July 3, 2025

Medical Device Software Development: Innovations and Best Practices

Anna Rozhentsova

Content Writer

Healthcare

medical device software development

Anna Rozhentsova

Content Writer

Healthcare

medical device software development

Software development for medical devices is the core of healthcare. They become more portable, accessible, and smarter, ensuring functionality, accuracy, and patient safety, as technologies evolve. Yet, whatever smart these machines become, they still require deep expertise from developers. Evolving technologies, safety standards, and regulatory compliance are the pieces that cannot be thrown from the puzzle.

In this article, we delve into the intricacies of what medical devices are, how they are built, and what essential things to keep in mind.

Key takeaways

  1. Medical device software development is not a new industry, yet it's begun evolving at a greater pace in the recent 20 years with the rise of advanced technologies. It opens up possibilities for improving healthcare in a range of directions, from patients to medical and R&D institutions and medical device manufacturers.  
  1. Broadly speaking, all medical devices can be divided into Software in Medical Device (SiMD), or embedded software, and Software as a Medical Device (SaMD). Each type has its area of application, development, and safety requirements.

  2. Although the market of software development for medical devices is growing, challenges still remain in implementation. Requirements, security issues, and a competitive market are but a few intricacies any developer should be aware of.

What is medical device software?


The U.S. Food and Drug Administration (FDA) uses the term 'medical device' for any devices 'intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease, in man or other animals'. In a nutshell, it is the software applied for diagnosis, treatment, patient monitoring, and healthcare management. It may come as standalone solutions such as apps or be embedded within medical devices.

Medical device software development is not a new field. The earliest medical devices with embedded software date back to the 1960s and 1970s when computer technology was first integrated into healthcare. Early medical devices like pacemakers or infusion pumps used basic software to control functions and process data. 

Further advancements in microprocessors and digital imaging led to the appearance of robotic-assisted surgery, MRI, and computerized diagnostic tools. In the 2000–2010s, the rise of the internet, AI tech, and cloud computing made software for medical devices even more sophisticated, which continues up to the present day.

Types of medical device software


Software for medical devices can be broadly divided into two main groups, according to the platform om which they run: Software in Medical Device (SiMD), or embedded software, and Software as a Medical Device (SaMD).

types of medical software


Software in a medical device (SiMD)


SiMD are software solutions integrated or synchronized with medical hardware and cannot function separately (for this reason, they are often called 'embedded software'). Yet, they help control and improve performance and functionality of various physical devices, like:

  • electronic thermometers 
  • glucometers
  • pulse oximeters 
  • electronic blood pressure sensors
  • smart sensors
  • defibrillators
  • medical imaging equipment
  • lab equipment

Software as a Medical Device (SaMD)

Software as a medical device is one of the fastest-growing areas within the MedTech sector. There are projections for the market size to reach $8.2 billion and for a CAGR of 11.0% by 2027. Typically, SaMD is not considered part of healthcare equipment and runs on computer platforms that are not necessarily used for medical purposes. It doesn't fulfill the equipment's functions or tasks, but can interact with the interface of certain devices or can be used in combination with their embedded components.

SaMD is used for several aspects:

  • data visualization and representation (e.g., creating 3D imaging for more precise diagnostics)
  • data management and storage (e.g., collecting patient's sleep data in real time to prevent sleep apnea)
  • data processing and interpretation (e.g., processing images to help detect breast cancer).

Benefits of developing medical device software


Advanced tech solutions are reshaping healthcare providers’s approach to day-to-day operations and their efficiency. Further, we break down the key benefits that stakeholders gain from integrating software into medical devices.

benefits of medical device software

Enhanced accuracy

Fewer mistakes and better patient outcomes are the results any healthcare provider strives for. AI imaging software can detect anomalies with higher precision than the human eye. Automated processes and built-in decision support systems also make diagnostics and treatments more accurate. Thus, healthcare providers are able to make informed choices, and the amount of human errors reduces drastically.

More examples:

  • Pharmaceutical companies are better empowered with information about their medications' effects, when ineffective treatments and false prescriptions are excluded.
  • Healthcare providers diagnose patients more precisely and offer them appropriate treatment plans. 
  • Research and development labs gain access to precise data that supports the development of new technologies and therapies.

Real-time monitoring

Wearables, smart implants, and connected monitoring systems ensure continuous monitoring of patient data. If abnormal patterns appear, these devices can detect them, send alerts to healthcare providers, who, in turn, ensure timely support for the patients.

More examples:

  • HealthTech startups can explore new business opportunities by developing monitoring solutions.
  • Healthcare institutions and hospitals that conduct continuous monitoring of patients with chronic diseases (e.g., heart conditions, diabetes) cut costs on hospital admissions and free up resources for critical care patients.
  • Clinical Research Organizations (CROs) use monitoring results to improve the accuracy of clinical trials.

Streamlined workflows

Processes that can be automated should be automated, which is especially true for the healthcare industry. Implementing software in a medical device makes the workflow smooth and efficient: it improves data exchange among healthcare providers and eliminates redundant paperwork. As professionals are more focused on patient care rather than bureaucracy, costs are reduced. Needless to say that in healthcare, saving time often means saving lives.

More examples:

  • Biotechnology companies can accelerate research and development with seamless access to health data.
  • Regulatory compliance consultants benefit from simplified audit processes, as well-structured software ensures data security and compliance with regulations.

Personalization

When empowered with AI and ML tools, software development for medical devices transform how care is delivered. These technologies analyze a patient’s real-time and medical history, to identify trends, predict risks, and recommend personalized treatment options. Such a tailored approach commonly results in better treatment outcomes.

  • Pharmaceutical companies profit from personalized medicine, as prescriptions are more accurate and patients experience fewer side effects.
  • Research and development labs refine their treatment algorithms and explore new therapeutic approaches thanks to access to large datasets.

Competitive edge

Firstly, creating custom medical device software that can be smoothly integrated with other platforms can extend their product line. Offering devices with built-in software increases product value.

Secondly, it opens up opportunities to explore new markets and proven sources of revenue, like maintenance contracts or licensing.

More examples:

  • Companies specializing in healthcare compliance solutions can offer guidance on software certification.
  • HealthTech startups can offer subscription-based models to generate recurring revenue streams from selling software.

Enhanced access and integration

Medical device software improves interoperability between healthcare systems and expands remote healthcare access. Thus, patients in remote or underserved areas who cannot visit in person get virtual consultations and monitoring through telemedicine and mobile solutions.

  • Healthcare providers use integrated electronic health record (EHR) systems to avoid redundant tests and improve care coordination.
  • Biotechnology companies conduct advanced research thanks to improved data sharing. 
  • Clinical Research Organizations (CROs) benefit from integration with medical software, as it simplifies clinical trial management and improves data reliability

Standards for building medical device software


Virtually all medical devices, whether embedded or standalone, are used while being connected to the internet, local networks, or hospital systems. This connectivity inevitably opens up vulnerability to ransomware, data breaches, and remote control of devices, both for devices and sensitive patient data. For this reason, cybersecurity is a non-negotiable priority for designing medical devices and should be regulated. Here are the key frameworks that developers should consider.

International standards

Each market has unique compliance requirements that impact how health data is handled, secured, and shared. Navigating cybersecurity and data protection in medical software development requires a deep understanding of these regional standards.

IEC 62304 standard for medical devices

This is the main globally recognized standard setting the framework for developing both SiMD and SaMD, with:

Additionally, it establishes a safety classification system for medical software (the higher the level, the more safety measures are required): 

  • Class A: No possibility of injury or damage to the patient (bandages, non-invasive instruments).
  • Class B: Potential for injury, but not severe (contact lenses).
  • Class C: Potential for severe harm or death (heart valves, implants)

Other International standards crucial for designing medical device software are:

  • ISO 14971 standard on risk management
  • ISO 13485, or Quality Management System (QMS)
  • ISO 60601-1 standard for medical electrical equipment (for SiMD)
  • ISO 82304-1 standard for product safety (applied for SaMD).

One more standard to keep in mind is the International IMDRF Guide on Cybersecurity of Medical Devices. This document aims to promote a globally accepted approach to cybersecurity in healthcare. It focuses on security principles and best practices implemented throughout all stages of the product life cycle, including design, development, testing, post-market monitoring activities, and the End of Support (EoS).

Standards for cybersecurity and health data protection

HIPPAA for the US and GPPR for the EU are the most well-known, but not the only standards for protecting personal patient data. Also, when you launch a product in international markets, consider that guidelines vary by location.

international standards for patient data protection


US

For the US, cybersecurity regulations for Software as a Medical Device are available in the Guidance issued by the FDA (Food and Drug Administration). This document prioritizes security by design, transparency, and risk management throughout their entire life cycle of a medical device.

HITECH Act (short for Health Information Technology for Economic and Clinical Health Act) is an extension of HIPAA, or Health Insurance Portability and Accountability Act. It encourages healthcare providers to adopt electronic health records (EHRs), improve standards for their interoperability, and implement security measures for electronic patient data, as well as give patients access to this information. Also, it promotes research and development in the field of health information technology (HIT).

EU

In the EU, cybersecurity measures for designing medical devices should adhere to the European Medical Devices Regulation (EU) 2017/745 (MDR) and In Vitro Diagnostics Regulation (EU) 2017/746 (IVDR). These two legislation documents consider all steps of software development and maintenance involved in risk management and cybersecurity.

Other important regulations include the NIS Directive (or Directive 2016/1148 of the European Parliament and of the Council of 6 July 2016), which focuses on legal measures for the security of network and information systems across the EU, and GDPR, which deals with the protection and transfer of personal information.

UK

In the UK, security for medical software devices is protected by the NIS Regulation 2018 (UK). It provides legal measures for improving security of networks and information systems. The UK version of GDPR (The Data Protection Act 2018) sets the guidelines for the processing and transfer of sensitive personal data in the UK.

Additionally, on January 9, 2024, the UK Medicines and Healthcare Regulatory Agency (MHRA) proposed a roadmap for the regulation of medical software devices, with the focus on patient safety and transformative technologies including AI, implantable devices, and early disease diagnostics.

Canada

While in the US, the FDA Guidance includes regulations for food, drugs, cosmetics, and devices, which also apply in Canada, the latter uses a specific regulation for medical devices, known as the Medical Devices Regulations (SOR/98-282), or CMDR, for short.

One more peculiarity: in Canada, healthcare devices are categorized into four classes based on their risk level, from low to highest. Consider this if you want to launch your product in the Canadian market.

PIPEDA, or Personal Information Protection and Electronic Documents Act, regulates how organizations deal with personal information during commercial activities. First, under this law, organizations must only collect, use, and disclose personal information when it is necessary for their stated purposes. Second, an individual's consent to use data is obligatory. And third, when using it, organizations must ensure that the information is complete, accurate, and up-to-date.

Australia

Similar to the FDA in the United States, Australia has its own Therapeutic Goods Administration (TGA) which regulates the production and use of therapeutic goods, such as prescription medicines, medical devices, and diagnostic tests. In 1989, it introduced the Therapeutic Goods Act, obliging manufacturers to work safely and maintain the required ethical standards for medical products.

The Australian analog of HIPAA and GDPR, the Privacy Act of 1988, protects personal information and regulates its use by third-party organizations.

Staying up to date with evolving international regulations not only ensures legal compliance and security of medical devices. It also builds trust with your users.

Software design for medical devices: 7 main steps


While building devices for healthcare, a standard Software Development Lifecycle (SDLC) gains specifics. The nuances are mostly caused by the increased need for data security, rigorous testing, and adherence to regulatory compliance. Here are the phases developers should follow.

Software Development Lifecycle for medical devices

1. Requirements gathering phase

Begin with gathering detailed requirements and inputs from healthcare professionals, patients, and other stakeholders. Understanding the patients’ medical issues and peculiarities of the providers’ workflow, the software aims to solve is crucial.

Cybersecurity, data protection, and compliance considerations should be considered already at this stage. For example, if you develop remote patient monitoring software, think of how it will securely transmit real-time data and how it will be integrated with hospital systems.

2. Risk analysis phase

Then, ensure to identify potential risks to patients and users, such as software malfunctions, cybersecurity vulnerabilities, and human errors. Refer to the international safety standards we described above and consider the legislation acts specific for the local market you want to work with.

3. Design and prototyping phase

Designing software that is both intuitive, accessible, and safe cannot go without prototypes. At this step, try to test the minimal functionality and receive as much feedback as possible. For instance, if you're working on AI-assisted diagnostic software, early prototypes will help you test the accuracy before full deployment.

After prototyping, it's advisable to run a minimum viable product. Cooperate with stakeholders to gather background data about industry best practices and incorporate it into your pilot product. Test the user experience and analyze what features and interfaces that may be lacking.

This will leave with a data-informed software development plan, which is the next step. Also, you'll gain a better understanding of whether you need more resources and skills to deploy the product.

4. Development and integration phase

Medical software can be developed in-house, if you have the necessary skill set, or in partnership with a seasoned vendor.

At this stage, developers code, integrate UI/UX design, and conduct quality assurance testing. This is the perfect time to collaborate with regulatory consultants, before the software is applied for commercial use.

Still, developing the software is only half the journey. Integrating it into existing healthcare ecosystems is often more complex. Devices must seamlessly interact with EHR systems, PACS for imaging, or lab systems, depending on the context. For instance, if your product is an AI-powered radiology tool, it must integrate with DICOM standards, support HL7 messaging, and be usable within existing radiologist workflows in all hospital radiology departments.

Failing to plan for smooth software integrations can cause delays, resistance from clinical staff, and costly rework.

5. Testing and validation phase

The step you should never skip is rigorous testing of the functionality, usability, and safety backed by compliance with medical regulations, especially IEC 62304 and data protection acts.

To validate that your medical device software meets all the requirements, it's advisable to conduct clinical trials and research studies.

6. Regulatory compliance phase

After testing and before market release, you are supposed to apply for regulatory approvals of the medical software. Keep in mind that submission and approval are a time-consuming process: it requires preparing extensive documentation, submitting the software, and finally receiving a response from the regulating body (FDA in the USA, MDR in Europe, MHRA in the UK, etc). 

Regulations may be more or less strict, depending on the software you deployed. For example, software for wearables must undergo stringent validation, while fitness apps still need validation. However, in most cases, they are mostly about adhering to GDPR requirements.

7. Maintenance and updates phase

Once all the previous steps are completed, the work is far from over. Medical devices are often in use for 10–15 years, or even more. This long lifecycle introduces a major challenge: operating systems may end up running on outdated operating systems. For instance, an infusion pump running on Windows 7 or 8 instead of the latest versions, may no longer receive updates and security patches, and starts accumulating bugs. Over time, vulnerabilities can put patient data at risk.

You can mitigate such problems and further complaints from the clients by proactive lifecycle planning. For instance, continuous monitoring, modular architecture, and remote update capabilities will detect and prevent potential issues with security early on.

It's also important to integrate new technologies that enhance functionality and efficiency of medical devices. Further we're going to elaborate on the tech stack you might need.

Tech stack for custom medical device software


The range of medical devices is diverse, and the choice of programming languages, tools, and frameworks depends on the functionality of the software. Whether it's embedded, runs on a desktop in a hospital, or supports mobile health applications, your set will differ.

Below is a breakdown of the most commonly used tech stack in medical device apps, along with its real-world applications.


Programming languages used in medical devices

Language When used
Embedded C Works best for embedded software in medical devices, like pacemakers and infusion pumps. Ensures precise hardware control and regulatory compliance during certification.
C# Commonly applied for developing Software as a Medical Device (SaMD) that operates on healthcare professionals' desktops and integrates with hospital management systems.
Java Widely used for clinical decision support systems, electronic health records (EHR), hospital management systems, and server-side applications due to its reliability and cross-platform capabilities
Swift Go-to language for developing robust, secure, andresponsive medical device apps on iOS and macOS, with tracking features and for seamless Apple device integration in telemedicine solutions.
Python Often preferred for AI- and ML-driven medical applications for diagnostics (for instance, imaging software) thanks to extensive libraries.
MatLab Frequently used for medical image processing and data analysis, such as MRI or CT scan interpretation, due to robust computational capabilities.


Tools used in software development for medical devices

Tools When used
Compilers Convert high-level code into machine code to ensure compatibility with medical hardware.
Example: compiler for embedded medical device firmware development.
Emulators Allow developers to simulate real-world use cases and test devices before deployment.
Example: Testing software for ventilators using hardware emulation before clinical trials.
Front-end development tools Used for building user-friendly interfaces for web-based healthcare applications.
Example: A patient portal dashboard with medical history and test results in a hospital system.
Cloud Services (AWS, Azure, Google Cloud) Provide scalable storage, processing, and synchronization of data in the cloud for medical applications, telemedicine, and patient monitoring systems.
Example: Cloud-based AI platforms analyzing electrocardiogram data in real time.
Middleware and AI modules Enhance medical devices with capabilities like 3D imaging, AR/VR, and AI-powered diagnostics.
Example: AI-assisted robotic surgery systems integrate middleware for decision support in real time.
Testing software Used in the testing stage to ensure that the custom medical device software functions correctly and meets safety and regulatory standards.
Example: LDRA Test Suite ensures code quality and cybersecurity in compliance with FDA, IEC 62304, and ISO 14971.

Choosing the right tech stack ensures your medical device software is not only functional but also secure and scalable.

Challenges in developing medical device software


When building medical devices, developers often face unique challenges, from regulatory compliance to interoperability and pricing pressure. Here's an overview of key challenges and how software developers can effectively overcome them to create reliable solutions.

1. Adherence to regulatory compliance

We have already mentioned the requirements and standards that manufacturers need to follow. Failing to meet these standards can lead to product recalls or market rejection.

How you can face the challenge:

  • Work with regulatory experts or software vendors specializing in developing medical software that ensures healthcare software compliance early in the development process to avoid costly revisions later.
  • Use traceability tools like codeBeamer or DOORS Next to document all decisions throughout the project and link them to regulatory requirements.

2. Security and privacy of data

It is still one of the primary concerns and challenges in software development for medical devices. According to the report, healthcare accounted for 23% of all data breaches, overtaking finance (22%) in 2024.

How you can face the challenge:

3. Interoperability with medical systems

Medical software communicates with EHR systems, imaging systems, and connected devices via Wi-Fi, Bluetooth, and custom protocols. Yet, challenges may arise, especially if the software originates from different vendors or platforms.

How you can face the challenge:

  • Use APIs and middleware solutions to bridge gaps between systems.
  • Follow standardized protocols like HL7 (Health Level 7) for EHR integration, DICOM (Digital Imaging and Communications in Medicine) for medical imaging.
  • Ensure cross-platform compatibility and seamless communication with technologies like FHIR (Fast Healthcare Interoperability Resources).

4. Reliability and smooth user experience

Medical software with a poorly designed interface and unstable performance can result in delays and even harm patients.

How to face the challenge:

  • Conduct user research involving medical specialists and patients to design intuitive workflows.
  • Perform usability testing with real-life scenarios.
  • For critical applications like patient monitoring systems or diagnostic tools, use low-latency architectures and real-time data processing, to maximize the response time.
  • To enhance efficiency and safety, prioritize principles of human-centered design (HCD).

5. Competition and pricing pressure

As the market of medical device apps grows, competition intensifies as well. Manufacturers often lower production costs and speed up the development and product cycle to stay competitive, but this comes at a price. Why so?

Medical devices require many resources on R&D and regulatory compliance, but in the need to make prices lower, such investments do not seem reasonable. Reduced budgets on research, testing, and regulatory compliance, as well as shortened timelines can compromise product safety.

In the long run, such a strategy may lead to a lack of innovation and lower quality of services provided to customers.

How to face the challenge:

  • Apply Agile and DevOps methodologies, as well as automated testing to make development cycles more iterative and faster.
  • Invest in cutting-edge technologies: use AI, cloud computing, and IoMT for efficient, and scalable software; explore Digital Twins and simulations to reduce costs on development and product testing.
  • Collaborate with healthcare institutions, research labs, and MedTech startups to co-develop innovative solutions.
  • Work with third-party SaaS providers for cloud infrastructure, reducing operational costs.

6. Collaboration with stakeholders

Successful implementation of software in a medical device implies input from healthcare professionals, patients, engineers, and regulators. When communication between these groups breaks down, misaligned requirements and delays happen as a consequence.

How to face the challenge:

  • Engage stakeholders early through interviews, surveys and prototype reviews.
  • Maintain transparent documentation to align development teams with clinical needs.
  • Use Agile methodologies for iterative development, leaving space for continuous feedback and refinement.

Emerging technologies in software for medical devices

With all existing tech advancements in healthcare, there's still a lot of potential to revolutionize it. Here we list the most promising technologies that push the industry forward.

Connected Medical Devices (IoMT) for remote monitoring

As a medical IoT devices software developer, you can take patient monitoring to a new level. With innovative devices at hand, both health providers and patients can track health conditions remotely and in real time with smart inhalers, wireless ECG monitors, and Bluetooth-enabled glucose meters.

If the patient' condition deteriorates — for instance, a sudden drop in oxygen saturation is detected — this can trigger a call to action, potentially preventing an admission to hospital. Moreover, this data can be integrated into patient records, enabling a more holistic view of health trends over time.

Cloud-based solutions for interoperability

Cloud computing solutions like SaaS allow connecting hospitals with patients via applications without the need to manage on-premise infrastructure.

Cloud-based EHR systems, telemedicine platforms, and AI-assisted diagnostics make updates seamless and healthcare services cost-efficient.

AI and ML for better diagnostics and personalization

The arsenal of AI and ML algorithms make way for more personalized and accurate medicine. Predictive analytics, personalized treatment plans, automated diagnostics, detection of anomalies in MRIs and CT scans are most vivid examples of how these technologies improve healthcare.

Blockchain for medical data management

Blockchain technology plays a crucial role in mitigating breaches and cyberattacks, which are so common in the healthcare industry. By encrypting patient information, blockchain improves data integrity in medical records and makes data sharing between providers more streamlined. As a consequence, compliance with privacy regulations also improves.

Digital twins for medical device testing

Testing and validating medical device apps has become easier after virtual replicas of medical devices were introduced. With digital twin technology it's possible to simulate real-world usage scenarios, predict failures and optimize performance before real device production. It saves resources and what is most important, enhances accuracy in surgical robotics and biomedical engineering.

Conclusion

Healthcare is undergoing a digital renaissance. As tech innovations continue to evolve and penetrate into healthcare, there is more space for having the lead as a manufacturer and trailblazer.

Although developing medical device software is no easy feat, requiring deep domain expertise, a grasp of regulatory frameworks, and the ability to scale, a reliable development partner can assist you on the way. In a crowded market, innovation is not just about building something new, but about building it right.

Want to make your mark in the healthcare industry? NEKLO will help you create high-class medical software while staying updated on regulations and best practices!