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Medtech Business Review | Tuesday, August 01, 2023
Considering evolving laws and social concerns, investors and strategic partners are increasingly concerned with protecting their intellectual property (IP).
FREMONT, CA: As more and more medtech businesses create systems that gather and use significant patient and provider data, they are evolving quickly.
Businesses that originally primarily created hardware-based medical solutions are now becoming data platform businesses, providing a more thorough look into the behaviors and health of their patients and clients. As many of these technologies rely on machine learning and artificial intelligence, it can be more difficult to safeguard intellectual property using conventional methods.
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In light of changing regulations and social concerns, investor and strategic partner mindsets have changed toward the best approaches to secure their intellectual property (IP) obligations.
We have selected the top 5 IP factors that medtech businesses need to be aware of during the product development lifecycle based on our decades of experience working with them. This is especially true for data platforms that include medical technology.
In the developing sectors of software as a medical service (SaMD), software in a medical device (SiMD), and AI in medical technologies, medtech enterprises should consider the following IP protection techniques.
Strategies for deliberately varying IP protection
Consider patenting the hardware together with the software it runs. Consider protecting techniques, AI/ML systems, and software as trade secrets as an alternative or in addition.
Be sure that non-compete and confidentiality agreements with workers are in place to the extent permissible, given jurisdictional restrictions. Consider exclusive licensing for training databases to prevent others from creating comparable solutions utilizing these databases.
Whether to patent new ideas or keep them a trade secret
In general, the essential factor in determining whether a patent or trade secret is the best protection for a company's data-enabled creation is the capacity to reverse engineer, together with the changing legal requirements surrounding the patentability of such inventions.
When protecting data-enabled software with AI/ML components generally, patenting requires disclosing specifics, which can be difficult. So, patenting is best for gadgets and for defending the interaction between software and physical objects.
Trade secrets can be duplicated if your concept becomes popular, but they require you always to preserve and safeguard secrecy. It works best for expensive or challenging-to-copy software, production techniques, or goods.
How to balance breadth and abstraction in patent claims if patenting to maximize protection
Claiming software uses essential functional language to describe the innovation, which may be too abstract to be covered by a patent if used at a high enough degree. The tension between breadth and abstraction levels in software patent drafting, however, is a result of patentees' constant desire to cover their innovation broadly.
Observing the development of patent subject matter eligibility
The patenting of natural laws or abstract concepts is prohibited by US law.
The US Supreme Court expanded this idea in 2014, providing the US Patent Office new grounds for rejecting AI-based patent applications and trial courts new grounds for invalidating them. The process of obtaining software and AI-based patents in the US has become more difficult due to this ruling. It is necessary to keep vigilant of the volatile nature of the industry. Still, there are inventive methods to leverage the changing case law and to show ideas to fall outside of this limitation.
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