Welcome to the March issue of RF Quarterly, which examines patient-focused regulatory practice and includes articles on patient-reported outcomes in regulatory decision making; real-world evidence and postmarket surveillance data; generating evidence for racial and ethnic minorities in oncologic drug development; structured, patient-focused benefit-risk assessment; and the role of the high-performance integrated virtual environment in research using patient-generated data....

Patient-reported outcome measures (PROMs) have been increasingly mandated to measure the success of clinical outcomes in regulatory decision making. However, these outcome measures require expertise in their application and interpretation to allow realistic assessment of the results. Published literature and guidances from the US Food and Drug Administration (FDA) can help with understanding how best these measures can be used in regulatory practice. Particularly, recent w...

This article compares real-world evidence (RWE) and postmarket surveillance (PMS) data collected outside of a randomized, controlled, clinical trial. Real-world data (RWD) include individual patient data points such as complaints and anecdotal findings. The recent explosion in RWD collection has led to new challenges in RWD evaluation globally. Solutions are rapidly evolving to analyze these relatively random data points for scientifically valid purposes. This article disc...

Discussions regarding diversity, equity, and inclusion in healthcare and clinical research have been ongoing for decades. However, the COVID-19 global pandemic brought about a new focus on this issue. As the pharmaceutical industry began strategizing on how to improve diversity in its clinical trials, the Reagan-Udall Foundation for the FDA in collaboration with the US Food and Drug Administration’s (FDA’s) Oncology Center of Excellence convened a series of interviews and ...

Benefit-risk (BR) assessment, a central part of regulatory decision making, has become increasingly structured in response to the need for consistency and transparency, and in alignment with the US Food and Drug Administration’s (FDA’s) 2021 draft BR guidance. Early planning and established processes are critical to successful execution. To help regulatory affairs professionals guide clinical development teams in planning and conducting patient-focused structured BR assess...

Patient-provided information (PPI) and patient-generated health data (PGHD) are critical sources of real-world data and evidence. Collecting this data empowers patients to become partners in informed decision making by all healthcare stakeholders. However, the increased demand for this type of data has given rise to logistic, technological, and ethical challenges. Technologies and operating systems such as the high-performance integrated virtual environment (HIVE) could si...

Welcome to the December issue of RF Quarterly in which global regulatory experts write about the role of artificial intelligence (AI) in regulatory practice, with a focus on global change management of AI-based medical devices, AI in regulatory intelligence knowledge management, synthetic data and the innovation, assessment, and regulation of AI medical devices, and digital transformation.   We thank the authors for their generosity in sharing their knowledge and exper...

Artificial intelligence as medical devices (AIaMDs) have the power to learn from real-world performance and over time and may provide a different output compared with that initially cleared for a given set of inputs. However, regulatory frameworks have remained relatively unchanged and are largely focused on approaches around traditional hardware-based medical devices. In this article, the authors explain the US Food and Drug Administration’s (FDA’s) current thinking on en...

In this article, the authors discuss how recent advances in AI can be applied to support and augment various regulatory intelligence functions, including knowledge management and precedent research.   Keywords – AI, computer vision, natural language processing, regulatory intelligence   Introduction Regulatory intelligence (RI) involves analyzing large amounts of regulatory information. Much of this research is done manually and requires repetitive and ti...

Synthetic data are artificial data that mimic the properties of, and relationships in, real data. They show promise for facilitating data access, validation, and benchmarking, addressing missing data and under-sampling, sample boosting, and the creation of control arms in clinical trials. The UK Medicines and Healthcare products Regulatory Agency (MHRA) is using its current research into the development of high-fidelity synthetic data to develop its regulatory position on ...

This article outlines the standardization work on artificial intelligence (AI) being carried out in the joint International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC) committee, ISO/IEC JTC 1/SC 42. 1 The SC 42 committee develops international standards that cover both technology capability and nontechnical requirements, such as business, regulatory and policy requirements, and application domain needs, as well as ethical an...

Welcome to the September issue of RF Quarterly in which global regulatory experts write about the key elements of regulatory strategy throughout the product lifecycle, CMS regulatory strategy, the application of project management strategies to postapproval CMC submissions, and medical writing strategies for aligning regulatory documents with strategic goals.   We thank the authors for their generosity in sharing their knowledge and expertise with the RAPS regulatory c...