In this webinar we will scrutinize quality and test solutions used in engineering for medical devices. With a focus on practical application and balancing the tradeoffs when using mainstream tools, we'll provide you with actionable information to optimize your approach to quality and testing in your medical devices.
5 Key Considerations at the Start of SaMD DevelopmentICS
Changes introduced once the software development process has begun can have an adverse impact on budget, schedule and the product itself. Fortunately, meticulous planning can mitigate most last-minute changes and minimize the impact of those deemed absolutely necessary. This webinar will cover 5 key aspects you should address at the outset of the SaMD development process, from regulatory concerns to technology considerations, to keep your project running smoothly.
Strategies to limit project timeline and cost in medical devicesJanel Heilbrunn
Developing medical devices under a quality management system for the FDA can be a complicated and subtle process with tremendous variability. The leading mitigatable risk to budget and schedule comes from minimizing the impact of change during the development process. This presentation will address common categories of change and how to minimize or even benefit from the disruption. You will learn about:
- Reordering your development to minimize work
Tuning your QMS to support your development process
- Deferred decisions and how ambiguity costs
- Taking credit for design evolution
5 Key Considerations at the Start of SaMD DevelopmentICS
Changes introduced once the software development process has begun can have an adverse impact on budget, schedule and the product itself. Fortunately, meticulous planning can mitigate most last-minute changes and minimize the impact of those deemed absolutely necessary. This webinar will cover 5 key aspects you should address at the outset of the SaMD development process, from regulatory concerns to technology considerations, to keep your project running smoothly.
Strategies to limit project timeline and cost in medical devicesJanel Heilbrunn
Developing medical devices under a quality management system for the FDA can be a complicated and subtle process with tremendous variability. The leading mitigatable risk to budget and schedule comes from minimizing the impact of change during the development process. This presentation will address common categories of change and how to minimize or even benefit from the disruption. You will learn about:
- Reordering your development to minimize work
Tuning your QMS to support your development process
- Deferred decisions and how ambiguity costs
- Taking credit for design evolution
MDG Panel - Creating Expert Level GUIs for Complex Medical DevicesICS
Graphical User Interfaces are so pervasive and have so many different design intents that it can be hard to see the norms and evolution of norms being applied over the past couple of decades. In medical devices, more than most, tradeoffs between safety, effectiveness and pleasure-to-use, dominate the design efforts.
.
Much focus and debate has been applied to paradigms of “simple yet effective” in GUI design. The most commonly cited ideals in the Apple eco-system and skeuomorphic design concern themselves with the novice user and technology adoption. But not all products are designed for the novice user.
.
For UIs that expose advanced or unstructured feature sets to the user, the normative approach has been to compromise on the simplicity to extend the functionality. But such an approach can be incremental and muddled where a better approach might be cogent redesign.
.
We will explore the evolution of a life-saving lung transplant medical device from Tevosol that implements an expert-level GUI for clinical users. Focus will be on lessons learned and the design principles ultimately chosen.
Presentazione dello speech tenuto da Carmine Spagnuolo (Postdoctoral Research Fellow - Università degli Studi di Salerno/ ACT OR) dal titolo "Technology insights: Decision Science Platform", durante il Decision Science Forum 2019, il più importante evento italiano sulla Scienza delle Decisioni.
Leveraging Artificial Intelligence Processing on Edge DevicesICS
The introduction of low-cost, high-performance embedded processors coupled with improvements in Neural Network model optimization lay the foundation for AI and Computer Vision at the edge. Moving intelligence from the cloud to the edge offers many advantages including the reduction of network traffic, predicable ML inference times, and data security to name a few. Challenges exist as many development teams do not have data scientist or AI development engineers. What is needed are practical AI solutions including ML development tools, optimized inference engines and reference platforms that will abstract out the development complexities to stream line prototyping and development.
In this joint webinar with Au-Zone Technologies we will discuss:
- Development challenges and solutions which can be use to enable AI/ML at the edge to implement object detection, classification and tracking for medical and industrial use-cases
- Visualization techniques for activity monitoring and object detection
When it comes to medical devices, best practices for software interface design are not an option. They're an absolute necessity. This truth has been recognized by international standards organizations, successful medical device manufacturers, and key regulatory bodies, including the Food and Drug Administration. To shed light on effective medical device design, we'll explore:
The role of poor design in medical errors
Software design as a cause of device recalls
Relevant international standards and FDA regulations
The emergence of software as a medical device (SaMD)
Best practices to follow when designing the interface for your next medical device
Bridging the Gap: from Data Science to ProductionFlorian Wilhelm
A recent but quite common observation in industry is that although there is an overall high adoption of data science, many companies struggle to get it into production. Huge teams of well-payed data scientists often present one fancy model after the other to their managers but their proof of concepts never manifest into something business relevant. The frustration grows on both sides, managers and data scientists.
In my talk I elaborate on the many reasons why data science to production is such a hard nut to crack. I start with a taxonomy of data use cases in order to easier assess technical requirements. Based thereon, my focus lies on overcoming the two-language-problem which is Python/R loved by data scientists vs. the enterprise-established Java/Scala. From my project experiences I present three different solutions, namely 1) migrating to a single language, 2) reimplementation and 3) usage of a framework. The advantages and disadvantages of each approach is presented and general advices based on the introduced taxonomy is given.
Additionally, my talk also addresses organisational as well as problems in quality assurance and deployment. Best practices and further references are presented on a high-level in order to cover all facets of data science to production.
With my talk I hope to convey the message that breakdowns on the road from data science to production are rather the rule than the exception, so you are not alone. At the end of my talk, you will have a better understanding of why your team and you are struggling and what to do about it.
A Deep Dive into Secure Product Development Frameworks.pdfICS
We tackle the question of what is a SPDF for medical device cybersecurity. We look to provide actionable advice that clarifies implementation, and you can apply in your day-to-day tasks.
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...ICS
A great deal of attention in medical devices has shifted towards cybersecurity with the ratification of section 524B of the FD&C act. This new law enables the FDA to enforce cybersecurity controls in any medical device that is capable of networked communications or that has software. In this webinar we will recap the process for managing vulnerabilities, identify categories of vulnerabilities and solutions and more.
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MDG Panel - Creating Expert Level GUIs for Complex Medical DevicesICS
Graphical User Interfaces are so pervasive and have so many different design intents that it can be hard to see the norms and evolution of norms being applied over the past couple of decades. In medical devices, more than most, tradeoffs between safety, effectiveness and pleasure-to-use, dominate the design efforts.
.
Much focus and debate has been applied to paradigms of “simple yet effective” in GUI design. The most commonly cited ideals in the Apple eco-system and skeuomorphic design concern themselves with the novice user and technology adoption. But not all products are designed for the novice user.
.
For UIs that expose advanced or unstructured feature sets to the user, the normative approach has been to compromise on the simplicity to extend the functionality. But such an approach can be incremental and muddled where a better approach might be cogent redesign.
.
We will explore the evolution of a life-saving lung transplant medical device from Tevosol that implements an expert-level GUI for clinical users. Focus will be on lessons learned and the design principles ultimately chosen.
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Leveraging Artificial Intelligence Processing on Edge DevicesICS
The introduction of low-cost, high-performance embedded processors coupled with improvements in Neural Network model optimization lay the foundation for AI and Computer Vision at the edge. Moving intelligence from the cloud to the edge offers many advantages including the reduction of network traffic, predicable ML inference times, and data security to name a few. Challenges exist as many development teams do not have data scientist or AI development engineers. What is needed are practical AI solutions including ML development tools, optimized inference engines and reference platforms that will abstract out the development complexities to stream line prototyping and development.
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When it comes to medical devices, best practices for software interface design are not an option. They're an absolute necessity. This truth has been recognized by international standards organizations, successful medical device manufacturers, and key regulatory bodies, including the Food and Drug Administration. To shed light on effective medical device design, we'll explore:
The role of poor design in medical errors
Software design as a cause of device recalls
Relevant international standards and FDA regulations
The emergence of software as a medical device (SaMD)
Best practices to follow when designing the interface for your next medical device
Bridging the Gap: from Data Science to ProductionFlorian Wilhelm
A recent but quite common observation in industry is that although there is an overall high adoption of data science, many companies struggle to get it into production. Huge teams of well-payed data scientists often present one fancy model after the other to their managers but their proof of concepts never manifest into something business relevant. The frustration grows on both sides, managers and data scientists.
In my talk I elaborate on the many reasons why data science to production is such a hard nut to crack. I start with a taxonomy of data use cases in order to easier assess technical requirements. Based thereon, my focus lies on overcoming the two-language-problem which is Python/R loved by data scientists vs. the enterprise-established Java/Scala. From my project experiences I present three different solutions, namely 1) migrating to a single language, 2) reimplementation and 3) usage of a framework. The advantages and disadvantages of each approach is presented and general advices based on the introduced taxonomy is given.
Additionally, my talk also addresses organisational as well as problems in quality assurance and deployment. Best practices and further references are presented on a high-level in order to cover all facets of data science to production.
With my talk I hope to convey the message that breakdowns on the road from data science to production are rather the rule than the exception, so you are not alone. At the end of my talk, you will have a better understanding of why your team and you are struggling and what to do about it.
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2. Integrated Computer Solutions Inc. www.ics.com
About ICS
Established in 1987, Integrated
Computer Solutions, Inc. (ICS)
delivers innovative software
solutions with a full suite of
services to accelerate development
of successful next-gen products.
ICS is headquartered outside
Boston in Waltham, Mass. with
offices in California, Canada and
Europe. Currently 160+ people.
3. Integrated Computer Solutions Inc. www.ics.com
www.ics.com
Delivering a Full Suite of
Medtech Services
● IEC 62366-UX/UI Design
● Custom Frontend & Backend Software Development
● Development with IEC 62304-Compliant Platform
● Low-code Tools that Convert UX Prototype to
Product
● Medical Device Cybersecurity
● AWS and Azure Cloud Services and Analytics
● ISO 14971-Compliant Hazard Analysis
● Software Verification Testing
● Digital Twins for Training and Simulation
● Complimentary Software Technology Assessments
4. Integrated Computer Solutions Inc. www.ics.com
Enhancing Quality and Test in Medical Device Design
Webinar Part 1 of 2
Part 1
1. Usability Design for Quality
2. Architecture design
a. Tiered
b. Error injection
c. Solid’s dependency inversion
d. Loose coupling
3. Code analyzers
4
Part 2
1. Automated testing
a. Unit tests with coverage metrics to
promote code stability
b. Automated User Interface testing to
shorten defect remediation cycles
c. Product verification
2. Tracing requirements to design
a. Requirement coverage analysis
b. Verification test protocols
6. Integrated Computer Solutions Inc. www.ics.com
Usability Design to Minimize Use Errors
Usability for Quality in Medical Devices
● Prioritizing Safety over Intuitive/User-friendly
● Quality relates to Use Errors
6
7. Integrated Computer Solutions Inc. www.ics.com
Usability Design to Minimize Use Errors (Cont’d)
User Error vs. Use Error
● User Error – is a user problem
● Use Error – is a device characteristic
“Safe and Effective”
○ “Safe and effective use of a medical device means that users do not make errors that lead to injury and they
achieve the desired medical treatment. If safe and effective use is not achieved, use error has occurred. Why
and how use error occurs is a human factors concern” (FDA Glossary of Medical Devices)
Use Error fixes: Training? Labeling? Who reads anymore?
Use Errors need to be fixed
7
8. Integrated Computer Solutions Inc. www.ics.com
Usability Design to Minimize Use Errors (Cont’d)
Context is critical for Use Errors
● Device intent + use environment + user types Use Errors
FDA wants Systematic treatment of Use Errors
● Over-familiar stakeholders tend to guess omissions
● Defined method to identify Use Errors
● Use Errors 🡪 Mitigations 🡪 Residual Risk 🡪 Test Effectiveness
● IEC 62366 - Application of usability
engineering to medical devices
8
10. Integrated Computer Solutions Inc. www.ics.com
How Architecture Impacts Device Quality
Maintainable, testable, extensible, reliable, available architecture
Why maintainable/extensible impacts quality?
● Things misbehave – Transparency (logging, simulators), Debuggability (determinism,
traceability, separation of concerns)
● Things change – Avoid inadvertent change, minimize change
● Things need to be tested - Testing can be hard
10
11. Integrated Computer Solutions Inc. www.ics.com
Architecture Principles
“If you think good architecture is expensive, try bad architecture!”
— Brian Foote & Joseph Yoder
How Architecture helps with Quality through application of principles
● SOLID – a series of principles to achieve quality through separation
and structured relationships
● Single-responsibility principle (SRP)
● Open-closed principle (OCP)
● Liskov substitution principle (LSP)
● Interface-segregation Principle (ISP)
● Dependency-inversion principle (DIP)
11
13. Integrated Computer Solutions Inc. www.ics.com
Dependency Inversion
Error injection/SOLID – diagram
Make it easier to test high-level modules by replacing low level
modules with simulators
Loose coupling
13
“Would you solder a
lamp directly to the
electrical wiring in a
wall?”
14. Integrated Computer Solutions Inc. www.ics.com
Architecture for Test
● Make it easy to test
● Software can be (relatively) inexpensive to test
● Hardware is usually expensive to test
● Person hours – manual test, manual configuration
● Test platforms/equipment – engineering costs, storage costs,
configurations
● Automated tests run ‘for free’
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15. Integrated Computer Solutions Inc. www.ics.com
Architecture Tradeoffs
Downsides
● Non-trivial to apply
● Correct application requires architectural expertise
● Has to be enforced on every check-in
● A lot of segregation and isolation within the code - may not be needed
● Bigger code
● Distributed code - harder to comprehend without detailed documentation
<for Medical Devices, still worth it, liability, recalls, patient health>
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17. Integrated Computer Solutions Inc. www.ics.com
Code Analyzers
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• Static
• Looks at syntax and conventions used in source code
to highlight potential problems
• Good for enforcing a code style, structure, conventions
• Most tools are static analysis tools - easier than
dynamic
• Dynamic
• Runs the application and looks for issues
• Can use statistical and inferential approaches
• Some have a management system for issues found
Upshot: Some solution needed - treat as a requirement
Popular tools
• Valgrind
• Coverity
• BoundsChecker
• Clang
• PC-Lint
• CPPLint
18. Integrated Computer Solutions Inc. www.ics.com
Code Analyzers - Drawbacks
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Static:
• Effort intensive
• Large number of rules to configure
• Large number of findings, most aren’t significant
• (1000s to 100,000s)
Dynamic:
• Usually requires inserting new code into your code (which
changes how your code runs!)
• Large number of findings
• Sophisticated ones can be expensive
Even the best still won’t find that deep-intermittent bug
19. Integrated Computer Solutions Inc. www.ics.com
Recap:
Enhancing Quality and Test in Medical Device Design
Webinar Part 1 of 2
Part 1
1. Usability Design for Quality
2. Architecture design
a. Tiered
b. Error injection
c. Solid’s dependency inversion
d. Loose coupling
3. Code analyzers
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Part 2
1. Automated testing
a. Unit tests with coverage metrics to
promote code stability
b. Automated User Interface testing to
shorten defect remediation cycles
c. Product verification
2. Tracing requirements to design
a. Requirement coverage analysis
b. Verification test protocols