Molecular, behavioral, and growth responses of juvenile yellow catfish (Tachysurus fulvidraco) exposed to carbamazepine.

Carbamazepine (CBZ) is an anticonvulsant medication used to treat epilepsy and bipolar disorder. Due to its persistence and low removal rate in wastewater treatment plants, it is frequently detected in the environment, raising concerns regarding its potential adverse effects on aquatic organisms and ecosystems. In this study, we aimed to assess the impact of CBZ on the behavior and growth of juvenile yellow catfish Tachysurus fulvidraco, a native and economically important species in China. Fish were exposed to CBZ at three concentrations of 1, 10, or 100 µg/L for 14 days. The fish exposed to 10 and 100 µg/L of CBZ exhibited decreased feeding, and a significant increase in cannibalistic tendencies was observed in fish exposed to 100 µg/L CBZ. Acetylcholinesterase activity was increased in the brain of fish exposed to 100 µg/L CBZ. CBZ also inhibited the growth of yellow catfish. To better elucidate mechanisms of toxicity, transcriptomics was conducted in both the brain and liver. In the brain, gene networks associated with neurotransmitter dysfunction were altered by CBZ, as well as networks associated with mitochondrial dysfunction and metabolism. In the liver, gene networks associated with the immune system were altered by CBZ. The current study improves comprehension of the sub-lethal effects of CBZ and reveals novel insight into molecular and biochemical pathways disrupted by CBZ, identifying putative key events associated with reduced growth and altered behavior. This study emphasizes the necessity for improved comprehension of the effects of pharmaceutical contaminants on fish at environmentally relevant levels.

ICH S1 prospective evaluation study: weight of evidence approach to predict outcome and value of 2-year rat carcinogenicity studies. A report from the regulatory authorities subgroup.

Introduction: The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) initiated a process in 2012 to revise the S1B Guideline "Testing for Carcinogenicity of Pharmaceuticals". Previous retrospective analysis indicated the importance of histopathological risk factors in chronic toxicity studies, evidence of endocrine perturbation, and positive genetic toxicology results as potentially predictive indicators of carcinogenic risk. In addition, a relationship between pharmacodynamic activity and carcinogenicity outcome in long-term rodent studies has been reported. It was postulated that these factors could be evaluated in a Weight-of-Evidence (WoE) approach to predict the outcome of a 2-year rat study. Methods: The ICH S1B(R1) Expert Working Group (EWG) conducted a Prospective Evaluation Study (PES) to determine the regulatory feasibility of this WoE approach. Drug Regulatory Authorities (DRAs) evaluated 49 Carcinogenicity Assessment Documents (CADs), which describe the WoE for submitted pharmaceutical compounds. Each compound was categorized into a carcinogenic risk category including a statement of the value of the 2-year rat study. The outcome of the completed 2-year rat studies was evaluated in relation to the prospective CAD to determine the accuracy of predictions. Results: Based on the results of the PES, the EWG concluded that the evaluation process for assessing human carcinogenic risk of pharmaceuticals described in ICH S1B could be expanded to include a WoE approach. Approximately 27% of 2-year rat studies could be avoided in cases where DRAs and sponsors unanimously agreed that such a study would not add value. Discussion: Key factors supporting a WoE assessment were identified: data that inform carcinogenic potential based on drug target biology and the primary pharmacologic mechanism of the parent compound and major human metabolites; results from secondary pharmacology screens for this compound and major human metabolites that inform carcinogenic risk; histopathology data from repeated-dose toxicity studies; evidence for hormonal perturbation; genotoxicity data; and evidence of immune modulation. The outcome of the PES indicates that a WoE approach can be used in place of conducting a 2-year rat study for some pharmaceuticals. These data were used by the ICH S1B(R1) EWG to write the R1 Addendum to the S1B Guideline published in August 2022.

Global Health Commodities Supply Chain in the Era of COVID-19 Pandemic: Challenges, Impacts, and Prospects: A Systematic Review.

Background: The COVID-19 pandemic led to the most substantial health crisis in the 21st Century. This pandemic interrupted the supply of essential commodities for human beings. Among the essential commodities for human survival, disruption of the supply of essential health commodities has become a global concern. Objective: The study aimed to systematically analyze published articles on the challenges, impacts, and prospects of the global health commodities' supply chain in the era of the COVID-19 pandemic. Methods: A standard searching strategy was conducted in seven research databases to retrieve pertinent articles. Finally, 459 articles were retrieved for further screening, and only 13 articles were selected for final synthesis. Results: Almost 38.5% of the studies targeted the supply chain of health commodities used to treat HIV, TB, and malaria. Lockdown policies, travel restrictions, lack of transportation, low manufacturing capacity, and rising costs were the significant challenges indicated for the supply interruption of essential health commodities and COVID-19 vaccines. Findings indicated that the supply interruption of essential health commodities leads to a devastating impact on global health. Conclusion: Global medicine shortages due to the pandemic crisis can have a devastatingly harmful impact on patient outcomes and might result in a devastatingly long-lasting effect on the health of the world community. Supply-related challenges of the COVID-19 vaccine affect countries' ambitions for achieving herd immunity quickly. Monitoring the pandemic's effect on the health commodities' supply system and designing a short-term and long-term resilient health supply chain system that can cope with current and future health catastrophes is pivotal.

Paediatric clinical study of 3D printed personalised medicines for rare metabolic disorders.

Rare diseases are infrequent, but together they affect up to 6-10 % of the world's population, mainly children. Patients require precise doses and strict adherence to avoid metabolic or cardiac failure in some cases, which cannot be addressed in a reliable way using pharmaceutical compounding. 3D printing (3DP) is a disruptive technology that allows the real-time personalization of the dose and the modulation of the dosage form to adapt the medicine to the therapeutic needs of each patient. 3D printed chewable medicines containing amino acids (citrulline, isoleucine, valine, and isoleucine and valine combinations) were prepared in a hospital setting, and the efficacy and acceptability were evaluated in comparison to conventional compounded medicines in six children. The inclusion of new flavours (lemon, vanilla and peach) to obtain more information on patient preferences and the implementation of a mobile app to obtain patient feedback in real-time was also used. The 3D printed medicines controlled amino acid levels within target levels as well as the conventional medicines. The deviation of citrulline levels was narrower and closer within the target concentration with the chewable formulations. According to participants' responses, the chewable formulations were well accepted and can improve adherence and quality of life. For the first time, 3DP enabled two actives to be combined in the same formulation, reducing the number of administrations. This study demonstrated the benefits of preparing 3D printed personalized treatments for children diagnosed with rare metabolic disorders using a novel technology in real clinical practice.

Developing a pragmatic consensus procedure supporting the ICH S1B(R1) weight of evidence carcinogenicity assessment.

The ICH S1B carcinogenicity global testing guideline has been recently revised with a novel addendum that describes a comprehensive integrated Weight of Evidence (WoE) approach to determine the need for a 2-year rat carcinogenicity study. In the present work, experts from different organizations have joined efforts to standardize as much as possible a procedural framework for the integration of evidence associated with the different ICH S1B(R1) WoE criteria. The framework uses a pragmatic consensus procedure for carcinogenicity hazard assessment to facilitate transparent, consistent, and documented decision-making and it discusses best-practices both for the organization of studies and presentation of data in a format suitable for regulatory review. First, it is acknowledged that the six WoE factors described in the addendum form an integrated network of evidence within a holistic assessment framework that is used synergistically to analyze and explain safety signals. Second, the proposed standardized procedure builds upon different considerations related to the primary sources of evidence, mechanistic analysis, alternative methodologies and novel investigative approaches, metabolites, and reliability of the data and other acquired information. Each of the six WoE factors is described highlighting how they can contribute evidence for the overall WoE assessment. A suggested reporting format to summarize the cross-integration of evidence from the different WoE factors is also presented. This work also notes that even if a 2-year rat study is ultimately required, creating a WoE assessment is valuable in understanding the specific factors and levels of human carcinogenic risk better than have been identified previously with the 2-year rat bioassay alone.

Effects of metformin on wild fathead minnows (Pimephales promelas) using in-lake mesocosms in a boreal lake ecosystem.

Due to its widespread use for the treatment of Type-2 diabetes, metformin is routinely detected in surface waters globally. Laboratory studies have shown that environmentally relevant concentrations of metformin can adversely affect the health of adult fish, with effects observed more frequently in males. However, the potential risk to wild fish populations has yet to be fully elucidated and remains a topic of debate. To explore whether environmentally relevant metformin exposure poses a risk to wild fish populations, the present study exposed wild fathead minnows (Pimephales promelas) to 5 or 50 µg/L metformin via 2 m diameter in-lake mesocosms deployed in a natural boreal lake in Northern Ontario at the International Institute for Sustainable Development - Experimental Lakes Area (IISD-ELA). Environmental monitoring was performed at regular intervals for 8-weeks, with fish length, weight (body, liver and gonad), condition factor, gonadosomatic index, liver-somatic index, body composition (water and biomolecules) and hematocrit levels evaluated at test termination. Metabolic endpoints were also evaluated using liver, brain and muscle tissue, and gonads were evaluated histologically. Results indicate that current environmental exposure scenarios may be sufficient to adversely impact the health of wild fish populations. Adult male fish exposed to metformin had significantly reduced whole body weight and condition factor and several male fish from the high-dose metformin had oocytes in their testes. Metformin-exposed fish had altered moisture and lipid (decrease) content in their tissues. Further, brain (increase) and liver (decrease) glycogen were altered in fish exposed to high-dose metformin. To our knowledge, this study constitutes the first effort to understand metformin's effects on a wild small-bodied fish population under environmentally relevant field exposure conditions.

LC-MS analysis of polar and highly polar organic pollutants in Barcelona urban groundwater using orthogonal LC separation modes.

Groundwater samples may contain thousands of organic pollutants from infiltration of surface water, sewer leakages, and to a minor extent from public water supply network losses. Polar (0 < log D < - 2.0) and very polar substances (log D < - 2.0) have been largely beyond the scope of applied analytical methodologies in environmental monitoring because of challenges related to their extraction from the sample and subsequent chromatographic separation. In this study, we developed an analytical workflow for 96 pollutants covering a broad polarity range, including pharmaceuticals, industrial chemicals, and artificial sweeteners, potentially seeping through the soil in urban areas. The Besos aquifer located at the Northern-eastern edge of the city of Barcelona was chosen as a study area due to the deterioration of the quality of the aquifers over the past years and the proven presence of numerous pollutants. The methodology consisted of vacuum-assisted evaporation (VAE) followed by chromatographic separation of the sample on two columns with orthogonal retention mechanisms, namely, an HSS T3 column (modified C18) and a BEH amide column (HILIC). The analytes were detected by high-resolution mass spectrometry on a Q Exactive Orbitrap system in data-independent acquisition mode. Taking into consideration the retention as well as the peak shape, a Quality Score (QS) was assigned for each analyte to evaluate the quality of each chromatographic peak of each compound. While 67 compounds, including 19 polar and 48 moderately polar, were satisfactorily retained on an HSS T3, 29 compounds, including 14 highly polar, 14 polar, and one moderately polar, were analyzed in the BEH amide column. The optimized methodology was applied for the analysis of 89 out of 96 validated contaminants with satisfactory recoveries in samples collected from seven wells, providing low LODs (0.02 to 0.45 ng L-1) and LOQs (0.06 to 1.34 ng L-1). A number of highly polar and polar compounds not previously reported to occur in GW, including artificial sweeteners, pharmaceuticals, and industrial chemicals, were detected at concentrations as high as few µ g L-1.

Competitive sorption experiments reveal new regression models to predict PhACs sorption on carbonaceous materials.

Sorption of hydrophobic organic contaminants onto thermally altered carbonaceous materials (TACM) constitutes a widely used technology for remediation of polluted waters. This process is typically described by sorption isotherms, with one of the most used models, the Polanyi-Dubinin-Manes (PDM) equation, including water solubility (Sw) as a normalizing factor. In case of pharmaceutical active compounds (PhACs), Sw depends on the pH of the environment due to the ionic/ionizable behavior of these chemicals, a fact frequently ignored in sorption studies of PhACs. In this work, we set the theoretical framework to include the variation of Sw with pH in the definition of the PDM model, and we applied this approach to describe the effect of ambient pH in the competitive sorption of three commonly detected PhACs (carbamazepine, ibuprofen, and sulfamethoxazole) onto three carbonaceous sorbents (biochar, powder activated carbon, and colloidal activated carbon). Changes in the ambient pH and hence in the hydrophobicity of the compounds could explain the strong variations observed in single-solute sorption and also in competitive sorption. Furthermore, Sw was used as a parameter for the linear regression model of sorption coefficients of our experiments, suggesting the incorporation of this variable as an improvement to existing approaches for prediction of PhACs sorption onto TACM.

A green approach for metoclopramide quantification in pharmaceutical products: new HPLC and spectrophotometric methods.

Green spectrophotometric and HPLC methods have been developed for the quantification of metoclopramide. In the spectrophotometric method, it was determined by direct absorbance measurement at 273 nm wavelength using ultrapure water as solvent. The Extend C18 column was used for the HPLC method. The mobile phase system consisted of a combination of ethanol and formic acid solution (pH 2.0; 30:70 v/v). Isocratic elution was applied and the flow rate was set at 1.0 mL min-1. Metoclopramide was detected at 273 nm. The methods performed were economical, rapid, environmentally friendly, and simple, providing metoclopramide analysis within 5 min. The methods have been successfully applied in pharmaceutical products without matrix interference. The results of the application of the developed methods to pharmaceutical products were statistically compared and no significant difference was observed between the methods. In addition, the greenness assessment of the developed methods was performed using AGREE software. Our developed methods, based on the use of solvents such as ethanol and water, are proposed as a more environmentally and analyst-friendly option for the quantification of metoclopramide in pharmaceutical products than other methods currently in use.

The increasing costs of medicines and their implications for patients, physicians and the health system.

Most new medicines entering the market are high-cost speciality drugs. These drugs can cost tens to hundreds of thousands of dollars per course of treatment and in some cases millions of dollars per dose. Approximately half of all spending on medicines is projected to target only 2-3% of patients, raising important questions about resource allocation. While there is no doubt that breakthrough innovations have transformed clinical care in some disciplines, it is also true that cost is becoming one of the primary barriers to treatment access and that many new medicines do not provide value commensurate with their prices. This article examines pricing trends, the reasons for high prices and their implications for access and clinical practice.

Effectiveness and safety of adalimumab biosimilar in patients with inflammatory bowel disease.

BACKGROUND: Adalimumab biosimilar MSB11022 (Idacio ®) has been approved for the same indications as its originator (Humira ®), based on findings from clinical trials in plaque psoriasis. Data on its efficacy and safety in inflammatory bowel disease, however, are scarce. METHODS: Retrospective, observational study of 44 patients with inflammatory bowel disease: 30 were treated with originator adalimumab, 5 were directly started on MSB11022, and 9 switched from originator to biosimilar adalimumab. To evaluate the effectiveness of the use of adalimumab in inflammatory bowel disease, both laboratory markers (fecal calprotectin and C-reactive protein) and scales that measure the activity of inflammatory bowel disease using specific scales (Harvey-Bradshaw Index (HBI) have been usEd.) for Crohn's disease and Mayo Score for Ulcerative Colitis. Efficacy was evaluated by recording the adverse effects that could occur with the administration of adalimumab (original or biosimilar). The success of the switch was determined by analyzing meaningful differences in effectiveness and safety criteria. Concomitant therapy and the need for dose intensification were also analyzed. Objective of this study was to assess the effectiveness and safety of biosimilar adalimumab in adalimumab-naïve patients and patients switched from originator adalimumab. RESULTS: No significant differences were observed in clinical disease activity (P=.317) or biochemical parameters [fecal calprotectin (P=.445) and C-reactive protein P=.661)] after the switch from the originator adalimumab to MSB11022. There was not a significant reduction in the concomitant use of corticosteroids and thiopurines (P=.157). No emergency room visits or hospitalizations were observed during the study period and none of the patients experienced serious adverse effects. CONCLUSIONS: Between originator adalimumab and biosimilar-start cohorts, no differences were observed, between originator adalimumab and switch cohorts, no significant differences were found either, and with the pre- and post-switch to biosimilar comparison, 2 of the 9 patients experienced AEs after the switch. The biosimilar showed a favorable safety profile (one patient with a serious adverse effect (rash) with biosimilar discontinued treatment) and no significant changes to clinical or biochemical parameters were observed after the switch.

Sequential, electrochemical-photochemical synthesis of 1,2,4-triazolo-[4,3-a]pyrazine.

1,2,4-triazolo-[4,3-a]pyrazine was prepared via a two-step electrochemical, photochemical process. First, a 5-substituted tetrazole is electrochemically coupled to 2,6-dimethoxypyrazine to yield 1,5- and 2,5- disubstituted tetrazoles. Subsequent photochemical excitation of the 2,5-disubstituted tetrazole species using an ultraviolet lamp releases nitrogen gas and produces a short-lived nitrilimine intermediate. Rapid cyclization of the nitrilimine intermediate yields a 1,2,4-triazolo-[4,3-a]pyrazine backbone. The scope of this reaction was explored using various tetrazoles and pyrazines. Materials produced were identified using chemical analytical techniques and computationally studied for potential application as an insensitive energetic material.

A systematic review investigating the proportion of clinical images shared in prospective randomized controlled trials involving patients with atopic dermatitis and systemic pharmacotherapy.

For individuals with atopic dermatitis (AD), interpreting scientific papers that present clinical outcomes including the Eczema Area and Severity Index (EASI) and Investigators Global Assessment may be difficult. When compared to tabulated data and graphs, images from before and after treatment are often far more meaningful to these patients that ultimately will be candidates for the treatment. This systematic review focused on determining the frequency of clinical image sharing in AD research.Conducted in accordance with PRISMA guidelines, the review concentrated on randomized controlled trials that investigated predefined and available systemic treatments for AD. The search was performed in the MEDLINE database for studies published from the inception until 21 December 2023.The review included 60 studies, encompassing 17,799 randomized patients. Across these studies, 16 images representing 6 patients were shared in the manuscripts, leading to a sharing rate of 0.3‰.The almost missing inclusion of patient images in clinical trial publications hinders patient understanding. Adding images to scientific manuscripts could significantly improve patients' comprehension of potential treatment outcomes. This review highlights the need for authors, the pharmaceutical industry, study sponsors, and publishers to enhance and promote patient information through increased use of visual data.

Occurrence of Pharmaceutical Micropollutants in Lake Nahuel Huapi, Argentine Patagonia.

Tourism is one of the most important activities for the economy of Nor Patagonia Argentina. In Bariloche City, located on the shores of Lake Nahuel Huapi, both the permanent and the temporary populations have increased significantly in recent decades, and this has not necessarily been accompanied by an improvement in sewage networks. Emerging micropollutants such as pharmaceutical compounds reach aquatic systems directly, in the absence of a domestic sewage network, or through effluents from wastewater treatment plants (WWTP), which do not efficiently remove these substances and represent a major threat to the environment. Therefore, the objective of our study was to monitor the presence of pharmaceutical compounds discharged both through wastewater effluents and diffusely from housing developments into Lake Nahuel Huapi. The results obtained demonstrate the presence of pharmaceuticals in Lake Nahuel Huapi with concentrations ranging from not detectable (ND) to 110.6 ng L-1 (caffeine). The highest pharmaceutical concentration recorded in WWTP influent corresponded to caffeine (41728 ng L-1), and the lowest concentration was paracetamol (18.8 ng L-1). The removal efficiency of pharmaceuticals in the WWTP was calculated, and ranged from 0% for carbamazepine to 66% for ciprofloxacin. This antibiotic showed the lowest % of attenuation (73%) in Lake Nahuel Huapi. These results on the occurrence of a wide variety of pharmaceuticals are the first generated in Patagonia, representing a regional baseline for this type of micropollutant and valuable information for the subsequent design of removal strategies for emerging pharmaceutical pollutants in surface water. Environ Toxicol Chem 2024;00:1-11. © 2024 SETAC.

Factor Analysis of Patients Who Find Tablets or Capsules Difficult to Swallow Due to Their Large Size: Using the Personal Health Record Infrastructure of Electronic Medication Notebooks.

BACKGROUND: Understanding patient preference regarding taking tablet or capsule formulations plays a pivotal role in treatment efficacy and adherence. Therefore, these preferences should be taken into account when designing formulations and prescriptions. OBJECTIVE: This study investigates the factors affecting patient preference in patients who have difficulties swallowing large tablets or capsules and aims to identify appropriate sizes for tablets and capsules. METHODS: A robust data set was developed based on a questionnaire survey conducted from December 1, 2022, to December 7, 2022, using the harmo smartphone app operated by harmo Co, Ltd. The data set included patient input regarding their tablet and capsule preferences, personal health records (including dispensing history), and drug formulation information (available from package inserts). Based on the medication formulation information, 6 indices were set for each of the tablets or capsules that were considered difficult to swallow owing to their large size and concomitant tablets or capsules (used as controls). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of each index. The index demonstrating the highest area under the curve of the ROC was selected as the best index to determine the tablet or capsule size that leads to swallowing difficulties. From the generated ROCs, the point with the highest discriminative performance that maximized the Youden index was identified, and the optimal threshold for each index was calculated. Multivariate logistic regression analysis was performed to identify the risk factors contributing to difficulty in swallowing oversized tablets or capsules. Additionally, decision tree analysis was performed to estimate the combined risk from several factors, using risk factors that were significant in the multivariate logistic regression analysis. RESULTS: This study analyzed 147 large tablets or capsules and 624 control tablets or capsules. The "long diameter + short diameter + thickness" index (with a 21.5 mm threshold) was identified as the best indicator for causing swallowing difficulties in patients. The multivariate logistic regression analysis (including 132 patients with swallowing difficulties and 1283 patients without) results identified the following contributory risk factors: aged <50 years (odds ratio [OR] 1.59, 95% CI 1.03-2.44), female (OR 2.54, 95% CI 1.70-3.78), dysphagia (OR 3.54, 95% CI 2.22-5.65), and taking large tablets or capsules (OR 9.74, 95% CI 5.19-18.29). The decision tree analysis results suggested an elevated risk of swallowing difficulties for patients with taking large tablets or capsules. CONCLUSIONS: This study identified the most appropriate index and threshold for indicating that a given tablet or capsule size will cause swallowing difficulties, as well as the contributory risk factors. Although some sampling biases (eg, only including smartphone users) may exist, our results can guide the design of patient-friendly formulations and prescriptions, promoting better medication adherence.

Crystal size, shape, and conformational changes drive both the disappearance and reappearance of ritonavir polymorphs in the mill.

Organic compounds can crystallize in different forms known as polymorphs. Discovery and control of polymorphism is crucial to the pharmaceutical industry since different polymorphs can have significantly different physical properties which impacts their utilization in drug delivery. Certain polymorphs have been reported to 'disappear' from the physical world, irreversibly converting to new ones. These unwanted polymorph conversions, initially prevented by slow nucleation kinetics, are eventually observed driven by significant gains in thermodynamic stabilities. The most infamous of these cases is that of the HIV drug ritonavir (RVR): Once its reluctant form was unwillingly nucleated for the first time, its desired form could no longer be produced with the same manufacturing process. Here we show that RVR's extraordinary disappearing polymorph as well as its reluctant form can be consistently produced by ball-milling under different environmental conditions. We demonstrate that the significant difference in stability between its polymorphs can be changed and reversed in the mill-a process we show is driven by crystal size as well as crystal shape and conformational effects. We also show that those effects can be controlled through careful design of milling conditions since they dictate the kinetics of crystal breakage, dissolution, and growth processes that eventually lead to steady-state crystal sizes and shapes in the mill. This work highlights the huge potential of mechanochemistry in polymorph discovery of forms initially difficult to nucleate, recovery of disappearing polymorphs, and polymorph control of complex flexible drug compounds such as RVR.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

Sources of persistent and mobile chemicals in municipal wastewater: a sewer perspective in Leipzig, Germany.

Persistent and mobile (PM) chemicals spread in the water cycle and have been widely detected, yet information about their sources is still scarce. In this study, 67 PM chemicals were analyzed in 19 wastewater samples taken in the sewer system of the city of Leipzig, Germany, covering different industrial, clinical, and domestic discharges. A total of 37 of these analytes could be detected, with highly variable median concentrations between substances (median: 0.5-800 µg L-1) and for single substances between samples (e.g., 1,4-diazabicyclo[2.2.2]octane) by up to three orders of magnitude, with the highest single concentration exceeding 10 mg L-1 (p-cumenesulfonic acid). The emission of PM chemicals into the sewer system was classified as stemming from diffuse (14 analytes) or point sources (23 analytes), while 9 analytes fulfill both criteria. Many so-called industrial chemicals were also discharged from households (e.g., tris(2-chloroethyl) phosphate or 1H-benzotriazole). Examples for analytes showing specific sources are tetrafluoroborate (traffic-related industry and metal production and finishing), ε-caprolactam (large-scale laundry), or cyanuric acid (likely swimming pool). Furthermore, a correlation between 1-cyanoguanidine and guanylurea was observed for the traffic-related industry. This study outlines that sewer sampling can provide valuable information on the sources of PM chemicals. This knowledge is a prerequisite for their future emission control at source or substitution as an alternative to end-of-pipe treatment in municipal wastewater treatment plants.

Performance and robustness of small molecule retention time prediction with molecular graph neural networks in industrial drug discovery campaigns.

This study explores how machine-learning can be used to predict chromatographic retention times (RT) for the analysis of small molecules, with the objective of identifying a machine-learning framework with the robustness required to support a chemical synthesis production platform. We used internally generated data from high-throughput parallel synthesis in context of pharmaceutical drug discovery projects. We tested machine-learning models from the following frameworks: XGBoost, ChemProp, and DeepChem, using a dataset of 7552 small molecules. Our findings show that two specific models, AttentiveFP and ChemProp, performed better than XGBoost and a regular neural network in predicting RT accurately. We also assessed how well these models performed over time and found that molecular graph neural networks consistently gave accurate predictions for new chemical series. In addition, when we applied ChemProp on the publicly available METLIN SMRT dataset, it performed impressively with an average error of 38.70 s. These results highlight the efficacy of molecular graph neural networks, especially ChemProp, in diverse RT prediction scenarios, thereby enhancing the efficiency of chromatographic analysis.