecosystem, results from decentralised diagnostics will flow into the same repositories as traditional laboratory data, becoming an integral part of the healthcare information asset base. This truly realises the vision of 'One Health data': clinical, central laboratory, peripheral laboratory and perhaps veterinary/environmental surveillance data brought together for holistic analysis.

One organisational aspect to consider is long-term economic and managerial sustainability. The distributed PCR network will need to be maintained (ensuring supplies of reagents, calibrations, software updates) and updated (adding new tests for new emerging pathogens). This is where innovative financing models come into play: European preparedness funds, investments in technology by organisations such as the WHO, or public-private co-financing. It is important to define performance metrics from the outset: for example, how many outbreaks have been detected in a timely manner thanks to the network? How many days in advance, on average, are outbreaks detected compared to the past? How many hospitalisations (or euros) have been avoided? These indicators will help demonstrate the ROI (Return on Investment) of enhanced surveillance. Already today, economic studies indicate that intensifying surveillance activities is cost-effective compared to the costs of managing uncontrolled epidemics. For decision-makers, this translates into the message: 'invest in diagnostic networks today to save lives and resources tomorrow'.

Epidemiological surveillance and distributed PCR represent a strategic evolution for public health in the post-pandemic era. By integrating portable molecular devices such as bCUBE™ into a cloud network (bAPP™) that is interoperable with existing systems, it is possible to obtain a real-time view of pathogen circulation, from the local to the national level. This model improves early warning capabilities and strengthens the response to outbreaks, better protecting vulnerable communities. It also enables more proactive and territorial medicine, where every test counts not only for the individual patient but also for the community, providing valuable data to the system.

From a strategic business perspective, for biotech groups such as Helyx Industries, this also means driving a paradigm shift: offering not only diagnostic tools, but an integrated service where hardware, cloud software and analytics work together to generate epidemiological value. The benefits for institutional stakeholders are clear: potentially reduced costs thanks to outbreaks being nipped in the bud, more effective public health interventions and a safer population. As this article has shown, there is already evidence and successful pilot projects; the challenge now is to move from experimentation to large-scale scalability, creating regulatory frameworks and partnerships that make decentralised surveillance an integral part of the healthcare system. "Every device in the territory is an additional ally in protecting public health," concludes Stefano Lo Priore. "Our vision is a future in which no epidemic signal goes unnoticed because we will have an intelligent network spread everywhere, always on alert."

Q: Why focus on decentralised molecular diagnostics?

Stefano Lo Priore: Because operational speed is crucial. Bringing qPCR closer to the point of need reduces the time between biological event and clinical decision. In many contexts, the limitation is not technical analysis, but sample logistics and process priority. A distributed platform shortens this distance. It does not replace the central laboratory. It complements it and expands its response capacity.

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Q: What has changed compared to the traditional model?

Stefano Lo Priore: The architecture of the system changes. In the traditional model, data is generated and remains confined to the laboratory. In our approach, testing can be performed locally, while data is managed in a centralised and structured manner. This ensures traceability, control and an aggregated view. Decentralisation concerns execution. Governance remains unified.

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Q: What is the industrial advantage of this architecture?

Stefano Lo Priore: The advantage lies in the clarity of the boundaries. Hyris oversees distributed qPCR. Vytro operates in clinical PCR under the IVD regime. Mytho focuses on NGS and advanced bioinformatics. Each division works with metrics and cycles consistent with its own market. However, the industrial base is common: quality, production, design and data management. This approach reduces operational ambiguity and limits overlap. From an industrial point of view, this means less friction between development and deployment and greater control over the technology supply chain.

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Q: What concrete impact could this model have on the healthcare system?

Stefano Lo Priore: An operational impact. Intercepting earlier means acting earlier. It means reducing diagnostic delays and easing the pressure on central laboratories. The resilience of the system also depends on the distribution of diagnostic capabilities. When access is closer to where it is needed, the response becomes faster and more effective.

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Q: How does this vision translate into value for investors?

Stefano Lo Priore: It translates into clarity and discipline. A clear industrial architecture allows you to understand where resources are allocated, what the operational priorities are, and what risk perimeters belong to each area. The three divisions should not be interpreted as simple product lines. They are not. They operate in different markets, with specific cycles and requirements, and require autonomous metrics. At the same time, they share critical infrastructures that form the common basis of the Group. From a financial point of view, the separation of perimeters reduces dependence on a single technology or a single commercial channel. Distributed qPCR, clinical IVD PCR and customised NGS respond to different demand dynamics and can evolve at different speeds. Integration allows skills and platforms to be transferred when necessary, without generating unproductive complexity. This balance improves industrial planning and makes execution more predictable over time.

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Q: What is Helyx's real competitive advantage?

Stefano Lo Priore: Integration along the entire molecular supply chain. Controlling reagents, platforms and data management ensures operational consistency. Innovation alone is not enough. It must be made scalable, verifiable and sustainable over time. It is this step that creates structural value.