Remediation is harder in a hospital than almost anywhere else. A vulnerable medical device cannot be pulled offline the way a laptop can, so patching one means working around clinical schedules and backup equipment. Every change also has to carry an approval and audit trail that will hold up to a regulator. Faced with those constraints, the industry built capable tools for identifying potential vulnerabilities and left the harder half of remediating them to spreadsheets, email threads, and manual ticket entry.

That manual process is losing ground. CVE submissions rose 263% between 2020 and 2025, according to NIST, outpacing the public vulnerability infrastructure hospitals rely on to turn a disclosure into a device-specific alert. The backlog now shows up in the fleet itself: the average connected medical device carries 6.2 known vulnerabilities, roughly 75% of infusion pumps carry one listed in CISA’s Known Exploited Vulnerabilities catalog, and roughly 60% of the installed base runs components no longer receiving manufacturer support at all, according to Ordr’s 2026 medical device research. Meanwhile, healthcare has remained the costliest industry for data breaches for more than a decade, averaging $7.42 million per incident in IBM’s 2025 Cost of a Data Breach Report.

A proven model, applied to a new device class

Gluware IoMT Exposure Management is built on the same foundational automation engine Gluware runs across enterprise network infrastructure, and on DIAL (Device Interaction and Automation Layer), the semantic translation layer proven across 56 operating systems and 22 vendors. This is not another point solution for hospitals to integrate and maintain. IoMT Exposure Management is that platform extended to a new class of devices the same platform, the same change-control model, and the same team already automating the network.

“Most hospitals can tell you what’s on their network. Far fewer can tell you which of those devices are actually exposed today, when each one was fixed, and who approved the change,” said Jeff Gray, CEO and Co-Founder of Gluware, Inc. “Hospitals shouldn’t have to stand up a separate platform and a separate team to protect the devices closest to patient care. We’ve spent nearly two decades closing that gap on enterprise networks, under the kind of change control that clinical environments demand.”

Also Read: Movemedical Launches Ask Move AI, the First AI Assistant Purpose-Built for Med Device Field Operations

The solution connects five stages into a single pipeline:

• Clinical-grade discovery. Gluware leverages Claroty xDome as the source of truth for IoMT inventory, pulling in device details and the vulnerability relationships tied to each device rather than standing up a second inventory for hospitals to reconcile.

• Component-level vulnerability matching. CVEs are enriched against data from the MITRE CVE Program and matched against the specific components and configurations present on each device to reduce the false positives and false negatives that erode staff confidence in alerts.

• From advisory to applicable patch. Knowing a CVE exists does not tell a team what to install. Gluware’s integration with the Microsoft Update Catalog retrieves the specific Knowledge Base update for each supported platform and flags components that no longer receive manufacturer support, where a compensating control is the best available option.

• A shared operational record. A new IoT Device Manager gives clinical engineering and IT the same continuously updated view of the device fleet, closing a longstanding gap between two teams that use different tools and different vocabularies.

• Change-controlled execution. Gluware’s Network RPA and ServiceNow integration open a change ticket for every patch action, route it through the hospital’s existing approval process, and write the completed action back as a system of record.

Most of these stages already exist in a large hospital, spread across separate tools owned by separate teams. The delay accumulates in the handoffs between them: the export from one system into another, the cross-reference done by hand, the ticket opened manually and closed without a link back to the device it covered. Running the stages as one pipeline removes those handoffs, transforming the change record into a product of the work itself rather than something reconstructed afterward for an auditor.

Built from a customer requirement

The solution grew out of work with The Ohio State University Wexner Medical Center. The academic medical center was already running Gluware to automate its network and had built visibility into its IoMT fleet. However, remediation was still being coordinated by hand across teams and systems that were never designed to work together. These workflow constraints meant known vulnerabilities stayed open longer than anyone wanted.

Siji Atekoja, Deputy CIO and CTO, saw that the platform his teams already used to change the network safely could carry a medical device the rest of the way from a published CVE to a patch applied, approved, and on the record. Gluware and Ohio State built that path together by connecting the medical center’s existing device inventory to automated vulnerability matching, patch identification, and change-controlled execution. That work became Gluware IoMT Exposure Management.

The post Gluware Extends Its Automation Platform Beyond the Network to Connected Medical Devices appeared first on ITDigest.

Also Read: Philips Introduces Fast, Secure Diagnostic Viewer Online

“Our collaboration with Murata allows us to move closer to a future where patients receive more proactive, personalized care. By integrating advanced sensing technologies with our digital twin platform, we aim to enhance how chronic conditions are monitored and managed, enabling earlier intervention and better outcomes.” Reaffirming the shared strategic focus on data-driven interventions, Mehul Udani, Vice President of Corporate Technology and Innovation at Murata, added: “By combining advanced sensing technologies with CIPRA.ai’s digital twin platform, we have an opportunity to unlock new possibilities in personalized healthcare. We share a common vision of leveraging technology to transform sensor data into meaningful insights that can support earlier intervention, improve patient engagement, and ultimately contribute to better health outcomes.” In conclusion, the whole process of collaboration involves both the production of specific hardware and artificial intelligence technology to produce a scalable remote monitoring solution.

Read More: CIPRA.ai Collaborates with Murata to Advance the Future of AI-Powered Health Wearables

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What happens when the same devices keeping patients alive become the easiest way into a hospital network? That question now sits at the center of smart medical devices security. The conversation is no longer just about protecting data. It is about protecting care itself, and why hospitals need to rethink security before the next connected device goes online.

Why Smart Medical Device Security Matters More in 2026

For a long time, healthcare organizations measured cyber risk by one question. Was patient data exposed? That question still matters, but it is no longer enough. Connected medical devices have changed the stakes. A compromised infusion pump, bedside monitor or imaging scanner doesn’t just expose medical records to risk. It can break treatment, stall clinical decisions, and even produce complications that doctors cannot just undo by restoring some backup. In other words, it does more than you’d expect at first glance.

The bigger challenge is that these devices are no longer standalone machines. They constantly exchange information with Electronic Health Record (EHR) systems, imaging platforms, and other hospital applications. Microsoft points out that connected medical devices are now a kind of healthcare endpoint. That implies that one compromised infusion pump or imaging scanner can spill protected health information (PHI), lead to HIPAA penalties, stall care, and even open a route for attackers into the wider hospital network.

Unfortunately, the odds are slowly tipping toward the attacker. IBM’s 2026 X-Force Threat Intelligence Index said there was a 44% jump in how often public facing applications were exploited, and 56% of the disclosed vulnerabilities didn’t require any authentication. In a hospital setting these aren’t just cybersecurity stats. They’re more like warnings that an overlooked device you thought was minor, can turn into a first step for disturbing PACS, ICU systems, or that larger EHR ecosystem. By the time clinicians realize something is off, the incident has usually already hopped past that single device, like it moved on without asking.

Also Read: Data Privacy Regulations and Compliance Guide: How Enterprises Can Navigate Global Privacy Laws 

Key Regulatory and Compliance Standards Shaping Smart Medical Device Security in 2026

Security requirements for connected medical devices have become far stricter because regulators have learned one lesson the hard way. Fixing vulnerabilities after deployment costs far more than preventing them before a device reaches a hospital.

That thinking sits behind FDA Section 524B. Manufacturers are now expected to provide a Software Bill of Materials (SBOM), submit cybersecurity documentation before market approval, and show how vulnerabilities will be managed and patched throughout the supported life of the device. Buying a connected device without understanding how it will be maintained is becoming far harder to justify.

Europe is moving in the same direction, sort of, EU MDR, RED, and ETSI EN 303 645 all put even more focus on secure software, defended wireless communication, and product integrity. Hospitals buying devices across global markets can’t just assume that if it is compliant in one region, it will somehow carry over to the next, not anymore.

The responsibility does not end with manufacturers. HIPAA protects PHI, NIST SP 800-53 helps healthcare organizations apply practical security controls, while ISO 14971 treats risk management as an ongoing process through hazard identification, risk evaluation, risk control, and continuous monitoring across the device lifecycle.

Building a Robust Smart Medical Device Security Architecture

Most hospitals do not struggle because they lack security tools. They struggle because nobody has a complete picture of every connected device running across the network. Equipment sort of gets added bit by bit over time, meanwhile older systems stay in service longer than anyone expected, and then, those forgotten devices quietly turn into the weakest link. With passive discovery, helped by machine learning, you can dig up legacy operating systems, outdated firmware, and kind of unusual network behavior, all without interrupting the clinical workflows.

Finding devices is only the first step. The harder part is controlling what they can access. Zero Trust works on a simple principle. Trust nothing by default. Google Cloud recommends making access decisions using identity, device security posture, and context rather than network location alone. Pair that with micro-segmentation and each device talks only to the systems it genuinely needs.

That approach has already proved its value. Dayton Children’s manages around 25,000 connected devices. During the ransomware scanning, five MRI machines were isolated in under five minutes using Zero Trust segmentation, so the activity couldn’t really spread across the wider network.

Strong architecture also depends on people and process. Security alerts should flow directly to clinical engineering teams through CMMS so vulnerable devices can be inspected and patched quickly. Secure firmware, TLS 1.3, certificate pinning, and strong authentication then help ensure trusted devices remain trusted.

Smart Medical Device Security Implementation Checklist for Healthcare Leaders

Hospitals usually discover security gaps long before they discover sophisticated attackers. They find a forgotten monitor still running an old operating system, a medical device nobody remembers approving, or equipment that has not received a firmware update in years. That is why every security program starts with visibility. Build a complete inventory of clinical OT and IoMT devices before trying to secure them.

The next conversation should happen with vendors, not after some incident, but before one. So ask about how long security updates will be provided, how vulnerabilities will be disclosed, and if an SBOM is available. Honestly those answers matter almost as much as the device specs, maybe even more in practice.

After you understand the devices, don’t just shrug and trust what subnet they sit in. Instead, limit what they can do, and apply Zero Trust Network Access so every connection is verified, and every device talks only with systems it truly needs.

Security also needs routine practice. Review vulnerabilities regularly, score them by clinical impact rather than volume, and involve both IT and HTM teams in incident response exercises. The objective is not to build a perfect security program. It is to ensure the next security event remains a manageable incident instead of becoming a clinical emergency.

The Future of Connected Care Depends on Getting Security Right

Connected healthcare is only becoming more connected. More devices, more data, and more automation will continue to improve clinical outcomes, but they will also expand the attack surface. That is why smart medical devices security cannot remain a project owned by the IT department alone. It has to seep into how healthcare organizations buy, roll out, and run each connected device.

The real trouble is not picking between innovation and security. It’s making sure you can scale up without gradually weakening the other. Hospitals that see cybersecurity as an ongoing clinical duty, instead of just a compliance check, will be much more ready for what comes next. Ultimately the most resilient healthcare organizations won’t necessarily be the ones with the greatest pile of connected devices. They will be the ones that patients can continue to trust when those devices become the backbone of care.

The post Smart Medical Devices Security: How Healthcare Organizations Can Protect Connected Care in 2026 appeared first on ITDigest.

Ask Move AI launches with four capabilities available immediately on mobile: smart case creation by voice or text, case inventory lookup, case rescheduling, and invoice lookup. Together these capabilities give field reps a conversational interface for the full arc of their case workflow — from creation to inventory confirmation, scheduling, and billing without navigating screens or losing time to manual processes. Subsequent releases will continue to extend the range of Ask Move AI’s capabilities.

The intelligence layer is built on top of Movemedical’s deterministic core, which encompasses the validated, auditable, SOC 2, HIPAA, and HITRUST-certified platform that has run enterprise field operations for more than 15 years. That foundation does not change. The AI agent layer sits above it, drawing on the richest surgical case data in the category to execute case workflows and respond to rep queries conversationally, while every interaction is logged, audited, and authenticated by the platform. Customer data is not used to train the underlying models.

Also Read: Alcon and RxSight Announce Collaboration to Develop Adjustable PCIOLs

“The field inventory management category is at an inflection point,” said Mark Herrington, CEO of Movemedical. “Companies across MedTech are debating whether to build AI internally, buy a platform, or wait for the market to settle. We have spent nearly two decades building the data foundation, the compliance infrastructure, and the domain expertise that any meaningful AI capability in this space requires. What we’re launching today is the first expression of that investment and it’s only the beginning.”

Movemedical’s AI capabilities are the first deliverables on their agentic roadmap that extends across the full field inventory lifecycle. Movemedical is planning a regular agentic AI release cadence that will optimize every major workflow in medical device inventory management. Near-term additions to the AI assistant include On-Demand Data Insights for plain-language operational queries, Streamlined Usage Capture for automated post-case reconciliation, and expanded case management capabilities. Looking further ahead, consignment optimization, demand forecasting, and inventory rebalancing are among the agentic capabilities on the roadmap.

“We built toward the highest-impact friction points first,” said Vito Salvaggio, Chief Product Officer at Movemedical. “Every rep who creates a case, confirms what is on it, checks a billing detail, or needs to move a date without losing their place in the day – these are the users we designed for. The AI assistant we are releasing today addresses where we know field reps will see immediate benefit, and the roadmap behind it is built to compound that advantage with every release.”

Source: PRNewswire

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Under the collaboration, the companies will be innovating on their respective platforms RxSight’s post-operative light-adjustable technology and Alcon’s PCIOL optical designs — and combining them to create a co-developed technology that enables surgeons to fine-tune visual outcomes for their cataract patients who choose a PCIOL.

“Our leading PCIOLs have helped millions of patients reduce or eliminate the need for glasses after cataract surgery,” said David J. Endicott, Chief Executive Officer of Alcon. “Together with RxSight’s technology, we have the opportunity to develop tunable PCIOLs, giving surgeons even greater confidence to refine outcomes after surgery.”

“We are excited to work with Alcon to provide patients greater access to outcomes customized to their needs after surgery,” said Ron Kurtz, President and Chief Executive Officer of RxSight. “This collaboration underscores our belief in the importance of adjustability and will help accelerate its expansion across a wider base of patients.”

As part of the agreement, RxSight will receive a $60 million upfront payment to begin development. RxSight could receive up to an additional $140 million in payments as development and regulatory milestones are met. Under the agreement, Alcon will lead global commercialization, while RxSight will be responsible for development and manufacturing and receive royalties on net sales.

Source: BusinessWire

The post Alcon and RxSight Announce Collaboration to Develop Adjustable PCIOLs appeared first on ITDigest.

The World Health Organization says there are nearly 2 million different kinds of medical devices on the global market across more than 7,000 generic device groups. That number alone explains why security challenges for smart medical devices in hospitals are no longer a niche IT concern. The scale has already outgrown traditional security models.

Most hospitals still approach cybersecurity like an outer wall problem. Build stronger perimeters. Add more monitoring tools. Hope attackers stay outside. Meanwhile, the real risk is already sitting inside the network through unmanaged devices, outdated firmware, and invisible connected systems that quietly expand cyber exposure every year.

The Operational Reality Behind Smart Medical Device Security Risks

Most connected medical devices were never designed for the threat environment hospitals face today. They were designed to deliver clinical outcomes first. Security came later. In some cases, it barely arrived at all.

That becomes a major problem since hospitals don’t really refresh medical infrastructure in the same way enterprises refresh laptops or cloud systems. A patient monitor, imaging scanner, or infusion pump can still work, for 10 to 15 years, and during that lifespan operating systems kind of age, firmware support weakens, patch cycles turn painfully slow. Also, some devices simply cannot be patched, without creating disruption to clinical certification or breaking vendor warranties.

The result is a strange contradiction. Hospitals now run highly advanced digital environments on top of aging medical infrastructure that was never built for continuous cyber conflict.

Visibility makes the situation worse. Security teams often do not have a complete inventory of connected devices operating across clinical networks. One department may deploy new monitoring equipment without informing central IT. Another may connect third-party diagnostic systems directly into hospital infrastructure. This creates what many security teams now describe as shadow IoMT. Devices exist on the network, exchange sensitive data, and interact with critical systems, yet nobody fully tracks their behavior.

That is where security challenges for smart medical devices in hospitals become operational instead of theoretical.

A compromised vitals monitor is not just another endpoint. It can become an access bridge into clinical systems, scheduling platforms, or electronic health record environments. Microsoft recently warned that connected healthcare devices such as infusion pumps, imaging scanners, and patient monitors can become entry points when endpoints are not properly secured. That changes the conversation completely because hospitals are no longer protecting only data centers. They are protecting thousands of connected physical devices spread across wards, labs, emergency rooms, and operating theaters.

Meanwhile, proprietary communication protocols continue to complicate defense strategies. Many medical devices use non-standard traffic patterns that traditional IT security tools struggle to inspect properly. Security teams often hesitate to segment or restrict these devices aggressively because clinical operations cannot tolerate downtime or connectivity interruptions. That hesitation creates blind spots attackers increasingly understand how to exploit.

The uncomfortable truth is simple. Healthcare organizations are trying to secure modern connected ecosystems using security assumptions built for a far less connected era.

Why Cybersecurity Failures Are Becoming Patient Safety Events

For years, healthcare cybersecurity discussions focused mainly on data theft. Patient records. Insurance data. Compliance fines. That framing now feels outdated.

A ransomware attack inside a hospital no longer stops at encrypted files. It can disrupt care delivery itself.

If a compromised infusion pump delays treatment, that becomes a clinical problem. If imaging systems go offline during emergency care, that becomes an operational problem. If hospital staff lose access to patient histories during a cyber-incident, that becomes a patient safety problem.

This shift matters because attackers are changing tactics too.

Google Cloud’s M-Trends 2026 report found a global median dwell time of 14 days, while exploits accounted for 32% of intrusions. More importantly, the report identified a growing shift toward recovery-denial tactics. That phrase deserves attention because it explains where modern healthcare cyberattacks are heading.

Attackers are no longer satisfied with stealing data. Increasingly, they want to disrupt recovery itself. They want hospitals locked out of systems, unable to restore operations quickly, and trapped inside prolonged service disruption cycles.

That pressure hits healthcare harder than almost any other sector because hospitals cannot simply pause operations for three days while infrastructure teams investigate malware. Clinical environments operate continuously. Emergency care does not wait for incident response meetings.

The financial consequences are severe too, although the operational consequences are even worse. IBM says the average healthcare breach cost reached USD 7.42 million in 2025, marking the highest breach cost across industries for the 14th consecutive year. Yet the real damage often extends beyond the balance sheet. Downtime erodes trust. Delayed procedures damage patient confidence. Repeated disruptions weaken the reliability hospitals depend on every day.

Cybersecurity in healthcare has quietly crossed into resilience engineering. That changes how leaders need to think about investment, governance, and risk ownership.

Why Regulatory Pressure Is Finally Catching Up

Regulators have started recognizing that connected healthcare systems cannot operate under outdated security assumptions forever.

That is why the FDA’s recent push around Predetermined Change Control Plans matters far more than many hospitals realize. AI-enabled medical devices now evolve after deployment through software updates, algorithm refinements, and performance adjustments. Traditional approval cycles were not built for systems that continue changing after entering clinical environments.

The FDA’s evolving approach signals something bigger underneath the surface. Security can no longer be treated as a one-time compliance checkbox completed during procurement. It has become part of the device lifecycle itself.

At the same time, NIST CSF 2.0 pushes organizations toward a more operational understanding of cyber resilience. The framework sounds straightforward on paper. Identify. Protect. Detect. Respond. Recover. Yet healthcare environments struggle because each layer intersects directly with patient care workflows.

Identifying assets sounds easy until a hospital realizes hundreds of unmanaged devices operate across multiple departments. Protecting systems sounds logical until aggressive segmentation risks disrupting clinical access. Detecting abnormal behavior becomes harder when proprietary medical protocols generate unusual traffic by default.

That tension is exactly why security challenges for smart medical devices in hospitals cannot be solved through compliance documents alone. Hospitals need security models that understand clinical realities instead of fighting against them.

The real shift happening now is philosophical. Cybersecurity is slowly moving from the IT department into enterprise risk management and operational governance.

That shift was overdue.

Also Read: Guide to Implementing Zero Trust Security Architecture: A Step-by-Step Framework for Modern Enterprises

How Healthcare Providers Can Actually Reduce Cyber Risk

Most hospitals do not need more cybersecurity slogans. They need architecture changes.

Zero Trust is one of the few approaches that genuinely fits modern hospital environments because it assumes compromise will happen somewhere inside the network. Instead of trusting connected devices automatically, Zero Trust limits how far an attacker can move after gaining access.

That matters enormously in healthcare. A compromised vitals monitor should never have unrestricted visibility into EHR databases or pharmacy systems. Micro-segmentation helps contain damage before attackers move laterally across clinical infrastructure.

At the same time, hospitals need to pressure vendors harder on transparency. Medical devices increasingly rely on layered software components, third-party libraries, and external dependencies that hospitals rarely see clearly. This is where Software Bills of Materials become critical.

An SBOM functions like an ingredient label for medical software. It tells healthcare organizations what components exist inside a device environment and whether vulnerable dependencies are present. Without that visibility, hospitals operate blind during vulnerability response cycles.

Continuous monitoring matters just as much, maybe even more. Annual security audits no longer really capture the tempo of modern cyber threats, because threat actors tend to move faster than traditional compliance schedules. So hospitals should switch toward real-time traffic observation, behavioral analytics and continuous weakness management rather than doing periodic checkbox assessments.

Recovery planning also deserves far more attention than it currently gets. Many organizations still spend heavily on prevention while underinvesting in operational recovery capabilities. That imbalance becomes dangerous during ransomware events.

AWS recently emphasized that healthcare organizations must strengthen their ability to prepare, respond, and recover quickly inside highly regulated environments. That sounds obvious until hospitals discover their backup environments, recovery workflows, or clinical restoration plans were never realistically tested under attack conditions.

Cyber resilience in healthcare is no longer about preventing every breach. That goal is unrealistic. The real objective is containing disruption before patient care absorbs the impact.

Future-Proofing Healthcare Means Securing Trust First

Healthcare keeps moving toward deeper connectivity because the clinical advantages are too significant to ignore. Remote monitoring improves care continuity. Smart diagnostics improve speed. Connected systems improve coordination across hospitals. None of that is slowing down.

The problem is that hospitals still buy many connected devices as medical assets first and cyber assets second. That thinking no longer works.

Security challenges for smart medical devices in hospitals are now tied directly to operational resilience, patient safety, and institutional trust. A hospital can survive a delayed software rollout. It cannot survive repeated failures in clinical reliability.

That is why cybersecurity must move upstream into procurement, architecture planning, vendor evaluation, and executive governance. Not after deployment. Not after a ransomware incident. Before all of it.

Patient trust remains the real infrastructure underneath healthcare. Every connected device either strengthens that trust quietly or weakens it silently. The hospitals that understand this early will not just become more secure. They will become more resilient when the next wave of healthcare cyber disruption arrives.

The post Security Challenges for Smart Medical Devices in Hospitals: How Healthcare Providers Can Reduce Cyber Risk appeared first on ITDigest.

Designed for complex coronary interventions, the Cora Torqueable Microcatheters introduce enhancements focused on spinning freedom and torque transmission, supporting controlled navigation and lesion crossing in challenging anatomies.

The updated microcatheters incorporate refinements to hub design, shaft construction, and distal profile to improve handling, pushability, and trackability.

The Cora Flex Torqueable Microcatheter is designed to support navigation in tortuous vessels, septals, and microchannels, while the Cora Force Torqueable Microcatheter, featuring a metal tip, is engineered to provide additional pushability and tip force in more resistant, calcified, and fibrotic lesions.

The devices are built on Cora Tech, a proprietary construction featuring a no-liner design with PTFE-coated coils to enable unrestricted torque rotation, combined with a stainless-steel braid intended to support controlled torque transmission and catheter stability. In addition to spinning freedom, the predictable torque transmission offers precise control, especially when navigating tortuous vessels.

Also Read: Aptar Digital Health Partners with Enable Injections for enFuse® Companion Digital Solution

“The new Cora Torqueable Microcatheters are truly next-generation devices that will become a standard in my daily practice,” said Garrett B. Wong, MD, FACC, FSCAI, Clinical Professor of Medicine at the UC Davis Medical Center, Sacramento, California. “Both versions deliver outstanding performance, especially spinning freedom. I can rotate the catheter without the risk of guidewire lock-up, which is a major benefit when crossing challenging anatomies.”

Dr. Wong was among the physicians who provided real-world procedural feedback during the iterative development of the Cora Torqueable Microcatheters.

“From an engineering perspective, we focused on optimizing rotational behavior, torque transmission, and overall handling characteristics,” said Outhit Bouasaysy, Vice President of Engineering at Reflow Medical. “These enhancements reflect direct physician input and our targeted approach to building endovascular solutions to advance the treatment of challenging coronary lesions.”

“The U.S. launch of the next-generation Cora platform represents an important step in expanding our coronary portfolio to support patients with coronary artery disease,” said Dejan Ilic, Vice President, Global Marketing at Reflow Medical.

Reflow Medical has recently expanded its presence in the coronary segment, including the presentation of first-in-human data from the DEEPER CORONARY study, evaluating the Spur^® Elute Coronary Sirolimus-Eluting Retrievable Stent System for the treatment of coronary in-stent restenosis.

Source: BusinessWire

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“The industry is in an arms race where a state-of-the-art model or point solution is outdated in weeks,” said Khan Siddiqui, MD, co-founder and CEO of HOPPR. “What matters is flexible, underlying infrastructure that teams can adapt to their specific environment. This model is built with flexibility in mind: it’s a component that organizations can shape to their workflows and data with the traceability and validation behind it to support responsible deployment.”

Core capabilities:

• Narrative Language Generation: Translates chest X-ray images into descriptive, structured language that can be adapted for use within radiology reporting workflows.
• Chest Radiography Image Input: Processes standard chest X-rays, including frontal and lateral views, and interprets visual patterns to generate corresponding text.
• Broad Coverage: Trained on a large set of chest X-ray reports and evaluated across a wide range of common patterns, with sampling designed to reflect diverse conditions and variability seen in real-world data.
• Training Data Traceability: HOPPR maintains records of training data to support transparency, traceability, and downstream evaluation by developers.
• Performance: The model has been evaluated against internal benchmarks and demonstrates strong performance with the flexibility to be further fine-tuned to align with the developer’s final application.
• Version Control: Allows teams to lock model versions, ensuring consistency and reproducibility across development and deployment.

Also Read: BD Launches a Drug Dispensing System with Artificial Intelligence in the European Market

The model is designed for organizations developing AI-powered radiology capabilities and is deployed with support from HOPPR Forward Deployed Services (FDS). This approach allows organizations to evaluate and adapt the model to their specific use cases, workflows, and data environments, helping ensure alignment with real-world operational needs. FDS works closely with partners to evaluate and implement the model, supporting initial applications across workflow augmentation, training, and research.

“We just gave medical images a voice,” said Roger Boodoo, MD, Medical Director of AI at HOPPR and practicing radiologist. “For over a decade, AI gave us a second set of eyes but left us to do all the talking. By providing models that enable developers to build applications that translate images into natural language workflows, we’re reducing AI friction and giving radiologists their time back.”

Source: PRNewswire

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Through this partnership, Aptar Digital Health will deliver a companion digital solution for Enable Injections’ enFuse^® system, designed to enhance the patient experience and support adherence. Key features of the solution will include treatment data recording, onboarding and training modules, injection guidance, patient-reported outcomes and symptom tracking – helping to empower patients and caregivers with greater confidence and control over the treatment process.

Built on a flexible and scalable architecture, the companion solution will be deployed alongside the enFuse^® system, enabling pharmaceutical partners to extend the value of their therapies beyond delivery. Designed to evolve across the drug development lifecycle, the solution will support use cases from clinical trials through commercialization, aligned with development and launch strategies.

Also Read: BD Launches a Drug Dispensing System with Artificial Intelligence in the European Market

Adherence data and patient reported outcomes will be captured remotely, securely stored and made available through analytics dashboards that generate actionable insights to support clinical development, launch readiness and real-world use. The modular, program-specific design will allow pharmaceutical partners to integrate digital components into their clinical or commercial programs based on their needs. By combining device-generated data with patient reported insights, the solution will help drive more informed decisions grounded in real-world usage.

“The enFuse^® companion solution reflects our vision of a more connected treatment experience that supports patients beyond the moment of injection,” said Michael D. Hooven, Chairman and CEO of Enable Injections. “Together with Aptar Digital Health, we aim to combine innovative drug delivery with digital support tools that can help patients remain engaged in their therapy and enable healthcare providers to better understand and support each patient’s journey.”

“We are excited to partner with Enable Injections to help bring the next generation of drug delivery solutions to life,” said Damien McKeon, SVP Strategic Partnerships, Aptar Digital Health. “Large-volume biologic therapies are increasingly used to treat complex chronic conditions. They often require long-term adherence to achieve optimal outcomes. Digital solutions supporting treatment tracking and patient engagement can help address common adherence challenges associated with self-administration.”

Source: GlobeNewswire

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, a leading global medical technology company, announced the European launch of the BD® Pyxis Pro dispensing solution and the BD® Incada connected care platform. This next-generation medication dispensing system combines advanced automation and artificial intelligence to modernize medication management, reduce disruptions, and improve efficiency, enabling healthcare professionals to spend more time on patient care.

Fast and reliable access to medications at the point of care is essential for effective healthcare, and BD is committed to providing secure and traceable storage as close to the patient as possible. The flexible, stackable configuration of the Pyxis Pro dispenser offers increased medication storage capacity in a similar footprint, improving availability from refrigerated to ambient temperature storage. This allows hospitals and healthcare systems to easily adapt to their patients’ evolving needs. Furthermore, it offers enhanced security features to optimize controlled substance management and more efficient access, with RFID card scanning, wireless barcode scanners, and illuminated trays for easy medication retrieval.

Following its established use in the United States, BD will also extend its AI-powered BD Incada Analytics platform to European hospitals and healthcare systems next year.

Also Read: RQM+ Launches SMART Solutions Life Cycle Partnership Model

Built on Amazon Web Services’ (AWS) on-demand cloud computing infrastructure, the BD Incada platform utilizes the latest AI technologies, such as natural language search for data analysis, and is scalable to handle the volume of data generated by nearly three million smart, connected BD devices. With BD Incada Analytics, healthcare professionals gain access to a comprehensive view of their medication inventory and customizable dashboards, helping them identify patterns, ensure medication availability, reduce waste, and improve work efficiency.

In the European market, BD will leverage AWS’s sovereign European cloud to enable EU healthcare systems to meet their digital sovereignty needs, without compromising the performance, innovation, security, or scalability of the AWS cloud and BD solutions.

“BD’s innovations in medication management are setting a new standard for unified, data-driven healthcare operations,” said Esteban Rossi, Vice President and General Manager of Medication Management Solutions for EMEA at BD. “By offering the BD® Pyxis Pro dispensing solution and the BD® Incada platform directly to European hospitals, our customers can strengthen medication availability, improve efficiency, and optimize patient care.”

Source: PRNewswire

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