Water safety planning for healthcare facilities for extreme events.

Disasters such as the Ahr Valley flood in 2021 make us aware of the importance of functioning healthcare facilities. Their functionality depends on the availability of drinking water. Water safety planning is a long-established method to increase the safety of water utilities. Our work supports the implementation of water safety planning in healthcare facilities during normal operations and emergency situations concerning the water supply. The authors conducted a stakeholder mapping exercise and problem awareness analysis. Based on these results, it was identified what is needed to overcome barriers to water safety planning (WSP). Building on existing procedures, the WSP concept, and latest scientific findings, an event-specific risk assessment method for healthcare facilities was developed and applied in a case study. Based on an analysis of water demand, water-related processes, and infrastructure, potentially necessary components for establishing an emergency supply were identified. For these, based on technical and legal requirements, planning principles were developed, and prototypes of components for emergency water supply were built. They were tested in pilot trials, particularly regarding hygienic safety. For the management of crises in hospitals, a survey was carried out on the command structures used in practice. Finally, recommendations were drawn based on the German Hospital Incident Command System.

A preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugs.

In vitro secondary pharmacology assays are an important tool for predicting clinical adverse drug reactions (ADRs) of investigational drugs. We created the Secondary Pharmacology Database (SPD) by testing 1958 drugs using 200 assays to validate target-ADR associations. Compared to public and subscription resources, 95% of all and 36% of active (AC50 < 1 µM) results are unique to SPD, with bias towards higher activity in public resources. Annotating drugs with free maximal plasma concentrations, we find 684 physiologically relevant unpublished off-target activities. Furthermore, 64% of putative ADRs linked to target activity in key literature reviews are not statistically significant in SPD. Systematic analysis of all target-ADR pairs identifies several putative associations supported by publications. Finally, candidate mechanisms for known ADRs are proposed based on SPD off-target activities. Here we present a freely-available resource for benchmarking ADR predictions, explaining phenotypic activity and investigating clinical properties of marketed drugs.

Identification of Brain-Penetrant ATP-Competitive mTOR Inhibitors for CNS Syndromes.

The allosteric inhibitor of the mechanistic target of rapamycin (mTOR) everolimus reduces seizures in tuberous sclerosis complex (TSC) patients through partial inhibition of mTOR functions. Due to its limited brain permeability, we sought to develop a catalytic mTOR inhibitor optimized for central nervous system (CNS) indications. We recently reported an mTOR inhibitor (1) that is able to block mTOR functions in the mouse brain and extend the survival of mice with neuronal-specific ablation of the Tsc1 gene. However, 1 showed the risk of genotoxicity in vitro. Through structure-activity relationship (SAR) optimization, we identified compounds 9 and 11 without genotoxicity risk. In neuronal cell-based models of mTOR hyperactivity, both corrected aberrant mTOR activity and significantly improved the survival rate of mice in the Tsc1 gene knockout model. Unfortunately, 9 and 11 showed limited oral exposures in higher species and dose-limiting toxicities in cynomolgus macaque, respectively. However, they remain optimal tools to explore mTOR hyperactivity in CNS disease models.

Should everyone in need be treated equally? A European survey of expert judgment on social vulnerability to floods and pandemics to validate multi-hazard vulnerability factors.

Several European countries were affected by severe floods in 2021. At the same time, despite the deployment of vaccines, Europe was the COVID-19 pandemic's epicenter several times during 2021. One research aim of this study is to identify socio-demographic groups vulnerable to floods and whether the groups vulnerable to floods and pandemics overlap or are disjoint. We ran a survey in four languages (English, French, German, and Spanish) and collected the judgment of 366 experts in disaster risk management and first-responders to find out how those people caring for "people in need" (be it operational or administratively) think about which persons are more at risk than others. Another research aim is to validate multi-hazard vulnerability factors by comparing judgment on groups vulnerable to the COVID-19 pandemic and to floods. The main findings are that experts think that socially vulnerable groups should be rescued or treated first. Treating everyone equally is less favored by comparison. Infrastructure losses, followed by economic losses, reveal better than deaths or psychological issues whether vulnerability played a role in a disaster. Regarding vulnerability characteristics, older, homeless people, and immigrants rank highest, and most factors can be used to explain both flood and COVID-19 vulnerability, while some differ; for example, mobility impairment is less important for COVID-19. There are major discrepancies between what respondents think should be done to prioritize help to certain groups and what they have experienced is being done on the field.

Acute cell stress screen with supervised machine learning predicts cytotoxicity of excipients.

Excipients serve as vehicles, preservatives, solubilizers, and colorants for drugs, food, and cosmetics. They are considered to be inert at biological targets; however, several reports suggest that some could interact with human targets and cause unwanted effects. We investigated 40 commonly used drug excipients for cellular stress in the AsedaSciences® SYSTEMETRIC® Cell Health Screen, which was developed to estimate toxicity risk of small molecular entities (SMEs). The screen uses supervised machine learning (ML) to classify test compound cell stress phenotypes relative to a training set of on-market and withdrawn drugs. While 80% (n = 32) of the excipients did not show elevated risk in a broad, but pharmacologically relevant, concentration range (5 nM to 100 µM), we identified 20% (n = 8) with elevated risk. This group included two mercury containing preservatives, propyl gallate, methylene blue, benzethonium chloride, and cetylpyridinium chloride, all known for previously reported safety issues. All compounds were tested in parallel in an in vitro assay panel regularly used to investigate off-target effects of drug candidates. Target engagement in this assay panel confirmed risk-indicative biological activity for the same excipients, except propyl gallate, which may have a separate, interesting mechanism. We conclude that the SYSTEMETRIC Cell Health Screen, in conjunction with in vitro pharmacological profiling, can provide a fast and cost effective methodology for first line testing of SMEs, including excipients, to avoid cellular damage, particularly in the GI, where they are represented in high concentrations.

The activities of drug inactive ingredients on biological targets.

Excipients, considered "inactive ingredients," are a major component of formulated drugs and play key roles in their pharmacokinetics. Despite their pervasiveness, whether they are active on any targets has not been systematically explored. We computed the likelihood that approved excipients would bind to molecular targets. Testing in vitro revealed 25 excipient activities, ranging from low-nanomolar to high-micromolar concentration. Another 109 activities were identified by testing against clinical safety targets. In cellular models, five excipients had fingerprints predictive of system-level toxicity. Exposures of seven excipients were investigated, and in certain populations, two of these may reach levels of in vitro target potency, including brain and gut exposure of thimerosal and its major metabolite, which had dopamine D3 receptor dissociation constant K d values of 320 and 210 nM, respectively. Although most excipients deserve their status as inert, many approved excipients may directly modulate physiologically relevant targets.

Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology.

BACKGROUND: Adverse drug reactions (ADRs) are one of the leading causes of morbidity and mortality in health care. Understanding which drug targets are linked to ADRs can lead to the development of safer medicines. METHODS: Here, we analyse in vitro secondary pharmacology of common (off) targets for 2134 marketed drugs. To associate these drugs with human ADRs, we utilized FDA Adverse Event Reports and developed random forest models that predict ADR occurrences from in vitro pharmacological profiles. FINDINGS: By evaluating Gini importance scores of model features, we identify 221 target-ADR associations, which co-occur in PubMed abstracts to a greater extent than expected by chance. Amongst these are established relations, such as the association of in vitro hERG binding with cardiac arrhythmias, which further validate our machine learning approach. Evidence on bile acid metabolism supports our identification of associations between the Bile Salt Export Pump and renal, thyroid, lipid metabolism, respiratory tract and central nervous system disorders. Unexpectedly, our model suggests PDE3 is associated with 40 ADRs. INTERPRETATION: These associations provide a comprehensive resource to support drug development and human biology studies. FUNDING: This study was not supported by any formal funding bodies.

Constructing a comprehensive disaster resilience index: The case of Italy.

Measuring disaster resilience is a key component of successful disaster risk management and climate change adaptation. Quantitative, indicator-based assessments are typically applied to evaluate resilience by combining various indicators of performance into a single composite index. Building upon extensive research on social vulnerability and coping/adaptive capacity, we first develop an original, comprehensive disaster resilience index (CDRI) at municipal level across Italy, to support the implementation of the Sendai Framework for Disaster Risk Reduction 2015-2030. As next, we perform extensive sensitivity and robustness analysis to assess how various methodological choices, especially the normalisation and aggregation methods applied, influence the ensuing rankings. The results show patterns of social vulnerability and resilience with sizeable variability across the northern and southern regions. We propose several statistical methods to allow decision makers to explore the territorial, social and economic disparities, and choose aggregation methods best suitable for the various policy purposes. These methods are based on linear and non-liner normalization approaches combining the OWA and LSP aggregators. Robust resilience rankings are determined by relative dominance across multiple methods. The dominance measures can be used as a decision-making benchmark for climate change adaptation and disaster risk management strategies and plans.

Vitamin C induces specific demethylation of H3K9me2 in mouse embryonic stem cells via Kdm3a/b.

BACKGROUND: Histone methylation patterns regulate gene expression and are highly dynamic during development. The erasure of histone methylation is carried out by histone demethylase enzymes. We had previously shown that vitamin C enhances the activity of Tet enzymes in embryonic stem (ES) cells, leading to DNA demethylation and activation of germline genes. RESULTS: We report here that vitamin C induces a remarkably specific demethylation of histone H3 lysine 9 dimethylation (H3K9me2) in naïve ES cells. Vitamin C treatment reduces global levels of H3K9me2, but not other histone methylation marks analyzed, as measured by western blot, immunofluorescence and mass spectrometry. Vitamin C leads to widespread loss of H3K9me2 at large chromosomal domains as well as gene promoters and repeat elements. Vitamin C-induced loss of H3K9me2 occurs rapidly within 24 h and is reversible. Importantly, we found that the histone demethylases Kdm3a and Kdm3b are required for vitamin C-induced demethylation of H3K9me2. Moreover, we show that vitamin C-induced Kdm3a/b-mediated H3K9me2 demethylation and Tet-mediated DNA demethylation are independent processes at specific loci. Lastly, we document Kdm3a/b are partially required for the upregulation of germline genes by vitamin C. CONCLUSIONS: These results reveal a specific role for vitamin C in histone demethylation in ES cells and document that DNA methylation and H3K9me2 cooperate to silence germline genes in pluripotent cells.

Xenobiotic CAR Activators Induce Dlk1-Dio3 Locus Noncoding RNA Expression in Mouse Liver.

Derisking xenobiotic-induced nongenotoxic carcinogenesis (NGC) represents a significant challenge during the safety assessment of chemicals and therapeutic drugs. The identification of robust mechanism-based NGC biomarkers has the potential to enhance cancer hazard identification. We previously demonstrated Constitutive Androstane Receptor (CAR) and WNT signaling-dependent up-regulation of the pluripotency associated Dlk1-Dio3 imprinted gene cluster noncoding RNAs (ncRNAs) in the liver of mice treated with tumor-promoting doses of phenobarbital (PB). Here, we have compared phenotypic, transcriptional ,and proteomic data from wild-type, CAR/PXR double knock-out and CAR/PXR double humanized mice treated with either PB or chlordane, and show that hepatic Dlk1-Dio3 locus long ncRNAs are upregulated in a CAR/PXR-dependent manner by two structurally distinct CAR activators. We further explored the specificity of Dlk1-Dio3 locus ncRNAs as hepatic NGC biomarkers in mice treated with additional compounds working through distinct NGC modes of action. We propose that up-regulation of Dlk1-Dio3 cluster ncRNAs can serve as an early biomarker for CAR activator-induced nongenotoxic hepatocarcinogenesis and thus may contribute to mechanism-based assessments of carcinogenicity risk for chemicals and novel therapeutics.

Discovery of an Acrylic Acid Based Tetrahydroisoquinoline as an Orally Bioavailable Selective Estrogen Receptor Degrader for ERα+ Breast Cancer.

Tetrahydroisoquinoline 40 has been identified as a potent ERα antagonist and selective estrogen receptor degrader (SERD), exhibiting good oral bioavailability, antitumor efficacy, and SERD activity in vivo. We outline the discovery and chemical optimization of the THIQ scaffold leading to THIQ 40 and showcase the racemization of the scaffold, pharmacokinetic studies in preclinical species, and the in vivo efficacy of THIQ 40 in a MCF-7 human breast cancer xenograft model.

Secondary pharmacology: screening and interpretation of off-target activities - focus on translation.

Secondary pharmacology is an essential component of drug discovery and is used extensively in the pharmaceutical industry for achieving optimal specificity of new drugs via early hazard identification and off-target mitigation. The importance of this discipline has been achieved by increasing its translational value, based on the recognition of biological target-drug molecule-adverse drug reaction (ADR) associations and integration of secondary pharmacology data with pharmacokinetic parameters. Information obtained from clinical ADRs, from recognition of specific phenotypes of animal models and from hereditary diseases provides increasing regulatory confidence in the target-based approach to ADR prediction and mitigation. Here, we review the progress of secondary pharmacology during the past decade and highlight and demonstrate its applications and impact in drug discovery.

A screening pattern recognition method finds new and divergent targets for drugs and natural products.

Computational target prediction methods using chemical descriptors have been applied exhaustively in drug discovery to elucidate the mechanisms-of-action (MOAs) of small molecules. To predict truly novel and unexpected small molecule-target interactions, compounds must be compared by means other than their chemical structure alone. Here we investigated predictions made by a method, HTS fingerprints (HTSFPs), that matches patterns of activities in experimental screens. Over 1,400 drugs and 1,300 natural products (NPs) were screened in more than 200 diverse assays, creating encodable activity patterns. The comparison of these activity patterns to an MOA-annotated reference panel led to the prediction of 5,281 and 2,798 previously unknown targets for the NP and drug sets, respectively. Intriguingly, there was limited overlap among the targets predicted; the drugs were more biased toward membrane receptors and the NPs toward soluble enzymes, consistent with the idea that they represent unexplored pharmacologies. Importantly, HTSFPs inferred targets that were beyond the prediction capabilities of standard chemical descriptors, especially for NPs but also for the more explored drug set. Of 65 drug-target predictions that we tested in vitro, 48 (73.8%) were confirmed with AC50 values ranging from 38 nM to 29 µM. Among these interactions was the inhibition of cyclooxygenases 1 and 2 by the HIV protease inhibitor Tipranavir. These newly discovered targets that are phylogenetically and phylochemically distant to the primary target provide an explanation for spontaneous bleeding events observed for patients treated with this drug, a physiological effect that was previously difficult to reconcile with the drug's known MOA.