Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline ATM sequence variants.

The ClinGen Hereditary Breast, Ovarian, and Pancreatic Cancer (HBOP) Variant Curation Expert Panel (VCEP) is composed of internationally recognized experts in clinical genetics, molecular biology, and variant interpretation. This VCEP made specifications for the American College of Medical Genetics and Association for Molecular Pathology (ACMG/AMP) guidelines for the ataxia telangiectasia mutated (ATM) gene according to the ClinGen protocol. These gene-specific rules for ATM were modified from the ACMG/AMP guidelines and were tested against 33 ATM variants of various types and classifications in a pilot curation phase. The pilot revealed a majority agreement between the HBOP VCEP classifications and the ClinVar-deposited classifications. Six pilot variants had conflicting interpretations in ClinVar, and re-evaluation with the VCEP's ATM-specific rules resulted in four that were classified as benign, one as likely pathogenic, and one as a variant of uncertain significance (VUS) by the VCEP, improving the certainty of interpretations in the public domain. Overall, 28 of the 33 pilot variants were not VUS, leading to an 85% classification rate. The ClinGen-approved, modified rules demonstrated value for improved interpretation of variants in ATM.

Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report.

Physiologically based biopharmaceutics modeling (PBBM) is used to elevate drug product quality by providing a more accurate and holistic understanding of how drugs interact with the human body. These models are based on the integration of physiological, pharmacological, and pharmaceutical data to simulate and predict drug behavior in vivo. Effective utilization of PBBM requires a consistent approach to model development, verification, validation, and application. Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM. To address this gap, industry submitted confidential PBBM case studies to be reviewed by the regulatory agencies; software companies committed to training. PBBM cases were independently and collaboratively discussed by regulators, and academic colleagues participated in some of the discussions. Successful bioequivalence "safe space" industry case examples are also presented. Overall, six regulatory agencies were involved in the case study exercises, including ANVISA, FDA, Health Canada, MHRA, PMDA, and EMA (experts from Belgium, Germany, Norway, Portugal, Spain, and Sweden), and we believe this is the first time such a collaboration has taken place. The outcomes were presented at this workshop, together with a participant survey on the utility and experience with PBBM submissions, to discuss the best scientific practices for developing, validating, and applying PBBMs. The PBBM case studies enabled industry to receive constructive feedback from global regulators and highlighted clear direction for future PBBM submissions for regulatory consideration.

How clinical laboratories select and use Analytical Performance Specifications (APS) in Italy.

OBJECTIVES: Even if the topic of the analytical quality required to provide laboratory results "fit for purpose" exists since the beginning of the modern medical laboratory, there is the suspect that the expression "Analytical Performance Specifications" (APS) is not well-known. To investigate this aspect a survey was conducted. METHODS: A questionnaire with seven questions related to the knowledge about the topic, the sources of information and the criteria used by the laboratories to set the APS and their applications was prepared. It was distributed to all the clinical pathology laboratories of Lombardy Region (143) and to the members of SIBioC Laboratory Medicine (excluding Lombardy). RESULTS: We received 201 replies: 127 from Lombardy and 74 from the rest of Italy. Fifteen percent declared to ignore the meaning of APS and only 64 % of those knowing the meaning of the term declared to use them in the daily practice. The state-of-the-art was the principle used more frequently to set APS (about 48 %) followed by biological variation (41 %), and APS were typically applied to set goals for Internal Quality Control for selected measurands. Usually imprecision or total error APS were used, much less frequently uncertainty APS. In fact only 27 % of the laboratories declared to have calculated the measurement uncertainty for part or the majority of their measurands. CONCLUSIONS: Even considering the limits of a survey that relies upon self-declarations, it appears clearly that, at list in Italy, there is some work to be done to promote the concept and the use of APS.

Analytical performance specifications for combined uncertainty budget in the implementation of metrological traceability.

In addition to the correct implementation of calibration traceability, the definition and fulfillment of maximum allowable measurement uncertainty (MAU) are essential in assuring that laboratory measurements are clinically usable. Across the entire calibration hierarchy, three major contributors to the measurement uncertainty (MU) budget are identified, starting with the higher-order reference providers, extending through the in vitro diagnostic (IVD) manufacturers and their processes for assigning calibrator values, and ending with medical laboratories generating the random variability of results reported to clinicians. To understand if it is possible to achieve MAU and, consequently, to fix the possible drawbacks, the definition of combined MU budget limits across the entire calibration hierarchy has a central role. In particular, quality specifications for MU of reference and commercial calibrator materials should be defined according to the MAU on clinical samples. All involved stakeholders (i.e., higher-order reference providers, IVD manufacturers, medical laboratories) should be prepared to improve their performance whenever the clinical application of the test is made questionable by the failure to achieve MAU.

When bias becomes part of imprecision: how to use analytical performance specifications to determine acceptability of lot-lot variation and other sources of possibly unacceptable bias.

ISO 15189 requires laboratories to estimate the uncertainty of their quantitative measurements and to maintain them within relevant performance specifications. Furthermore, it refers to ISO TS 20914 for instructions on how to estimate the uncertainty and what to take into consideration when communicating uncertainty of measurement with requesting clinicians. These instructions include the responsibility of laboratories to verify that bias is not larger than medically significant. If estimated to be larger than acceptable, such bias first needs to be eliminated or (temporarily) corrected for. In the latter case, the uncertainty of such correction becomes part of the estimation of the total measurement uncertainty. If small enough to be acceptable, bias becomes part of the long term within laboratory random variation. Sources of possible bias are (not limited to) changes in reagent or calibrator lot variation or calibration itself. In this paper we clarify how the rationale and mathematics from an EFLM WG ISO/A position paper on allowable between reagent lot variation can be applied to calculate whether bias can be accepted to become part of long-term imprecision. The central point of this rationale is to prevent the risk that requesting clinicians confuse changes in bias with changes in the steady state of their patients.

State-of-the-art model for derivation of analytical performance specifications: how to define the highest level of analytical performance technically achievable.

To be accurate and equivalent among assays, laboratory results should be traceable to higher-order references and their quality should fulfill maximum allowable measurement uncertainty (MU) as defined to fit the intended clinical use. Accordingly, laboratory professionals should estimate and validate MU of performed tests using appropriate analytical performance specifications (APS). Current consensus supports the derivation of APS by using one of the three models established by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Strategic Conference held in Milan in 2014. It is recognized that some models are better suited for certain measurands than for others and the attention should be primarily directed towards their biological and clinical characteristics. Among others, model 3 should reflect the state of the art of the measurements that can be defined as the best analytical performance that is technically achievable. Taking serum C-reactive protein and ferritin as examples, here we describe the theoretical premises and the experimental protocol to be used to derive APS for MU when a measurand is allocated to this model. Although the model lacks a direct relationship with clinical outcomes, useful information about the in vitro diagnostic medical device performance and the average quality of provided results may be obtained.

The role of analytical performance specifications in international guidelines and standards dealing with metrological traceability in laboratory medicine.

The goal of metrological traceability is to have equivalent results for a measurand in clinical samples (CSs) irrespective of the in-vitro diagnostic medical device (IVD-MD) used for measurements. The International Standards Organization standard 17511 defines requirements for establishing metrological traceability of values assigned to calibrators, trueness control materials and human samples used with IVD-MDs. Each step in metrological traceability has an uncertainty associated with the value assigned to a material. The uncertainty at each step adds to the uncertainty from preceding steps such that the combined uncertainty gets larger at each step. The combined uncertainty for a CS result must fulfil an analytical performance specification (APS) for the maximum allowable uncertainty (umax CS). The umax CS can be partitioned among the steps in a metrological traceability calibration hierarachy to derive the APS for maximum allowable uncertainty at each step. Similarly, the criterion for maximum acceptable noncommutability bias can be derived from the umax CS. One of the challenges in determining if umax CS is fulfilled is determining the repeatability uncertainty (u Rw) from operating an IVD-MD within a clinical laboratory. Most of the current recommendations for estimating u Rw from internal quality control data do not use a sufficiently representative time interval to capture all relevant sources of variability in measurement results. Consequently, underestimation of u Rw is common and may compromise assessment of how well current IVD-MDs and their supporting calibration hierarchies meet the needs of clinical care providers.

APS calculator: a data-driven tool for setting outcome-based analytical performance specifications for measurement uncertainty using specific clinical requirements and population data.

OBJECTIVES: According to ISO 15189:2022, analytical performance specifications (APS) should relate to intended clinical use and impact on patient care. Therefore, we aimed to develop a web application for laboratory professionals to calculate APS based on a simulation of the impact of measurement uncertainty (MU) on the outcome using the chosen decision limits, agreement thresholds, and data of the population of interest. METHODS: We developed the "APS Calculator" allowing users to upload and select data of concern, specify decision limits and agreement thresholds, and conduct simulations to determine APS for MU. The simulation involved categorizing original measurand concentrations, generating measured (simulated) results by introducing different degrees of MU, and recategorizing measured concentrations based on clinical decision limits and acceptable clinical misclassification rates. The agreements between original and simulated result categories were assessed, and values that met or exceeded user-specified agreement thresholds that set goals for the between-category agreement were considered acceptable. The application generates contour plots of agreement rates and corresponding MU values. We tested the application using National Health and Nutrition Examination Survey data, with decision limits from relevant guidelines. RESULTS: We determined APS for MU of six measurands (blood total hemoglobin, plasma fasting glucose, serum total and high-density lipoprotein cholesterol, triglycerides, and total folate) to demonstrate the potential of the application to generate APS. CONCLUSIONS: The developed data-driven web application offers a flexible tool for laboratory professionals to calculate APS for MU using their chosen decision limits and agreement thresholds, and the data of the population of interest.

The surveys on quality indicators for the total testing process in clinical laboratories of Fujian Province in China from 2018 to 2023.

OBJECTIVES: This study investigates the application of 15 Quality Indicators (QIs) in clinical laboratories in Fujian Province, China, from 2018 to 2023. It identifies the main causes of laboratory errors and explores issues in the application of QIs, providing a reference for establishing provincial state-of-the-art and operational quality specifications (QSs). METHODS: All clinical laboratories in Fujian Province were organized to submit general information and original QIs data through the online External Quality Assessment (EQA) system of the National Clinical Laboratory Center (NCCL) for a survey of 15 QIs. Data from 2018 to 2023 were downloaded for statistical analysis, and the current QSs for the 15 QIs in Fujian Province were compared and analyzed with those published by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Working Group on Laboratory Errors and Patient Safety (WG-LEPS). RESULTS: QIs data from 542 clinical laboratories were collected. The survey on data sources showed that the number of laboratories recording QIs data using Laboratory Information Systems (LIS) increased annually, but the growth was modest and the proportion was less than 50 %. Among the laboratories using LIS to record QIs data, 133 continuously participated in this survey for six years, reporting different QIs. Over the six years, all reported QIs showed significant improvement or at least remained stable. The best median Sigma (σ) metrics were for the percentage of critical values notification and timely critical values notification, reaching 6σ, followed by the percentage of incorrect laboratory reports, with σ metrics ranging from 4.9σ to 5.1σ. In contrast, the percentage of tests covered by internal quality control (IQC) (1.5σ-1.7σ) and inter-laboratory comparison (0.1σ) remained consistently low. Compared to the QSs published by IFCC WG-LEPS, the QSs for the 15 QIs in Fujian Province in 2023 were stricter or roughly equivalent, except for the percentage of incorrect laboratory reports (Fujian Province: 0-0.221, IFCC WG-LEPS: 0-0.03). CONCLUSIONS: 1. The application of QIs has significantly improved the quality of testing in clinical laboratories in Fujian Province, but the percentage of tests covered by IQC and inter-laboratory comparison remain low; 2. Effective application of QIs requires the establishment of comprehensive LIS, unified calculation standards, and other supporting measures.

The biological variation of insulin resistance markers: data from the European Biological Variation Study (EuBIVAS).

OBJECTIVES: An insulin resistant state is characteristic of patients with type 2 diabetes, polycystic ovary syndrome, and metabolic syndrome. Identification of insulin resistance (IR) is most readily achievable using formulae combining plasma insulin and glucose results. In this study, we have used data from the European Biological Variation Study (EuBIVAS) to examine the biological variability (BV) of IR using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and the Quantitative Insulin sensitivity Check Index (QUICKI). METHODS: Ninety EuBIVAS non-diabetic subjects (52F, 38M) from five countries had fasting HOMA-IR and QUICKI calculated from plasma glucose and insulin samples collected concurrently on 10 weekly occasions. The within-subject (CVI) and between-subject (CVG) BV estimates with 95 % CIs were obtained by CV-ANOVA after analysis of trends, variance homogeneity and outlier removal. RESULTS: The CVI of HOMA-IR was 26.7 % (95 % CI 25.5-28.3), driven largely by variability in plasma insulin and the CVI for QUICKI was 4.1 % (95 % CI 3.9-4.3), reflecting this formula's logarithmic transformation of glucose and insulin values. No differences in values or BV components were observed between subgroups of men or women below and above 50 years. CONCLUSIONS: The EuBIVAS, by utilising a rigorous experimental protocol, has produced robust BV estimates for two of the most commonly used markers of insulin resistance in non-diabetic subjects. This has shown that HOMA-IR, in particular, is highly variable in the same individual which limits the value of single measurements.

What the Milan conference has taught us about analytical performance specification model definition and measurand allocation.

Analytical performance specifications (APS) represent the criteria that specify the quality required for laboratory test information to satisfy clinical needs. In 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) considered timely to update the topic of APS by organizing a conference in Milan in which some strategic concepts were proposed. Here I summarize the essential points representing the EFLM Strategic Conference heritage and discuss the approaches that will permit us to become more concrete, including roles and main actions expected from each of involved stakeholders for contributing a quantum leap forward in the way of practicality of Milan consensus about APS.

Analytical performance specifications based on biological variation data - considerations, strengths and limitations.

Analytical performance specifications (APS) are typically established through one of three models: (i) outcome studies, (ii) biological variation (BV), or (iii) state-of-the-art. Presently, The APS can, for most measurands that have a stable concentration, be based on BV. BV based APS, defined for imprecision, bias, total allowable error and allowable measurement uncertainty, are applied to many different processes in the laboratory. When calculating APS, it is important to consider the different APS formulae, for what setting they are to be applied and if they are suitable for the intended purpose. In this opinion paper, we elucidate the background, limitations, strengths, and potential intended applications of the different BV based APS formulas. When using BV data to set APS, it is important to consider that all formulae are contingent on accurate and relevant BV estimates. During the last decade, efficient procedures have been established to obtain reliable BV estimates that are presented in the EFLM biological variation database. The database publishes detailed BV data for numerous measurands, global BV estimates derived from meta-analysis of quality-assured studies of similar study design and automatic calculation of BV based APS.

Using analytical performance specifications in a medical laboratory.

Analytical performance specifications (APS) are used for the quantitative assessment of assay analytical performance, with the aim of providing information appropriate for clinical care of patients. One of the major locations where APS are used is in the routine clinical laboratory. These may be used to assess and monitor assays in a range of settings including method selection, method verification or validation, external quality assurance, internal quality control and assessment of measurement uncertainty. The aspects of assays that may be assessed include imprecision, bias, selectivity, sample type, analyte stability and interferences. This paper reviews the practical use of APS in a routine clinical laboratory, using the laboratory I supervise as an example.

Applying the Milan models to setting analytical performance specifications - considering all the information.

Analytical performance specifications (APS) are used for decisions about the required analytical quality of pathology tests to meet clinical needs. The Milan models, based on clinical outcome, biological variation, or state of the art, were developed to provide a framework for setting APS. An approach has been proposed to assign each measurand to one of the models based on a defined clinical use, physiological control, or an absence of quality information about these factors. In this paper we propose that in addition to such assignment, available information from all models should be considered using a risk-based approach that considers the purpose and role of the actual test in a clinical pathway and its impact on medical decisions and clinical outcomes in addition to biological variation and the state-of-the-art. Consideration of APS already in use and the use of results in calculations may also need to be considered to determine the most appropriate APS for use in a specific setting.

Analytical performance specifications for trace elements in biological fluids derived from six countries federated external quality assessment schemes over 10 years.

OBJECTIVES: This article defines analytical performance specifications (APS) for evaluating laboratory proficiency through an external quality assessment scheme. METHODS: Standard deviations for proficiency assessment were derived from Thompson's characteristic function applied to robust data calculated from participants' submissions in the Occupational and Environmental Laboratory Medicine (OELM) external quality assurance scheme for trace elements in serum, whole blood and urine. Characteristic function was based on two parameters: (1) ß - the average coefficient of variation (CV) at high sample concentrations; (2) α - the average standard deviation (SD) at low sample concentrations. APSs were defined as 1.65 standard deviations calculated by Thompson's approach. Comparison between OELM robust data and characteristic function were used to validate the model. RESULTS: Application of the characteristic function allowed calculated APS for 18 elements across three matrices. Some limitations were noted, particularly for elements (1) with no sample concentrations near analytical technique limit of detection; (2) exhibiting high robust CV at high concentration; (3) exhibiting high analytical variability such as whole blood Tl and urine Pb; (4) with an unbalanced number of robust SD above and under the characteristic function such as whole blood Mn and serum Al and Zn. CONCLUSIONS: The characteristic function was a useful means of deriving APS for trace elements in biological fluids where biological variation data or outcome studies were not available. However, OELM external quality assurance scheme data suggests that the characteristic functions are not appropriate for all elements.

To rule-in, or not to falsely rule-out, that is the question: evaluation of hs-cTnT EQA performance in light of the ESC-2020 guideline.

OBJECTIVES: To accurately evaluate non-ST-elevated acute cardiac syndrome (NSTE-ACS), the quality of high-sensitive cardiac troponin (hs-cTn) assays is of vital importance. The 2020 revision of the NSTE-ACS guideline includes clinical decision-limits (CDL's) to both rule-in and rule-out NSTE-ACS for most commercially available platforms, providing both 0/1 h and 0/2 h delta limits. Our study evaluated whether laboratories are able to meet the analytical performance specifications for imprecision (APS) for hs-cTnT. METHODS: Results from external quality assurance (EQA) in commutable samples were used to evaluate the current and historic performance of analyzers. The performance of analyzers that either passed or failed to comply with 0/1 h-APS were used on a real-world dataset of first hs-cTnT-values to simulate 10.000 samples of t=0, t=1 and t=2 h values with multiple delta's for all relevant CDL's. We compared the simulated values to the input values to obtain the percentage of aberrant results simulated. RESULTS: The majority of analyzers complies with APS for rule-in in 2022 (0/1 h: 90.4 % and 0/2 h: 100 %), compliance for the 0/1 h rule-out is still far from optimal (0/1 h: 30.7 %, 0/2 h: 75.4 %), with improving compliance over the past years (rule-in p=<0.0001, rule-out p=0.011, χ2). Whilst 0/1 h-APS-passing analyzers have a minute risk to falsely rule-out patients whom should be ruled-in (0.0001 %), failing performance increases this risk to 2.1 % upon using 0/1 h CDL's. Here, adopting 0/2 h CDL's is favorable (0.01 %). CONCLUSIONS: Laboratories that fail to meet hs-cTnT 0/1 h-APS should improve their performance to the required and achievable level. Until performance is reached clinics should adopt the 0/2 h CDL's.

Justification of widened dissolution specifications of an extended-release product using physiologically based biopharmaceutics modeling.

Drug products meeting the dissolution specifications is crucial in order to ensure consistent clinical performance. However, in certain cases, wider dissolution specifications may be required based on product behaviour. While the justification of such wider specifications may be challenging from a regulatory context, approaches such as physiological-based biopharmaceutics modeling (PBBM) can be utilised for this purpose.Product DRL is a fixed-dose combination product consisting of immediate release (IR) and extended-release (ER) portions. For the ER portion, the dissolution specifications consisted of four time points, and a proposal was made to relax the specification at the 2h time point (from 50-70% to 45-67%) to reduce the batch failures at the commercial scale.To support the wider specification, a PBBM was developed and extensively validated with literature & in-house studies. Virtual bioequivalence was performed using the pivotal clinical study data.Virtual dissolution profiles for proposed wider specifications were generated using three different approaches. The incorporation of lower and upper dissolution profiles into the model indicated the absence of impact on in vivo performance thereby justifying the specifications.Regulatory acceptance of proposed specifications with PBBM indicated the significance of using modeling approaches to reduce repeated testing thereby facilitating faster approvals.

Maintaining the quality of vaccines through the use of standards: Current challenges and future opportunities.

An international hybrid meeting held 21-22 June 2023 in Ottawa, Canada brought together regulators, scientists, and industry experts to discuss a set of principles and best practices in the development and implementation of standards. Although the use of international standards (ISs) and international units (IUs) has been an essential part of ensuring human and animal vaccine quality in the past decades, the types and uses of standards have expanded with technological advances in manufacture and testing of vaccines. The needs of stakeholders are evolving in response to the ever-increasing complexity, diversity, and number of vaccine products as well as increasing efforts to replace animal-based potency tests with in vitro assays that measure relevant quality attributes. As such, there must be a concomitant evolution in the design and implementation of both international and in-house standards. Concomitantly, greater harmonization of regulatory expectations must be achieved through collaboration with standard-setting organizations, national control laboratories and manufacturers. Stakeholders provided perspectives on challenges and several recommendations emerged as essential to advancing agreed upon objectives.

Experiences and Initiatives on Pharmacokinetics Modeling and Simulation Data analyses: Perspectives from the Brazilian Health Regulatory Agency (ANVISA).

The landscape of drug product development and regulatory sciences is evolving, driven by the increasing application of systems thinking and modeling and simulation (M&S) techniques, especially from a biopharmaceutics perspective. Patient-centric quality standards can be achieved within this context through the application of quality by design (QbD) principles and M&S, specifically by defining clinically relevant dissolution specifications (CRDS). To this end, it is essential to bridge in vitro results to drug product in vivo performance, emphasizing the need to explore the translational capacity of biopharmaceutics tools. Physiologically based M&S analyses offer a unique avenue for integrating the drug, drug product, and biological properties of a target organism to study their interactions on the pharmacokinetic response. Accordingly, Physiologically Based Biopharmaceutics Modeling (PBBM) has seen increasing use to support drug development and regulatory applications globally. In Brazil, a Model-Informed Drug Development (MIDD) policy and strategic project are not yet established, limiting applicability of M&S techniques. Drawing from the experience of the ANVISA-Academia PBBM Working Group (WG), this article assesses the opportunities and challenges for pharmacometrics (PMx) in Brazil and proposes strategies to advance the adoption of M&S analyses into regulatory decision-making.

A Semi-Mechanistic Physiologically Based Biopharmaceutics Model to Describe Complex and Saturable Absorption of Metformin: Justification of Dissolution Specifications for Extended Release Formulation.

Physiologically based pharmacokinetic (PBPK) or physiologically based biopharmaceutics models (PBBM) demonstrated plethora of applications in both new drugs and generic product development. Justification of dissolution specifications and establishment of dissolution safe space is an important application of such modeling approaches. In case of molecules exhibiting saturable absorption behavior, justification of dissolution specifications requires development of a model that incorporates effects of transporters is critical to simulate in vivo scenario. In the present case, we have developed a semi-mechanistic PBBM to describe the non-linearity of BCS class III molecule metformin for justification of dissolution specifications of extended release formulation at strengths 500 mg and 1000 mg. Semi-mechanistic PBBM was built using physicochemical properties, dissolution and non-linearity was accounted through incorporation of multiple transporter kinetics at absorption level. The model was extensively validated using literature reported intravenous, oral (immediate & extended release) formulations and further validated using in-house bioequivalence data in fasting and fed conditions. Virtual dissolution profiles at lower and upper specifications were generated to justify the dissolution specifications. The model predicted literature as well as in-house clinical study data with acceptable prediction errors. Further, virtual bioequivalence trials predicted the bioequivalence outcome that matched with clinical study data. The model predicted bioequivalence when lower and upper specifications were compared against pivotal test formulations thereby justifying dissolution specifications. Overall, complex and saturable absorption pathway of metformin was successfully simulated and this work resulted in regulatory acceptance of dissolution specifications which has ability to reduce multiple dissolution testing.