AI-powered medical devices are becoming increasingly popular, as they have the potential to improve the accuracy and efficiency of medical diagnosis and treatment. As a patent lawyer with over 20 years of helping medical device companies, I believe that we will see a large segment of medical device startups augment traditional mechanical designs with AI-based intelligence to arrive at new and exciting treatment solutions that make life easier for everyone from physicians to patients. If you are a medical device founder, read on to see techniques to protect your company as it develops its products and how to use the patent system to increase your company valuation.
Table of Contents
- Trends for AI medical devices
- Medical Device Patenting
- There are several types of patents to consider:
- Provisional Patents for Medical Device inventions
- Utility Patents for Medical Devices
- Design Patents for Medical Device inventions
- Trade secret protection for aI training methods and training data
- Trademark protection for AI-based medical devices
Trends for aI medical devices
It’s worth noting that AI-powered medical devices are still in their early stages of development and more research is needed to fully understand their potential benefits and risks. Additionally, AI-powered medical devices are subject to regulation by the FDA and other regulatory bodies, which can affect their development, approval, and usage.
Investors are often attracted to medical devices that have both FDA approval and patent status. Patents grant the company exclusive rights to the invention and prevent others from using it or selling it without permission. This can help companies recover development costs and FDA clearance. FDA approval also proves that the device meets the strict standards of safety and effectiveness set by the FDA and can legally be sold and marketed in the United States.
FDA approval can give a company an advantage in the marketplace because it provides a legal framework for marketing and selling its products. Potential investors have this assurance that the product is safe and has been properly vetted.
A patented, FDA-approved medical product can help a company stand apart in a competitive market. This can increase its chances for success and attract more investors.
FDA clearance allows the company to expand internationally and enter new markets. The device is already approved for use in the United States, where there are some of the strictest regulations in the world.
Medical devices that have received FDA and patent approvals are considered more attractive investments because they give you exclusive rights to the invention and legal framework to market it. They also provide a level of safety and security to use.
In this context, medical device startups with AI software assistance are booming. Some of the current trends in AI-powered medical devices include:
- Remote monitoring: AI-powered medical devices are being developed to monitor patients remotely, allowing healthcare professionals to access patient data and make diagnoses remotely.
- Image analysis: AI-powered medical devices are being used to analyze medical images, such as X-rays and CT scans, to assist in the diagnosis of medical conditions.
- Predictive analytics: AI-powered medical devices are being used to predict the likelihood of certain medical conditions, such as chronic diseases, and to develop personalized treatment plans.
- Natural Language Processing (NLP): AI-powered medical devices are being used in natural language processing to extract information from unstructured data such as clinical notes and patient records.
- Robotics: AI-powered medical devices are being used in robotic surgery to assist surgeons in performing complex procedures with greater precision and accuracy.
- Drug Discovery: AI-powered medical devices are being used to assist in the discovery and development of new drugs, by analyzing large amounts of data and identifying potential drug candidates.
Medical Device Patenting
Patenting AI software for medical devices can be complex, as it involves both software and medical technology. In order to be eligible for a patent, AI software for medical devices must meet certain requirements, such as novelty, non-obviousness, and usefulness.
Novelty means that the invention must be new and not previously disclosed or known. Non-obviousness means that the invention must not be obvious to a person having ordinary skills in the relevant field. And usefulness means that the invention must have a specific, substantial, and credible utility.
AI software for medical devices can be patented as a process, system, or device. A process patent would protect the method of using AI to accomplish a specific task or function. A system patent would protect the specific hardware and software components that make up the AI system. And a device patent would protect the overall apparatus or machine that includes the AI software.
It’s worth noting that AI-related patent applications are becoming increasingly complex and contested areas in the field of patent law. Obtaining a patent for an AI-related invention can be a time-consuming and costly process, and it’s also important to have a thorough understanding of the legal landscape surrounding AI and software patents.
There are several types of patents to consider:
Provisional Patents for Medical Device inventions
A provisional patent is a type that lasts one year for medical device software. This allows the inventor to evaluate the invention and decide if it is worth filing a full patent application.
A provisional patent covering medical device software can also be called “patent pending” (or a “design patent”). Patents that protect the design of a device can also be used to protect its exterior design.
These medical devices include instruments and equipment for surgery, drug delivery systems, and patient monitoring devices. Software solutions are often used to develop these types of products. The software can be used for tracking health information as well as hospital management, staff allocation, and staff allocation.
A provisional patent is a good option for anyone who wants to patent medical device software. The first is that it’s cheaper. Because the United States Patent and Trademark Office, USPTO (USPTO), does not examine provisional applications, you will pay less for a Patent than for a complete non-provisional one.
A provisional patent also preserves rights while you decide whether to file a full patent request. This allows you to test your invention and determine its worth without having to pay for a patent.
Provisional patents can have negative side effects. They may not offer complete protection. You won’t get full patent protection if you aren’t clear on the scope of your invention. You won’t get a priority date if your invention is only partially disclosed.
Utility Patents for Medical Devices
Utility patents cover an invention. Anyone who discovers a useful invention is eligible to receive a utility patent. Utility patents are often granted for new methods and mechanical inventions. They also cover new compositions of matter or processes.
Each year, the USPTO receives more than 500,000 patent applications. These applications are mostly non-provisional utility patent applications. These applications are reviewed by a patent examiner before being issued if they satisfy certain patentability requirements.
There are many types of patents for medical devices. A utility patent is the most common. It focuses on the device’s functionality.
Patents may be granted for medical device software. The software must be unique and improve the performance of the computer to meet the patentable subject matter test. Functionality is also a requirement. It must also meet FDA requirements for medical devices. It must, for example, be able to track data and perform more functions than just calculate. It will not be eligible to receive a patent if it doesn’t meet the FDA’s requirements.
When preparing a patent application for software devices, it is important to take into account the eligibility criteria for patentability. These criteria were set by the United States Patent and Trademark Office. Patent allowance is only possible if the invention is novel, useful, and unobvious.
To draft a medical device with AI software as a patent application with a high likelihood of being granted, it is important to clearly and precisely describe your invention. To help explain the invention’s operation, you should include technical details and drawings.
It is important to make sure that the claims in the application are clear and specific enough to distinguish the invention from prior art.
A patent attorney can help you with the drafting of a mobile patent application that meets all patent eligibility criteria. It can be difficult to obtain a patent for a medical device. It can also be costly. It is recommended that you seek legal advice before considering patent protection.
Design Patents for Medical Device inventions
Design patents are sought by most medical device companies. These patents cover both the design and graphical interfaces of the device, including how the AI software interacts with the user. This protects a company against a competitor copying a design.
For medical devices, utility patents can also be granted. These patents are granted to inventors who have created a useful product or process. The invention must be original and not already known by the applicant.
To protect the visual elements of a medical device, a design patent can also be obtained. It is less frequently used than a utility patent.
Mobile medical devices have seen a surge in popularity due to the COVID pandemic. These devices can be designed in a way that is attractive and makes them easy to use. These customizations can be used by companies to distinguish their products from others.
Medical device manufacturers have the ability to create innovative products. They must also protect their intellectual property. They must protect their intellectual property, no matter if it’s a utility or design patent.
A patent examination can be complicated and time-consuming. Hire an expert to speed up the process. You might be able to get a provisional patent if you don’t have the funds to hire an outside patent attorney. This will allow you to file your patent application within one year. After one year, the patent can be converted to a non-provisional.
trade secret protection for aI training methods and training data
Trade secret protection is a way for companies to protect their confidential information, including their AI training methods and training data. Trade secret protection allows companies to keep their information confidential, rather than disclosing it to the public through the patent process.
Trade secret protection can be used to protect the methods and techniques used to train an AI model, as well as the training data used to teach the model. This can include the algorithms, data sets, and parameters used to train the model, as well as any other information that the company considers to be a trade secret.
To protect trade secrets, companies should take steps to keep their information confidential. This can include implementing security measures such as access controls, encryption, and firewalls, as well as training employees and contractors on their obligations to maintain the confidentiality of the information.
It’s worth noting that trade secret protection is perpetual, unlike patents. The protection lasts as long as the information is kept secret. Once the information is made public or is independently discovered, it can no longer be protected as a trade secret. Additionally, trade secret protection is only enforceable in civil court, if someone misappropriates the trade secret.
trademark protection for aI-based medical devices
Trademark protection is a way for companies to protect their brand, including their AI-based medical devices. A trademark is a distinctive word, phrase, logo, or symbol that is used to identify and distinguish a particular company’s goods or services from those of other companies.
In the case of AI-based medical devices, companies can use trademarks to protect the name of their device, the logo or symbol used to represent the device, and any slogans or catchphrases associated with the device.
To obtain trademark protection for an AI-based medical device, a company must first conduct a trademark search to ensure that the proposed trademark is not already in use by another company. Once a unique trademark is selected, the company can file an application with the United States Patent and Trademark Office (USPTO) to register the trademark.
It’s worth noting that obtaining a trademark is not always straightforward and it can take several months or years to be granted. The USPTO may refuse to register a trademark if it is too similar to existing trademarks, or if it is considered generic, descriptive, or misleading. Also, once a trademark is granted, the owner has to enforce it, by monitoring and taking action against any infringement.
FDA oversight of AI and ML technologies
Artificial intelligence (AI) and machine learning (ML) technologies continue to fuel advances in life science and biopharmaceuticals. They are also increasingly being used in healthcare delivery systems. As such, policymakers will be faced with the task of creating a regulatory framework for AI in health care. While global regulators have yet to agree on key benchmarks, their policies will likely evolve as technology continues to improve. In the meantime, lawmakers must grapple with how to protect consumers and encourage AI integration.
The Food and Drug Administration (FDA) recently published an Action Plan to address AI/ML-based software as medical devices (SaMDs). Specifically, FDA outlined a potential approach to the premarket review of SaMDs. It is hoped that FDA’s new approach will provide manufacturers with a roadmap to ensure the safety of their AI/ML products.
For medical devices, the proposed framework outlines five actions. First, the FDA will develop a methodology for evaluating machine learning algorithms. Second, the agency will assess whether changes to SaMDs will increase safety or risk to patients. Third, it will create guidance on the labeling of these products. Lastly, the agency will establish a framework for gathering real-world performance data.
Despite the rapid pace of change in AI and ML technologies, the FDA has remained committed to developing a sound regulatory framework. This means the agency will continue to develop and implement policies and processes that will help ensure the safety of these products. However, as new products come to market, the agency will also need to adjust its oversight practices to accommodate evolving software and algorithm needs.
FDA has demonstrated support for medical diagnostics, including a pilot program that leveraged machine learning to predict the likelihood of contaminated food shipments. It is currently reviewing the findings from this program.