Facing the Inevitable: Being Prepared for Regulatory Requirements for Laboratory Developed Tests

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.

Harnessing non-destructive 3D pathology

High-throughput methods for slide-free three-dimensional (3D) pathological analyses of whole biopsies and surgical specimens offer the promise of modernizing traditional histology workflows and delivering improvements in diagnostic performance. Advanced optical methods now enable the interrogation of orders of magnitude more tissue than previously possible, where volumetric imaging allows for enhanced quantitative analyses of cell distributions and tissue structures that are prognostic and predictive. Non-destructive imaging processes can simplify laboratory workflows, potentially reducing costs, and can ensure that samples are available for subsequent molecular assays. However, the large size of the feature-rich datasets that they generate poses challenges for data management and computer-aided analysis. In this Perspective, we provide an overview of the imaging technologies that enable 3D pathology, and the computational tools-machine learning, in particular-for image processing and interpretation. We also discuss the integration of various other diagnostic modalities with 3D pathology, along with the challenges and opportunities for clinical adoption and regulatory approval.

A Regulatory Science Initiative to Harmonize and Standardize Digital Pathology and Machine Learning Processes to Speed up Clinical Innovation to Patients

Unlocking the full potential of pathology data by gaining computational access to histological pixel data and metadata (digital pathology) is one of the key promises of computational pathology. Despite scientific progress and several regulatory approvals for primary diagnosis using whole-slide imaging, true clinical adoption at scale is slower than anticipated. In the U.S., advances in digital pathology are often siloed pursuits by individual stakeholders, and to our knowledge, there has not been a systematic approach to advance the field through a regulatory science initiative. The Alliance for Digital Pathology (the Alliance) is a recently established, volunteer, collaborative, regulatory science initiative to standardize digital pathology processes to speed up innovation to patients. The purpose is: (1) to account for the patient perspective by including patient advocacy; (2) to investigate and develop methods and tools for the evaluation of effectiveness, safety, and quality to specify risks and benefits in the precompetitive phase; (3) to help strategize the sequence of clinically meaningful deliverables; (4) to encourage and streamline the development of ground-truth data sets for machine learning model development and validation; and (5) to clarify regulatory pathways by investigating relevant regulatory science questions. The Alliance accepts participation from all stakeholders, and we solicit clinically relevant proposals that will benefit the field at large. The initiative will dissolve once a clinical, interoperable, modularized, integrated solution (from tissue acquisition to diagnostic algorithm) has been implemented. In times of rapidly evolving discoveries, scientific input from subject-matter experts is one essential element to inform regulatory guidance and decision-making. The Alliance aims to establish and promote synergistic regulatory science efforts that will leverage diverse inputs to move digital pathology forward and ultimately improve patient care.

Multicenter flow cytometry proficiency testing of canine blood and lymph node samples

BACKGROUND

Flow cytometry (FC) is used increasingly in veterinary medicine for further characterization of hematolymphoid cells. Guidelines for optimizing assay performance and interpretation of results are limited, and concordance of results across laboratories is unknown.

OBJECTIVES

This study aimed to determine inter-investigator agreement on the interpretation of FC results from split samples analyzed in different laboratories using various protocols, cytometers, and software; and on the interpretation of archived FC standard (FCS) data files contributed by the different investigators.

METHODS

This was a multicenter observational cross-sectional study. Anticoagulated blood or lymph node aspirate samples from nine client-owned dogs were aliquoted and shipped to participating laboratories. Samples were analyzed with individual laboratory-developed protocols. In addition, FCS files from a set of separate samples from 11 client-owned dogs were analyzed by participating investigators. A person not associated with the study tabulated the results and interpretations. Agreement of interpretations was assessed with Fleiss' kappa statistic.

RESULTS

Prolonged transit times affected sample quality for some laboratories. Overall agreement among investigators regarding the FC sample interpretation was strong (κ = 0.86 ± 0.19, P < .001), and for specific categories, ranged from moderate to perfect. Agreement of the lymphoproliferation or other leukocyte sample category from the analysis of the FCS files was weak (κ = 0.58 ± 0.05, P < .001).

CONCLUSIONS

Lymphoproliferations were readily identified by FC, but identification of the categories of hematolymphoid neoplasia in fresh samples or archived files was variable. There is a need for a more standardized approach to maximize the enormous potential of FC in veterinary medicine.

After another decade: LC-MS/MS became routine in clinical diagnostics

Tandem mass spectrometry - especially in combination with liquid chromatography (LC-MS/MS) - is applied in a multitude of important diagnostic niches of laboratory medicine. It is unquestioned in its routine use and is often unreplaceable by alternative technologies. This overview illustrates the development in the past decade (2009-2019) and intends to provide insight into the current standing and future directions of the field. The instrumentation matured significantly, the applications are well understood, and the in vitro diagnostics (IVD) industry is shaping the market by providing assay kits, certified instruments, and the first laboratory automated LC-MS/MS instruments as an analytical core. In many settings the application of LC-MS/MS is still burdensome with locally lab developed test (LDT) designs relying on highly specialized staff. The current routine applications cover a wide range of analytes in therapeutic drug monitoring, endocrinology including newborn screening, and toxicology. The tasks that remain to be mastered are, for example, the quantification of proteins by means of LC-MS/MS and the transition from targeted to untargeted omics approaches relying on pattern recognition/pattern discrimination as a key technology for the establishment of diagnostic decisions.