The Rapid Acceleration of Diagnostics (RADx®) Regulatory Core was established as part of the National Institutes of Health (NIH)-funded RADx US response to the COVID-19 pandemic. The RADx Regulatory Core is charged with supporting COVID-19 in vitro diagnostic manufacturers admitted into the RADx program with the goal of obtaining Emergency Use Authorization (EUA) and planning for full authorizations to increase COVID-19 testing throughput on the US market. This chapter outlines the EUA process and how it differs from full authorization and describes the inception and evolution of the RADx Regulatory Core, including collaborations made with the NIH, the US Food and Drug Administration, and industry sponsors to successfully bring new tests to the market.

In this chapter, we review the history of clinical trials. We review the famous 1948 streptomycin trial for tuberculosis to highlight how the discipline of randomised clinical trials was born out of economic hardship. Other historical events of adaptive trial designs and master protocols are discussed in this chapter.

New product development processes need to be compliant to regulatory requirements, and this chapter highlights the salient processes and quality systems to put into place to achieve success. Project management is made simple with specific tools provided here. Customer feedback is channeled into specific product characteristics, and the right tools are shown in this chapter. The biopharma industry has statistics showing less than 10% of starting compounds succeed in reaching market approval, and this chapter explains what causes these failures. The key issues that have repeatedly caused failure during device and diagnostic product development are also pointed out. Ethical decisions have to be made during product development as shown in this chapter. Outsourcing is a real option due to the availability of many contract research and manufacturing organizations, and judicious use of this option is discussed in this chapter. Key milestones that reduce risk and show transition from early stage to preclinical prototype stages are reviewed here. Does the popular concept of minimum viable product in software development apply in biomedicine prototyping? Other similar questions that help the reader understand pitfalls and best practices are answered here.

From the long path through preclinical development, entering the regulatory field of interactions for human clinical trials can sometimes feel like you are walking into the lion’s den. This chapter guides you through an understanding of how to interact and how to prepare for FDA meetings so that they are on your side rather than fighting you. The common goals of companies and the FDA are highlighted here. Specific issues with identifying the appropriate regulatory approval pathway are discussed here with cautionary case studies. Complex new technologies which combine diagnostics and drugs, or devices and software, or AI-based dynamic software are reviewed here. The best approach to the appropriate regulatory pathway will be clear after reading this chapter. Case studies are used to show successful pathways taken by cutting-edge developments, such as cell-based therapy.

As vaccines are complex technologies that interact with the human body, their development is overseen by regulators in the administrative state. Countries structure the review of pharmaceutical products according to domestic rules and institutional design. As such, vaccines are reviewed as biologic products by regulatory authorities at the domestic level, such as the Therapeutic Goods Administration in Australia or the Pharmaceutical and Medical Devices Agency in Japan. The national basis of vaccine regulation inevitably leads to country-specific processes and timelines and may in some cases lead to different decisions.

The FDA’s Guidance to the Breakthrough Devices Program states the agency “may accept a greater extent of uncertainty of the benefit-risk profile for these devices if appropriate under the circumstances.” The CMS recently began providing supplemental reimbursement through New Technology Add-On Payments for “Breakthrough Devices.” CMS has waived a nearly two-decade criterion that devices receiving such payments must provide a “substantial clinical improvement” to Medicare beneficiaries. These policies will accelerate the approval and adoption into clinical practice of novel medical devices which may later be determined to not meet the statutory standard of reasonable assurance of safety and effectiveness (FDA) and/or “reasonable and necessary” (CMS). A crucial, but underutilized, regulatory authority can improve patient safety: conditional approval with withdrawal of approval when (1) clinical data demonstrate the threshold of reasonable assurance of safety and effectiveness is not met or (2) postmarket studies are not completed in a timely manner to demonstrate safety and effectiveness. It is rarely used, but there is precedent for FDA revocation of pharmaceutical approvals. In addition, payor coverage should be conditional (and proportional) on data of safety and effectiveness and withdrawn for data showing net harms or if data are not generated in a timely manner.

Attempts to modernize and speed up the FDA’s premarketing clearance and classification process for medical devices have included both new device classifications and ways of filing abbreviated applications. The FDA’s “De Novo” classification and Breakthrough Devices program allow applicants to create entirely new medical device types, with special controls and technological characteristics, including specifications on hardware and software. To encourage innovation and competition, the 21st Century Cures Act allows De Novo devices to serve as “predicates” for subsequent follow-on medical devices through the 510(k) application process, if such follow-on devices use the same controls and possess “the same” technological characteristics as the “predicate” device. This lends itself to a potentially anticompetitive strategy mediated by the interaction between IP and the 510(k) application requirements: successful De Novo applicants could use their portfolios to prevent follow-on applicants from making use of similar characteristics – potentially stymying an entire class of follow-on devices in the process. This strategy could threaten a greater diversity of new devices; may encourage an “up” classification of devices; and incentivizes technical characteristics and special controls of De Novo devices where general ones may suffice. This chapter concludes by proposing future evidence-based research in the area.

Between 2017-2018, the FDA cleared fourteen AI and ML-based software products as devices. This chapter analyzes how these products were cleared by the FDA and discusses how a lifecycle-based framework for regulating AI/ML-based software would address some of these characteristics. It is important to address the currently limited evidence for safety and effectiveness available at the time of market entry. To address the post-approval period, manufacturers and the FDA should work together to generate a list of industry-wide allowable changes and modifications that the software can employ to adapt in real-time to new data that would be subject to a “safe harbor” and thus not necessarily require premarket review by the FDA. Even anticipated changes may accumulate to generate an unanticipated divergence in the software’s eventual performance. There should be appropriate guardrails as software evolves over time. Finally, AI/ML is often criticized as a “black box” that is not well understood by or well explained to users. Given the inherent opacity of AI/ML-based software, the FDA should require a high standard of transparency to allow patients and clinicians to make informed decisions.

Relying chiefly on the combination of costly, unsystematic, and unreliable FDA monitoring and state negligence actions, the current postapproval system for controlling medical device risks falls far short of assuring optimal levels of safety. The reform proposal we advance comprehensively addresses these law enforcement deficiencies. The contemplated changes are straightforward and simple to implement yet would substantially reduce cost while increasing the effectiveness of both FDA monitoring and civil liability deterrence. Monitoring would be improved by requiring first-party insurers to investigate and report to the FDA the potential existence of a causal connection between the personal injury for which they are funding treatment and the patient’s (insured’s) use of or exposure to a medical device. The FDA would be authorized to enlist DOJ Civil Division enforcement of a federal cause-based strict liability action against the medical device manufacturer. The manufacturer would bear liability in full, with no reduction for risk contributions from the injured patient or other parties and would pay damages in total to the US Government. We explain the regulatory advantages of this new regulatory rule of cause-based strict liability relative to conventional rules of negligence and strict liability.

Are Electronic Health Records Medical Devices? While statute (largely) excludes EHRs from the medical device category, commentators have struggled to offer a justification. They have argued that EHRs inform but do not replace clinical decision-making, do not directly interact with patients, and are constantly being upgraded and modified. But all these characteristics are often true of many medical devices. I argue the key aspect of EHRs that render them foreign to the FDA’s jurisdiction is their systemwide interconnectedness. The patient’s EHR affects others. EHRs must work in a certain way, for the integrity of the whole system. EHR data is used for both clinical and quality management research. Alternatively, the safety of EHRs involves greater systematic, upstream regulation – of third-party networks, data formats, and other issues that present collective action problems. This goes far beyond the mandate of the FDA that fails to consider such issues and lacks jurisdiction over many necessary third parties. I argue that the distinction between EHR functions that have a direct and primary effect on the particular patient versus those such as data format and interoperability that present these third-party and systematic considerations should determine the respective jurisdictions of the FDA and health data subagencies.

All agents approved for marketing must meet the regulatory standards of the country in which they will be marketed, and drug development programs are designed to meet these regulatory requirements.  There are frequent interactions between regulators and sponsors during the development and trial process.  The FDA in the USA, the EMA in Europe, the NMPA in China, and the Japanese PMDA and other national regulatory bodies communicate regularly and share information.  Regulators promote drug development for serious diseases with unmet needs such as Alzheimer’s disease (AD) and can use regulatory tools to facilitate the drug development process.  Regulatory agencies oversee the manufacture of treatments (drugs, monoclonal antibodies) in addition to supervising the development process through clinical trials.  Regulatory science and regulatory specifications evolve in concert with new knowledge.  Agencies now recognize mild cognitive impairment and preclinical AD as populations where therapeutic indications could apply.  Agencies have integrated biomarkers into their concepts of drug development and have specified approaches to biomarker qualification.

The recent FDA marketing authorizations granted for testing for mutations associated with hereditary breast and colon cancer, as well as pharmacogenomic susceptibilities, provide an opportunity to re-examine the medical as well as regulatory underpinnings of DTC genetic testing. In this chapter, we first examine the historical emergence of enabling technologies that have provided for the availability of DNA sequence information on a broad scale, the efforts by the medical community to incorporate these advances into models of “precision” or “personalized” medicine, and the risks and benefits of offering access to DNA germline sequence analysis outside of the traditional medical model. We then turn to the current and proposed regulatory schemes to provide oversight over DTC genetic testing, with a focus on the role of the FDA as an information regulator and guardian of public health and safety.

The rise and ease of genome-editing technologies, like CRISPR, has ushered in communities of “biohackers,” do-it-yourself enthusiasts for molecular genetics who perform experiments outside traditional institutional laboratory settings. Conventional wisdom posits that such research is beyond traditional modes of regulation or legal enforcement and that new biohacking laws are needed. This view, however, is incorrect; both public and private regulators currently possess–and in other contexts, use–many of the tools needed to regulate the safety and ethics of biohacking. The U.S. Food and Drug Administration, for example, has expansive authority over “biologics,” which includes many of the biohacking kits currently in use. Patent holders and community laboratories similarly have the power to impose ethical and safety restrictions on biohacking activities. Rather than new laws or stiffer enforcement, regulators should do what they do for other industries: actively engage with the community to educate and promote the advancement of technology.