Regulatory Acceptance Research Articles

Validation, Optimization, and Application of the Zebrafish Developmental Toxicity Assay for Pharmaceuticals Under the ICH S5(R3) Guideline.

The zebrafish as an alternative animal model for developmental toxicity testing has been extensively investigated, but its assay protocol was not harmonized yet. This study has validated and optimized the zebrafish developmental toxicity assay previously reported by multiple inter-laboratory studies in the United States and Europe. In this study, using this classical protocol, of 31 ICH-positive compounds, 23 compounds (74.2%) were teratogenic in zebrafish, five had false-negative results, and three were neither teratogenic nor non-teratogenic according to the protocol standard; of 14 ICH-negative compounds, 12 compounds (85.7%) were non-teratogenic in zebrafish and two had false-positive results. After we added an additional TI value in the zebrafish treated with testing compounds at 2 dpf along with the original 5 dpf, proposed a new category as the uncategorized compounds for those TI values smaller than the cutoff both at 2 dpf and 5 dpf but inducing toxic phenotypes, refined the testing concentration ranges, and optimized the TI cut-off value from ≥ 10 to ≥ 3 for compounds with refined testing concentrations, this optimized zebrafish developmental assay reached 90.3% sensitivity (28/31 positive compounds were teratogenic in zebrafish) and 88.9% (40/45) overall predictability. Our results from this study strongly support the use of zebrafish as an alternative in vivo method for screening and assessing the teratogenicity of candidate drugs for regulatory acceptance.

Determination of ceftriaxone in human plasma using liquid chromatography-tandem mass spectrometry.

Ceftriaxone is a cephalosporin antibiotic drug used as first-line treatment for a number of bacterial diseases. Ceftriaxone belongs to the third generation of antibiotics and is available as an intramuscular or intravenous injection. Previously published pharmacokinetic studies have used high-performance liquid chromatography coupled with ultraviolet detection (HPLC-UV) for the quantification of ceftriaxone. This study aimed to develop and validate a bioanalytical method for the quantification of ceftriaxone in human plasma using liquid chromatography followed by tandem mass spectrometry (LC-MS/MS). Sample preparation was performed by protein precipitation of 100 µl plasma sample in combination with phospholipid-removal techniques to minimize matrix interferences. The chromatographic separation was performed on an Agilent Zorbax Eclipse Plus C18 column with 10 mM ammonium formate containing 2% formic acid: acetonitrile as mobile phase at a flow rate of 0.4 ml/min with a total run time of 10 minutes. Both the analyte and cefotaxime (internal standard) were quantified using the positive electrospray ionization (ESI) mode and selected reaction monitoring (SRM) for the precursor-product ion transitions m/z 555.0→396.1 for ceftriaxone and 456.0→324.0 for cefotaxime. The method was validated over the concentration range of 1.01-200 μg/ml. Calibration response showed good linearity (correlation coefficient > 0.99) and matrix effects were within the ±15% limit in 6 different lots of sodium heparin plasma tested. However, citrate phosphate dextrose plasma resulted in a clear matrix enhancement of 24% at the low concentration level, which was not compensated for by the internal standard. Different anticoagulants (EDTA, heparin and citrate phosphate dextrose) also showed differences in recovery. Thus, it is important to use the same anticoagulant in calibration curves and clinical samples for analysis. The intra-assay and inter-assay precision were less than 5% and 10%, respectively, and therefore well within standard regulatory acceptance criterion of ±15%.

Developing a Novel Measurement of Sleep in Rheumatoid Arthritis: Study Proposal for Approach and Considerations

The development of novel digital endpoints (NDEs) using digital health technologies (DHTs) may provide opportunities to transform drug development. It requires a multidisciplinary, multi-study approach with strategic planning and a regulatory-guided pathway to achieve regulatory and clinical acceptance. Many NDEs have been explored; however, success has been limited. To advance industry use of NDEs to support drug development, we outline a theoretical, methodological study as a use-case proposal to describe the process and considerations when developing and obtaining regulatory acceptance for an NDE to assess sleep in patients with rheumatoid arthritis (RA). RA patients often suffer joint pain, fatigue, and sleep disturbances (SDs). Although many researchers have investigated the mobility of joint functions using wearable technologies, the research of SD in RA has been limited due to the availability of suitable technologies. We proposed measuring the improvement of sleep as the novel endpoint for an anti-TNF therapy and described the meaningfulness of the measure, considerations of tool selection, and the design of clinical validation. The recommendations from the FDA patient-focused drug development guidance, the Clinical Trials Transformation Initiative (CTTI) pathway for developing novel endpoints from DHTs, and the V3 framework developed by the Digital Medicine Society (DiMe) have been incorporated in the proposal. Regulatory strategy and engagement pathways are also discussed.

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool.

STOFFENMANAGER® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER® and ART are based on a modified multiplicative model where an exposure base level (mg m−3) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m−3) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER® and ART. A literature review showed that the models have been validated only at the ‘operational analysis’ level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson’s correlations (r is <0.6) for both STOFFENMANAGER® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.

Overexpression of SHORT VEGETATIVE PHASE-LIKE (SVL) in Populus delays onset and reduces abundance of flowering in field-grown trees

The spread of transgenes and exotic germplasm from planted crops into wild or feral species is a difficult problem for public and regulatory acceptance of genetically engineered plants, particularly for wind-pollinated trees such as poplar. We report that overexpression of a poplar homolog of the floral repressor SHORT VEGETATIVE PHASE-LIKE (SVL), a homolog of the Arabidopsis MADS-box repressor SHORT VEGETATIVE PHASE (SVP), delayed the onset of flowering several years in three genotypes of field-grown transgenic poplars. Higher expression of SVL correlated with a delay in flowering onset and lower floral abundance, and did not cause morphologically obvious or statistically significant effects on leaf characteristics, tree form, or stem volume. Overexpression effects on reproductive and vegetative phenology in spring was modest and genotype-specific. Our results suggest that use of SVL and related floral repressors can be useful tools to enable a high level of containment for vegetatively propagated short-rotation woody energy or pulp crops.

Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Applications of interpretability in deep learning models for ophthalmology.

In this article, we introduce the concept of model interpretability, review its applications in deep learning models for clinical ophthalmology, and discuss its role in the integration of artificial intelligence in healthcare. The advent of deep learning in medicine has introduced models with remarkable accuracy. However, the inherent complexity of these models undermines its users' ability to understand, debug and ultimately trust them in clinical practice. Novel methods are being increasingly explored to improve models' 'interpretability' and draw clearer associations between their outputs and features in the input dataset. In the field of ophthalmology, interpretability methods have enabled users to make informed adjustments, identify clinically relevant imaging patterns, and predict outcomes in deep learning models. Interpretability methods support the transparency necessary to implement, operate and modify complex deep learning models. These benefits are becoming increasingly demonstrated in models for clinical ophthalmology. As quality standards for deep learning models used in healthcare continue to evolve, interpretability methods may prove influential in their path to regulatory approval and acceptance in clinical practice.

A narrative review about regulatory acceptability standards for clinical assays

A narrative review about regulatory acceptability standards for clinical assays

Regulatory procedures for emergency approval of medical products by regulatory agencies

Emergency use authorization of medical products by the regulatory agencies is not a usual procedure; it happens to cope with unanticipated health emergencies affecting a large group of population, these can be because of outbreak agents like virus, bacteria, etc., which can cause contagious diseases. Contagious diseases are classified into an outbreak, epidemic and pandemic disease, based on size and intensity of spread of the disease. Epidemic and Pandemic disease conditions such as CoVID-19 will trigger the emergency use authorization of products that help in the control, prevention and/or cure for the disease. EMA and FDA are well known advanced regulatory bodies, with eminent procedures for approval of the medication, harmonization of the standards as per the global regulatory acceptance. However, there are some differences between the two, in case of initiating the procedure, timelines, data required for approval of products under the emergency use. This article focuses on emergency approval of medications, regulations involved in the approval of medications and vaccines by EMA and FDA, some of the important data companies or sponsors need to submit to the regulatory bodies for approval, verification procedure and timelines for evaluation of manufacturer submitted data. Mutual recognition agreement and timeline of Remdesivir for approval by EC and FDA.

Fractions of Concern: Challenges and Strategies for the Safety Assessment of Biological Matter in Cosmetics

Cosmetic ingredients based on more or less refined biological matter (plants, fungi, bacteria, etc.) are gaining popularity. Advances in green chemistry and biotechnology are supporting this general trend further. Following numerous bans on the use of newly generated animal testing data in cosmetic safety assessments, and the worldwide demand for “cruelty-free” products, many alternative methods have been developed to assess the toxicity of ingredients. Whilst great strides have been, and continue to be, made, the area of systemic toxicity is one where international harmonisation and regulatory acceptance is still evolving. A strategy for the fractional assessment of biological matter is suggested to make approaches, such as threshold of toxicological concern (TTC) methodology, fit for purpose. Within this strategy, analytical data are used to generate compound classes which are quantified and assessed separately. Whilst this strategy opens new windows for assessing the safety of complex mixtures with a lack of toxicological data, it also raises awareness of the increasing complexity of cosmetic formulations and the general problem of additivity/synergy being rarely addressed. Extremely complex mixtures are and will be a growing challenge for safety assessors.

Distributed and localized cooling with thermoelectrics

G. Jeffrey Snyder is a Professor of Materials Science and Engineering at Northwestern University in Evanston Illinois. His interests are focused on engineering of electronic and thermal properties, and he is well known for his work on thermoelectric materials. He has developed new methods of electron band structure engineering and microstructure engineering of thermal and electrical properties of complex materials. His interdisciplinary approach stems from his background in solid state chemistry at Cornell University and the Max Planck Institute for solid state research, applied physics at Stanford University, and thermoelectric materials and device engineering at NASA/Jet Propulsion Laboratory and California Institute of Technology (Caltech).

Assessment of Realistic Departure from Nucleate Boiling Ratio (DNBR) Considering Uncertainty Quantification of Core Flow Asymmetry

Concern over the asymmetric phenomena in the core region has increased considering safety issues that are highly possible to reduce the thermal margin significantly in nuclear power plants. Since the seized reactor coolant pump (RCP) accident of an advanced power reactor 1400 (APR1400) can be regarded as a representative core asymmetric event with respect to core inlet flow, the departure from nucleate boiling ratio (DNBR), which is a regulatory acceptance criterion in nuclear safety, should be evaluated with consideration of the uncertainty range of the core inlet flow reflecting the actual geometry. This study investigates the DNBR quantitatively in the entire fuel assemblies in the core using several codes for system behavior, computational flow dynamics, sub-channel analysis, and uncertainty evaluation. Based on the results from a system thermal-hydraulic analysis of a seized RCP accident of APR1400, this study presents the uncertainty range calculated by computational fluid dynamics on the asymmetry of the core inlet flow. Damaged fuel rods are quantitatively identified through a sub-channel analysis, which presents statistic relevance to obtain the DNBR at 95% reliability and 95% accuracy level. Additionally, an optimized evaluation methodology of a non-loss of coolant accident (non-LOCA) is realized by several nuclear codes.

Evaluation of three rapid lateral flow antigen detection tests for the diagnosis of SARS-CoV-2 infection.

IntroductionThe COVID-19 pandemic has led to high demand of diagnostic tools. Rapid antigen detection tests have been developed and many have received regulatory acceptance such as CE IVD or FDA markings. Their performance needs to be carefully assessed.Materials and Methods158 positive and 40 negative retrospective samples collected in saline and analyzed by a laboratory-developed RT-PCR test were used to evaluate Sofia (Quidel), Standard Q (SD Biosensor), and Panbio™ (Abbott) rapid antigen detection tests (RADTs). A subset of the specimens was subjected to virus culture.ResultsThe specificity of all RADTs was 100 % and the sensitivity and percent agreement was 80 % and 85 % for Sofia, 81 % and 85 % for Standard Q, and 83 % and 86 % for Panbio™, respectively. All three RADTs evaluated in this study reached a more than 90 % sensitivity for samples with a high viral load as estimated from the low Ct (Cycle threshold) values in the reference RT-PCR. Virus culture was successful in 80 % of specimens with a Ct value <25.ConclusionsAs expected, the RADTs were less sensitive than RT-PCR. However, they benefit from the speed and ease of testing, and lower price as compared to RT-PCR. Repeated testing in appropriate settings may improve the overall performance.

Environmental Genomics Applications for Environmental Management Activities in the Oil and Gas Industry - State of the Art Review and Future Research Needs

The International Association of Oil and Gas Producers (IOGP) Environmental Genomics Joint Industry Program (JIP) was formed in June 2019. The aim of the JIP is to facilitate the development of guidelines for the application of environmental genomics to support environmental management activities in the oil and gas industry. Towards this goal, a white paper summarizing the state-of-the-art in environmental genomics research and how it may be used to advance technology development opportunities for the oil and gas industry was drafted. More specifically, a series of applications and focus areas of primary interest to oil and gas companies were covered including: baseline assessments; detection of key species; rapid assessment of invasive species; population status and dynamics; monitoring of environmental effects of oil and gas activities; remediation and restoration; sampling design; data analysis and interpretation; community representation; species abundance, distribution and viability; and real-time on-site measurement and analysis. baseline assessments; detection of key species; rapid assessment of invasive species; population status and dynamics; monitoring of environmental effects of oil and gas activities; remediation and restoration; sampling design; data analysis and interpretation; community representation; species abundance, distribution and viability; and real-time on-site measurement and analysis. In addition to the literature review, consultation of professionals from academic, regulatory, and industrial backgrounds with expertise on these topics was conducted. While there was a consensus that the application of environmental genomics has advanced greatly in a short period of time with demonstrable benefit potential, there was acknowledgement that key aspects of best management practices are still lacking. Furthermore, while the majority of regulators interviewed were aware to varying degrees of the methodological limitations which restrict the present use of environmental genomics in regulatory affairs, it transpired that there is considerable appetite and capacity amongst the regulatory community to engage in collaborative research initiatives with the oil and gas industry and academia. Through these academic, regulatory, and industrial consultation, specific environmental genomics study areas and applications requiring further development and refinement were identified. These include: methodological standardization, persistence and dispersal of eDNA; eDNA data integration with various other data types; improvement of reference databases; and refinement of molecular indices. methodological standardization, persistence and dispersal of eDNA; eDNA data integration with various other data types; improvement of reference databases; and refinement of molecular indices. Based on the above and considering the most efficient path to greater regulatory uptake for environmental genomic approaches for the oil and gas industry, the JIP’s recommendation is to pursue a Common-Garden Experiment. Such experiment should seek the involvement and ultimately endorsement from the Regulators marking the path towards wider regulatory acceptance and uptake of eDNA-based approaches.

Toward High-Throughput Fish Embryo Toxicity Tests in Aquatic Toxicology.

Addressing the shift from classical animal testing to high-throughput in vitro and/or simplified in vivo proxy models has been defined as one of the upcoming challenges in aquatic toxicology. In this regard, the fish embryo toxicity test (FET) has gained significant popularity and wide standardization as one of the sensitive alternative approaches to acute fish toxicity tests in chemical risk assessment and water quality evaluation. Nevertheless, despite the growing regulatory acceptance, the actual manipulation, dispensing, and analysis of living fish embryos remains very labor intensive. Moreover, the FET is commonly performed in plastic multiwell plates under static or semistatic conditions, potentially inadequate for toxicity assessment of some organic, easily degradable or highly adsorptive toxicants. Recent technological advances in the field of mechatronics, fluidics and digital vision systems demonstrate promising future opportunities for automation of many analytical stages in embryo toxicity testing. In this review, we highlight emerging advances in fluidic and laboratory automation systems that can prospectively enable high-throughput FET testing (HT-FET) akin to pipelines commonly found in in vitro drug discovery pipelines. We also outline the existing challenges, barriers to future development and provide an outlook of ground-breaking fluidic technologies in embryo toxicity testing.

Correction to: Biometric technology in “no-gate border crossing solutions” under consideration of privacy, ethical, regulatory and social acceptance

Correction to: Biometric technology in “no-gate border crossing solutions” under consideration of privacy, ethical, regulatory and social acceptance

Development and validation of a simple and rapid ICP-OES method for quantification of elemental impurities in voriconazole drug substance

BackgroundThe aim of the present study was to develop and validate an inductively coupled plasma optical emission spectroscopic (ICP–OES) method for quantification of elemental impurities, i.e., Lead, Palladium, and Zinc, in voriconazole drug substance, and this method was employed for the regular sample analysis of Lead, Palladium, and Zinc in voriconazole drug substance for pharmaceutical use. The method has been validated using RF power of 1150 W, auxiliary gas of 0.5 L/min, and nebulizer flow of 0.4 L/min and plasma view at axial mode for Lead and Palladium and radial mode for Zinc. The wavelength was monitored for Lead, Palladium, and Zinc at 220.3 nm, 340.4 nm, and 213.8 nm respectively.ResultsThe method is selective and is capable of detecting desired elemental impurities with regulatory acceptance limits in the presence of other elements. The validation experiments involve the demonstration of system suitability, specificity, LOD and LOQ, linearity, precision, and accuracy experiments. The linearity results obtained ˃ 0.9990 for all three impurities.ConclusionThe proposed method is simple, sensitive quality control tool for the simultaneous quantitative determination of Lead, Palladium, and Zinc at low levels in voriconazole drug substance.Graphical abstract

Non-Animal Strategies for Toxicity Assessment of Nanoscale Materials: Role of Adverse Outcome Pathways in the Selection of Endpoints.

Faster, cheaper, sensitive, and mechanisms-based animal alternatives are needed to address the safety assessment needs of the growing number of nanomaterials (NM) and their sophisticated property variants. Specifically, strategies that help identify and prioritize alternative schemes involving individual test models, toxicity endpoints, and assays for the assessment of adverse outcomes, as well as strategies that enable validation and refinement of these schemes for the regulatory acceptance are needed. In this review, two strategies 1) the current nanotoxicology literature review and 2) the adverse outcome pathways (AOPs) framework, a systematic process that allows the assembly of available mechanistic information concerning a toxicological response in a simple modular format, are presented. The review highlights 1) the most frequently assessed and reported ad hoc in vivo and in vitro toxicity measurements in the literature, 2) various AOPs of relevance to inhalation toxicity of NM that are presently under development, and 3) their applicability in identifying key events of toxicity for targeted in vitro assay development. Finally, using an existing AOP for lung fibrosis, the specific combinations of cell types, exposure and test systems, and assays that are experimentally supported and thus, can be used for assessing NM-induced lung fibrosis, are proposed.

Understanding the Development, Standardization, and Validation Process of Alternative In Vitro Test Methods for Regulatory Approval from a Researcher Perspective.

Due to economic, practical, ethical, and scientific reasons, researchers, among others, are pushing for alternative in vitro test methods to replace or reduce existing animal experiments. In order for these tests to be more broadly used by the industrial sector and regulatory bodies, orchestrated efforts are required to show the robustness and reliability of in vitro methods, which can accelerate the use for early screening testing. Another way of increasing the use of alternatives is to coordinate validation studies, that is, multi-laboratory trials, and to gain regulatory approval and instatement as test guidelines or standard method. However, awareness of the exact standardization, validation, and approval process has been a major obstacle for many researchers. Herein, the process has been broken down into three main phases: i) test method development; ii) intra- and inter-laboratory validation; and iii) regulatory acceptance. This general process applies to all alternative methods seeking validation and approval, although the intricacies of different toxicological endpoints and/or chemical sectors may lead to additional work, particularly in the validation stage. The authors' aim is to provide insight in the development process of alternative methods with a focus on in vitro cell culture methods over validation to regulatory acceptance.

Blockchain or Aggregator? An Assessment of Service Provision Approaches for Prosumer Engagement in Grid Congestion Management

Distributed load-management is seen as a means to enhance the integration of fluctuating renewable energy sources into the energy system and address the increasing strain on the German electricity grid. However, the advantages and disadvantages of different service provision approaches for this application, in particular blockchain-based solutions in contrast to aggregators, have not yet been investigated, a research avenue important to inform policymakers in the early stages of market and technology development. The sustainability and feasibility of three approaches, public blockchain, consortium blockchain and an aggregator using a relational database, were evaluated for their suitability to provide grid redispatch services through prosumer engagement, according to seven criteria by applying a multi-criteria analysis (MCA). The three feasibility criteria considered were scalability, regulatory acceptance and implementation network capacity, while the four sustainability criteria considered were privacy, security, costs and energy consumption. The analysis showed that public blockchain is least suitable for this application, whilst consortium blockchain and an aggregator using a relational database perform similarly on sustainability criteria, with the consortium blockchain performing better on security and the aggregator model on energy consumption. From a feasibility perspective, an aggregator using a relational database clearly outperformed blockchain solutions, suggesting better suitability at this point in time, with a need for regulatory innovation to allow for the future adoption of blockchain models.