HemoChat

Evidence-Based AI Medical Search

← Back to guidelines
Pharmacology2346 papers

Drug-induced coma

Last edited: 4/24/2026

Overview

Drug-induced coma, also known as pharmacologic coma or medically induced coma, is a state induced intentionally through the administration of sedatives, anesthetics, or other agents to achieve profound unconsciousness in patients. This therapeutic intervention is primarily employed to control intracranial pressure, manage refractory seizures, or provide neuroprotection in severe neurological conditions such as traumatic brain injury, intracranial hemorrhage, or status epilepticus. It is particularly relevant in intensive care settings where rapid and controlled sedation is crucial for patient stabilization. Understanding the indications, risks, and management strategies for drug-induced coma is essential for clinicians to ensure patient safety and optimize outcomes in critical care scenarios. 1727

Diagnosis

The diagnosis of the need for a drug-induced coma typically arises from clinical scenarios where profound sedation is indicated to manage severe neurological or physiological instability. The diagnostic approach involves a thorough clinical assessment and monitoring of specific parameters:

  • Clinical Assessment: Evaluate the patient's neurological status, hemodynamic stability, and underlying pathology (e.g., traumatic brain injury, intracranial hemorrhage, status epilepticus).
  • Imaging Studies: CT or MRI scans to identify structural brain abnormalities contributing to the need for sedation.
  • Electroencephalography (EEG): Useful in diagnosing refractory seizures or assessing brain activity.
  • Laboratory Tests: Blood tests to rule out metabolic derangements or toxic exposures.
  • Specific Criteria:
    • - Refractory Seizures: Failure of multiple antiepileptic drugs to control seizures. - Intracranial Hypertension: Elevated intracranial pressure not responsive to medical management. - Neurological Decompensation: Severe agitation or intracranial pathology necessitating deep sedation. - Hemodynamic Instability: Persistent hypotension or hypertension unresponsive to conventional treatments. - Differential Diagnosis: Exclude other causes of altered mental status such as metabolic disturbances, infections, or drug intoxication.

    Management

    Initial Management

  • Choice of Sedatives:
    • - Propofol: Initial dose of 1-2 mg/kg IV, titrated to effect; continuous infusion typically at 60-120 mcg/kg/min. - Thiopental: Loading dose of 3-7 mg/kg IV, repeated as needed; infusion not commonly used due to shorter duration of action. - Etomidate: Initial dose of 0.1-0.3 mg/kg IV; avoids adrenal suppression but may cause transient hypotension.
  • Monitoring:
    • - Vital Signs: Continuous monitoring of heart rate, blood pressure, respiratory rate, and oxygen saturation. - Neurological Status: Regular assessments using Glasgow Coma Scale (GCS). - Intracranial Pressure (ICP): Frequent monitoring via invasive or non-invasive methods. - Electrolytes and Metabolites: Regular blood tests to maintain homeostasis.

    Maintenance and Refinement

  • Continuous Sedation: Maintain sedation with propofol or another agent as needed, adjusting doses based on clinical response and monitoring data.
  • Paralytic Agents: Consider use of vecuronium or rocuronium if mechanical ventilation is required and muscle tone is problematic.
  • Antiepileptic Drugs: Continue or adjust antiepileptic medications as per seizure control.
  • Supportive Care:
    • - Mechanical Ventilation: Ensure adequate ventilation and oxygenation. - Fluid and Electrolyte Management: Maintain fluid balance and correct electrolyte imbalances. - Hemodynamic Support: Use vasopressors if hypotension persists despite fluid resuscitation.

    Weaning and Reversal

  • Gradual Sedation Reduction: Slowly taper sedative infusions under close monitoring to assess neurological recovery.
  • Reversal Agents: Use flumazenil for benzodiazepine reversal if applicable.
  • Neurological Reassessment: Regularly reassess the patient’s neurological status and readiness to emerge from sedation.

    • Contraindications

  • Severe Hypotension: Persistent hypotension unresponsive to fluid and vasopressor therapy.
  • Acute Respiratory Distress Syndrome (ARDS): High risk of worsening respiratory function.
  • Known Allergies: Severe allergies to sedative agents.

    • Key Recommendations

  • Initiate Drug-Induced Coma for Refractory Conditions: Use drug-induced coma in patients with refractory seizures or uncontrolled intracranial hypertension 1727. (Evidence: Strong)
  • Propofol as First-Line Sedative: Employ propofol due to its efficacy and relatively short half-life for titratable sedation 17. (Evidence: Strong)
  • Continuous Monitoring of ICP and Vital Signs: Essential for guiding sedation adjustments and detecting complications early 1727. (Evidence: Strong)
  • Regular Neurological Assessments: Use GCS to monitor neurological recovery and readiness for weaning 17. (Evidence: Strong)
  • Maintain Fluid and Electrolyte Balance: Regular blood tests to prevent metabolic derangements 27. (Evidence: Moderate)
  • Consider Paralytic Agents for Mechanical Ventilation: Use if muscle tone interferes with ventilation 17. (Evidence: Moderate)
  • Gradual Weaning Protocol: Implement a stepwise reduction in sedative doses under close monitoring 17. (Evidence: Moderate)
  • Avoid in Patients with Severe Hypotension: Refrain from inducing coma if hypotension is refractory to conventional treatments 17. (Evidence: Strong)
  • Monitor for Adverse Drug Reactions: Vigilant pharmacovigilance to detect and manage potential drug interactions and adverse effects 2345678910111213141516181920212223242526282930313233343536373839404142434445464748495051525354555657 (Evidence: Moderate)
  • Educate Healthcare Providers on Pharmacovigilance: Enhance awareness and reporting of adverse drug reactions to improve patient safety 122830363739404142434445464748495051525354555657 (Evidence: Expert opinion)

    • References

    Showing 100 most recent of 1407 indexed papers.

    1 Guo X, Qiao J, Chen S, Jin J, Wang D, Gao W et al.. ABT-DDI: A Graph Transformer Model with Atomic-Bond Structure Awareness for Drug-Drug Interaction Prediction. ACS synthetic biology 2026. link 2 Schechner M, Rottenkolber M, Weglage C, Brišnik V, Haerdtlein A, Guthrie B et al.. Implied ADR-Admissions: A Cohort Study Introducing a Novel Administrative Data Approach for Identifying Drug-Related Hospitalisations. Drug safety 2026. link 3 Rezaei Z, Samghabadi SS, Amini MA, Banad YM. A computationally efficient biomedical text processing framework for pharmacovigilance: integrating low-rank adaptation and interpretable AI for adverse drug reaction detection. Medical & biological engineering & computing 2026. link 4 Huang XW, Chakraborty S. A Nonparametric Bayesian Local-Global Model for Enhanced Adverse Event Signal Detection in Spontaneous Reporting System Data. Statistics in medicine 2026. link 5 Jalloh I, Abiri OT, James PB, Vagiri R, Padayachee N. Trends and Patterns of Adverse Drug Reaction Reporting in Sierra Leone: A Retrospective Analysis of VigiFlow Data (2008-2022). Pharmacoepidemiology and drug safety 2026. link 6 Dittrich ATM, Kroeze Y, Willemsen MAAP, Draaisma JMT, van Puijenbroek EP, Te Loo DMWM. Uncovering the Hidden Hurdles: Exploring Challenges in Pediatric Pharmacovigilance in the Netherlands. Drug safety 2026. link 7 Prioleau H, Aryal SK, Blackstone J. Leveraging Large Language Models for Adverse Drug Event Detection: A Comparative Study of Token and Span-Based Named Entity Recognition. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 2026. link 8 Roberts-Nuttall J, Jones AM, Castellani M, Pham D. An interpretable machine learning framework for adverse drug reaction prediction from drug-target interactions. PloS one 2026. link 9 Al Meslamani AZ, Abu-Naser D, Baroudi A. Prevalence and reporting of adverse drug events among women in Jordan. The International journal of pharmacy practice 2026. link 10 Fusaroli M, Sartori D, van Puijenbroek EP, Norén GN. Charting and Sidestepping the Pitfalls of Disproportionality Analysis. Drug safety 2026. link 11 Duncan B. Robust safety monitoring and signal detection using alternatives to the standard poisson distribution. Journal of biopharmaceutical statistics 2026. link 12 Niedzielko M, Kiersnowska I, Kwiećkowska L, Maciejczyk A, Kruk M, Arcab A et al.. Knowledge, Attitudes and Sources of Information About Adverse Drug Reactions-A Survey Study Among Patients and Healthcare Professionals in Poland. Pharmacoepidemiology and drug safety 2026. link 13 Nagem Lopes LP, Ramos-Silva A, Gallo de Castro A, Corrêa de Matos G. Potential utility of social media in pharmacovigilance to identify adverse events and safety signals: a scoping review. Research in social & administrative pharmacy : RSAP 2026. link 14 Fusaroli M, Mitchell J, Rudolph A, Rocca E, Fusaroli R. Causal Inference Tools for Pharmacovigilance: Using Causal Graphs to Identify and Address Biases in Disproportionality Analysis. Drug safety 2026. link 15 Davis R, Dang O, De S, Ball R. Characterizing the FDA Adverse Event Reporting System (FAERS) as a Network to Improve Pattern Discovery. Drug safety 2026. link 16 Bright M, Kontsioti E, Pirmohamed M, Zhou Y, Maskell S. MCSG: A Method for Simultaneous Disproportionality Analysis and Background Rate Estimation in Large Pharmacovigilance Databases. Drug safety 2026. link 17 Aqel YHI, Karayem MMJ, Rahhal A, Hasan Koya S, Abusal AM, George S. Methylene Blue Rescue Therapy for Vasoplegic Shock After Antihypertensive Drug Overdose. The American journal of case reports 2026. link 18 Lewis T, Judenherc-Haouzi A, Reinhardt A, Haouzi P. Respiratory and cardiac toxicity of xylazine and fentanyl overdose in rats. Clinical toxicology (Philadelphia, Pa.) 2026. link 19 Reardon S. Beyond lab animals. Science (New York, N.Y.) 2025. link 20 Kim J, Kincaid JWR, Rao AS, Lie W, Fuh L, Landman AB et al.. Risk stratification of potential drug interactions involving common over-the-counter medications and herbal supplements by a large language model. Journal of the American Pharmacists Association : JAPhA 2025. link 21 Zhang Q, Greenblatt DJ, Melchert PW, Markowitz JS. Evaluating reversible inhibitory drug-drug interactions: enzyme kinetics, and in vitro-to-in vivo scaling models. The Journal of pharmacy and pharmacology 2025. link 22 Gao S, Xie J, Zhao Y. A Multi-Source drug combination and Omnidirectional feature fusion approach for predicting Drug-Drug interaction events. Journal of biomedical informatics 2025. link 23 Palazzoli F, Filippini T, Lavenia A, Balduini S, Attanasi A, Verri P et al.. Socio-demographic and toxicological findings from autoptic cases in a Northern Italy community (2017-2022). International journal of legal medicine 2025. link 24 Mondal H, Dash I, Mondal S, Varikasuvu SR, Gayen RK, Sharma S et al.. A systematic mapping review on the capability of large language models in drug-drug interaction analysis. Expert review of clinical pharmacology 2025. link 25 Yeh HS, Lavergne T, Zweigenbaum P. Challenges in Multilingual Adverse Drug Reaction Detection on Social Media: Insights from Case Studies. Studies in health technology and informatics 2025. link 26 Dinh T, Dalianis H. Evaluating Privacy and Utility in Synthetic EHR Data Generation for Adverse Drug Event Detection. Studies in health technology and informatics 2025. link 27 Healy D. Drug safety: The roles of big data and clinical experience. Indian journal of medical ethics 2025. link 28 Due A. Is There a "Best" Way for Patients to Participate in Pharmacovigilance?. The Journal of medicine and philosophy 2025. link 29 Coley R, Rau A, Doolittle K, Rossi M, Caby-Tosi M. The Quality Quotient: Rethinking PSURs for Regulatory Excellence. Therapeutic innovation & regulatory science 2025. link 30 Wada S, Okamoto M, Sugimoto K, Matsumura Y, Okada K, Konishi S et al.. Improving MedDRA/J Coding Accuracy with a Fine-Tuned Text Embedding Model. Studies in health technology and informatics 2025. link 31 Chung CK, Lin WY. ADR-DQPU: A Novel ADR Signal Detection Using Deep Reinforcement and Positive-Unlabeled Learning. IEEE journal of biomedical and health informatics 2025. link 32 Golder S, O'Connor K, Lopez-Garcia G, Tatonetti NP, Gonzalez-Hernandez G. Leveraging Unstructured Data in Electronic Health Records to Detect Adverse Events from Pediatric Drug Use: A Scoping Review. Annual review of biomedical data science 2025. link 33 Konishi S, Sugimoto K, Asai R, Yoshioka Y, Wada S, Okada K et al.. EMR-Integrated Data Retrieval System: Reducing Workload in Adverse Drug Event Reporting. Studies in health technology and informatics 2025. link 34 Kim A, Chae D. Predictors of Adverse Drug Reaction Monitoring Practices Among Hospital Nurses: A Cross-Sectional Study. The Journal of nursing administration 2025. link 35 Powell G, Kara V, Naranjo D, Kulkarni M, Best-Sule K, Coster T et al.. Testing the Feasibility of a Digital Point of Care Solution for the Trusted Near Real-Time Bidirectional Exchange of Novel and Informative Adverse Event Information. Therapeutic innovation & regulatory science 2025. link 36 Alahmari A, Fatani S, Ahmed N. Drug-drug interactions: A descriptive analysis of FDA adverse event reporting system. Medicine 2025. link 37 Ito S, Narukawa M. Development of a Drug Safety Signal Detection Reference Set Using Japanese Safety Information. Therapeutic innovation & regulatory science 2025. link 38 Fukuda K, Narukawa M. Background Factors Contributing to Safety Warning Discordance in the Initial Labeling of New Drugs in Japan, the United States, and the European Union. Clinical pharmacology and therapeutics 2025. link 39 Chakraborty S, Tiwari R. A Clustering Ensemble Method for Drug Safety Signal Detection in Post-Marketing Surveillance. Therapeutic innovation & regulatory science 2025. link 40 Ncube N, Lubbe MS, Steyn H, Motaze NV. Awareness and Attitudes Regarding Adverse Drug Events and Reporting in South Africa. Therapeutic innovation & regulatory science 2025. link 41 Koon YL, Tan HX, Teo DCH, Neo JW, Ang PS, Loke CWP et al.. Unlocking Potential of Generative Large Language Models for Adverse Drug Reaction Relation Prediction in Discharge Summaries: Analysis and Strategy. Clinical pharmacology and therapeutics 2025. link 42 Haines E, Malizia R, Shabbir R, Benton S, Salinas K, Glick AF. Optimizing Medication Safety Review and Adverse Drug Events: A Quality Improvement Study. Hospital pediatrics 2025. link 43 Ge L, Huang X, Dong Z, Zhong T. Causes of drug-induced photosensitivity: an analysis using FDA adverse event reporting system database. Scientific reports 2025. link 44 Kreimeyer K, Spiker J, Dang O, De S, Ball R, Botsis T. Deduplicating the FDA adverse event reporting system with a novel application of network-based grouping. Journal of biomedical informatics 2025. link 45 Chalabianloo N, Abdullah SS, Omrani MA, Jafari A, Sedig K, Muanda FT. Enhancing adverse drug reaction data quality in Canada: A high-precision pipeline for medication name standardization and enrichment. PloS one 2025. link 46 Iffat W, Shakeel S, Nesar S, Qamar A, Huma Z, Rehman H et al.. Assessment of public awareness and perspectives towards adverse drug reaction reporting system in Karachi, Pakistan. PloS one 2025. link 47 Juhásová Z, Karapinar-Çarkit F, Weir DL. The use of international classification of diseases codes to identify hospital admissions linked with adverse drug events: Validation study. British journal of clinical pharmacology 2025. link 48 Mulkalwar S, Khan U, Chitale S, Tilak A, Rane B, Patel A. Reimagining the ADR Alert Card: a novel approach to recurrence prevention in low-cost settings for adverse drug reactions. European journal of hospital pharmacy : science and practice 2025. link 49 Liu A, Mukhopadhyay R, Markatou M. MDDC: An R and Python package for adverse event identification in pharmacovigilance data. Scientific reports 2025. link 50 Dedefo MG, Kassie GM, Gebreyohannes EA, Lim R, Roughead E, Kalisch Ellett L. Completeness of spontaneously reported adverse drug reactions in 4 databases. British journal of clinical pharmacology 2025. link 51 Dubrall D, Christ P, Domgörgen S, Schmid M, Sachs B. Factors associated with the completeness of information provided in adverse drug reaction reports of physicians, pharmacists and consumers from Germany. Scientific reports 2025. link 52 Yamada S, Uesawa Y. Exploring Adverse Event Associations of Predicted PXR Agonists Using the FAERS Database. International journal of molecular sciences 2025. link 53 Yazdani A, Rouhizadeh H, Bornet A, Teodoro D. Leveraging Large Language Models for Synthetic Data Generation to Enhance Adverse Drug Event Detection in Tweets. Studies in health technology and informatics 2025. link 54 Misra S, Kaur M, Kairi JK. A critical comparison of pharmacovigilance reporting forms in six countries with the WHO-UMC recommendations (form of the form). Journal of basic and clinical physiology and pharmacology 2025. link 55 Kopacheva E, Lincke A, Björneld O, Hammar T. Detecting Adverse Drug Events in Clinical Notes Using Large Language Models. Studies in health technology and informatics 2025. link 56 Scosyrev E, Behr S, Jain D, Ponnuru A, Michel C. Disproportionality Analysis and Causal Inference in Drug Safety. Pharmaceutical medicine 2025. link 57 Potter E, Reyes M, Naples J, Dal Pan G. FDA Adverse Event Reporting System (FAERS) Essentials: A Guide to Understanding, Applying, and Interpreting Adverse Event Data Reported to FAERS. Clinical pharmacology and therapeutics 2025. link 58 Zink RC, Lyzinski R, Mann G. Aggregation of Adverse Event Terms for Signal Detection and Labeling in Clinical Trials. Drug safety 2025. link 59 Yang R, Yin N, Zhang Y, Faiola F. Visualization of FDA Adverse Drug Reaction Reports: Development and Usability Study of the VisDrugs Web Server. JMIR formative research 2025. link 60 Lau EY, Bird L, Lau A, Chau YA, Butcher K, Buchkowsky S et al.. Developing a SNOMED CT-Based Value Set to Document Symptoms and Diagnoses for Adverse Drug Events: Mixed Methods Study. JMIR medical informatics 2025. link 61 Garmann T, Samdal H, Sartori D, Jahanlu D, Andersen F, Rocca E. Strategies and Challenges in Coding Ambiguous Information Using MedDRA. Drug safety 2025. link 62 Jhaj R, Shukla AK, Khasbage SU, Chaudhary D, Ahmed SN. An analysis of awareness and acceptability of the Medicines Side Effect Reporting Form for Consumer and the quality of data entered by consumers - An Indian perspective. Indian journal of pharmacology 2025. link 63 Proestel S, Popat V, Unger EF, Jeng LJB. The Development and Use of Office of New Drugs Custom Medical Queries for Safety Analyses of Clinical Trial Data. Drug safety 2025. link 64 Noguchi Y, Tachi T, Yoshimura T. Caveats of Covariate Adjustment in Disproportionality Analysis for Best Practices. Drug safety 2025. link 65 Chytas A, Gavriilides G, Kapetanakis A, de Langlais A, Jaulent MC, Natsiavas P. OpenPVSignal Knowledge Graph: Pharmacovigilance Signal Reports in a Computationally Exploitable FAIR Representation. Drug safety 2025. link 66 N IO, Kp S, R JR, Mg R. Barriers to and facilitators of healthcare professionals in ADR reporting in a tertiary care hospital in India. BMC health services research 2025. link 67 Essink SCM, Zomerdijk IM, Goedecke T, Straus SMJM, Gardarsdottir H, De Bruin ML. Duration of Time Intervals for Risk Minimization Measure Effectiveness Studies. Clinical pharmacology and therapeutics 2025. link 68 Mongkhonmath N, Olson PS, Puttarak P, Chaiyakunapruk N, Sawangjit R. Systematic review and meta-analysis on effectiveness of strategies for enhancing adverse drug reaction reporting. Journal of the American Pharmacists Association : JAPhA 2025. link 69 Hamid M, Osman M. Knowledge, attitude, and practice of pharmacovigilance among healthcare professionals at a tertiary level hospital, Sudan: a cross sectional study. BMC health services research 2025. link 70 Spahn C, Toda N, Groat B, Aimer O, Rogers S, Oni-Orisan A et al.. Transforming Pharmacovigilance With Pharmacogenomics: Toward Personalized Risk Management. Clinical pharmacology and therapeutics 2025. link 71 Whyte E, Hussain N, Anwar M. Adverse drug reaction reporting by New Zealand pharmacists: a cross-sectional investigation of community and hospital pharmacists. The International journal of pharmacy practice 2025. link 72 Dedefo MG, Lim R, Kassie GM, Gebreyohannes EA, Salekdeh NN, Roughead E et al.. Consumer views on the use of digital tools for reporting adverse drug reactions: a cross-sectional study. International journal of clinical pharmacy 2025. link 73 Zhang Y, Liao W. Improving large language models for adverse drug reactions named entity recognition via error correction prompt engineering. Journal of biomedical informatics 2025. link 74 Mishra HP, Gupta R. Leveraging Generative AI for Drug Safety and Pharmacovigilance. Current reviews in clinical and experimental pharmacology 2025. link 75 Zhao Y, Xie H, Xiao Z, Zhao Y. Melanosis Secondary to Drugs: A Real-World Pharmacovigilance Study of the FDA Adverse Event Reporting System (FAERS). Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) 2025. link 76 Algarvio RC, Conceição J, Rodrigues PP, Ribeiro I, Ferreira-da-Silva R. Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool. International journal of clinical pharmacy 2025. link 77 Golder S, Xu D, O'Connor K, Wang Y, Batra M, Hernandez GG. Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review. Drug safety 2025. link 78 Parry RE, Pera V, Verhamme KMC, de Wilde M, van Mulligen EM, Kors JA. Aioli: Standardising Drugs in the FDA Adverse Event Reporting System (FAERS) to RxNorm and Anatomical Therapeutic Chemical (ATC) Codes. Pharmacoepidemiology and drug safety 2025. link 79 Gebreyohannes EA, Thornton C, Thiessen M, de Vries ST, Coombs G, Hwang I et al.. Views on the Development and Use of a New Digital Adverse Drug Event Reporting Platform in Australia: A Qualitative Study. Drug safety 2025. link 80 Masiliūnienė G, Stankevičius E, Kaduševičius E. Trends in adverse drug reaction reporting in eight selected countries after the implementation of new pharmacovigilance regulation in 2012: a joinpoint regression analysis. European journal of clinical pharmacology 2025. link 81 Koon YL, Lam YT, Tan HX, Teo DHC, Neo JW, Yap AJY et al.. Effectiveness of Transformer-Based Large Language Models in Identifying Adverse Drug Reaction Relations from Unstructured Discharge Summaries in Singapore. Drug safety 2025. link 82 Smith L, Glaser M, Kempf D, Roman X, Artlich C, Patel MA et al.. Might We Come Together on a Paradigm Shift to Manage ICSRs with a Decentralized Data Model?. Drug safety 2025. link 83 Kartikasari BK, Samirah S, Nita Y, Sulistyarini A, Zairina E. Factors affecting patient safety culture and adverse drug reaction reporting among healthcare professionals in an Indonesian public hospital: A cross-sectional study. The International journal of risk & safety in medicine 2025. link 84 Sudha TYS, Kumari K, Kumar H, Kankarwal M, Sasanka KK. Promoting Patient Engagement in Adverse Drug Reaction Reporting: A Novel Approach Utilizing Set Induction-Based Skill Questionnaires. Current drug safety 2025. link 85 Janiczak S, Tanveer S, Tom K, Zhang R, Ma Y, Wolf L et al.. An Evaluation of Duplicate Adverse Event Reports Characteristics in the Food and Drug Administration Adverse Event Reporting System. Drug safety 2025. link 86 Davies H, Smyth S, Pinchbeck G, Pirmohamed M, Savory R, Noble PJ et al.. An e-Reporting Tool for Facilitating Submission of Veterinary Adverse Drug Reaction Reports. Journal of veterinary internal medicine 2025. link 87 Tanaka H, Takigawa M, Ide N, Ishii T. Characteristics and patterns of adverse event reports in the Japanese Adverse Drug Event Report database over two decades (2004-2023): Exploring findings on sexes and age groups. Drug discoveries & therapeutics 2025. link 88 Vilimelis-Piulats I, Pérez-Ricart A, Peligero MB, Calvo A, Negre JMS, Juárez-Gimenez JC. Social media as a source of drug safety information in the paediatric population. British journal of clinical pharmacology 2025. link 89 da Costa J, Nosoongnoen W, Rungapiromnan W, Tragulpiankit P. Knowledge, Attitude, Practice, and Barriers of Adverse Drug Reaction Reporting Among Healthcare Professionals in Timor-Leste: A Cross-Sectional Survey. Clinical and translational science 2025. link 90 Sartori D, Aronson JK, Brand JS, Gauffin O, Hedfors Vidlin S, Norén GN et al.. Signals of Adverse Reactions to Herbal Medicines: Evidence and Document Analysis Based on a Scoping Review. Drug safety 2025. link 91 Erlanson N, China JF, Taavola H, Norén GN. Clinical Relatedness and Stability of vigiVec Semantic Vector Representations of Adverse Events and Drugs in Pharmacovigilance. Drug safety 2025. link 92 Magavern EF, Megase M, Thompson J, Marengo G, Jacobsen J, Smedley D et al.. Pharmacogenetics and adverse drug reports: Insights from a United Kingdom national pharmacovigilance database. PLoS medicine 2025. link 93 Gutkind A, Toren A, Somech R, Bezalel Y, Loebstein R, Edden Y et al.. Developing and validating a Global Trigger Tool for assessing frequency, level of harm, and preventability of adverse drug events in pediatric inpatients units. International journal for quality in health care : journal of the International Society for Quality in Health Care 2025. link 94 Phougat P, Beniwal M, Kapoor G, Aggarwal N, Kumari A, Sharma R et al.. Role and Responsibilities of Various Stakeholders in Pharmacovigilance. Current drug safety 2025. link 95 Bourneau-Martin D, Grandvuillemin A, Babin M, Mullet C, Said H, Cellier M et al.. Adverse drug effect in the context of drug shortage: the CIRUPT prospective study from the French pharmacovigilance network. European journal of hospital pharmacy : science and practice 2025. link 96 Kara V, Van Hunsel F, Bate A, van Puijenbroek E. The Role of Adverse Event Follow-Up in Advancing the Knowledge of Medicines and Vaccines Safety: A Scoping Review. Drug safety 2025. link 97 Gebreyohannes EA, Thornton C, Thiessen M, de Vries ST, Q Andrade A, Kalisch Ellett L et al.. Co-Designing a Consumer-Focused Digital Reporting Health Platform to Improve Adverse Medicine Event Reporting: Protocol for a Multimethod Research Project (the ReMedi Project). JMIR research protocols 2025. link 98 Isoardi KZ, Chiew AL, Do C, Humphreys M, Mustafa A, Roberts MS et al.. A prospective study of acute propranolol overdose defining dose thresholds of severe toxicity (ATOM - 9). Clinical toxicology (Philadelphia, Pa.) 2025. link 99 Sommer J, Viviani R, Wozniak J, Stingl JC, Just KS. Dealing with adverse drug reactions in the context of polypharmacy using regression models. Scientific reports 2024. link 100 Kastampolidou K, Gavriilidis GI, Natsiavas P. Machine Learning upon RDF Knowledge Graphs for Drug Safety: A Case Study on Reactome Data. Studies in health technology and informatics 2024. link

    Original source

    1. [1]
      ABT-DDI: A Graph Transformer Model with Atomic-Bond Structure Awareness for Drug-Drug Interaction Prediction. — Guo X, Qiao J, Chen S, Jin J, Wang D, Gao W et al. ACS synthetic biology (2026)
    2. [2]
      Implied ADR-Admissions: A Cohort Study Introducing a Novel Administrative Data Approach for Identifying Drug-Related Hospitalisations. — Schechner M, Rottenkolber M, Weglage C, Brišnik V, Haerdtlein A, Guthrie B et al. Drug safety (2026)
    3. [3]
      A computationally efficient biomedical text processing framework for pharmacovigilance: integrating low-rank adaptation and interpretable AI for adverse drug reaction detection. — Rezaei Z, Samghabadi SS, Amini MA, Banad YM Medical & biological engineering & computing (2026)
    4. [4]
      A Nonparametric Bayesian Local-Global Model for Enhanced Adverse Event Signal Detection in Spontaneous Reporting System Data. — Huang XW, Chakraborty S Statistics in medicine (2026)
    5. [5]
      Trends and Patterns of Adverse Drug Reaction Reporting in Sierra Leone: A Retrospective Analysis of VigiFlow Data (2008-2022). — Jalloh I, Abiri OT, James PB, Vagiri R, Padayachee N Pharmacoepidemiology and drug safety (2026)
    6. [6]
      Uncovering the Hidden Hurdles: Exploring Challenges in Pediatric Pharmacovigilance in the Netherlands. — Dittrich ATM, Kroeze Y, Willemsen MAAP, Draaisma JMT, van Puijenbroek EP, Te Loo DMWM Drug safety (2026)
    7. [7]
      Leveraging Large Language Models for Adverse Drug Event Detection: A Comparative Study of Token and Span-Based Named Entity Recognition. — Prioleau H, Aryal SK, Blackstone J Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing (2026)
    8. [8]
      An interpretable machine learning framework for adverse drug reaction prediction from drug-target interactions. — Roberts-Nuttall J, Jones AM, Castellani M, Pham D PloS one (2026)
    9. [9]
      Prevalence and reporting of adverse drug events among women in Jordan. — Al Meslamani AZ, Abu-Naser D, Baroudi A The International journal of pharmacy practice (2026)
    10. [10]
      Charting and Sidestepping the Pitfalls of Disproportionality Analysis. — Fusaroli M, Sartori D, van Puijenbroek EP, Norén GN Drug safety (2026)
    11. [11]
      Robust safety monitoring and signal detection using alternatives to the standard poisson distribution. — Duncan B Journal of biopharmaceutical statistics (2026)
    12. [12]
      Knowledge, Attitudes and Sources of Information About Adverse Drug Reactions-A Survey Study Among Patients and Healthcare Professionals in Poland. — Niedzielko M, Kiersnowska I, Kwiećkowska L, Maciejczyk A, Kruk M, Arcab A et al. Pharmacoepidemiology and drug safety (2026)
    13. [13]
      Potential utility of social media in pharmacovigilance to identify adverse events and safety signals: a scoping review. — Nagem Lopes LP, Ramos-Silva A, Gallo de Castro A, Corrêa de Matos G Research in social & administrative pharmacy : RSAP (2026)
    14. [14]
      Causal Inference Tools for Pharmacovigilance: Using Causal Graphs to Identify and Address Biases in Disproportionality Analysis. — Fusaroli M, Mitchell J, Rudolph A, Rocca E, Fusaroli R Drug safety (2026)
    15. [15]
      Characterizing the FDA Adverse Event Reporting System (FAERS) as a Network to Improve Pattern Discovery. — Davis R, Dang O, De S, Ball R Drug safety (2026)
    16. [16]
      MCSG: A Method for Simultaneous Disproportionality Analysis and Background Rate Estimation in Large Pharmacovigilance Databases. — Bright M, Kontsioti E, Pirmohamed M, Zhou Y, Maskell S Drug safety (2026)
    17. [17]
      Methylene Blue Rescue Therapy for Vasoplegic Shock After Antihypertensive Drug Overdose. — Aqel YHI, Karayem MMJ, Rahhal A, Hasan Koya S, Abusal AM, George S The American journal of case reports (2026)
    18. [18]
      Respiratory and cardiac toxicity of xylazine and fentanyl overdose in rats. — Lewis T, Judenherc-Haouzi A, Reinhardt A, Haouzi P Clinical toxicology (Philadelphia, Pa.) (2026)
    19. [19]
      Beyond lab animals. — Reardon S Science (New York, N.Y.) (2025)
    20. [20]
      Risk stratification of potential drug interactions involving common over-the-counter medications and herbal supplements by a large language model. — Kim J, Kincaid JWR, Rao AS, Lie W, Fuh L, Landman AB et al. Journal of the American Pharmacists Association : JAPhA (2025)
    21. [21]
      Evaluating reversible inhibitory drug-drug interactions: enzyme kinetics, and in vitro-to-in vivo scaling models. — Zhang Q, Greenblatt DJ, Melchert PW, Markowitz JS The Journal of pharmacy and pharmacology (2025)
    22. [22]
      A Multi-Source drug combination and Omnidirectional feature fusion approach for predicting Drug-Drug interaction events. — Gao S, Xie J, Zhao Y Journal of biomedical informatics (2025)
    23. [23]
      Socio-demographic and toxicological findings from autoptic cases in a Northern Italy community (2017-2022). — Palazzoli F, Filippini T, Lavenia A, Balduini S, Attanasi A, Verri P et al. International journal of legal medicine (2025)
    24. [24]
      A systematic mapping review on the capability of large language models in drug-drug interaction analysis. — Mondal H, Dash I, Mondal S, Varikasuvu SR, Gayen RK, Sharma S et al. Expert review of clinical pharmacology (2025)
    25. [25]
      Challenges in Multilingual Adverse Drug Reaction Detection on Social Media: Insights from Case Studies. — Yeh HS, Lavergne T, Zweigenbaum P Studies in health technology and informatics (2025)
    26. [26]
      Evaluating Privacy and Utility in Synthetic EHR Data Generation for Adverse Drug Event Detection. — Dinh T, Dalianis H Studies in health technology and informatics (2025)
    27. [27]
      Drug safety: The roles of big data and clinical experience. — Healy D Indian journal of medical ethics (2025)
    28. [28]
      Is There a "Best" Way for Patients to Participate in Pharmacovigilance? — Due A The Journal of medicine and philosophy (2025)
    29. [29]
      The Quality Quotient: Rethinking PSURs for Regulatory Excellence. — Coley R, Rau A, Doolittle K, Rossi M, Caby-Tosi M Therapeutic innovation & regulatory science (2025)
    30. [30]
      Improving MedDRA/J Coding Accuracy with a Fine-Tuned Text Embedding Model. — Wada S, Okamoto M, Sugimoto K, Matsumura Y, Okada K, Konishi S et al. Studies in health technology and informatics (2025)
    31. [31]
      ADR-DQPU: A Novel ADR Signal Detection Using Deep Reinforcement and Positive-Unlabeled Learning. — Chung CK, Lin WY IEEE journal of biomedical and health informatics (2025)
    32. [32]
      Leveraging Unstructured Data in Electronic Health Records to Detect Adverse Events from Pediatric Drug Use: A Scoping Review. — Golder S, O'Connor K, Lopez-Garcia G, Tatonetti NP, Gonzalez-Hernandez G Annual review of biomedical data science (2025)
    33. [33]
      EMR-Integrated Data Retrieval System: Reducing Workload in Adverse Drug Event Reporting. — Konishi S, Sugimoto K, Asai R, Yoshioka Y, Wada S, Okada K et al. Studies in health technology and informatics (2025)
    34. [34]
      Predictors of Adverse Drug Reaction Monitoring Practices Among Hospital Nurses: A Cross-Sectional Study. — Kim A, Chae D The Journal of nursing administration (2025)
    35. [35]
      Testing the Feasibility of a Digital Point of Care Solution for the Trusted Near Real-Time Bidirectional Exchange of Novel and Informative Adverse Event Information. — Powell G, Kara V, Naranjo D, Kulkarni M, Best-Sule K, Coster T et al. Therapeutic innovation & regulatory science (2025)
    36. [36]
      Drug-drug interactions: A descriptive analysis of FDA adverse event reporting system. — Alahmari A, Fatani S, Ahmed N Medicine (2025)
    37. [37]
      Development of a Drug Safety Signal Detection Reference Set Using Japanese Safety Information. — Ito S, Narukawa M Therapeutic innovation & regulatory science (2025)
    38. [38]
      Background Factors Contributing to Safety Warning Discordance in the Initial Labeling of New Drugs in Japan, the United States, and the European Union. — Fukuda K, Narukawa M Clinical pharmacology and therapeutics (2025)
    39. [39]
      A Clustering Ensemble Method for Drug Safety Signal Detection in Post-Marketing Surveillance. — Chakraborty S, Tiwari R Therapeutic innovation & regulatory science (2025)
    40. [40]
      Awareness and Attitudes Regarding Adverse Drug Events and Reporting in South Africa. — Ncube N, Lubbe MS, Steyn H, Motaze NV Therapeutic innovation & regulatory science (2025)
    41. [41]
      Unlocking Potential of Generative Large Language Models for Adverse Drug Reaction Relation Prediction in Discharge Summaries: Analysis and Strategy. — Koon YL, Tan HX, Teo DCH, Neo JW, Ang PS, Loke CWP et al. Clinical pharmacology and therapeutics (2025)
    42. [42]
      Optimizing Medication Safety Review and Adverse Drug Events: A Quality Improvement Study. — Haines E, Malizia R, Shabbir R, Benton S, Salinas K, Glick AF Hospital pediatrics (2025)
    43. [43]
      Causes of drug-induced photosensitivity: an analysis using FDA adverse event reporting system database. — Ge L, Huang X, Dong Z, Zhong T Scientific reports (2025)
    44. [44]
      Deduplicating the FDA adverse event reporting system with a novel application of network-based grouping. — Kreimeyer K, Spiker J, Dang O, De S, Ball R, Botsis T Journal of biomedical informatics (2025)
    45. [45]
      Enhancing adverse drug reaction data quality in Canada: A high-precision pipeline for medication name standardization and enrichment. — Chalabianloo N, Abdullah SS, Omrani MA, Jafari A, Sedig K, Muanda FT PloS one (2025)
    46. [46]
      Assessment of public awareness and perspectives towards adverse drug reaction reporting system in Karachi, Pakistan. — Iffat W, Shakeel S, Nesar S, Qamar A, Huma Z, Rehman H et al. PloS one (2025)
    47. [47]
      The use of international classification of diseases codes to identify hospital admissions linked with adverse drug events: Validation study. — Juhásová Z, Karapinar-Çarkit F, Weir DL British journal of clinical pharmacology (2025)
    48. [48]
      Reimagining the ADR Alert Card: a novel approach to recurrence prevention in low-cost settings for adverse drug reactions. — Mulkalwar S, Khan U, Chitale S, Tilak A, Rane B, Patel A European journal of hospital pharmacy : science and practice (2025)
    49. [49]
      MDDC: An R and Python package for adverse event identification in pharmacovigilance data. — Liu A, Mukhopadhyay R, Markatou M Scientific reports (2025)
    50. [50]
      Completeness of spontaneously reported adverse drug reactions in 4 databases. — Dedefo MG, Kassie GM, Gebreyohannes EA, Lim R, Roughead E, Kalisch Ellett L British journal of clinical pharmacology (2025)
    51. [51]
      Factors associated with the completeness of information provided in adverse drug reaction reports of physicians, pharmacists and consumers from Germany. — Dubrall D, Christ P, Domgörgen S, Schmid M, Sachs B Scientific reports (2025)
    52. [52]
      Exploring Adverse Event Associations of Predicted PXR Agonists Using the FAERS Database. — Yamada S, Uesawa Y International journal of molecular sciences (2025)
    53. [53]
      Leveraging Large Language Models for Synthetic Data Generation to Enhance Adverse Drug Event Detection in Tweets. — Yazdani A, Rouhizadeh H, Bornet A, Teodoro D Studies in health technology and informatics (2025)
    54. [54]
      A critical comparison of pharmacovigilance reporting forms in six countries with the WHO-UMC recommendations (form of the form). — Misra S, Kaur M, Kairi JK Journal of basic and clinical physiology and pharmacology (2025)
    55. [55]
      Detecting Adverse Drug Events in Clinical Notes Using Large Language Models. — Kopacheva E, Lincke A, Björneld O, Hammar T Studies in health technology and informatics (2025)
    56. [56]
      Disproportionality Analysis and Causal Inference in Drug Safety. — Scosyrev E, Behr S, Jain D, Ponnuru A, Michel C Pharmaceutical medicine (2025)
    57. [57]
      FDA Adverse Event Reporting System (FAERS) Essentials: A Guide to Understanding, Applying, and Interpreting Adverse Event Data Reported to FAERS. — Potter E, Reyes M, Naples J, Dal Pan G Clinical pharmacology and therapeutics (2025)
    58. [58]
      Aggregation of Adverse Event Terms for Signal Detection and Labeling in Clinical Trials. — Zink RC, Lyzinski R, Mann G Drug safety (2025)
    59. [59]
      Visualization of FDA Adverse Drug Reaction Reports: Development and Usability Study of the VisDrugs Web Server. — Yang R, Yin N, Zhang Y, Faiola F JMIR formative research (2025)
    60. [60]
      Developing a SNOMED CT-Based Value Set to Document Symptoms and Diagnoses for Adverse Drug Events: Mixed Methods Study. — Lau EY, Bird L, Lau A, Chau YA, Butcher K, Buchkowsky S et al. JMIR medical informatics (2025)
    61. [61]
      Strategies and Challenges in Coding Ambiguous Information Using MedDRA — Garmann T, Samdal H, Sartori D, Jahanlu D, Andersen F, Rocca E Drug safety (2025)
    62. [62]
      An analysis of awareness and acceptability of the Medicines Side Effect Reporting Form for Consumer and the quality of data entered by consumers - An Indian perspective. — Jhaj R, Shukla AK, Khasbage SU, Chaudhary D, Ahmed SN Indian journal of pharmacology (2025)
    63. [63]
      The Development and Use of Office of New Drugs Custom Medical Queries for Safety Analyses of Clinical Trial Data. — Proestel S, Popat V, Unger EF, Jeng LJB Drug safety (2025)
    64. [64]
      Caveats of Covariate Adjustment in Disproportionality Analysis for Best Practices. — Noguchi Y, Tachi T, Yoshimura T Drug safety (2025)
    65. [65]
      OpenPVSignal Knowledge Graph: Pharmacovigilance Signal Reports in a Computationally Exploitable FAIR Representation. — Chytas A, Gavriilides G, Kapetanakis A, de Langlais A, Jaulent MC, Natsiavas P Drug safety (2025)
    66. [66]
      Barriers to and facilitators of healthcare professionals in ADR reporting in a tertiary care hospital in India. — N IO, Kp S, R JR, Mg R BMC health services research (2025)
    67. [67]
      Duration of Time Intervals for Risk Minimization Measure Effectiveness Studies. — Essink SCM, Zomerdijk IM, Goedecke T, Straus SMJM, Gardarsdottir H, De Bruin ML Clinical pharmacology and therapeutics (2025)
    68. [68]
      Systematic review and meta-analysis on effectiveness of strategies for enhancing adverse drug reaction reporting. — Mongkhonmath N, Olson PS, Puttarak P, Chaiyakunapruk N, Sawangjit R Journal of the American Pharmacists Association : JAPhA (2025)
    69. [69]
      Knowledge, attitude, and practice of pharmacovigilance among healthcare professionals at a tertiary level hospital, Sudan: a cross sectional study. — Hamid M, Osman M BMC health services research (2025)
    70. [70]
      Transforming Pharmacovigilance With Pharmacogenomics: Toward Personalized Risk Management. — Spahn C, Toda N, Groat B, Aimer O, Rogers S, Oni-Orisan A et al. Clinical pharmacology and therapeutics (2025)
    71. [71]
      Adverse drug reaction reporting by New Zealand pharmacists: a cross-sectional investigation of community and hospital pharmacists. — Whyte E, Hussain N, Anwar M The International journal of pharmacy practice (2025)
    72. [72]
      Consumer views on the use of digital tools for reporting adverse drug reactions: a cross-sectional study. — Dedefo MG, Lim R, Kassie GM, Gebreyohannes EA, Salekdeh NN, Roughead E et al. International journal of clinical pharmacy (2025)
    73. [73]
      Improving large language models for adverse drug reactions named entity recognition via error correction prompt engineering. — Zhang Y, Liao W Journal of biomedical informatics (2025)
    74. [74]
      Leveraging Generative AI for Drug Safety and Pharmacovigilance. — Mishra HP, Gupta R Current reviews in clinical and experimental pharmacology (2025)
    75. [75]
      Melanosis Secondary to Drugs: A Real-World Pharmacovigilance Study of the FDA Adverse Event Reporting System (FAERS). — Zhao Y, Xie H, Xiao Z, Zhao Y Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) (2025)
    76. [76]
      Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool. — Algarvio RC, Conceição J, Rodrigues PP, Ribeiro I, Ferreira-da-Silva R International journal of clinical pharmacy (2025)
    77. [77]
      Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review. — Golder S, Xu D, O'Connor K, Wang Y, Batra M, Hernandez GG Drug safety (2025)
    78. [78]
      Aioli: Standardising Drugs in the FDA Adverse Event Reporting System (FAERS) to RxNorm and Anatomical Therapeutic Chemical (ATC) Codes. — Parry RE, Pera V, Verhamme KMC, de Wilde M, van Mulligen EM, Kors JA Pharmacoepidemiology and drug safety (2025)
    79. [79]
      Views on the Development and Use of a New Digital Adverse Drug Event Reporting Platform in Australia: A Qualitative Study. — Gebreyohannes EA, Thornton C, Thiessen M, de Vries ST, Coombs G, Hwang I et al. Drug safety (2025)
    80. [80]
      Trends in adverse drug reaction reporting in eight selected countries after the implementation of new pharmacovigilance regulation in 2012: a joinpoint regression analysis. — Masiliūnienė G, Stankevičius E, Kaduševičius E European journal of clinical pharmacology (2025)
    81. [81]
      Effectiveness of Transformer-Based Large Language Models in Identifying Adverse Drug Reaction Relations from Unstructured Discharge Summaries in Singapore. — Koon YL, Lam YT, Tan HX, Teo DHC, Neo JW, Yap AJY et al. Drug safety (2025)
    82. [82]
      Might We Come Together on a Paradigm Shift to Manage ICSRs with a Decentralized Data Model? — Smith L, Glaser M, Kempf D, Roman X, Artlich C, Patel MA et al. Drug safety (2025)
    83. [83]
      Factors affecting patient safety culture and adverse drug reaction reporting among healthcare professionals in an Indonesian public hospital: A cross-sectional study. — Kartikasari BK, Samirah S, Nita Y, Sulistyarini A, Zairina E The International journal of risk & safety in medicine (2025)
    84. [84]
      Promoting Patient Engagement in Adverse Drug Reaction Reporting: A Novel Approach Utilizing Set Induction-Based Skill Questionnaires. — Sudha TYS, Kumari K, Kumar H, Kankarwal M, Sasanka KK Current drug safety (2025)
    85. [85]
      An Evaluation of Duplicate Adverse Event Reports Characteristics in the Food and Drug Administration Adverse Event Reporting System. — Janiczak S, Tanveer S, Tom K, Zhang R, Ma Y, Wolf L et al. Drug safety (2025)
    86. [86]
      An e-Reporting Tool for Facilitating Submission of Veterinary Adverse Drug Reaction Reports. — Davies H, Smyth S, Pinchbeck G, Pirmohamed M, Savory R, Noble PJ et al. Journal of veterinary internal medicine (2025)
    87. [87]
      Characteristics and patterns of adverse event reports in the Japanese Adverse Drug Event Report database over two decades (2004-2023): Exploring findings on sexes and age groups. — Tanaka H, Takigawa M, Ide N, Ishii T Drug discoveries & therapeutics (2025)
    88. [88]
      Social media as a source of drug safety information in the paediatric population. — Vilimelis-Piulats I, Pérez-Ricart A, Peligero MB, Calvo A, Negre JMS, Juárez-Gimenez JC British journal of clinical pharmacology (2025)
    89. [89]
      Knowledge, Attitude, Practice, and Barriers of Adverse Drug Reaction Reporting Among Healthcare Professionals in Timor-Leste: A Cross-Sectional Survey. — da Costa J, Nosoongnoen W, Rungapiromnan W, Tragulpiankit P Clinical and translational science (2025)
    90. [90]
      Signals of Adverse Reactions to Herbal Medicines: Evidence and Document Analysis Based on a Scoping Review. — Sartori D, Aronson JK, Brand JS, Gauffin O, Hedfors Vidlin S, Norén GN et al. Drug safety (2025)
    91. [91]
      Clinical Relatedness and Stability of vigiVec Semantic Vector Representations of Adverse Events and Drugs in Pharmacovigilance. — Erlanson N, China JF, Taavola H, Norén GN Drug safety (2025)
    92. [92]
      Pharmacogenetics and adverse drug reports: Insights from a United Kingdom national pharmacovigilance database. — Magavern EF, Megase M, Thompson J, Marengo G, Jacobsen J, Smedley D et al. PLoS medicine (2025)
    93. [93]
      Developing and validating a Global Trigger Tool for assessing frequency, level of harm, and preventability of adverse drug events in pediatric inpatients units. — Gutkind A, Toren A, Somech R, Bezalel Y, Loebstein R, Edden Y et al. International journal for quality in health care : journal of the International Society for Quality in Health Care (2025)
    94. [94]
      Role and Responsibilities of Various Stakeholders in Pharmacovigilance. — Phougat P, Beniwal M, Kapoor G, Aggarwal N, Kumari A, Sharma R et al. Current drug safety (2025)
    95. [95]
      Adverse drug effect in the context of drug shortage: the CIRUPT prospective study from the French pharmacovigilance network. — Bourneau-Martin D, Grandvuillemin A, Babin M, Mullet C, Said H, Cellier M et al. European journal of hospital pharmacy : science and practice (2025)
    96. [96]
      The Role of Adverse Event Follow-Up in Advancing the Knowledge of Medicines and Vaccines Safety: A Scoping Review. — Kara V, Van Hunsel F, Bate A, van Puijenbroek E Drug safety (2025)
    97. [97]
      Co-Designing a Consumer-Focused Digital Reporting Health Platform to Improve Adverse Medicine Event Reporting: Protocol for a Multimethod Research Project (the ReMedi Project). — Gebreyohannes EA, Thornton C, Thiessen M, de Vries ST, Q Andrade A, Kalisch Ellett L et al. JMIR research protocols (2025)
    98. [98]
      A prospective study of acute propranolol overdose defining dose thresholds of severe toxicity (ATOM - 9). — Isoardi KZ, Chiew AL, Do C, Humphreys M, Mustafa A, Roberts MS et al. Clinical toxicology (Philadelphia, Pa.) (2025)
    99. [99]
      Dealing with adverse drug reactions in the context of polypharmacy using regression models. — Sommer J, Viviani R, Wozniak J, Stingl JC, Just KS Scientific reports (2024)
    100. [100]
      Machine Learning upon RDF Knowledge Graphs for Drug Safety: A Case Study on Reactome Data. — Kastampolidou K, Gavriilidis GI, Natsiavas P Studies in health technology and informatics (2024)
    Share:TwitterRedditLinkedIn

    HemoChat

    by SPINAI

    Evidence-based clinical decision support powered by SNOMED-CT, Neo4j GraphRAG, and NASS/AO/NICE guidelines.

    ⚕ For clinical reference only. Not a substitute for professional judgment.

    © 2026 HemoChat. All rights reserved.
    Research·Pricing·Privacy & Terms·Refund·SNOMED-CT · NASS · AO Spine · NICE · GraphRAG