An in silico method has been developed that permits the binary differentiation between pure liquids causing serious eye damage or eye irritation, and pure liquids with no need for such classification, according to the UN GHS system. The method is based on the finding that the Hansen Solubility Parameters (HSP) of a liquid are collectively important predictors for eye irritation. Thus, by applying a two-tier approach in which in silico predicted pKa values (firstly) and a trained model based solely on in silico-predicted HSP data (secondly) were used, we have developed, and validated, a fully in silico approach for predicting the outcome of a Draize test (in terms of UN GHS Cat. 1/Cat. 2A/Cat. 2B or UN GHS No Cat.) with high validation set performance (sensitivity = 0.846, specificity = 0.818, balanced accuracy = 0.832) using SMILES only. The method is applicable to pure non-ionic liquids with molecular weight below 500 g/mol, fewer than six hydrogen bond donors (e.g. nitrogen–hydrogen or oxygen–hydrogen bonds) and fewer than eleven hydrogen bond acceptors (e.g. nitrogen or oxygen atoms). Due to its fully in silico characteristics, this method can be applied to pure liquids that are still at the desktop design stage and not yet in production.

Objectives: New drugs and methods to efficiently fight carbapenem-resistant gram-negative pathogens are sorely needed. In this study, we characterized the preclinical pharmacokinetics (PK) and pharmacodynamics of the clinical stage drug candidate apramycin in time kill and mouse lung infection models. Based on in vitro and in vivo data, we developed a mathematical model to predict human efficacy. Methods: Three pneumonia-inducing gram-negative species Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae were studied. Bactericidal kinetics were evaluated with time-kill curves; in vivo PK were studied in healthy and infected mice, with sampling in plasma and epithelial lining fluid after subcutaneous administration; in vivo efficacy was measured in a neutropenic mouse pneumonia model. A pharmacokinetic-pharmacodynamic model, integrating all the data, was developed and simulations were performed. Results: Good lung penetration of apramycin in epithelial lining fluid (ELF) was shown (area under the curve (AUC)ELF/AUCplasma = 88%). Plasma clearance was 48% lower in lung infected mice compared to healthy mice. For two out of five strains studied, a delay in growth (∼5 h) was observed in vivo but not in vitro. The mathematical model enabled integration of lung PK to drive mouse PK and pharmacodynamics. Simulations predicted that 30 mg/kg of apramycin once daily would result in bacteriostasis in patients. Discussion: Apramycin is a candidate for treatment of carbapenem-resistant gram-negative pneumonia as demonstrated in an integrated modeling framework for three bacterial species. We show that mathematical modelling is a useful tool for simultaneous inclusion of multiple data sources, notably plasma and lung in vivo PK and simulation of expected scenarios in a clinical setting, notably lung infections. © 2022 The Author(s)

In the past 15 years, close to 1000 of new psychoactive substances (NPS) have been reported in Europe and globally. At the time of identification, data on safety, toxicity and carcinogenic potential of many NPS are not available or very limited. To work more efficiently, a strategy and collaboration between the Public Health Agency of Sweden (PHAS) and the National Board of Forensic Medicine was established involving in vitro receptor activity assays to demonstrate neurological activity of NPS. This report summarizes the first results on the synthetic cannabinoid receptor agonists (SCRAs), and subsequent actions taken by PHAS. A total of 18 potential SCRAs were selected by PHAS for in vitro pharmacological characterization. 17 compounds could be acquired and investigated for their activity on the human cannabinoid-1 (CB1) receptors expressed together with the AequoScreen system in CHO-K1 cells. Dose-response curves were established using eight different concentrations in triplicates at three occasions with JWH-018 as reference. For the MDMB-4en-PINACA, MMB-022, ACHMINACA, ADB-BUTINACA, 5F-CUMYL-PeGACLONE, 5C-AKB48, NM-2201, 5F-CUMYL-PINACA, JWH-022, 5Cl-AB-PINACA, MPhP-2201, 5F-AKB57 the half maximal effective concentration values ranged from 2.2 nM (5F-CUMYL-PINACA) to 171 nM (MMB-022). EG-018 and 3,5-AB-CHMFUPPYCA were none-active. The results contributed to 14 of these compounds being scheduled as narcotics in Sweden. In conclusion, many of the emerging SCRAs are potent activators of the CB1 receptor in vitro, although some lack activity or are partial agonists. The new strategy proved useful when data on psychoactive effects of the SCRAs under investigation were not available or limited. © 2023 The Authors

The objective of the present study was to investigate some commonly detected halogenated textile pollutants for their bioavailability and hazardous properties. Release into artificial sweat and skin absorption in vitro were examined as well as mutagenic effects by Ames test, and skin-sensitizing properties from a peptide reactivity assay combined with a cell test. All investigated compounds were shown to migrate from the textile into sweat and be absorbed by the skin, although to a different extent. The experimental values for migration were found to be up to 390 times higher compared to literature values. Two of the studied compounds, 2,5-dinitrochlorobenzene and 3,5-dinitrobromobenzene, both exhibited mutagenic effects in the Ames test, while both 2,5-dinitrochlorobenzene and 2,6-dichlorobenzene-1,4-diamine were classified as skin sensitizers. The allergenic reactivity of the latter was found to be due to an oxidized transformation product. Risks for the induction of skin allergy and other non-carcinogenic effects from dermal exposure to the individual compounds were found low, even when considering clothing with the highest reported levels. However, the complex mixtures of chemicals often present in garments may still constitute a health risk, especially when considering the many hours of daily exposure. It is important to further study the toxicity of other frequently occurring chemicals as well as the synergistic effects of chemicals that co-occur in clothing.

A new series of dual low nanomolar benzothiazole inhibitors of bacterial DNA gyrase and topoisomerase IV were developed. The resulting compounds show excellent broad-spectrum antibacterial activities against Gram-positive Enterococcus faecalis, Enterococcus faecium and multidrug resistant (MDR) Staphylococcus aureus strains [best compound minimal inhibitory concentrations (MICs): range, <0.03125-0.25 μg/mL] and against the Gram-negatives Acinetobacter baumannii and Klebsiella pneumoniae (best compound MICs: range, 1-4 μg/mL). Lead compound 7a was identified with favorable solubility and plasma protein binding, good metabolic stability, selectivity for bacterial topoisomerases, and no toxicity issues. The crystal structure of 7a in complex with Pseudomonas aeruginosa GyrB24 revealed its binding mode at the ATP-binding site. Expanded profiling of 7a and 7h showed potent antibacterial activity against over 100 MDR and non-MDR strains of A. baumannii and several other Gram-positive and Gram-negative strains. Ultimately, in vivo efficacy of 7a in a mouse model of vancomycin-intermediate S. aureus thigh infection was also demonstrated. © 2023 The Authors. 

Nitric oxide (NO) contributes to maintaining normal cardiovascular and renal function. NO is generally formed enzymatically by NO synthase in the vascular endothelium. NO bioactivity can also be attributed to dietary intake of inorganic nitrate, which is abundant in our diet, especially in green leafy vegetables and beets. Ingested nitrate is reduced to nitrite by oral commensal bacteria and further to NO systemically. Previous studies have shown that dialysis, by means of removing nitrate and nitrite from the body, can reduce NO bioactivity. Hence, dietary intervention approaches aimed to boost the nitrate–nitrite–NO pathway may be of benefit in dialysis patients. The purpose of this study was to examine the kinetics of plasma nitrate and nitrite after a single intake of nitrate-rich concentrated beetroot juice (BJ) in adult hemodialysis (HD) patients and in healthy volunteers (HV). Eight HD patients and seven HV participated in this single center, randomized, single-blind, placebo-controlled, crossover study. Each participant received a sequential single administration of active BJ (70 mL 400 mg nitrate) and placebo BJ (70 mL 0 mg nitrate) in a random order separated by a washout period of seven days. For the kinetic analysis, blood samples were collected at different time-points before and up to 44 h after BJ intake. Compared with placebo, active BJ significantly increased plasma nitrate and nitrite levels both in HD patients and HV. The area under the curve and the maximal concentration of plasma nitrate, but not of nitrite, were significantly higher in HD patients as compared with HV. In both groups, active BJ ingestion did not affect blood pressure or plasma potassium levels. Both BJs were well tolerated in all participants with no adverse events reported. Our data provide useful information in planning dietary nitrate supplementation efficacy studies in patients with reduced NO bioactivity. © 2022 by the authors. 

In several countries forest-based biofuels are being developed and to some extent also deployed. Fast pyrolysis bio-oil produced from, for example, sawdust, has now been coprocessed in fluid catalytic cracking refinery units in a number of commercial trials. However, this application is limited to about 10% of the total feed, and coprocessing in conventional fixed bed hydrotreaters is necessary to reach the high potential with this feedstock. Feeding and upgrading of fast pyrolysis bio-oil in a fixed bed reactor configuration is still problematic due to the inherent bio-oil properties. Stabilization of reactive compounds in fast pyrolysis bio-oil and mild hydrotreatment in a separate refining unit prior to refinery integration has therefore been developed the past decade. Another approach, presented here, involves complete dewatering of fast pyrolysis bio-oil by azeotropic distillation using mesityl oxide as the solvent, followed by conversion of the abundant hydroxyl compounds via mixed anhydride esterification methodology using an external source of mixed carboxylic acids of different chain lengths originating from renewable tall oil fatty acids, providing a lipophilic feed component. Dewatering and derivatizing were carried out in reactors up to 50 dm3 with a mass ratio of fast pyrolysis bio-oil to tall oil fatty acid of 10:13. The produced lipophilic oils were miscible with a petroleum light gas oil fraction and exhibited superior stability even after accelerated aging at elevated temperature (80 °C). The derivatized oils were thus mixed with light gas oil, with a proportion of 30 wt % derivatized oil in final blends and hydrotreated continuously in pilot fixed bed reactors for 14 days at 4 operating conditions without plugging or excessive exotherms. The test conditions were varied; the reactor pressure was either 55 or 80 bar, temperature 380 or 400 °C, and liquid hourly space velocity either 1 or 2 h-1 during the hydrotreatment. Successful hydrodeoxygenation and desulfurization were accomplished, whereas an increasing nitrogen concentration could be observed in the liquid products with the particular catalyst and reaction conditions employed. The observed hydrogen consumption (15-20 g/kg feed) was compared with the stoichiometric consumption for direct deoxygenation and with typical consumptions for industrial hydrotreated vegetable oil processing. The measured biogenic carbon content in hydrotreated liquid products (26.7%) agreed extremely well with the calculated biogenic carbon content in the hydrotreating feed (26.6%) that consisted of the blend of derivatized oil and petroleum light gas oil. The overall results are very promising since simple unit operations can be used to produce derivatized fast pyrolysis bio-oils that do not need additional standalone hydrotreating units but can be coprocessed in existing ones

Background: In addition to facilitating lipid digestions, bile acids (BA) are signalling molecules acting on receptors on immune cells and along the gastrointestinal (GI) tract. The aim of this study was to assess if altered bile acid profiles in plasma are associated with Crohn’s disease (CD). Method: This cross-sectional study included individuals (aged ≥18 years) referred for colonoscopy at a tertiary centre in Stockholm between 2016 and 2019. All participants received bowel preparation, completed a lifestyle questionnaire and provided blood samples for analysis. During colonoscopy, severity of disease was graded, and biopsies were taken from colonic mucosa. In the current substudy, 88 individuals with CD and 88 age-matched controls were selected for analysis of BA in plasma with ultra performance liquid chromatography (UPLC). Linear regression models were then used to compare mean bile acid concentrations and concentration ratios between CD and controls. Results: Individuals with CD had lower plasma concentrations of the majority of secondary BA compared to controls, in total CD/CC ratio 0.60 (SE 0.12), p = 0.001. The most prominent observations were lower levels of deoxycolic acid derivates and lithocolic acid derivates among participants with CD. Moreover, plasma concentration for secondary BA among participants with active CD was significantly lower compared to those with CD in remission, CD active/CD remission ratio 0.65 (SE 0.11), p < 0.002. Conclusion: Crohn’s disease may be associated with altered plasma bile acid composition. The significance of colonic bacterial diversity in this context needs to be investigated in further studies. 

Semi-volatile organic compounds (SVOCs) can be found in air, dust and on surfaces in car cabins, leading to exposure to humans via dust ingestion, inhalation, and dermal contact. This review aims at describing current understanding concerning sampling, levels, and human exposure of SVOCs from car cabin environments. To date, several different methods are used to sample SVOCs in car cabin air and dust and there are no standard operating procedures for sampling SVOCs in cars detailed in the literature. The meta-analysis of SVOCs in car cabin air and dust shows that brominated flame retardants (BFRs) and organophosphate flame retardants (OPFRs) have been most frequently studied, primarily focusing on concentrations in dust. In dust, detected concentrations span over three to seven orders of magnitude, with highest median concentrations for OPFRs, followed by BFRs and, thereafter, polychlorinated biphenyls (PCBs). In air, the variation is smaller, spanning over one to three orders of magnitude, with phthalates and siloxanes having the highest median concentrations, followed by OPFRs, fluorotelomer alcohols (FTOHs) and BFRs. Assessments of human exposures to SVOCs in cars have, so far, mainly focused on external exposure, most often only studying one exposure route, primarily via dust ingestion. In order to perform relevant and complete assessments of human exposure to SVOCs in cars, we suggest broadening the scope to which SVOCs should be studied, promoting more comprehensive external exposure assessments that consider exposure via all relevant exposure routes and making comparisons of external and internal exposure, in order to understand the importance of in-car exposure as a source of SVOC exposure. We also suggest a new sampling approach that includes sampling of SVOCs in both car cabin air and dust, aiming to reduce variability in data due to differences in sampling techniques and protocols. © 2021 The Authors

The coming years are expected to bring rapid changes in the nanotechnology regulatory landscape, with the establishment of a new framework for nano-risk governance, in silico approaches for characterisation and risk assessment of nanomaterials, and novel procedures for the early identification and management of nanomaterial risks. In this context, Safe(r)-by-Design (SbD) emerges as a powerful preventive approach to support the development of safe and sustainable (SSbD) nanotechnology-based products and processes throughout the life cycle. This paper summarises the work undertaken to develop a blueprint for the deployment and operation of a permanent European Centre of collaborating laboratories and research organisations supporting safe innovation in nanotechnologies. The proposed entity, referred to as “the Centre”, will establish a ‘one-stop shop’ for nanosafety-related services and a central contact point for addressing stakeholder questions about nanosafety. Its operation will rely on significant business, legal and market knowledge, as well as other tools developed and acquired through the EU-funded EC4SafeNano project and subsequent ongoing activities. The proposed blueprint adopts a demand-driven service update scheme to allow the necessary vigilance and flexibility to identify opportunities and adjust its activities and services in the rapidly evolving regulatory and nano risk governance landscape. The proposed Centre will play a major role as a conduit to transfer scientific knowledge between the research and commercial laboratories or consultants able to provide high quality nanosafety services, and the end-users of such services (e.g., industry, SMEs, consultancy firms, and regulatory authorities). The Centre will harmonise service provision, and bring novel risk assessment and management approaches, e.g. in silico methodologies, closer to practice, notably through SbD/SSbD, and decisively support safe and sustainable innovation of industrial production in the nanotechnology industry according to the European Chemicals Strategy for Sustainability.

This review article delves into the details of the 3R-Refinement principles as a vital framework for ethically sound rodent research laboratory. It highlights the core objective of the refinement protocol, namely, to enhance the well-being of laboratory animals while simultaneously improving the scientific validity of research outcomes. Through an exploration of key components of the refinement principles, the article outlines how these ethics should be implemented at various stages of animal experiments. It emphasizes the significance of enriched housing environments that reduce stress and encourage natural behaviors, non-restraint methods in handling and training, refined dosing and sampling techniques that prioritize animal comfort, the critical role of optimal pain management and the importance of regular animal welfare assessment in maintaining the rodents well-being. Additionally, the advantages of collaboration with animal care and ethics committees are also mentioned. The other half of the article explains the extensive benefits of the 3R-Refinement protocol such as heightened animal welfare, enhanced research quality, reduced variability, and positive feedback from researchers and animal care staff. Furthermore, it addresses avenues for promoting the adoption of the protocol, such as disseminating best practices, conducting training programs, and engaging with regulatory bodies. Overall, this article highlights the significance of 3R-Refinement protocol in aligning scientific advancement with ethical considerations along with shaping a more compassionate and responsible future for animal research.

A dataset consisting of measured values for LogD, solubility, metabolic stability in human liver microsomes (HLMs), and Caco-2 permeability was used to evaluate the prediction models for lipophilicity (S+LogD), water solubility (S+Sw_pH), metabolic stability in HLM (CYP_HLM_Clint), intestinal permeability (S+Peff), and P-glycoprotein (P-gp) substrate identification (P-gp substrate) in the software ADMET Predictor (AP) from Simulations Plus. The dataset consisted of a total of 4, 794 compounds, with at least data from metabolic stability determinations in HLM, from multiple discovery projects at Medivir. Our evaluation shows that the global AP models can be used for categorization of high and low values based on predicted results for metabolic stability in HLM and intestinal permeability, and to give good predictions of LogD (R25 0.79), guiding the synthesis of new compounds and for prioritizing in vitro ADME experiments. The model seems to overpredict solubility for the Medivir compounds, however. We also used the in-house datasets to build local models for LogD, solubility, metabolic stability, and permeability by using artificial neural network (ANN) models in the optional Modeler module of AP. Predictions of the test sets were performed with both the global and the local models, and the R2 values for linear regression for predicted versus measured HLM in vitro intrinsic clearance (CLint) based on logarithmic data were 0.72 for the in-house model and 0.53 for the AP model. The improved predictions with the local models are likely explained both by the specific chemical space of the Medivir dataset and laboratory-specific assay conditions for parameters that require biologic assay systems. .

Amide bond synthesis is ranked as the second most important challenge in key green chemistry research areas identified by the ACS Green Chemistry Institute. While developing more sustainable amide bond forming reactions has been in focus, significantly less attention has been given to human toxicity and environmental aspects of the underlying amine and acid substrates and their corresponding coupled products, a potentially important contribution to the overall sustainability of the amide-bond-forming reactions. Here, we explore biocatalytic amide bond formation from a safer-and-more-sustainable-by-design perspective in which commercially available amines and acids as well as their corresponding amide products were evaluated in silico based on potential human toxicity and environmental fate and exposure. This in silico filtering resulted in a panel of 188 amine and 54 acid building blocks that could be classified as safe, referred to herein as “safechems”. To enable couplings of safechems, we generated a panel of robust and promiscuous ancestral ATP-dependent amide bond synthetases (ABS) using McbA from Marinactinospora thermotolerans SCSIO 00652 as a template. Ancestral ABS enzymes exhibited complementary specificities in the coupling of a representative safechem subset of 17 amines and 16 acids while showing an increased thermostability of up to 20 °C compared to the extant biocatalyst. Finally, the pool of safechems and their corresponding amides were evaluated by USEtox (the UNEP-SETAC toxicity model), analysing not only the intrinsic properties of the compounds but evaluating their complete impact pathway including fate, exposure and effects. The amides were in general predicted as more toxic compared to the starting acids and amines through non-additive effects, emphasising that focusing on the toxicity of the building blocks alone is not sufficient to strive towards low human and ecotoxicity impact. Pursuing a safer and more sustainable by design perspective in the implementation of safechems did not prevent us from generating an array of novel products with potentially potent applications as exemplified here by enzymatic synthesis of substructures that are part of drug candidates for e.g. cancer treatment. 

The rise of artificial intelligence (AI) based algorithms has gained a lot of interest in the pharmaceutical development field. Our study demonstrates utilization of traditional machine learning techniques such as random forest (RF), support-vector machine (SVM), extreme gradient boosting (XGBoost), deep neural network (DNN) as well as advanced deep learning techniques like gated recurrent unit-based DNN (GRU-DNN) and graph neural network (GNN), towards predicting human ether-á-go-go related gene (hERG) derived toxicity. Using the largest hERG dataset derived to date, we have utilized 203,853 and 87,366 compounds for training and testing the models, respectively. The results show that GNN, SVM, XGBoost, DNN, RF, and GRU-DNN all performed well, with validation set AUC ROC scores equals 0.96, 0.95, 0.95, 0.94, 0.94 and 0.94, respectively. The GNN was found to be the top performing model based on predictive power and generalizability. The GNN technique is free of any feature engineering steps while having a minimal human intervention. The GNN approach may serve as a basis for comprehensive automation in predictive toxicology. We believe that the models presented here may serve as a promising tool, both for academic institutes as well as pharmaceutical industries, in predicting hERG-liability in new molecular structures.