Unintended Reactions Research Articles

A PROSPECTIVE OBSERVATIONAL STUDY OF MONITORING AND REPORTING OF ANTIMICROBIAL DRUGS ASSOCIATED ADVERSE DRUG REACTIONS AND THEIR SIGNIFICANCE ON PATIENTS SAFETY AND HEALTH-CARE OUTCOMES

Objective: Adverse drug reaction (ADR) surveillance and reporting practices are at an early stage of development within the Indian context. The pharmacovigilance rate in India falls below 1%, which is notably lower compared to the global average of 5%. India holds the position of being the fourth most significant contributor to the pharmaceutical industry worldwide. Therefore, there exists a pressing demand to enhance the pharmacovigilance framework for safeguarding the health of the Indian population. ADR is defined as the unintended, obnoxious, and unwanted reaction due to the use of a drug. The administration of antimicrobial agents causes various ADR that has been analyzed throughout the study. The main objective of the research is to monitor and report the adverse drug reaction caused by antimicrobial drugs Methods: A prospective observational study was carried out in the various departments of the hospital with duration of 3 months including 100 patients using patient profile form and ADR reporting forms and analyzing with the scales for causality, severity, and preventability assessment. Results: During the study, 29 ADRs were found among 100 patients, with an incidence rate of 9.6%, more common in females (52%) than in males (48%). ADRs were most frequently reported in the age group of 35–51 years (34%), then 18–34 years (28%), and 1–17 years (24%). The general medicine department reported the highest number of ADRs (66%), followed by the pediatric department (24%). Cephalosporins caused the most ADRs (35%). Common ADRs included constipation, diarrhea (34%) and rashes, nausea, and vomiting (34%). Naranjo scale indicated that the causality of ADRs was probable (52%). Hartwig severity scale showed 55% ADRS to be mild. Schumock and Thornton method found that 76% of ADRs were preventable.Management of most of ADRs included drug withdrawal (52%). Conclusion: The majority of cephalosporin-related side effects, which included constipation, diarrhoea, and rashes, were observed. Most of the patients got better with the help of ADR monitoring and management. Finding and treating drug-related problems early make patients feel better and keep them safe. This study shows health-care system why it is important to monitor and report ADR caused by drugs.

Predicting Drugs Suspected of Causing Adverse Drug Reactions Using Graph Features and Attention Mechanisms.

Adverse drug reactions (ADRs) refer to an unintended harmful reaction that occurs after the administration of a medication for therapeutic purposes, which is unrelated to the intended pharmacological action of the drug. In the United States, ADRs account for 6% of all hospital admissions annually. The cost of ADR-related illnesses in 2016 was estimated at USD 528.4 billion. Increasing the awareness of ADRs is an effective measure to prevent them. Assessing suspected drugs in adverse events helps to enhance the awareness of ADRs. In this study, a suspect drug assisted judgment model (SDAJM) is designed to identify suspected drugs in adverse events. This framework utilizes the graph isomorphism network (GIN) and an attention mechanism to extract features based on patients' demographic information, drug information, and ADR information. By comparing it with other models, the results of various tests show that this model performs well in predicting the suspected drugs in adverse reaction events. ADR signal detection was conducted on a group of cardiovascular system drugs, and case analyses were performed on two classic drugs, Mexiletine and Captopril, as well as on two classic antithyroid drugs. The results indicate that the model can accomplish the task of predicting drug ADRs. Validation using benchmark datasets from ten drug discovery domains shows that the model is applicable to classification tasks on the Tox21 and SIDER datasets. This study applies deep learning methods to construct the SDAJM model for three purposes: (1) identifying drugs suspected to cause adverse drug events (ADEs), (2) predicting the ADRs of drugs, and (3) other drug discovery tasks. The results indicate that this method can offer new directions for research in the field of ADRs.

BiMPADR: A Deep Learning Framework for Predicting Adverse Drug Reactions in New Drugs.

Detecting the unintended adverse reactions of drugs (ADRs) is a crucial concern in pharmacological research. The experimental validation of drug-ADR associations often entails expensive and time-consuming investigations. Thus, a computational model to predict ADRs from known associations is essential for enhanced efficiency and cost-effectiveness. Here, we propose BiMPADR, a novel model that integrates drug gene expression into adverse reaction features using a message passing neural network on a bipartite graph of drugs and adverse reactions, leveraging publicly available data. By combining the computed adverse reaction features with the structural fingerprints of drugs, we predict the association between drugs and adverse reactions. Our models obtained high AUC (area under the receiver operating characteristic curve) values ranging from 0.861 to 0.907 in an external drug validation dataset under differential experiment conditions. The case study on multiple BET inhibitors also demonstrated the high accuracy of our predictions, and our model's exploration of potential adverse reactions for HWD-870 has contributed to its research and development for market approval. In summary, our method would provide a promising tool for ADR prediction and drug safety assessment in drug discovery and development.

Time to develop adverse drug reactions and associated factors among children HIV positive patients on antiretroviral treatment in North West Amhara Specialized Hospitals: Retrospective cohort study, 2022.

Adverse drug reactions (ADRs) are harmful and unintended reactions to medicines given at standard doses through a proper route of administration for the purpose of prophylaxis, diagnosis, or treatment. The objective of this research paper was to assess median time to development of ADRs and associated factors among children HIV positive patients on antiretroviral treatment (ART) in North West Amhara Specialized Hospitals. The adverse drug effect survival time was estimated using the Kaplan-Meier survival method and log-rank test curves was applied for analyze "time-to-event" data. Cox regression model was used to identify the associated factors. Adjusted hazard ratios with their respective 95% confidence intervals (CIs) were estimated and a value of p less than 0.05 was used to declare the presence of a significant association. The overall incidence of ADRs was 0.67 (95% CI: 3.74-4.44) per 10,000 person-year observation, with a median of 57 months. Adults are presenting with opportunistic Infections (OIs) experiences, baseline CD4 < 200 cells/µL counts, 1e, tenofovir disoproxil fumarate-lamivudine-efavirenz ART regimen, bedridden baseline functional status, World Health Organization (WHO) clinical stage II and III were notably associated with the incidence of ADRs development. ADRs were uncommon in this study. predictors, such as OIs experiences, a low CD4 count, ART regimen, an advanced WHO stage, and bedridden functional status were significantly associated with ADRs.

Spontaneously reported adverse drug reaction pattern in a tertiary care teaching hospital: A cross-sectional study

Background: Adverse drug reactions (ADRs) are unintended and harmful reactions to medications that occur at doses normally used for therapeutic purposes. The reporting of ADRs is essential for the identification and prevention of ADRs. Aims and Objectives: The aim of the study was to estimate the frequency and distribution of spontaneously reported ADRs in the tertiary care teaching hospital. Materials and Methods: A retrospective cross-sectional study was conducted from July 2020 to June 2023, from spontaneously reported ADRs by the ADR Monitoring Centre, MGM Medical College, Kishanganj, Bihar. Distribution of age, gender, department, medication groups, and systems involved were examined. Utilizing certain scales, causality, severity, and preventability were evaluated. Results: Total 47 ADRs were reported during the study period. The most common ADRs were cutaneous ADRs (n = 19,40.43%) followed by the central nervous system (CNS) (n = 12, 25.53%), gastrointestinal system (GI) (n = 9, 19.15%), musculoskeletal (n = 4, 8.51%) and others. The most commonly implicated drugs were Antibiotics (21.28%) followed by analgesics (12.77%), DMARD (12.77%), antihypertensive (12.77%), and others shown in the study. The severity assessment of ADRs was done by Modified Hartwig et al. severity assessment scale and was found mild (87%), followed by moderate (8.5%) and severe (4.3%). Using the modified Schumock and Thronton preventability scale preventability assessment of ADRs was done and was found 51.06% of ADRs were definitely preventable, 38.30% were probably preventable and 12.77% of ADRs were not preventable. Conclusion: The findings of this study emphasize the significance of pharmacovigilance and the requirement that medical personnel be knowledgeable about the indications and symptoms of ADRs.

Deductive machine learning models for product identification.

Deductive solution strategies are required in prediction scenarios that are under determined, when contradictory information is available, or more generally wherever one-to-many non-functional mappings occur. In contrast, most contemporary machine learning (ML) in the chemical sciences is inductive learning from example, with a fixed set of features. Chemical workflows are replete with situations requiring deduction, including many aspects of lab automation and spectral interpretation. Here, a general strategy is described for designing and training machine learning models capable of deduction that consists of combining individual inductive models into a larger deductive network. The training and testing of these models is demonstrated on the task of deducing reaction products from a mixture of spectral sources. The resulting models can distinguish between intended and unintended reaction outcomes and identify starting material based on a mixture of spectral sources. The models also perform well on tasks that they were not directly trained on, like performing structural inference using real rather than simulated spectral inputs, predicting minor products from named organic chemistry reactions, identifying reagents and isomers as plausible impurities, and handling missing or conflicting information. A new dataset of 1 124 043 simulated spectra that were generated to train these models is also distributed with this work. These findings demonstrate that deductive bottlenecks for chemical problems are not fundamentally insuperable for ML models.

Adverse Drug Reactions: Identification, Prevention and Management

This article addresses the critical aspects of adverse drug reactions (ADRs), focusing on their identification, prevention, and management. ADRs, defined as harmful or unintended reactions to drugs, necessitate a nuanced understanding due to their varying severity. Side effects, though not always harmful, can evolve into ADRs, prompting intervention. The decision-making process involves assessing the adverse reaction's severity, potential benefits of the drug, and the overall risk-benefit profile for the patient. Healthcare professionals play a pivotal role in monitoring and reporting ADRs to regulatory authorities for ongoing drug safety assessment. The article further discusses the classification of ADRs and outlines strategies for identification, including clinical manifestations, patient reporting, and pharmacovigilance systems. Management strategies, particularly in the case of anaphylaxis, underscore the importance of early recognition, acute therapy, and drug discontinuation. The prevention of ADRs involves a comprehensive approach, encompassing patient assessment, communication among healthcare providers, education, and the use of electronic health records. The collaborative effort between stakeholders and active participation in pharmacovigilance programs contribute to ongoing drug safety enhancement. The article concludes by emphasizing the collective goal of minimizing ADR occurrence and impact to enhance overall pharmacotherapy safety and effectiveness.

Naming for Sustainability: Interrogating the Efficacy and Sustainability of COVID-19 Metaphor and Nomenclature

Language matters for sustainability, and diseases’ names and attendant terminology should serve language users’ extant and future needs. The currency and pandemic proportion of COVID-19, and the viral or pervasive use of its attendant vocabulary and metaphors, makes it an apt case for interrogating the sustainability of its nomenclature. This paper interrogates the efficacy and sustainability of COVID-19 related English vocabulary and metaphors among the Shona speaking people, as a microcosm of their efficacy and sustainability among Bantu African language speakers. The paper is framed by the Sapir-Whorf hypothesis, which posits that language filters people’s reality and colors their attitudes and actions. By implication, unstainable and inefficacious language compromises an appreciation of one’s reality. Acknowledging that any linguistic inventiveness should serve a utilitarian rather than ornamental function, the paper interrogates the sustainability and efficacy of the ‘war’ metaphor and lexical innovations replete within the COVID-19 discourse. The paper analyzes efficacy regarding the terms and metaphor engendering the desired or intended effects and sustainability of the terms’ intelligibility, pronounceability, memorability, and translatability. The paper concludes that the selected English COVID-19 related terms engendered unintended thoughts and reactions within the language users, and that, owing to them being products of English lexical innovation, they defy translatability into, and intelligibility within, African languages; rendering the COVID-19 discourse exclusive and unsustainable.

Small is Beautiful: Electronic Origin and Synthetic Evolution of Single-Benzene Fluorophores.

ConspectusSingle-benzene fluorophores (SBFs) are small molecules that produce visible light by using only one benzene ring as the sole aromatic core. This Account centers around the chemistry of a new class of SBF that we accidentally discovered but rationally developed and refined afterward. In a failed experiment that took an unintended reaction pathway, we encountered the bright green fluorescence of ortho-diacetylphenylenediamine (o-DAPA). Despite its uninspiring look, reminiscent of textbook examples of simple benzene derivatives, this molecule had neither been synthesized nor isolated before. This discovery led to our studies on the larger DAPA family, including isomeric m-DAPA and p-DAPA. Remarkably, p-DAPA is the lightest red fluorophore, with a molecular weight of only 192. While o- and p-DAPA are emissive, m-DAPA rapidly undergoes internal conversion, facilitated by sequential proton transfer reactions in the excited state.Leveraging the synthetic utility of the amine group, we carried out straightforward single-step modifications to create a full-color SBF library from p-DAPA as the common precursor. During the course of the investigation, we made another fortuitous discovery. With increasing acidity of the N-H group, the excited-state intramolecular proton transfer reaction is promoted, opening up additional pathways for emission to occur at even longer wavelengths. Tipping the balance between the two excited-state tautomers enabled the first example of a single-benzene white-light emitter. We demonstrated the practical utility of these molecules in white light-emitting devices and live cell imaging.According to the particle-in-a-box model, it is difficult to expect a molecule with only one small aromatic ring to produce long-wavelength emission. SBFs rise to this challenge by exploiting electron donor-acceptor pairs around the benzene core, which lowers the energy of light absorption. However, this answers only half of the question. Where do the exceptionally large spectral shifts in the light emission of SBFs originate from? Chemists have long been curious about the molecular mechanisms underlying the dramatic spectral shifts observed in SBFs. Prevailing paradigms invoke the charge transfer (CT) between electron donor and acceptor groups in the excited state. However, without a large π-skeleton for effective charge separation, how could benzene support a CT-type excited state? Our experimental and theoretical studies have revealed that large excited-state antiaromaticity (ESAA) of the benzene core itself is responsible for this remarkable phenomenon. The core matters, not the periphery. With appropriate molecular design, large and extended π-conjugation is no longer a prerequisite for long-wavelength light emission.

Therapeutic outcomes arising from adverse drug reactions

Summary This article examines five cases where unintended adverse reactions have led to new therapeutic outcomes. The cases cover subsequent applications of acetylsalicylic acid, sildenafil, thalidomide, domperidone, and disulfiram. These examples demonstrate the versatility of drugs in addressing diverse medical challenges. The discussion highlights the importance of analyzing adverse drug reactions to identify therapeutic opportunities arising from adverse reactions.

Moving Beyond Resistance and Readiness: Reframing Change Reactions as Change Related Subject Positioning

ABSTRACT In this paper, line managers’ experiences of, and discursive subject positioning in, a participatory work environment initiative in four nursing homes called ‘The Health Circle Project’ is examined. We focus on line managers’ change related subject positioning by interviewing the managers of the four workplaces before and after the initiative and conduct a comparative case study from a discursive psychology frame. The aim of this paper is to focus on change reactions from managers and move beyond a reductionistic dichotomy of change resistance/readiness. Instead, we focus our analysis on the change related subject positioning the managers engage in, and how they position both themselves and their subordinates. Hence, we examine how the line managers experienced the participatory Health Circle intervention, and how they reacted to potential loss of power to discursively construct and define work environment problems caused by the initiative. The study exemplifies how the line managers experienced the Health Circle intervention as both confirming and challenging their subject positions as capable managerial subjects. Finally, in the light of the analysis, the potential unintended consequences of engaging in participatory work environment intiatives and similar activities are discussed. MAD statement Resistance to change is one of the most frequently used explanations for why change processes fail. The current study presents a more nuanced theoretical concept, change-related subject positioning and explores how increasing employee participation, can elicit unintended reactions from managers. This study hence contributes to our understanding of how a, in principle, positive change process of empowering employees to improve working conditions leads to a multitude of change related subject positioning from managers. Some managers embrace the change and position themselves in line with the employee participants. Others feel threatened which in extreme cases leads to negative positioning of their subordinates.

A systematic scoping review evaluating sugar-sweetened beverage taxation from a systems perspective

Systems thinking can reveal surprising, counterintuitive or unintended reactions to population health interventions (PHIs), yet this lens has rarely been applied to sugar-sweetened beverage (SSB) taxation. Using a systematic scoping review approach, we identified 329 papers concerning SSB taxation, of which 45 considered influences and impacts of SSB taxation jointly, involving methodological approaches that may prove promising for operationalizing a systems informed approach to PHI evaluation. Influences and impacts concerning SSB taxation may be cyclically linked, and studies that consider both enable us to identify implications beyond a predicted linear effect. Only three studies explicitly used systems thinking informed methods. Finally, we developed an illustrative, feedback-oriented conceptual framework, emphasizing the processes that could result in an SSB tax being increased, maintained, eroded or repealed over time. Such a framework could be used to synthesize evidence from non-systems informed evaluations, leading to novel research questions and further policy development.

Addressing illegal practices: intergenerational transfer and creative engagement as a way to compensate boomerang effects

IntroductionThis study investigates the effectiveness of using an educational comic book to facilitate the intergenerational transfer of knowledge and intentions concerning dynamite fishing in Borneo, Malaysia. The aim is to explore how children can influence their parents' understanding of the issue and their willingness to address it within the community. Additionally, the research examines unintended reactions within the participant groups.MethodsThe study employed a controlled experimental design with two groups: a treatment group exposed to the educational comic book and a control group without this intervention. Participants were families residing in communities where dynamite fishing is still practiced. Data collection included pre- and post-intervention surveys and follow-up measurements to assess short-term and long-term effects on knowledge and intentions.ResultsThe findings revealed a successful intergenerational transfer of knowledge from children to parents, evident both in the short and long term. Furthermore, the intergenerational transfer of intentions demonstrated a two-fold pattern. The intention to discuss the dynamite fishing problem within the community was transferred from children to their parents at the second measurement point, highlighting the time required for the development of new intentions. A boomerang effect was observed for the intention to cease dynamite fishing among individuals reliant on fishing for their livelihood. This rebound effect was solely observed in the control group but was effectively mitigated in the treatment group, where engagement with the comic book influenced positive outcomes.DiscussionThe study's results underscore the power of intergenerational transfer of knowledge and intentions from younger to older generations, facilitated by educational comic books as a communication tool for addressing environmental issues. Moreover, a boomerang effect seen in the control group highlights the complexity of behavior change in economically motivated practices like dynamite fishing. Engaging interventions, such as educational materials, can play a crucial role in curbing these behaviors. Furthermore, the study emphasizes the necessity of carefully monitoring unintended reactions within participant groups, particularly in research related to sensitive topics.

Context-Aware Safe Medication Recommendations with Molecular Graph and DDI Graph Embedding

Molecular structures and Drug-Drug Interactions (DDI) are recognized as important knowledge to guide medication recommendation (MR) tasks, and medical concept embedding has been applied to boost their performance. Though promising performance has been achieved by leveraging Graph Neural Network (GNN) models to encode the molecular structures of medications or/and DDI, we observe that existing models are still defective: 1) to differentiate medications with similar molecules but different functionality; or/and 2) to properly capture the unintended reactions between drugs in the embedding space. To alleviate this limitation, we propose Carmen, a cautiously designed graph embedding-based MR framework. Carmen consists of four components, including patient representation learning, context information extraction, a context-aware GNN, and DDI encoding. Carmen incorporates the visit history into the representation learning of molecular graphs to distinguish molecules with similar topology but dissimilar activity. Its DDI encoding module is specially devised for the non-transitive interaction DDI graphs. The experiments on real-world datasets demonstrate that Carmen achieves remarkable performance improvement over state-of-the-art models and can improve the safety of recommended drugs with a proper DDI graph encoding.

Recent Advancements in Herbal Bioactive-based Nanoformulations for the Treatment of Psoriasis

Abstract: Psoriasis is a multifaceted inflammatory dermatological skin disease characterized by Tcell (T-lymphocyte) activation, hyperproliferation, and abnormal epidermal keratinocyte differentiation. Natural bioactive agents from plants including Psoralea corylifolia, Nigella sativa, Curcuma longa, Capsicum annum, Smilax china, Woodfordia fructicosa, and others have recently gained a lot of attention for their anti-psoriatic properties. However, inadequate drug absorption, lack of specificity in drug release, and unintended skin reactions largely restrict their clinical efficacy. Nanoformulations improve the pharmacodynamic characteristics that overcome drug delivery challenges and enhance the anti-psoriatic activity. Nanostructured systems such as liposome, ethosome, liposphere, and others have been reported to improve plant extract solubility, penetration, bioavailability, bioactivity, and minimize undesirable effects, providing the way for the development of herbal nanoformulation. This review enlights the therapeutic efficacy of lead phytocompounds and its nanoformulations in managing psoriasis.

Prayer, Magic and Memory in Plotinus’ Treatise on the Soul (Enneads iv 4 [28], 30-45)

Abstract In an environment where astrology was widely respected, Plotinus accepted the role of heavenly bodies in answering prayer. Considering them divine, he denied them the use of memory (iv 4, 6-8); how then could he explain response to prayer received after an interval of time? Plotinus was also concerned to deny attributing intentionality in any response given, for good or evil, since that would make the astral deities responsible also for morally dubious answers. In his treatment of the issue in this passage, Plotinus draws on a lengthy earlier discussion of the role of memory in the soul’s thinking and knowing (iv 3, 25-iv 4, 12), as associated primarily with that which exists in time and is characterized by αἴσθησις, i.e., the lower soul belonging to the composite living being (iv 3, 25.12-14; iv 4, 16-17). If astral deities have bodies, these are of a highly refined fiery nature, and can be affected only inasmuch as they participate in the cosmic circuit. What suppliants may regard as intentional response must therefore be understood as the effect of a type of ‘linking’ of the universe as a living organism in which all parts are coordinated in an interrelationship characterized by sympathy. This is why answers to prayer represent no more than the unintended reaction of natural forces in the universe, the very same forces also responsible for effective use of magic. If Plotinus does not assign much value to prayer, he does recognize that, as with magic, such incantations may have a harmful effect, if only for the lower soul. He therefore warns the wise person to guard against such outcomes by focusing the soul in its contemplation of what is higher, i.e., its inner life.

Standardized excitable elements for scalable engineering of far-from-equilibrium chemical networks.

Engineered far-from-equilibrium synthetic chemical networks that pulse or switch states in response to environmental signals could precisely regulate the kinetics of chemical synthesis or self-assembly. Currently, such networks must be extensively tuned to compensate for the different activities of and unintended reactions between a network's various chemical components. Modular elements with standardized performance could be used to rapidly construct networks with designed functions. Here we develop standardized excitable chemical regulatory elements, termed genelets, and use them to construct complex in vitro transcriptional networks. We develop a protocol for identifying >15 interchangeable genelet elements with uniform performance and minimal crosstalk. These elements can be combined to engineer feedforward and feedback modules whose dynamics match those predicted by a simple kinetic model. Modules can then be rationally integrated and organized into networks that produce tunable temporal pulses and act as multistate switchable memories. Standardized genelet elements, and the workflow to identify more, should make engineering complex far-from-equilibrium chemical dynamics routine.

Impact of existing and potential e-cigarette flavor restrictions on e-cigarette use among young adult e-cigarette users in 6 US metropolitan areas

Given the 2020 federal restrictions on flavored cartridge-based e-cigarettes and increasing state/local flavored e-cigarette sales restrictions, this mixed-methods study examined US young adult e-cigarette users’ responses to flavored e-cigarette sales restrictions (e.g., changes in use, products used, access). We descriptively analyzed Fall 2020 survey data from 726 past 6-month e-cigarette users (Mage = 24.15, 51.1% female, 4.4% Black, 10.2% Asian, 12.1% Hispanic, 35.5% sexual minority), and qualitatively analyzed Spring 2021 semi-structured interview data among 40 participants (Mage = 26.30, 35.0% female, 5.0% Black, 22.5% Asian, 12.5% Hispanic, 45.0% sexual minority). Across all participants (i.e., survey and interview participants), ≥80% most commonly used non-tobacco flavors; ≥40% used tank-based devices. Survey participants most commonly reported that the federal restrictions did not impact their use: 35.8% used available flavors (i.e., tobacco, menthol), 30.4% continued to use tank-based e-cigarettes, and 10.1% switched to tank-based e-cigarettes. Only 8.4% reduced their e-cigarette use. Among interview participants, some indicated no impact on their e-cigarette use because they stocked up or obtained flavors from alternative sources (e.g., online). Some filled their own pods with e-liquids, switched to menthol/tobacco flavors, switched e-cigarette devices or brands, and/or reduced use. Regarding the anticipated impact of comprehensive flavor restrictions, some participants reported that they would: 1) quit vaping; 2) switch to cigarettes; or 3) not change their use (e.g., stock up on flavors). The potential unintended reactions to flavored e-cigarette sales restrictions (e.g., continued use of flavored cartridge-based e-cigarettes) underscore the need for ongoing surveillance of retail and consumer behavior to inform policy and compliance/enforcement efforts.

In vitro basophil activation test for drug hypersensitivity diagnosis

According to the definition of the World Health Organization, drug allergy is one of the types of adverse reactions to drugs, and is defined as any harmful or unintended reaction that occurs in doses used for prevention, diagnosis or treatment (Astakhova A. V., 2008). In accordance with the studies data, patients with an adverse drug reaction (ADR) account for approximately 6.5 % of all hospitalizations, and the incidence of fatal ADRs is 0.32 %. This explains why drug allergy is an important clinical problem (Kostyleva M. N., 2014, Verlan N. V., Rybalko M. V., 2013). Purpose of the study: to conduct a CAST (drug intolerance test) in children with a positive result on the Naranjo scale.

Analysis of genotoxic N-nitrosamines in active pharmaceutical ingredients and market authorized products in low abundance by means of liquid chromatography – tandem mass spectrometry

In 2018, high levels of the IARC class IIA carcinogen N-nitrosodimethylamine (NDMA) were analytically verified in the active pharmaceutical ingredient (API) valsartan, resulting in extensive regulatory action on angiotensin-II-receptor antagonists and recall of finished drug products by the pharmaceutical industry to ensure patient safety. The root cause of contamination was the unintended reaction of common reagents utilized during drug synthesis. This lead to serious effects on drug quality and immediate regulatory action. Thus, routine analysis of drug product contents are inevitable and necessitate thoroughly performed work up procedures of the product as well as adequate validated analytical methods. The nature of N-nitrosamines (NA), ranging from small, semi-volatile compounds up to highly polar molecules, effort sophisticated requirements in terms of instrumental analysis. Up today, gas as well as liquid chromatographic devices coupled to mass spectrometers are the most widespread systems for analysis. Gas chromatographic – mass spectrometric (GC-MS) systems, obviously superior towards liquid chromatography – mass spectrometry (LC-MS) for detecting small volatile compounds like NDMA, reach their limits for broadly designed studies including polar or acidic NA. In this study, a complementary and highly sensitive approach by means of liquid chromatography – tandem mass spectrometry (LC-MS/MS) is presented, including detection of 13 NA deduced from major classes of secondary amines. Thereby, the fully validated approach was performed in accordance to ICH and European Medicines Agency (EMA) guidelines. Quantitative proof-of-concept measurements with various APIs and market authorized tablets as representative drug formulations conclude applicability for further presumably contaminated substances. The approach employs organic or inorganic extraction steps with solid phase extraction (SPE). The limit of detection for the most prominent NA, NDMA and N-diethylnitrosamine (NDEA), were both 0.025 parts-per-billion (ppb) per matrix, respectively.