Regulatory Toxicology and Pharmacology最新文献

Novel medical devices must conform to medical device regulation (MDR) for European market entry. Likewise, chemicals must comply with the Registration, Evaluation, Authorization and Restriction of Chemicals (REACh) regulation. Both pose regulatory challenges for manufacturers, but concordantly provide an approach for transferring data from an already registered device or compound to the one undergoing accreditation. This is called equivalence for medical devices and read-across for chemicals.

Although read-across is not explicitly prohibited in the process of medical device accreditation, it is usually not performed due to a lack of guidance and acceptance criteria from the authorities. Nonetheless, a scientifically justified read-across of material-based endpoints, as well as toxicological assessment of chemical aspects, such as extractables and leachables, can prevent failure of MDR device equivalence if data is lacking. Further, read-across, if applied correctly can facilitate the standard MDR conformity assessment.

The need for read-across within medical device registration should let authorities to reconsider device accreditation and the formulation of respective guidance documents. Acceptance criteria like in the European Chemicals Agency (ECHA) read-across assessment framework (RAAF) are needed. This can reduce the impact of the MDR and help with keeping high European innovation device rate, beneficial for medical device patients.

Ethylene thiourea, or ETU, is used in the rubber industry and is a degradation product and impurity in some fungicides. The general public may be exposed to low concentrations of residues of ETU in a variety of ways, including food treated with ethylene bis-dithiocarbamate (EBDC) fungicides or migration from rubber products. Biomonitoring of ETU in urine is useful for an assessment of integrated exposures to ETU across different sources and routes of exposure. In this evaluation, we review available health-based risk assessments and toxicological reference values (TRVs) for ETU and derive Biomonitoring Equivalent (BE) values for interpretation of population biomonitoring data. BEs were derived based on existing TRVs derived by Health Canada, yielding a BE of 27 μg of total ETU/L in urine associated with the Acceptable Daily Intake (ADI) and 6.7 μg/L associated with a 1e-6 cancer risk. These BEs are based on an analytical method that involves a digestion step to liberate conjugated ETU, thus producing ‘total’ ETU in urine. The BE values derived in this manuscript can serve as a guide to help public health officials and regulators interpret population based ETU biomonitoring data in a public health risk context.

Chemical equivalence testing can be used to assess the biocompatibility implications of a materials or manufacturing change for a medical device. This testing can provide a relatively facile means to evaluate whether the change may result in additional or different toxicological concerns. However, one of the major challenges in the interpretation of chemical equivalence data is the lack established criteria for determining if two sets of extractables data are effectively equivalent. To address this gap, we propose a two–part approach based upon a relatively simple statistical model. First, the probability of a false positive conclusion, wherein there is an incorrectly perceived increase for a given analyte in the comparator relative to the baseline device, can be reduced to a prescribed level by establishing an appropriate acceptance criterion for the ratio of the observed means. Second, the probability of a false negative conclusion, where an actual increase in a given analyte cannot be discerned from the test results, can be minimized by specifying a limiting value of applicability based on the margin of safety (MoS) of the analyte. This approach provides a quantitative, statistically motivated method to interpret chemical equivalence data, despite the relatively high intrinsic variability and small number of replicates typically associated with a chemical characterization evaluation.

Regulatory agencies consistently deal with extensive document reviews, ranging from product submissions to both internal and external communications. Large Language Models (LLMs) like ChatGPT can be invaluable tools for these tasks, however present several challenges, particularly the proprietary information, combining customized function with specific review needs, and transparency and explainability of the model's output. Hence, a localized and customized solution is imperative.

To tackle these challenges, we formulated a framework named askFDALabel on FDA drug labeling documents that is a crucial resource in the FDA drug review process. AskFDALabel operates within a secure IT environment and comprises two key modules: a semantic search and a Q&A/text-generation module. The Module S built on word embeddings to enable comprehensive semantic queries within labeling documents. The Module T utilizes a tuned LLM to generate responses based on references from Module S. As the result, our framework enabled small LLMs to perform comparably to ChatGPT with as a computationally inexpensive solution for regulatory application.

To conclude, through AskFDALabel, we have showcased a pathway that harnesses LLMs to support agency operations within a secure environment, offering tailored functions for the needs of regulatory research.

The United States Environmental Protection Agency (USEPA) uses the lethal dose 50% (LD₅₀) value from in vivo rat acute oral toxicity studies for pesticide product label precautionary statements and environmental risk assessment (RA). The Collaborative Acute Toxicity Modeling Suite (CATMoS) is a quantitative structure-activity relationship (QSAR)-based in silico approach to predict rat acute oral toxicity that has the potential to reduce animal use when registering a new pesticide technical grade active ingredient (TGAI). This analysis compared LD₅₀ values predicted by CATMoS to empirical values from in vivo studies for the TGAIs of 177 conventional pesticides. The accuracy and reliability of the model predictions were assessed relative to the empirical data in terms of USEPA acute oral toxicity categories and discrete LD₅₀ values for each chemical. CATMoS was most reliable at placing pesticide TGAIs in acute toxicity categories III (>500–5000 mg/kg) and IV (>5000 mg/kg), with 88% categorical concordance for 165 chemicals with empirical in vivo LD₅₀ values ≥ 500 mg/kg. When considering an LD₅₀ for RA, CATMoS predictions of 2000 mg/kg and higher were found to agree with empirical values from limit tests (i.e., single, high-dose tests) or definitive results over 2000 mg/kg with few exceptions.

Accumulating evidence has shown that the abnormal toxicity test (ATT) is not suitable as a quality control batch release test for biologics and vaccines. The purpose of the current study was to explore the optimal ATT experimental design for an adenoviral vector-based vaccine product to avoid false positive results following the standard test conditions stipulated in the Pharmacopoeias. ATT were conducted in both mice and guinea pigs based on methods in Pharmacopeias, with modifications to assess effects of dose volume and amount of virus particles (VPs). The results showed intraperitoneal (IP) dosing at human relevant dose and volume (i.e., VPs), as required by pharmacopeia study design, resulted in false positive findings not associated with extraneous contaminants of a product. Considering many gene therapy products use adeno associated virus as the platform for transgene delivery, data from this study are highly relevant in providing convincing evidence to show the ATT is inappropriate as batch release test for biologics, vaccine and gene therapy products. In conclusion, ATT, which requires unnecessary animal usage and competes for resources which otherwise can be spent on innovative medicine research, should be deleted permanently as batch release test by regulatory authorities around the world.

Pharmacokinetic (PK) models are increasingly submitted to the FDA to support first-in-human (FIH) dose selection of immune-oncology products. To examine whether a simple PK modeling (SPM) using clearance for scaling was acceptable for dose estimation, FIH_(SPM) doses were computed and compared to doses that were safely administered to patients. We concluded that the SPM approach is acceptable in FIH dose estimation, but the variables should be carefully selected for CD3 constructs. For CD3 constructs, use of 60 kg BW_h, a clearance exponent of 0.75, and a targeted plasma concentration based on relevant and/or sensitive activity assays was an acceptable approach for FIH dose selection; use of 0.85 as the scaling factor is questionable at this time as it resulted in a FIH dose that was too close to the AHD for one product (7%). Immune activating mAbs were not sensitive to changes in the clearance exponent (0.75–0.85) or body weight (60–70 kg). For PD-1/PD-L1 mAbs, using products’ in vitro EC50 in the model resulted in suboptimal FIH doses and clinical data of closely related products informed FIH dose selection. PK models submitted by sponsors were diverse in methods, assumptions, and variables, and the resulting FIH doses were not always optimal.

RIVM convened a workshop on the use of New Approach Methodologies (NAMs) for the ad hoc human health risk assessment of food and non-food products. Central to the workshop were two case studies of marketed products with a potential health concern: the botanical Tabernanthe iboga which is used to facilitate mental or spiritual insight or to (illegally) treat drug addiction and is associated with cardiotoxicity, and dermal creams containing female sex hormones, intended for use by perimenopausal women to reduce menopause symptoms without medical supervision. The workshop participants recognized that data from NAM approaches added valuable information for the ad hoc risk assessment of these products, although the available approaches were inadequate to derive health-based guidance values. Recommendations were provided on how to further enhance and implement NAM approaches in regulatory risk assessment, specifying both scientific and technical aspects as well as stakeholder engagement aspects.

A Value of Information (VOI) analysis can play a key role in decision-making for adopting new approach methodologies (NAMs). We applied EPA's recently developed VOI framework to the Threshold of Toxicological Concern (TTC). Obtaining/deriving a TTC value for use as a toxicity reference value (TRV) for substances with limited toxicity data was shown to provide equivalent or greater health protection, immense return on investment (ROI), greater net benefit, and substantially lower costs of delay (CoD) compared with TRVs derived from either traditional human health assessment (THHA) chronic toxicity testing in lab animals or the 5-day in vivo EPA Transcriptomic Assessment Product (ETAP). For all nine exposure scenarios examined, the TTC was more economical terms of CoD and ROI than the ETAP or the THHA; expected net benefit was similar for the TTC and ETAP with both of these more economical than the THHA The TTC ROI was immensely greater (5,000,000-fold on average) than the ROI for THHA and the ETAP ROI (100,000-fold on average). These results support the use of the TTC for substances within its domain of applicability to waive requiring certain in vivo tests, or at a minimum, as an initial screening step before conducting either the ETAP or THHA in vivo studies.