The regulatory landscape of precision oncology laboratory medicine in the United States - Perspective on the past 5 years and considerations for future regulation

Revolutionising Cardio-Oncology Care with Precision Genomics

Cardiovascular disease is the worldwide leading cause of mortality among survivors of cancer due in part to the cardiotoxicity of anticancer therapies. This paper explores the progress in precision cardio-oncology, particularly in genetic testing and therapeutics, and its impact on cardiovascular diseases in clinical and laboratory settings. These advancements enable clinicians to better assess risk, diagnose conditions, and deliver personalised, cost-effective therapeutics. Through case studies of cancer-therapy-related cardiac dysfunction, clonal haematopoiesis of indeterminate potential, and polygenic risk scoring, we demonstrate the benefits of incorporating precision genomics in individualised care in cardio-oncology. Furthermore, leveraging real-world genomic data in clinical settings can advance our understanding of long noncoding RNAs and microRNAs, which play important regulatory roles in cardio-oncology. Additionally, employing human-induced pluripotent stem cells to stratify risk and guide prevention strategies represents a promising avenue for modelling precision cardio-oncology. While these advancements showcase the significant progress in genetic approaches, they also raise substantial ethical, legal, and societal concerns. Regulatory oversight of genetic and genomic technologies should therefore evolve suitably to keep up with rapid advancements in technology and analysis. Provider education is crucial for the appropriate use of new genetic and genomic applications, including on the existing protection available for patients regarding genetic information. This can provide confidence for diverse study groups to advance genetic studies looking to develop a comprehensive understanding and effective clinical applications for heterogeneous populations. In clinical settings, the implementation of genetic and genomic applications within electronic medical records can offer point-of-care clinical decision support, thus providing timely information to guide clinical management decisions.

Translating the regulatory landscape of medical devices to create fit-for-purpose artificial intelligence (AI) cytometry solutions

The implementation of medical software and artificial intelligence (AI) algorithms into routine clinical cytometry diagnostic practice requires a thorough understanding of regulatory requirements and challenges throughout the cytometry software product lifecycle. To provide cytometry software developers, computational scientists, researchers, industry professionals, and diagnostic physicians/pathologists with an introduction to European Union (EU) and United States (US) regulatory frameworks. Informed by community feedback and needs assessment established during two international cytometry workshops, this article provides an overview of regulatory landscapes as they pertain to the application of AI, AI-enabled medical devices, and Software as a Medical Device in diagnostic flow cytometry. Evolving regulatory frameworks are discussed, and specific examples regarding cytometry instruments, analysis software and clinical flow cytometry in-vitro diagnostic assays are provided. An important consideration for cytometry software development is the modular approach. As such, modules can be segregated and treated as independent components based on the medical purpose and risk and become subjected to a range of context-dependent compliance and regulatory requirements throughout their life cycle. Knowledge of regulatory and compliance requirements enhances the communication and collaboration between developers, researchers, end-users and regulators. This connection is essential to translate scientific innovation into diagnostic practice and to continue to shape the development and revision of new policies, standards, and approaches.

Temporary Regulatory Deviations and the Coronavirus Disease 2019 (COVID-19) PCR Labeling Update Study Indicate What Laboratory-Developed Test Regulation by the US Food and Drug Administration (FDA) Could Look Like

The coronavirus disease 2019 (COVID-19) response necessitated innovations and a series of regulatory deviations that also affected laboratory-developed tests (LDTs). To examine real-world consequences and specify regulatory paradigm shifts, legislative proposals were aligned on a common timeline with Emergency Use Authorization (EUA) of LDTs and the US Food and Drug Administration (FDA)-orchestrated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) labeling update study. The initial EUA adoption by LDT developers shows that the FDA can have oversight over LDTs. We used efficiency-corrected microcosting of our EUA PCR assay to estimate the national cost of the labeling update study to $0.3 to $1.4 million US dollars. Labeling update study performance data showed lower average detection limits in commercial in vitro diagnostic (IVD) assays versus LDTs (32,000 ± 75,000 versus 71,000 ± 147,000 nucleic acid amplification tests/mL; P = 0.04); however, comparison also shows that FDA review of IVD assays and LDTs did not prevent differences between initial and labeling update performance (IVD assay, P < 0.0001; LDT, P = 0.003). The regulatory shifts re-emphasized that both commercial tests and LDTs rely heavily on laboratory competence and procedures; however, lack of performance data on authorized tests, when clinically implemented, precludes assessment of the benefit related to regulatory review. Temporary regulatory deviations during the pandemic and regulatory science tools (ie, reference material) have generated valuable real-world evidence to inform pending legislation regarding LDT regulation.

Tissue Multiplex Analyte Detection in Anatomic Pathology - Pathways to Clinical Implementation

Background: Multiplex tissue analysis has revolutionized our understanding of the tumor microenvironment (TME) with implications for biomarker development and diagnostic testing. Multiplex labeling is used for specific clinical situations, but there remain barriers to expanded use in anatomic pathology practice.

Methods: We review immunohistochemistry (IHC) and related assays used to localize molecules in tissues, with reference to United States regulatory and practice landscapes. We review multiplex methods and strategies used in clinical diagnosis and in research, particularly in immuno-oncology. Within the framework of assay design and testing phases, we examine the suitability of multiplex immunofluorescence (mIF) for clinical diagnostic workflows, considering its advantages and challenges to implementation.

Results: Multiplex labeling is poised to radically transform pathologic diagnosis because it can answer questions about tissue-level biology and single-cell phenotypes that cannot be addressed with traditional IHC biomarker panels. Widespread implementation will require improved detection chemistry, illustrated by InSituPlex technology (Ultivue, Inc., Cambridge, MA) that allows coregistration of hematoxylin and eosin (H&E) and mIF images, greater standardization and interoperability of workflow and data pipelines to facilitate consistent interpretation by pathologists, and integration of multichannel images into digital pathology whole slide imaging (WSI) systems, including interpretation aided by artificial intelligence (AI). Adoption will also be facilitated by evidence that justifies incorporation into clinical practice, an ability to navigate regulatory pathways, and adequate health care budgets and reimbursement. We expand the brightfield WSI system “pixel pathway” concept to multiplex workflows, suggesting that adoption might be accelerated by data standardization centered on cell phenotypes defined by coexpression of multiple molecules.

Conclusion: Multiplex labeling has the potential to complement next generation sequencing in cancer diagnosis by allowing pathologists to visualize and understand every cell in a tissue biopsy slide. Until mIF reagents, digital pathology systems including fluorescence scanners, and data pipelines are standardized, we propose that diagnostic labs will play a crucial role in driving adoption of multiplex tissue diagnostics by using retrospective data from tissue collections as a foundation for laboratory-developed test (LDT) implementation and use in prospective trials as companion diagnostics (CDx).