The Promise of Digital Therapeutics
According to Wikipedia, digital therapeutics can be defined as a treatment or therapy that utilizes digital health technologies to spur changes in patient behavior. The first mention of the term in a peer-reviewed research publication was in 2015, in which Dr. Sepah et al. defined “digital therapeutics” as “evidence-based behavioral treatments delivered online that can increase accessibility and effectiveness of health care.” See Long-Term Outcomes of a Web-Based Diabetes Prevention Program: 2-Year Results of a Single-Arm Longitudinal Study, J Med Internet Res 2015 | vol. 17 | iss. 4 | e92.
The methods employed by digital therapeutics can be used as a stand-alone therapy or in conjunction with more conventional treatments, such as pharmacological or in-person therapy. Such methods use various digital devices (e.g., smartphones, apps, sensors, computers) to help manage, monitor and prevent illnesses in at-risk patients. These devices are used to collect data from different sources. Such data may include personalized physiological parameters; behavior, social and geographical patterns; and even data indicative of the user’s mood or feelings.
In the mental health area, we believe that digital therapeutic approaches can overcome three of the biggest problems with conventional therapies: lack of access, lack of affordability and stigma. The problems with access and affordability are mainly caused by the relative scarcity of trained counselors as compared to the number of people in need of counseling. Stigma, on the other hand, is a psychological impediment to seeking help based on a person’s feeling of shame about his or her mental afflictions. The field of digital therapeutics offers the promise of delivering behavior therapies safely and effectively via a digital device, and thereby largely overcome the problems of access, affordability and stigma. For this reason, we believe that now is a good time to invest in the digital therapeutics space.
FDA Regulatory Environment: Software as a Medical Device
Software has become an important part of all products, integrated widely into digital platforms that serve both medical and nonmedical purposes. Software, which on its own is a medical device, called Software as a Medical Device (SaMD), is one of three types of software related to medical devices. The other two types are software that is integral to a medical device (software in a medical device) and software used in the manufacture or maintenance of a medical device. See also Software as a Medical Device (SAMD): Clinical Evaluation – Guidance for Industry and Food and Drug Administration Staff. The term Software as a Medical Device is defined by the International Medical Device Regulators Forum (IMDRF) as “software intended to be used for one or more medical purposes that perform these purposes without being part of a hardware medical device.” Examples of SaMD include
- software that allows a smartphone to view images obtained from an MRI medical device for diagnostic purposes;
- computer aided detection (CAD) software that performs image post-processing to help detect breast cancer; and
- software with a medical purpose that operates on a general purpose computing platform, e.g., software intended for diagnosis of a condition using the tri-axial accelerometer that operates on the embedded processor on a consumer digital camera.
In addition, the FDA has recognized that artificial intelligence (AI) and machine learning (ML) technologies have the potential to transform healthcare by deriving important insights from the data generated during the delivery of healthcare. Medical device manufacturers are using these technologies to innovate their products. The FDA is considering a total product life cycle-based regulatory framework for these technologies that would allow for modifications to be made from real-world learning and adaptation, while still ensuring that the safety and effectiveness of the software as a medical device is maintained. Adaptive AI/ML technologies differ from other SaMD in that they have the potential to adapt and optimize device performance in real time to continuously improve healthcare for patients.
Traditionally, the FDA reviews medical devices through an appropriate premarket pathway, such as premarket clearance (510(k)), De Novo classification or premarket approval. The FDA may also review and clear modifications to medical devices, including SaMD, depending on the significance or risk posed to patients by that modification. The FDA’s traditional paradigm of medical device regulation was not designed for adaptive artificial intelligence and machine learning technologies. Under the FDA’s current approach to software modifications, AI- and ML-driven software changes to a device may need a premarket review.
On April 2, 2019, the FDA published the discussion paper Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) – Discussion Paper and Request for Feedback that describes the FDA’s foundation for a potential approach to premarket review for AI- and ML-driven software modifications. The ideas presented leverage practices from current premarket programs and rely on IMDRF’s risk categorization principles. The FDA introduces a “predetermined change control plan” in premarket submissions, which would include the types of anticipated modifications – referred to as the “Software as a Medical Device Pre-Specifications” – and the associated methodology being used to implement those changes in a controlled manner that manages risks to patients – referred to as the “Algorithm Change Protocol.” In this approach, the FDA would expect a commitment from manufacturers on transparency and real-world performance monitoring for AI- and ML-based software as a medical device, as well as periodic updates to the FDA on what changes were implemented as part of the approved pre-specifications and the algorithm change protocol. The proposed regulatory framework could enable the FDA and manufacturers to evaluate and monitor a software product from its premarket development to post-market performance.
To summarize, SaMD is software used for one or more medical purposes without being part of a hardware medical device. Examples include software that allows commercially available devices to view and process images or other data for diagnostic purposes. SaMD does not include software that drives or controls a medical device, embedded software (firmware), nonmedical software that just encrypts data (medical records), and software that enables clinical communication and workflow such as patient registration, scheduling visits, voice calls and video calling.
In the final part of the series, I will explore the 21st Century Care Act, mobile medical application, medical device IP considerations and provide some reasons to invest in digital therapeutics.