MetaDAMA - Data Management in the Nordics

3#16 - Navigating the Regulatory Landscape for AI in Healthcare (Eng)

May 06, 2024 Elisabeth M.J. Klaussen - DoMore Diagnostics Season 3 Episode 16
3#16 - Navigating the Regulatory Landscape for AI in Healthcare (Eng)
MetaDAMA - Data Management in the Nordics
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MetaDAMA - Data Management in the Nordics
3#16 - Navigating the Regulatory Landscape for AI in Healthcare (Eng)
May 06, 2024 Season 3 Episode 16
Elisabeth M.J. Klaussen - DoMore Diagnostics

«AI will be so important in transforming health care as we know it today."

Join us as we sit down with Elisabeth M.J. Klaussen from DoMore Diagnostics, who are on a mission to transform cancer diagnostics with artificial intelligence to improve patient care and make drug development more effective. With a rich background in quality assurance and R&D within Pharma, Biotech, and MedTech, Elisabeth shares how AI is revolutionizing patient care and the pathway to personalized medicine.

Navigating the complexities of starting a healthcare venture can be as intricate as the regulations that govern it. In this episode, we discuss the maze of regulations across continents, the implications of the European AI Act for innovators, and the non-negotiable necessity of protecting patient data.

Wrapping up our dialogue, we emphasize the importance of a Quality Management System (QMS), especially when developing AI models. As we delve into the EU's AI Act and its potential to harmonize standards, Elisabeth offers invaluable advice to health startups: the development of a robust QMS is not just a regulatory tick box but a foundational pillar for market readiness.

Here are my key takeaways:
AI in Health Care:

  • Personalized medicine requires to analyze a lot of data and set it in a personalized context.
  • To create value with AI in health care is challenging, due to the high density of regulations, yet benefits can be huge.
  • AI can enable us to use investments in pharmaceuticals, biotech as well as patient care more effectively.
  • You need to ensure you can constrain AI models, not only on the data input, but also through use of parameters or model-architecture.
  • The product from DoMore Diagnostics is i.e. a static model, not generative, that gives an output on leanings only.
  • There is a need to apply for a new CE marking, if model would change.

Regulations in Health Care:

  • You need to understand both your product and its intended purpose to understand what regulation will apply to you.
  • You need to set up a team with the right people and competency.
  • Try to find generalists - People that have a core competency, but are really good at adopting and learning new surrounding competencies at a more generalist level to complement each other.
  • Laws and regulations in the industry are getting more and more globally standardized.
  • If you adhere to the area with the most stringent rules, you can basically introduce your product to any market you like.
  • If you set up your organization for regulatory compliance, you have two perspectives to keep in mind:
     
    • Internally - how do you set up your principles, polices and processes internally?
    • How do you act towards your sector and market?
  • The regulation on EU level provides a framework, within you can find national regulations and laws that go beyond. One example is product labeling that can vary between EU countries.

The EU AI Act:

  • The EU AI Act introduces requirements that the heavily regulated industry is following already. (E.g. quality systems, documented design and development of your product, validations, performance studies)
  • EU regulations are political documents, that are build on compromise.
  • There is a huge constraint within the EU commission as well as on the authority side to take on the workload that results from the AI Act and other new regulations.
  • The more cumbersome regulations are and the more regulations you build in, the more expensive will products get.
  • Standards and regulations can help to structure your ways of working, ensuring efficiency, not wasting time and money in doing things over and over again.
  • «You can be more creative, if you have a structured way of working.»
Show Notes Chapter Markers

«AI will be so important in transforming health care as we know it today."

Join us as we sit down with Elisabeth M.J. Klaussen from DoMore Diagnostics, who are on a mission to transform cancer diagnostics with artificial intelligence to improve patient care and make drug development more effective. With a rich background in quality assurance and R&D within Pharma, Biotech, and MedTech, Elisabeth shares how AI is revolutionizing patient care and the pathway to personalized medicine.

Navigating the complexities of starting a healthcare venture can be as intricate as the regulations that govern it. In this episode, we discuss the maze of regulations across continents, the implications of the European AI Act for innovators, and the non-negotiable necessity of protecting patient data.

Wrapping up our dialogue, we emphasize the importance of a Quality Management System (QMS), especially when developing AI models. As we delve into the EU's AI Act and its potential to harmonize standards, Elisabeth offers invaluable advice to health startups: the development of a robust QMS is not just a regulatory tick box but a foundational pillar for market readiness.

Here are my key takeaways:
AI in Health Care:

  • Personalized medicine requires to analyze a lot of data and set it in a personalized context.
  • To create value with AI in health care is challenging, due to the high density of regulations, yet benefits can be huge.
  • AI can enable us to use investments in pharmaceuticals, biotech as well as patient care more effectively.
  • You need to ensure you can constrain AI models, not only on the data input, but also through use of parameters or model-architecture.
  • The product from DoMore Diagnostics is i.e. a static model, not generative, that gives an output on leanings only.
  • There is a need to apply for a new CE marking, if model would change.

Regulations in Health Care:

  • You need to understand both your product and its intended purpose to understand what regulation will apply to you.
  • You need to set up a team with the right people and competency.
  • Try to find generalists - People that have a core competency, but are really good at adopting and learning new surrounding competencies at a more generalist level to complement each other.
  • Laws and regulations in the industry are getting more and more globally standardized.
  • If you adhere to the area with the most stringent rules, you can basically introduce your product to any market you like.
  • If you set up your organization for regulatory compliance, you have two perspectives to keep in mind:
     
    • Internally - how do you set up your principles, polices and processes internally?
    • How do you act towards your sector and market?
  • The regulation on EU level provides a framework, within you can find national regulations and laws that go beyond. One example is product labeling that can vary between EU countries.

The EU AI Act:

  • The EU AI Act introduces requirements that the heavily regulated industry is following already. (E.g. quality systems, documented design and development of your product, validations, performance studies)
  • EU regulations are political documents, that are build on compromise.
  • There is a huge constraint within the EU commission as well as on the authority side to take on the workload that results from the AI Act and other new regulations.
  • The more cumbersome regulations are and the more regulations you build in, the more expensive will products get.
  • Standards and regulations can help to structure your ways of working, ensuring efficiency, not wasting time and money in doing things over and over again.
  • «You can be more creative, if you have a structured way of working.»
Healthcare AI Impact and Regulations
Startup Regulations and Team Building Discussion
Regulatory Compliance in the MedTech Industry
Importance of Quality Management Systems