From Lab to Legislation: Brain-Machine Interfaces and Privacy Considerations

Several neurotechnology companies have developed implantable brain-machine interfaces (BMIs). A BMI is a device that translates neuronal information into commands capable of controlling external software or hardware, such as a computer or robotic arm. BMIs are often used as assisted living devices for people with motor or sensory impairments. The devices’ main objective is to monitor brain activity and provide electrical stimulation which enables brain-computer interactions.  By using this technology, people with paralysis, blindness, deafness, or speech impairment could potentially regain control over their electronic devices using their thoughts, opening new possibilities for improving their quality of life.

Current Status of Neurotechnology Research

In essence, the development and approval of medical devices encompasses a comprehensive sequence of stages, each involving innovation, safety, and advancement in healthcare.  Privacy laws and regulations are key components that intersect with the innovation of these technologies.

Both in the United States and abroad, there are comprehensive privacy laws that could oversee how brain-computer interfaces (BCIs) are utilized. For instance, the European Union’s (GDPR) and the California Privacy Rights Act (CPRA) define biometric information broadly, implying that neurodata could fall under their rules. Examples of biometric data include fingerprints, facial features, iris patterns, voiceprints, and more. Neurodata, which refers to data collected from the brain or nervous system, could potentially be considered a type of biometric data if neurodata is used to identify people or could potentially be used in such a manner. Neurotechnology research is still in the early stages.

If these privacy laws are triggered, they impose specific obligations on organizations that are regulated by them, while also granting certain rights to people whose data is being processed. Neurodata processing may lead to additional rules under these laws. For instance, if a healthcare facility employs BCI technology to oversee patients’ neural patterns and identify potential signs of neurological conditions, this utilization of neurodata would fall within the purview of the Health Insurance Portability and Accountability Act (HIPAA) in the United States. The institution would need to ensure the collection, storage, and sharing of patients’ neurodata comply with HIPAA’s stringent regulations on safeguarding sensitive health information. Additionally, if courts determine that the neurodata, including brainwave patterns, contain biometric identifiers or are covered by statutory definitions of biometric data, it could trigger obligations under state-specific laws like Illinois’ Biometric Information Privacy Act (BIPA), which requires obtaining informed consent and protecting biometric data from unauthorized access.

In a significant milestone toward conducting human clinical trials in the United States, another neurotech company recently obtained an investigational device exemption (IDE) from the U.S. Food and Drug Administration (FDA). This exemption grants permission to utilize their device in clinical studies. However, detailed information regarding the specifics of these trials, including their scope, focus, and design, has not been publicly disclosed. Privately held companies are not obligated to provide extensive details about their regulatory interactions with the FDA, making it challenging to gain a comprehensive understanding of the approval process and trial parameters. The FDA mentioned it follows an evaluation process to ensure the safety and effectiveness of medical devices. The agency also emphasized its commitment to responsible and humane treatment of animals involved in testing.

Steps for FDA Device Approval

Before marketing the technology in the United States, medical devices must undergo several review steps. These include device classification, choosing the appropriate premarket submission, preparing submission data, interacting with FDA during a review, and completing establishment registration. Neurological devices often require an IDE submission before data collection for a premarket submission. BCI’s often are approved for investigational device exemption’swhich allow devices not yet approved for the market to be used in clinical studies to gather safety and effectiveness data. FDA establishes a review team based on device technology and intended use, considering benefits and risks. Demonstrating device safety is crucial in IDE approval, with specific attention to the patient population, implantation, stimulation-related risks, imaging, and more.

When developing BCI’s, the first step involves understanding the classification of these devices, which serves as a compass guiding the development process. The FDA categorizes medical devices based on the risks they pose, a classification that can evolve as scientific insights emerge. This classification system entails three primary classes, each carrying distinct regulatory requirements.

Image Source

Class 1 devices are those with the least risk to consumers, such as oxygen masks and surgical tools. These devices are subject to “general controls,” or a set of regulations that ensure their safety and efficacy post-manufacturing. Class 2 devices present higher risks to consumers and require “special controls” in addition to general ones. These controls encompass specific labeling, performance standards, and testing requirements. The highest risk are Class 3 devices, including life-supporting implants or high-risk diagnostic tools. These devices demand premarket approval, entailing the demonstration of both safety and effectiveness.

Moving beyond the classifications, the development of a medical device commences with innovation and recognition of unmet medical needs. Researchers embark on the creation of device concepts that could revolutionize healthcare. From these concepts emerges the “proof of concept,” a document outlining the idea’s feasibility. This dynamic step is characterized by adaptation and refinement, as concepts showing promise progress toward further stages of development.

As concepts take shape, the second step leads us to preclinical research and prototyping. Here, researchers craft early versions of medical devices, prototypes that aren’t yet fit for human use. These prototypes undergo rigorous testing in controlled laboratory settings, where the product’s potential benefits and risks are evaluated. This phase, though meticulous, cannot entirely eliminate risk, but it endeavors to reduce potential harm when the devices reach human subjects.

Navigating the regulatory landscape forms the third step, where the pathway to approval is delineated, contingent upon the device’s risk classification. The diverse classification spectrum translates into a range of pathways, offering developers options that align with their device’s level of risk.

In the penultimate stage, or the FDA Device Review, developers with comprehensive safety and effectiveness data can proceed to file applications for device marketing. This step varies depending on the device’s class, with Class 1 and 2 devices requiring premarket notification or an application comparing the new device to existing ones and Class 3 devices necessitating a more comprehensive premarket approval application. This process ensures that devices reaching the market are scrutinized and held to stringent standards.

Finally, even after a device secures approval and enters the market, the review does not end. The FDA Post-Market Device Safety Monitoring phase acknowledges that new safety concerns might emerge post-launch. Rigorous manufacturer inspections, problem-reporting programs, and active surveillance mechanisms are deployed to ensure the continued safety and effectiveness of medical devices.

Conclusion

The journey from lab to legislation reveals the potential of brain-machine interfaces. These interfaces, aiding people with physical limitations, come with ethical and legal responsibilities, particularly in safeguarding our neurodata. Laws like GDPR and CPRA can help protect our privacy as this technology advances in healthcare and beyond. This process highlights the balance between innovation and respecting privacy, guiding us towards a future where neurotechnology aligns with privacy principles and enhances lives.