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Newsletter Summer 2019 - M Prasad Palthur, Artificial Pancreas Device Systems (ADPS) – General Product Development and Regulatory Pathways

Artificial Pancreas Device Systems (ADPS) General Product Development and Regulatory Pathways 

M Prasad Palthur, PhD 

Co-founder & VP, Design & Development, Innoneo Health Technologies, Inc. 

This article is a continuation and extension of the article Artificial pancreas device systems – an evolving approach and research pathway. 

ABSTRACT: 

The modular architecture of artificial pancreas device systems (APDS) consists of various functional components that must be functionally compatible as a medical device and work together as a closed loop system. APDS falls under a specialized product category – the technology is complex, and the regulatory scenario is generally multifaceted. In general, APDS demands a more carefully tailored regulatory approach for each of the functional components within the APDS and the APDS as a comprehensive system. The modular architecture may also require diverse requirements for performance, software, biocompatibility, sterility, shelf life, electrical safety, magnetic resonance imaging safety, user interface, data management, and human factors.  

The FDA intends for a future regulatory model to provide more streamlined and efficient regulatory oversight of APDS.As the FDA is creating a more efficient regulatory process, italso recognizes the inherent risks of regulating APDS. 

A regulatory-science driven and outcome-oriented regulatory strategy is an essential part of today's medical device early development planning and successful product development. Judicious and well-executed regulatory strategy, as well as proactive and cooperative interactions with regulatory authorities, is often a critical factor for bringing successful and innovative APDS products to the market. An early understanding of the registration requirements offers efficiencies that can be realized throughout the development. Early engagement of an experienced team of regulatory professionals, regulatory consultants, and compliance consultants is advised to help with compliance and regulatory efforts. This article intends to provide key references and sources of information to conceptualize a generalizedAPDS product development and regulatory strategies. 

ABBREVIATIONS 

American National Standards Institute (ANSI) 

Artificial Pancreas (AP) 

Artificial Pancreas Device Systems (APDS) 

American Society for Testing and Materials (ASTM) 

Association for the Advancement of Medical Instrumentation (AAMI) 

Clinical and Laboratory Standards Institute (CLSI) 

Continuous Glucose Monitoring (CGM) 

Continuous Subcutaneous Insulin Delivery (CSII) 

Diabetes Technology Society (DTS) 

Federal Food, Drug, and Cosmetic Act (FD&C Act) 

Institute of Electrical and Electronics Engineers (IEEE) 

International Electrotechnical Commission (IEC) 

International Medical Device Regulators Forum (IMDRF) 

International Organization for Standardization (ISO) 

Juvenile Diabetes Research Foundation (JDRF) 

Premarket Approval application (PMA) 

Real-time Continuous Glucose Monitoring (rtCGM) 

U.S. Food and Drug Administration (FDA) 

INTRODUCTION  

The fourth industrial revolution combines the physical, digital, and biological spaces and is rapidly changing the healthcare industry [1].The internet-of-things (IoT), wireless medical devices, mobile medical apps, digital health software, and a vast and heterogeneous combination of sensors capable of generating actionable information are transforming the landscape of digital and connected healthcare [2,3]. Many innovative digital health tools, such as wearable sensors and companion software that provide information, decision support, or even control of a drug delivery system, are being developed. As a result of this industrial revolution, the fusion of physical, digital, and biological technologies allowpatients to be connected to each other, their caregivers, and clinicians [4]. 

Data generated online and by digital technologies representby the quantity and variety of informationa major potential to modify the way people with diabetes are monitored to identify new digital markers and patterns of risk [5].In recent years, digital biomarker development has begun integration into translational and clinical research [6].The development of data science methods and artificial intelligence (AI) adapted for health data has led to the development of ecosystems of digital tools and digital interventions for behavioral changes tailored to patient preferences and characteristics [5, 7].Additionally, digital health methodologies are well positioned to improve patient identity, patient privacy, study transparency, data sharing, competent informed consent, and the confidentiality and security of humanitarian operations [8]. 

As an area of therapy with the best market potential and one of the most expensive global diseases, diabetes attracts healthcare players to embrace innovative technologies [9].Data from the industry, academic, and regulatory communities indicate that there is a recent surge of interest in digital health as a paradigm for treating diabetes and other chronic diseases.Ultimately, digital advancements and the innovation of future technology will lead to more patient-centered and highly personalized resources that, in turn, will improve the delivery of diabetes care and overall quality of life [10].Although digital solutions have a considerable potential to modify the diabetes ecosystem, many barriers and challenges persist [5]. 

Given the hyper transformation of technology and business models, the discovery, development, and deployment paths of medical devices, particularly of digital health products, have recently transformed significantly and resulted inthe emergence of new product categories like APDS andsoftware-as-a-medical device (SaMD). 

MEDICAL DEVICE DEVELOPMENT – TRANSFORMATION AND STRATEGIC PLANNING 

Medical device developmentgenerally follows a well-established path. The development of a successful medical device requires not only reliable engineering design, but also clinical, regulatory, marketing, and business proficiency.The conventional medical device discovery, development, and deploymentframework includesa dynamic representation of thetranslational science, regulatory science, modern engineering, and therapeutic development process to expedite new therapies for patients.“Regulatory science” integrates the knowledge within and among basic science research, clinical research, clinical medicine, and other specific scientific disciplines, focusing on product development and regulatory decision making [11, 12].“Translational science” is generally the application of the scientific method to address a health need [12].The translation is the process of turning observations in the laboratory, clinic, and community into interventions that improve the health of individualsand induce behavioral changes [13]. 

However, the contemporary medical device framework of discovery, development, and deployment embraces the inclusion of human-centered design, clinically-inspired engineering, patient-inspired approaches, and human factors engineering. Human factors engineering is the discipline thatintegrates human physical and psychological characteristics in the design of devices and interactive systems that involve people, tools and technology, and environments to ensure safety, effectiveness, and ease of use [14]. A patient-inspired approach focuses on the clinical problem(s) and needs of the patient. Human-centered design is considered an integral part of both regulatory compliance and commercial success. 

On the other hand, medical devices related to digital health consider the inclusion of advanced sensor technologies, artificial intelligence technologies, machine learning technologies, intelligent decision support systems, health informatics, software intended for medical purposes, and cybersecurity approaches.Intelligent decision support systems aid the better diagnosis, therapeutic guidance, and tailored treatment plan [15]. Data mining-based intelligent decision support systems are embedded with concepts like data mining, neural networks, deep learning, and evolutionary algorithms [16]. These advanced technologies facilitate the application of systematic, quantitative, and integrative digital health approaches.  

Additionally, medical devices that aim for automated and closed-loop drug delivery need to consider three aspects of interdisciplinary research: (i) modeling of physiological processes on a whole-body level; (ii) using optimal control theory for designing therapy protocols; and (iii) using simulation and analysis techniques for identification of complex intracellular regulatory mechanisms [17]. 

Moreover, medical devices related to digital health, such as computer systems, can be vulnerable to security breaches, potentially impacting the safety and effectiveness of the device. The product development approach should better anticipate cybersecurity risks and apply mitigation strategies early in the total product lifecycle of a device and with increased agility throughout the device lifespan as necessary. Examples of strategies include:identifying and preparing for cyber intrusions, reducing medical device vulnerabilities, mitigating potential impacts on patients, and enabling timely restoration of devices and systems [18]. 

Strategic planning of medical device development and deployment is dependent on a well-conceptualized regulatory strategy. A regulatory-science driven and outcome-oriented regulatory strategy is an essential part of today's medical device early development planning and successful product development. Furthermore, such regulatory strategy can facilitate a central agenda for the overall development plan, align the clinical development plan with business objectives, and assist in defining the value path to market. Furthermore, it can enable the synchronization of technical, nonclinical, and clinical requirements required for registration, as well as preemptively identify challenges and proposed alternative/innovative approaches.  

For brevity, a regulatory strategy is expressed as a formal document that aligns regulatory activities to bring a new or modified product to market with the business strategy for that product. A regulatory plan is a document that describes the specific steps and actions required to successfully meet the regulatory strategy objectives. A comprehensive and systematic approach to regulatory compliance is vital for medical device manufacturers to more accurately plan the resources and time required to achieve compliance, leverage new standards for evidence generation, support continuing development, and gain global market authorizations.  

 MEDICAL DEVICE DEVELOPMENT – MODULAR ARCHITECTURE AND UNIQUE REQUIREMENTS OF APDS 

For this article, APDS is used to generalize the context of integrated systems and technologies of electromechanical AP approaches. A hundred years after the discovery of insulin, the technology is entering the stage of fully automated portable APDS that provides real-time, long-term optimal control of diabetes in patients’ natural environments [19]. 

 APDS as a medical device embodies the modular architecture of various functional components. In general, APDS modular architecture, at a minimum, represents the following functional components: 

  1. Continuous Glucose Monitoring (CGM) Component 

  1. Continuous Subcutaneous Infusion (CSI) Pump Component 

  1. Control Algorithm (CA) Component  

  1. Communication Pathway (CP) Component 

  1. User Interface (UI) Component 

The modular architecture of AP systems on both the hardware and software level allows APDS to be assembled from independent but compatible modules, each performing a specific function [20]. 

There are several AP systems currently under development in both academic and commercial endeavors. APDS systems in development can be broadly grouped into those using dedicated embedded hardware, those relying on a dedicated locked-down smartphone device, or some combination of the two approaches [21].Each system offers unique features in the configuration of pumps, glucose sensors, algorithms, single- or dual-hormone delivery functionality, user interface, and data management. Also, various closed-loop APDS systems employ different combinations of hormonal approaches, control algorithms, and glycemic control strategies [22]. This modular architecture may also require different types of partnerships or business ecosystems and may represent new roles for digital health companies to increase the adoption of advanced technologies and accelerate innovation. 

The modular architecture of APDS systems allows for accommodation of rapidly changing diabetes device technology and advanced algorithms [23].However, the modular architecture may also require diverse requirements for performance, software, biocompatibility, sterility, shelf life, electrical safety, magnetic resonance imaging safety, and human factors. This modular architecture positions a complex regulatory scenario for each of the functional components within the APDS systemand the APDS system as a whole.  

The unique requirements of APDS can have a substantial impact on the size of the clinical development program as well as on the risk. APDS is a more specialized product category – the technology is more complex, and the regulatory environment may be intricate. An early understanding of the registration requirements offers efficiencies that can be realized throughout the development of a novel APDS product. Judicious and well-executed regulatory strategy, as well as proactive and cooperative interactions with regulatory authorities, is often a critical factor for bringing successful and innovative APDS products to market.  

  1. USA REGULATORY SCENARIO 

  1. Medical Devicesin General 

In general, the product approval process takes place within a structured framework that includes analysis of the target condition and available treatments, assessment of benefits and risks from clinical data, and strategies for managing risks [24]. 

The Food and Drug Administration (FDA) Center for Devices and Radiological Health (CDRH) supports and fosters medical device innovation as it upholds its mission of ensuring that medical devices are safe and effective. CDRH provides comprehensive regulatory resources that explain many aspects of medical device law, regulation, guidance, and policies encompassing the entire product life cycle [25]. 

Federal law (FD&C Act, section 513) established the risk-based device classification system for medical devices. Regulatory classes for medical devices are based on the level of control necessary to provide reasonable assurance of its safety and effectiveness. The FDA assigns devices to 3 main regulatory classes: Class I (low to moderate risk; required general controls), Class II (moderate to high risk; required general controls and special controls), and Class III (high risk; required general controls and premarket approval (PMA)) [26]. 

Device product classifications can be found by searching the Product Classification Database [27]. The database provides the name of the device, classification, and a link to the Code of Federal Regulations (CFR), if any. If there are 510(k)s cleared by FDA and the new device is substantially equivalent to any of those cleared devices, then the sponsor/applicant should submit a premarket submission (510(k)). If the proposed device is a high-risk device and is not substantially equivalent to a Class I, II, or Class III device with a 510(k), then the sponsor/applicant must submit a PMA before marketing in the U.S.  

Class I, II, and III devices intended for human use, for which a PMA is not required, must submit a 510(k) to FDA, unless the device is exempt from the 510(k) requirements of the FD&C Act and does not exceed the limitations of exemptions [28].A 510(k) is a premarket submission made to FDA to demonstrate that the device to be marketed is at least as safe and effective (i.e., substantially equivalent) to a legally marketed device (21 CFR 807.92(a)(3)) that is not subject to PMA. Substantial equivalence has to be established concerning: intended use, design, energy used or delivered, materials, performance, safety, effectiveness, labeling, biocompatibility, standards, and other applicable characteristics. FDA’s 510(k) submission process webpage provides additional aspects of laws, regulations, guidance, and policies encompassing the entire product life cycle [29]. 

Premarket approval (PMA) is the FDA process of scientific and regulatory review to evaluate the safety and effectiveness of Class III medical devices. PMA is the most stringent type of device marketing application required by the FDA. The applicant must receive FDA approval of its PMA application before marketing the device. PMA approval is based on a determination by FDA that the PMA contains sufficient valid scientific evidence to assure that the device is safe and effective for its intended use(s). FDA’s PMA webpage provides additional aspects of laws, regulations, guidance, and policies encompassing the entire product life cycle [30]. 

Some devices that are found to be not substantially equivalent to a cleared Class I, II, or III (not requiring PMA) device may be eligible for the de novo process as a Class I or Class II device. The de novo process provides a pathway to classify novel medical devices for which general controls alone, or general and special controls, provide reasonable assurance of safety and effectiveness for the intended use, but for which there is no legally marketed predicate device [31, 32]. Manufacturers must identify a primary predicate device that is most similar to the device under review with respect to indications for use and technological characteristics. Manufacturers may identify more than one predicate device to help demonstrate substantial equivalence in certain circumstances [32]. 

Medical devices may have one or more accessories that support, supplement, and/or augment the performance of the parent device. An accessory is a finished device that is intended to support, supplement, and/or augment the performance of one or more parent devices [33]. FDA will classify an accessory based on the risks of the accessory when used as intended and the level of regulatory controls necessary to provide reasonable assurance of the safety and effectiveness of the accessory, notwithstanding the classification of any other device with which such accessory is intended to be used.The guidance document “Medical Device Accessories Describing Accessories and Classification Pathways” [34] describes the risk- and regulatory control-based framework for the classification of accessories separate from the classification of parent devices and the appropriate processes for submitting an accessory classification request [33]. An accessory classification request is a written request submitted to the FDA under section 513(f)(6) of the FD&C Act. 

Digital health technology changes at a rapid pace, and the regulatory landscape for digital health is constantly evolving. The traditional paradigm of medical device regulation does not suit digital health technologies in a way that optimizes and fully leverages their potential impact on healthcare and patients [35].

The FDA is working to align itself with the needs of the digital health industry and recognizes that a new regulatory pathway is needed to enable products to be available to patients faster without compromising safety or effectiveness [10]. The FDA's CDRH has established the Digital Health Program, which seeks to better protect and promote public health and provide continued regulatory clarity by: (a) fostering collaborations and enhancing outreach to digital health customers, and (b) developing and implementing regulatory strategies and policies for digital health technologies [36].Early FDA publications on digital health contained three important novel initiatives: (a) clarity on the medical software provisions of the 21st Century Cures legislation, (b) launch of a pilot precertification program (called the FDA Pre-Certification for Software), and (c) expansion of the FDA’s digital health expertise by creating a Center of Excellence (CoE)for Digital Health. This new CoE also will create a cybersecurity unit to complement advances in software-based devices and to aid in the review of cyber advances affecting the more traditional hardware and software-based medical devices. 

The highly iterative nature of digital health technologies requires a flexible regulatory approach to allow product developers, patients, and regulators to keep pace with the software updates that frequently happen in this space. Having a regulatory framework that enables a rapid cycle of product improvement is integral to ensuring innovation and success for digital health technologies. 

As medical devices become more digitally interconnected and interoperable, they can improve the care patients receive and create efficiencies in the health care system. However, medical devices, like computer systems, can be vulnerable to security breaches, potentially impacting the safety and effectiveness of the device [18]. Ensuring that medical devices are safeguarded from cyber intrusions is a shared responsibility across the medical device ecosystem.  

The FDA’s role and commitment to medical device cybersecurity continue to increase in scope and nature, considering the implications of compromised devices across their total product lifecycle [18, 37]. The FDA has been working to stay a step ahead of these changing cybersecurity vulnerabilities. The FDA has issued draft guidance that provides updated recommendations to industry on cybersecurity considerations for device design, labeling, and documentation that the FDA recommends being included in premarket submissions for medical devices with cybersecurity risk. This guidance incorporates new recommendations, including premarket submission of a “cybersecurity bill of materials” (analogous to the ingredient list for a medication), which is a list of commercial and/or off-the-shelf software and hardware components of a device that could be susceptible to vulnerabilities [38]. 

FDA intends for a future regulatory model to provide more streamlined and efficient regulatory oversight of software-based medical devices [39].Historically, most softwareproducts have been categorized as software in a medical device (SiMD), which operates the device and sensors (e.g., firmware). More recently, they are categorized as software as a medical device (SaMD) solutions [6].The term “SaMD is defined by the International Medical Device Regulator’s Forum (IMDRF) as software intended to be used for one or more medical purposes without being part of a hardware medical device [40]. 

As theFDA is creating a more efficient regulatory process, italso recognizes the inherent risks to software and digital products that may not be as visible as those in other types of products that FDA regulates. The FDA is collaborating with stakeholders in the medical device ecosystem to build the National Evaluation System for health Technology (NEST) to more efficiently generate better evidence for medical device evaluation and regulatory decision-making. The collaborative national evaluation system will link and synthesize data from different sources across the medical device landscape, including clinical registries, electronic health records, and medical billing claims [41]. 

  1. Medical Devices –ADPS 

APDS consists of separate components that must be functionally compatible as a medical device, and the components work together as a closed loop system [42].The modular architecture of APDS systems allows for accommodation of rapidly changing diabetes device technology and advanced algorithms [23]. However, the modular architecture may also require diverse requirements for performance, software, biocompatibility, sterility, shelf life, electrical safety, magnetic resonance imaging safety, and human factors. This modular architecture positions a complex regulatory scenario for each of the functional components within the APDS system and the APDS system as a whole.  

Currently, APDS components are authorized for sale as diabetes management devices only in a specific configuration, while others are authorized for use with other compatible devices, which may include automated insulin dosing systems, insulin pumps, blood glucose meters, or other devices used for diabetes management. Some of these diabetes management devices may be reviewed by the FDA as a whole system, or they may be reviewed to be compatible with other FDA-authorized components, such as integrated continuous glucose monitoring (CGM) systems [43]. This is known as interoperability, which allows patients to safely tailor their diabetes management to their individual preferences by choosing devices that are authorized by the FDA to work together. For example, an authorized automated insulin dosing system will include a specific CGM system, a specific insulin pump, and a specific algorithm. These devices are all tested and authorized together as a system.  

Recently, FDA has issued safety communication warning patients and health care professionals of risks associated with the use of unapproved or unauthorized devices for diabetes management, including CGM systems, insulin pumps, and automated insulin dosing systems [44].Earlier in 2019, FDA received a report of a serious adverse event, in which a patient used an unauthorized device that received electronic signals from an FDA-authorized glucose sensor and converted it to a glucose value using an unauthorized algorithm [43].In its communication FDA expressed its concern around the movement known as the do-it-yourself (DIY) approach. The Open Artificial Pancreas System (OpenAPS) movement includes individuals building their own DIY closed-loop systems from commercially available insulin pumps (although sometimes out of warranty), CGM devices, and an open-source algorithm [45].The algorithms used in DIY APS are currently unregulated and untested in clinical trials. While CGM and insulin pump technology are regulated for use in diabetes care, their use in combination with DIY APS algorithms makes their use off-label [46].The risks are unknown, but could relate to the algorithm itself, user interaction with the system, general safe pump use, or use of out-of-warranty pumps [46].Also, when devices that are not intended for use with other devices are combined or when unauthorized devices are used, new risks that have not been properly evaluated by the FDA for safety are introduced.Efficient and effective algorithms are routinely developed and embedded in various formats for closed-loop control of APDS.  

A challenge to the evaluation of algorithms is that many are proprietary, patented, or are trade secrets. Structured collaboration between engineers, mathematicians, computer scientists, data scientists, and clinical researchers is required for mathematical modeling, simulation, and formal analysis for the development of efficient algorithms. Future work may involve the achievement of greater sensitivity by factoring specific aspects of body physiology, patient statistics to fine-tune control parameters, algorithm self-learning capabilities, and integration of auxiliary sensors for individualized treatment and treatment adaption over time [47].FDA recently announced steps to consider a new regulatory framework specifically tailored to promote the development of safe and effective medical devices that use advanced artificial intelligence algorithms [48]. The artificial intelligence technologies granted marketing authorization and cleared by the Agency so far are generally called “locked” algorithms that don’t continually adapt or learn every time the algorithm is used [48].On the other hand, machine learning algorithms that continually evolve are often called “adaptive” or “continuously learning” algorithms. These algorithms can learn from new user data presented to the algorithm through real-world use. 

As the current diabetes technology ecosystem is heterogeneous, a major concern in an APDS system is interoperability [21]. Development of soluble pumpable glucagon, dual-chamber pumps, and dual-lumen catheters, as well as finalization of algorithms,is considered one of the main challenges for the dual-hormone approach [47].Zealand Pharma is working with Beta Bionics on a next-generation first-in-class dual-hormone APDScontaining both insulin and glucagon (dasiglucagon) which guided by an algorithm could maintain and control blood glucose levels without the need for patient intervention [49]. 

The unique requirements of APDS can have a substantial impact on the size of the clinical development program as well as on the risk. To appropriately evaluate the effectiveness, risks, and benefits of an APDS, different kinds of clinical studies may be needed [42]. Studies might be conducted in clinical research centers and/or transitional settings. Transitional settings are similar to clinical research settings because they provide ready access to health care providers and monitoring equipment, but patients have more control over daily activities during the study period. To gain FDA approval to market an APDS, investigators will generally perform an outpatient study. In many cases, patients in the study will use the devices in their homes while under the care of a doctor or nurse [42]. 

Recent advances in the development of mobile digitally connected technologies have led to the emergence of a new class of biomarkers measured across multiple layers of hardware and software [6].Digital biomarkers are consumer-generated physiological and behavioral measures collected through connected digital tools [50].The modular software-hardware combination has created new opportunities for patient care and biomedical research, enabling remote monitoring and decentralized clinical trial designs [6]. The identification of new digital biomarkers, based on data generated by CGMs or other connected devices, is likely to profoundly change clinical practice by moving from an era in which controlling HbA1c is the gold standard to an era where an individualized approach towards HbA1c monitoring can be combined with parameters derived from these devices, including time spent in range, glycemic exposure, glycemic variability, and hypo- and hyperglycemia [5].For example, Eli Lilly & Co. is expanding its collaboration with Evidation Health into a multi-year project aimed at developing digital biomarkers [51].However, a systematic approach to assessing the quality and utility of digital biomarkers to ensure an appropriate balance between their safety and effectiveness is needed [6]. Furthermore, verification and validation of digital biomarkers require a uniquely collaborative approach, with engineering, data science, health information technology, and clinical research functions tightly coordinated as integrated multidisciplinary units. 

An early understanding of the registration requirements offers efficiencies throughout the development of a novel APDS product. Conceptualizing a regulatory strategy of APDS is dependent on multiple factors: the nature of hardware components, software components, integration of software and hardware to provide reasonable assurance of performance, safety and effectiveness, substantial equivalency to any cleared devices, and intended use.Sponsors and/or applicants are advised to review the Total Product Life Cycle (TPLC) database [52]. It includes information pulled from CDRH databases including PMAs, Premarket Notifications (510(k)), adverse events, and recalls, presenting an integrated record of premarket and postmarket activity for medical devices [52]. 

Additionally, each of the functional components within an APDS may have a differentregulatory device classification and can be different from the complete APDS system. An example is analternate controllerenabled insulin infusion pump (Class II), bi-hormonal control automated insulin dosing device system (Class III), integrated CGM system for non-intensive diabetes management (Class II), and CGM retrospective data analysis software (Class I). Table 1 represents a few examples of device classification of APDS components in the US and their regulation reference. Furthermore, accessories that support, supplement, and/or augment the performance of APDS may have a different level of regulatory control necessary to provide a reasonable assurance of safety and effectiveness of the accessory, notwithstanding the classification of the parent device. 

 

Table 1: Examples of APDS Components and Device Classifications 

Product Code 

Medical Device 

Device Class 

Regulation Number 

QBJ 

Integrated continuous glucose monitoring system, factory calibrated [53] 

2 

862.1355 

QDK 

Integrated continuous glucose monitoring system for non-intensive diabetes management [54] 

2 

862.1355 

QDL 

Integrated continuous glucose monitoring system for professional retrospective use [55] 

2 

862.1355 

LZG 

Pump, Infusion, Insulin 

2 

880.5725 

OPP 

Pump, Infusion, Insulin bolus [56] 

2 

880.5725 

QCD 

Continuous glucose monitor, implanted, adjunctive use [57] 

3 

None referred 

OYC 

Pump, infusion, insulin, to be used with invasive glucose sensor 

3 

880.5725 

OZO 

Automated insulin dosing, threshold suspend [58] 

3 

880.5725 

OZP 

Automated insulin dosing device system, single hormonal control [59] 

3 

880.5725 

OZQ 

Automated insulin dosing device system, bihormonal control [60] 

3 

880.5725 

PKU 

Insulin pump secondary display [61] 

2 

862.1350 

QCC 

Insulin pump therapy adjustment calculator for healthcare professionals [62] 

2 

862.1358 

QFG 

Alternate controller enabled insulin infusion pump [63] 

2 

880.5730 

PHV 

Continuous glucose monitor retrospective data analysis software [64] 

1 

862.2120 

FDA is helping to advance the development of APDS by prioritizing the review of research protocol studies, providing clear guidelines to industry, setting performance and safety standards, fostering discussions between government and private researchers, co-sponsoring public forums, and finding ways to shorten study and review time [65].Additionally, the FDA is involved in developing two standards related to the APDS: a CGMstandard (CLSI POCT05-A) that discusses performance characteristics, and a standard that discusses characteristics of a feedback control system applied to closed-loop control algorithms, such as the one used in the artificial pancreas (ISO 60601-1-10) [65]. 

FDA recently authorized the first interoperable insulin pump intended to allow patients to customize treatment through their individual diabetes management devices [66]. Tandem’s Diabetes Care t:Slim X2 insulin pump has interoperable technology (interoperable t:Slim X2) for delivering insulin under the skin for children and adults with diabetes [67].This new type of insulin pump, referred to as an alternate controller enabled (ACE) infusion pump (or ACE insulin pump) can be used with different components that make up diabetes therapy systems, allowing patients to tailor their diabetes management to their individual device preferences.Because of the interoperability with other diabetes device components, the ACE pump was reviewed through the de novo premarket review pathway, a regulatory pathway for novel, low-to-moderate-risk devices of a new type.  

Because FDA’s ACE insulin pump authorization created a new regulatory classification [63], future ACE insulin pumps will be able to go through the more efficient 510(k) review process, helping to advance this innovative technology [66]. Along with this authorization,the FDA is establishing criteria called special controls, which outline requirements for assuring the accuracy, reliability, cybersecurity, and clinical relevance of ACE infusion pumps, as well as describe the type of studies and data required to demonstrate acceptable pump performance.  

Various prescription-only software medical device for dosing recommendations have also been approved. These products have potential to interface with APDS in the near future. Glucommanderis a therapy management cloud-based software solution suite of FDA-cleared proprietary algorithms for intravenous, subcutaneous, and pediatric insulin dosing [68].Insulia® is a prescription-only software medical device intended for use by healthcare professionals and adult type 2 diabetes patients treated with long-acting insulin analogs as an aid that recommends basal insulin doses based on the treatment plan created by the healthcare provider [69]. Mellitus Health's Insulin Insight software makes precision insulin dosing recommendations in seconds, enabling clinicians to optimize insulin regimens [70]. 

  1. RECOMMENDED SOURCES OF INFORMATION AND REFERENCES 

Although this article attempts to be a comprehensive guide, it is impossible for an article to be an all-inclusive exhaustive guide. This article intends to provide key references and sources of information to conceptualize APDS general product development and regulatory strategies. 

  1. Regulations, guidance, and informationrelated to the product development and regulatory affairs of APDS and its components 

  • Guidance for Industry and FDAStaff: The Content of Investigational Device Exemption (IDE) and Premarket Approval (PMA) Applications for Artificial Pancreas Device Systems [71] 

  • FDA Artificial Pancreas Device Systems website [72] 

  • American Diabetes Association. Diabetes Technology: Standards of Medical Care in Diabetes2019 [73] 

  • FDA databases: 510(k) Premarket Notification database [74], Premarket Approval (PMA) database [75], and Device Classification under Section 513(f)(2)(de novo) [76] 

  • Total Product Life Cycle (TPLC) databasepresents an integrated record of premarket and postmarketdata for medical devices [52] 

  • FDA infusion pumps webpage for specific information and regulatory scenarios of infusion pumps, one of the functional components that make an APDS [77] 

  • Guidance for Industry and FDA Staff: Infusion Pumps Total Product Life Cycle [78] 

  • Ongoing and completed clinical trials of APDSU.S. National Library of Medicine resource ClinicalTrials.gov [79] 

  • FDA Software as a Medical Device (SaMD) website [80]  

  • Guidance for Industry and FDA Staff: Software as a Medical Device (SAMD): Clinical Evaluation [81] 

  • Global Approach to Software as a Medical Device Software as a Medical Device [82] 

  • Diabetes Technology Society Mobile Platform Controlling a Diabetes Device Security and Safety Standard (DTMoSt). Diabetes Device Security and Safety Standard.Guidance for the Use of Mobile Devices in Diabetes Control Contexts [83] 

  • Draft Guidance for Industry and FDA Staff: Content of Premarket Submissions for Management of Cybersecurity in Medical Devices [38] 

  • Medical Device Cybersecurity Regional Incident Preparedness and Response Playbook [84] 

  • Medical Device Data Systems [85]   

  • Artificial Intelligence and Machine Learning in Software as a Medical Device [86] 

  • FDA guidance webpage over premarket information device design and documentation processes [87]  

 Standards related to the development of APDS and its components 

 

Standard Designation Number/Date 

Title of Standard 

Standard Developing Organization 

DTSEC-2017-11-001 

Standard for Wireless Diabetes Device Security (DTSec) [83] 

DTS 

DTSec Protection Profile Version 2.0 -November 25, 2017 

Protection Profile for ConnectedDiabetes Devices(CDD) [83] 

DTS 

ISO 60601-1-10 

Medical electrical equipment Part 1-10: General requirements for basic safety and essential performance Collateral standard: Requirements for the development of physiologic closed-loop controllers 

ISO 

POCT05-A 

Performance Metrics for Continuous Interstitial Glucose Monitoring; Approved Guideline 

CLSI 

IMDRF/SaMD WG/N10FINAL:2013 

Software as a Medical Device (SaMD): Key Definitions 

IMDRF 

IMDRF/SaMD WG/N12FINAL:2014 

Software as a Medical Device (SaMD): Possible Framework for Risk Categorization and Corresponding Considerations 

IMDRF 

IMDRF/SaMD WG/N23 FINAL:2015 

Software as a Medical Device (SaMD): Application of Quality Management System 

IMDRF 

11073-10425 First edition 2016-06-15 

Health informatics - Personal health device communication - Part 10425: Device specialization - Continuous glucose monitor (CGM) 

IEEE ISO 

11073-10417 Third edition 2017-04 

Health informatics - Personal health device communication - Part 10417: Device specialization - Glucose meter 

IEEE ISO 

11073-10419 First edition 2016-06-15 

Health informatics - Personal health device communication - Part 10419: Device specialization - Insulin pump 

IEEE ISO 

11073-10417 Third edition 2017-04 

Health informatics - Personal health device communication - Part 10417: Device specialization - Glucose meter 

IEEE ISO 

11073-10419 First edition 2016-06-15 

Health informatics - Personal health device communication - Part 10419: Device specialization - Insulin pump 

IEEE ISO 

Std 11073-10425-2014  

Health informatics - Personal health device communication Part 10425: Device Specialization - Continuous Glucose Monitor (CGM)  

IEEE 

TIR57:2016  

Principles for medical device security - Risk management 

AAMI 

SW87:2012 

Application of quality management system concepts to medical device data systems 

ANSI AAMI 

TIR 45:2012 

Guidance on the use of AGILE practices in the development of medical device software 

AAMI 

82304-1 Edition 1.0 2016-10  

Health software - Part 1: General requirements for product safety 

IEC 

2900-2-1 First Edition 2017 

Standard for Safety Software Cybersecurity for Network-Connectable Products Part 2-1: Particular Requirements for Network Connectable Components of Healthcare and Wellness Systems 

ANSI UL 

646 Third edition 1991-12-15 

Information technology - IS0 7-bit coded character set for information interchange 

IEC ISO 

TR 80001-2-8 Edition 1.0 2016-05  

Application of risk management for IT-networks incorporating medical devices - Part 2-8: Application guidance - Guidance on standards for establishing the security capabilities identified in IEC TR 80001-2-2 

IEC 

TR 80002-1 Edition 1.0 2009-09 

Medical device software - Part 1: Guidance on the application of ISO 14971 to medical device software 

IEC 

15026-2 First edition 2011-02-15 

Systems and software engineering - Systems and software assurance - Part 2: Assurance case 

IEC ISO 

2900-1 First Edition 2017 

Standard for Safety Standard for Software Cybersecurity Network-Connectable Products Part 1: General Requirements 

ANSI UL 

15026-1 First edition 2013-11-01 

Systems and software engineering - Systems and software assurance - Part 1: Concepts and vocabulary 

IEC ISO 

TR 80001-2-2 Edition 1.0 2012-07 

Application of risk management for IT Networks incorporating medical devices - Part 2-2: Guidance for the disclosure and communication of medical device security needs risks and controls 

IEC 

SW91:2018 

Classification of defects in health software 

ANSI AAMI 

29147 First edition 2014-02-15 

Information technology - Security techniques - Vulnerability disclosure 

IEC ISO 

POCT1-A2 

Point-of-Care Connectivity 

CLSI 

TR 80001-2-5 Edition 1.0 2014-12 

Application of risk management for IT-networks incorporating medical devices - Part 2-5: Application guidance - Guidance on distributed alarm systems 

IEC 

11073-10101 First edition 2004-12-15 

Health informatics - Point-of-care medical device communication - Part 10101: Nomenclature 

IEEE ISO 

Std 11073-10207-2017 

Health informatics - Point-of-care medical device communication Part 10207: Domain Information and Service Model for Service-Oriented Point-of-Care Medical Device Communication 

IEEE 

11073-20702 First edition 2018-09 

Health informatics - Point-of-care medical device communication - Part 20702: Medical devices communication profile for web services 

ISO 

60812 Edition 3.0 2018-08 

Analysis techniques for system reliability - Procedure for failure mode and effects analysis (FMEA) 

IEC 

62304 Edition 1.1 2015-06 consolidated version  

Medical device software - Software life cycle processes 

IEC 

30111 First edition 2013-11-01 

Information technology - Security techniques - Vulnerability handling processes 

IEC ISO 

F2761-09 (2013) 

Medical Devices and Medical Systems - Essential safety requirements for equipment comprising the patient-centric integrated clinical environment (ICE) - Part 1: General requirements and conceptual model 

ASTM 

  1. Regulations, guidance, and informationrelated to the product development and regulatory affairs of medical devices 

  • Guidance for Industry and FDA Staff: Medical Device Classification Product Codes 

  • Guidance for Industry and FDA Staff: Factors to Consider When Making Benefit-Risk Determinations in Medical Device Premarket Approval and De Novo Classifications 

  • Guidance for Sponsors, Clinical Investigators, Institutional Review Boards, and FDA Staff: FDA Decisions for Investigational Device Exemption Clinical Investigations 

  • Guidance for Industry, Clinical Investigators, Institutional Review Boards, and FDA Staff: Design Considerations for Pivotal Clinical Investigations for Medical Devices 

  • Guidance for Industry and FDA Staff: De Novo Classification Process (Evaluation of Automatic Class III Designation) 

  • Draft Guidance for Industry and FDA Staff: Benefit-Risk Factors to Consider When Determining Substantial Equivalence in Premarket Notifications [510(k)] with Different Technological Characteristics 

  • Guidance for Industry and FDA Staff: Center for Devices and Radiological Health Appeals Processes 

  • Guidance for Industry and FDA Staff: Requests for Feedback on Medical Device Submissions: The Pre-Submission Program and Meetings with Food and Drug Administration Staff 

  • Proposed Rule: Human Subject Protection; Acceptance of Data From Clinical Studies for Medical Devices 

  • Draft Guidance for Industry, FDA Staff, and Third Party Review Organizations: 510(k) Third Party Review Program 

  • Guidance for Industry and FDA Staff: Applying Human Factors and Usability Engineering to Medical Devices   

  • Draft Guidance for Industry and FDA Staff: List of Highest Priority Devices for Human Factors Review 

  • Guidance for Industry and FDA Staff: Guidance for the Content of Premarket Submissions for Software Contained in Medical Device 

  • Final Guidance for Industry and FDA Reviewers: Guidance on Medical Device Patient Labeling 

  • Guidance for Industry and FDA Staff: Content of Premarket Submissions for Management of Cybersecurity in Medical Devices  

  • Guidance for Industry and FDA Staff: PostmarketManagement of Cybersecurity in Medical Devices [88] 

  • Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices 

  • Guidance to Industry: Cybersecurity for Networked Medical Devices Containing Off-the-Shelf (OTS) Software 

  • FDA Digital Health webpage [36]   

  • Qualification of Medical Device Development Tools Guidance for Industry, Tool Developers, and FDA Staff 

  • Prescription Drug-Use-Related Software; Establishment of a Public Docket; Request for Comments [89] 

  1. Technology agencies and references for open protocol systems 

  • Diabetes Technology Society [83] 

  • National Evaluation System for health Technology Coordinating Center (NESTcc) [90] 

  • JDRF launched its initiative in 2017 with the goal to explore ways to overcome potential challenges in the use and adoption of open protocol systems, notably helping to establish clear financial, regulatory, and legal frameworks [91]. 

  • OpenAPS code framework is designed to work with interoperable insulin pumps and CGMs from any manufacturer to build and facilitate building DIY closed loop implementation [92]. 

  • AndroidAPS is an application with a code framework tobuild a closed-loopsystem that can communicate with bluetooth-enabled insulin pumps [93]. 

  • Tidepool Loop is an open source hybrid closed-loop system currently in development for iPhone and Apple Watch [94]. 

  1. CONCLUSION 

Healthcare is undergoing a massive technological transformation, and it is imperative for the industry to leverage new technologies to create new product approaches and generate, collect, and track novel data. The convergence of new technologies, digital health approaches, computational capabilities, advanced data techniques, algorithmic design, miniaturization, and the ability to generate and harness large-scale data enables new pathways for the discovery, development, and deployment of wearable APDS. The overarching goal of APDS is the development of innovative technologies and systems that enable an integrated, wearable/implantable, and more accurate glucose-regulated closed-loop insulin/pancreatic hormone delivery system to achieve and sustain daily euglycemia management and prevent acute and chronic complications in a personalized fashion, ultimately relieving patients of the burden of diabetes self-management. 

APDS demands a more carefully tailored regulatory approach.It is a more specialized product category the technology is more complex, and the regulatory scenario is generally multifaceted. An APDS consists of separate components that must be functionally compatible as a medical device, and the components must work together as a closed-loop system. The modular architecture of APDS at both the hardware and software level allows APDS to be assembled from independent but compatible modules, each performing a specific function.  Each system can offer unique features in configuration, functionality, user interface, and data management. However, the modular architecture may also require diverse requirements for performance, software, biocompatibility, sterility, shelf life, electrical safety, magnetic resonance imaging safety, and human factors.Guidelines and directives for many emerging technologies are either evolving, or there are no development guidelines available yet. Submission and approval requirements continuously evolve with technological and scientific field advances. 

Early engagement of an experienced team of regulatory professionals, regulatory consultants, and compliance consultants is advised to help with compliance and regulatory efforts, including the development of regulatory strategy, planning and development of evidence to include in submissions, and execution of the submission process. The regulatory complexity for conceptualizing a regulatory strategy of APDS is dependent on the nature of hardware components, software components, integration of software and hardware to provide reasonable assurance of performance, safety and effectiveness, substantial equivalency to any of cleared devices, and intended use. The unique requirements of APDS may have a substantial impact on the size of the clinical development program, as well as on the risk assessment. Early and frequent dialogue between the FDA and APDS sponsors addressing critical aspects of study design and submission adequacies has the potential to mitigate several potentially preventable submission deficiencies and reduce delays in the approval process.Furthermore, the modular architecture of various functional components of APDS may require different types of partnerships,business ecosystems, and relationships for product development and regulatory submissions. 

The regulation of APDS generally involves competing goals of assuring safety and efficacy while providing rapid adoption of emerging innovative technologies through the investigative and regulatory processes as quickly as possible. The FDA is planning for a future regulatory model to provide more streamlined and efficient regulatory oversight of APDS. To the best extent possible, FDA is helping to advance the development and regulation of APDS by prioritizing the review of research protocol studies, providing clear guidelines to industry, setting performance and safety standards, and fostering stakeholders’ discussions. 

  1. DISCLAIMERS   

The interpretations, conclusions, and recommendations in this article are the author’s personal views and do not necessarily represent those of the organization(s) and committees of the author’s affiliation. The reader must not construe the information of this article as an alternative to regulatory advice from an appropriately qualified regulatory affairs professional/agency.  

Although the author and publisher have made every effort to ensure that the information in this article is reliable, the author and publisher do not assume any responsibility for the accuracy, completeness, topicality, or quality of the information provided. Any liability claims against the author in respect of any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from negligence, accident, or any other cause, including any information which is incorrect or incomplete, are therefore excluded. 

Copyright: The author retains copyright. This article in its entirety, with its tables/images/mappings/annexures may, however, be reproduced without redaction, with acknowledgment to the author and current publisher, and with the copyright retained by the author. This article may not be used in support of a commercial medical product or investigational product.  

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