Aim: Improvement and harmonization of European clinical pharmacology and therapeutics (CPT) education is urgently required. Because digital educational resources can be easily shared, adapted to local situations and re-used widely across a variety of educational systems, they may be ideally suited for this purpose. Methods: With a cross-sectional survey among principal CPT teachers in 279 out of 304 European medical schools, an overview and classification of digital resources was compiled. Results: Teachers from 95 (34%) medical schools in 26 of 28 EU countries responded, 66 (70%) of whom used digital educational resources in their CPT curriculum. A total of 89 of such resources were described in detail, including e-learning (24%), simulators to teach pharmacokinetics and/or pharmacodynamics (10%), virtual patients (8%), and serious games (5%). Together, these resources covered 235 knowledge-based learning objectives, 88 skills, and 13 attitudes. Only one third (27) of the resources were in-part or totally free and only two were licensed open educational resources (free to use, distribute and adapt). A narrative overview of the largest, free and most novel resources is given. Conclusion: Digital educational resources, ranging from e-learning to virtual patients and games, are widely used for CPT education in EU medical schools. Learning objectives are based largely on knowledge rather than skills or attitudes. This may be improved by including more real-life clinical case scenarios. Moreover, the majority of resources are neither free nor open. Therefore, with a view to harmonizing international CPT education, more needs to be learned about why CPT teachers are not currently sharing their educational materials.
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To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).
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For almost fifteen years, the availability and regulatory acceptance of new approach methodologies (NAMs) to assess the absorption, distribution, metabolism and excretion (ADME/biokinetics) in chemical risk evaluations are a bottleneck. To enhance the field, a team of 24 experts from science, industry, and regulatory bodies, including new generation toxicologists, met at the Lorentz Centre in Leiden, The Netherlands. A range of possibilities for the use of NAMs for biokinetics in risk evaluations were formulated (for example to define species differences and human variation or to perform quantitative in vitro-in vivo extrapolations). To increase the regulatory use and acceptance of NAMs for biokinetics for these ADME considerations within risk evaluations, the development of test guidelines (protocols) and of overarching guidance documents is considered a critical step. To this end, a need for an expert group on biokinetics within the Organisation of Economic Cooperation and Development (OECD) to supervise this process was formulated. The workshop discussions revealed that method development is still required, particularly to adequately capture transporter mediated processes as well as to obtain cell models that reflect the physiology and kinetic characteristics of relevant organs. Developments in the fields of stem cells, organoids and organ-on-a-chip models provide promising tools to meet these research needs in the future.
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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Hyperhomocysteinemia is a risk factor for cardiovascular disease, neurological disorders, and bone abnormalities. The key enzyme in homocysteine metabolism, cystathionine-β-synthase (CBS) is recognized as a target for new homocysteine-lowering therapies including enzyme replacement and gene therapy. Currently, there are no pharmacotherapies available that enhance CBS activity through its allosteric mechanism. The only known allosteric activator of CBS is S-adenosyl-L-methionine (SAM), which is available as a food supplement, but its effectiveness is limited by low membrane permeability and universal involvement in methylation reactions as a substrate. The discovery of CBS activators in high-throughput screening is challenging due to a lack of dedicated assays. Available HTS-compatible activity assays for CBS rely on measuring the product hydrogen sulfide or methanethiol where the signal increases with increased CBS activity. In the case of fluorescence-based assays, it is challenging to discern activators from autofluorescent compounds. In this study, we introduce a homocysteine consumption assay for isolated human CBS (HconCBS) based on the absorbance of Ellman's reagent. This assay leverages a decrease in signal upon CBS activation, with performance parameters exceeding the requirements for high-throughput screening. In a commercial library of 3010 compounds, the HconCBS assay identified 10 hit compounds as more active than SAM, whereas a fluorescence-based assay using 7-azido-4-methylcoumarin (AzMC) identified 141 hits. HconCBS identified 101 compounds with autoabsorbance which did not include hit compounds, while the fluorescence-based assay identified 383 autofluorescent compounds which included all hit compounds. While 4 out of 10 HconCBS hits were confirmed when purchased from a new source, the compounds affected homocysteine rather than CBS. Nevertheless, HconCBS consistently detected the CBS activator seleno-adenosyl-L-methionine (SeAM) added to 4 library plates and re-discovered the same library hits in 3 out of 4 re-screened plates. Taken together, HconCBS was designed to enable the discovery of allosteric CBS activators with greater reliability than fluorescence-based methods. Despite identifying some compounds that acted on homocysteine rather than CBS, the assay consistently identified the CBS activators SAM and SeAM and demonstrated reproducibility across two screening rounds. These findings establish HconCBS as a valuable tool for identifying potential therapeutic candidates for hyperhomocysteinemia, addressing a key gap in the development of CBS-targeted pharmacotherapies.
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ABSTRACT Introduction Junior doctors are responsible for a substantial number of prescribing errors, and final-year medical students lack sufficient prescribing knowledge and skills just before they graduate. Various national and international projects have been initiated to reform the teaching of clinical pharmacology and therapeutics (CP&T) during undergraduate medical training. However, there is as yet no list of commonly prescribed and available medicines that European doctors should be able to independently prescribe safely and effectively without direct supervision. Such a list could form the basis for a European Prescribing Exam and would harmonise European CP&T education. Therefore, the aim of this study is to reach consensus on a list of widely prescribed medicines, available in most European countries, that European junior doctors should be able to independently prescribe safely and effectively without direct supervision: the European List of Essential Medicines for Medical Education. Methods and analysis This modified Delphi study will recruit European CP&T teachers (expert group). Two Delphi rounds will be carried out to enable a list to be drawn up of medicines that are available in ≥80% of European countries, which are considered standard prescribing practice, and which junior doctors should be able to prescribe safely and effectively without supervision. Ethics and dissemination The study has been approved by the Medical Ethics Review Committee of VU University Medical Center (no. 2020.335) and by the Ethical Review Board of the Netherlands Association for Medical Education (approved project no. NVMO‐ERB 2020.4.8). The European List of Essential Medicines for Medical Education will be presented at national and international conferences and will be submitted to international peer-reviewed journals. It will also be used to develop and implement the European Prescribing Exam.
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The European Open Platform for Prescribing Education (EurOP2 E) seeks to improve and harmonize European clinical pharmacology and therapeutics (CPT) education by facilitating international collaboration and sharing problem-based, online, open educational resources. The COVID-19 pandemic forced teachers to switch to virtual modalities, highlighting the need for high-quality online teaching materials. The goal of this study was to establish the online problem-based teaching resources needed to sustain prescribing education during the pandemic and thereafter. A nominal group technique study was conducted with prescribing teachers from 15 European countries. Results were analyzed through thematic analysis. In four meetings, 20 teachers from 15 countries proposed and ranked 35 teaching materials. According to the participants, the most necessary problem-based-online teaching materials related to three overarching themes. Related to learning outcomes for CPT, participants proposed creating prescription scenarios, including materials focusing on background knowledge and resources on personalized medicine and topical/ethical issues such as the prescription’s impact on planetary health. Second, related to teaching, they proposed online case discussions, gamification and decision support systems. Finally, in relation to faculty development, they recommend teacher courses, a repository of reusable exam questions and harmonized formularies. Future work will aim to collaboratively produce such materials.
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From the article: Abstract Sub-chronic toxicity studies of 163 non-genotoxic chemicals were evaluated in order to predict the tumour outcome of 24-month rat carcinogenicity studies obtained from the EFSA and ToxRef databases. Hundred eleven of the 148 chemicals that did not induce putative preneoplastic lesions in the sub-chronic study also did not induce tumours in the carcinogenicity study (True Negatives). Cellular hypertrophy appeared to be an unreliable predictor of carcinogenicity. The negative predictivity, the measure of the compounds evaluated that did not show any putative preneoplastic lesion in de sub-chronic studies and were negative in the carcinogenicity studies, was 75%, whereas the sensitivity, a measure of the sub-chronic study to predict a positive carcinogenicity outcome was only 5%. The specificity, the accuracy of the sub-chronic study to correctly identify non-carcinogens was 90%. When the chemicals which induced tumours generally considered not relevant for humans (33 out of 37 False Negatives) are classified as True Negatives, the negative predictivity amounts to 97%. Overall, the results of this retrospective study support the concept that chemicals showing no histopathological risk factors for neoplasia in a sub-chronic study in rats may be considered non-carcinogenic and do not require further testing in a carcinogenicity study.
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Despite changing attitudes towards animal testing and current legislation to protect experimental animals, the rate of animal experiments seems to have changed little in recent years. On May 15–16, 2013, the In Vitro Testing Industrial Platform (IVTIP) held an open meeting to discuss the state of the art in alternative methods, how companies have, can, and will need to adapt and what drives and hinders regulatory acceptance and use. Several key messages arose from the meeting. First, industry and regulatory bodies should not wait for complete suites of alternative tests to become available, but should begin working with methods available right now (e.g., mining of existing animal data to direct future studies, implementation of alternative tests wherever scientifically valid rather than continuing to rely on animal tests) in non-animal and animal integrated strategies to reduce the numbers of animals tested. Sharing of information (communication), harmonization and standardization (coordination), commitment and collaboration are all required to improve the quality and speed of validation, acceptance, and implementation of tests. Finally, we consider how alternative methods can be used in research and development before formal implementation in regulations. Here we present the conclusions on what can be done already and suggest some solutions and strategies for the future.
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Development of novel testing strategies to detect adverse human health effects is of interest to replace in vivo-based drug and chemical safety testing. The aim of the present study was to investigate whether physiologically based kinetic (PBK) modeling-facilitated conversion of in vitro toxicity data is an adequate approach to predict in vivo cardiotoxicity in humans. To enable evaluation of predictions made, methadone was selected as the model compound, being a compound for which data on both kinetics and cardiotoxicity in humans are available. A PBK model for methadone in humans was developed and evaluated against available kinetic data presenting an adequate match. Use of the developed PBK model to convert concentration–response curves for the effect of methadone on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) in the so-called multi electrode array (MEA) assay resulted in predictions for in vivo dose–response curves for methadone-induced cardiotoxicity that matched the available in vivo data. The results also revealed differences in protein plasma binding of methadone to be a potential factor underlying variation between individuals with respect to sensitivity towards the cardiotoxic effects of methadone. The present study provides a proof-of-principle of using PBK modeling-based reverse dosimetry of in vitro data for the prediction of cardiotoxicity in humans, providing a novel testing strategy in cardiac safety studies.
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