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Machine learning in pharmacometrics: Opportunities and challenges
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Computational design of clinical trials using a combination of simulation and the genetic algorithm
inferred← citeshttps://doi.org/10.1002/psp4.13079openalex-snapshot
Realizing the promise of Project Optimus: Challenges and emerging opportunities for dose optimization in oncology drug development
inferred← citeshttps://doi.org/10.1002/psp4.13124openalex-snapshot
Deep‐NCA: A deep learning methodology for performing noncompartmental analysis of pharmacokinetic data
inferred← citeshttps://doi.org/10.1002/psp4.13182openalex-snapshot
Simulating realistic patient profiles from pharmacokinetic models by a machine learning postprocessing correction of residual variability
inferred← citeshttps://doi.org/10.1002/psp4.13313openalex-snapshot
Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations
inferred← citeshttps://doi.org/10.1002/psp4.70012openalex-snapshot
Precision Dosing in Presence of Multiobjective Therapies by Integrating Reinforcement Learning and PK ‐ PD Models: Application to Givinostat Treatment of Polycythemia Vera
inferred← citeshttps://doi.org/10.1002/psp4.70084openalex-snapshot
Machine Learning‐Based Model Selection and Averaging Outperform Single‐Model Approaches for a Priori Vancomycin Precision Dosing
inferred← citeshttps://doi.org/10.1002/psp4.70146openalex-snapshot
Neural Controlled Differential Equation and Its Application in Pharmacokinetics and Pharmacodynamics
inferred← citeshttps://doi.org/10.1002/psp4.70214openalex-snapshot
Learning Covariate Relations in Disease Progression Models Using Symbolic Neural Networks
inferred← citeshttps://doi.org/10.1007/164_2025_752openalex-snapshot
Role of Data in Development and Application of Quantitative Systems Pharmacology Models
inferred← citeshttps://doi.org/10.1007/s00228-024-03780-9openalex-snapshot
Leveraging machine learning in limited sampling strategies for efficient estimation of the area under the curve in pharmacokinetic analysis: a review
inferred← citeshttps://doi.org/10.1007/s10928-021-09786-5openalex-snapshot
Machine learning-guided, big data-enabled, biomarker-based systems pharmacology: modeling the stochasticity of natural history and disease progression
inferred← citeshttps://doi.org/10.1007/s10928-022-09820-0openalex-snapshot
Towards a comprehensive assessment of QSP models: what would it take?
inferred← citeshttps://doi.org/10.1007/s10928-022-09838-4openalex-snapshot
Generative models for age, race/ethnicity, and disease state dependence of physiological determinants of drug dosing
inferred← citeshttps://doi.org/10.1007/s10928-023-09875-7openalex-snapshot
Go beyond the limits of genetic algorithm in daily covariate selection practice
inferred← citeshttps://doi.org/10.1007/s10928-023-09886-4openalex-snapshot
Low-dimensional neural ODEs and their application in pharmacokinetics
inferred← citeshttps://doi.org/10.1007/s10928-023-09887-3openalex-snapshot
Learning pharmacometric covariate model structures with symbolic regression networks
inferred← citeshttps://doi.org/10.1007/s10928-024-09931-wopenalex-snapshot
Mixed effect estimation in deep compartment models: Variational methods outperform first-order approximations
inferred← citeshttps://doi.org/10.1007/s10928-025-10005-8openalex-snapshot
Scoping review of the role of pharmacometrics in model-informed drug development
inferred← citeshttps://doi.org/10.1007/s10928-026-10031-0openalex-snapshot
A structure-preserving hybrid learning framework for compartmental pharmacokinetic models
inferred← citeshttps://doi.org/10.1007/s11095-026-04206-0openalex-snapshot
Comparative Predictive Performance of Machine Learning and Population Pharmacokinetic Models for Valproic Acid Clearance and Trough Concentrations: An In-silico Simulation Study in Epilepsy Scenarios
inferred← citeshttps://doi.org/10.1007/s12247-026-10946-8openalex-snapshot
From Detection to Prediction: AI-driven Process Analytical Technology for Nitrosamine and NDSRI Control in Pharmaceuticals
inferred← citeshttps://doi.org/10.1007/s40005-026-00805-6openalex-snapshot
Evolution of human pharmacokinetics prediction methods: from allometry to artificial intelligence
inferred← citeshttps://doi.org/10.1007/s40262-023-01265-zopenalex-snapshot
Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates
inferred← citeshttps://doi.org/10.1007/s40272-024-00633-xopenalex-snapshot
Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians
inferred← citeshttps://doi.org/10.1007/s41111-024-00265-zopenalex-snapshot
Predicting Successful Treatment Completion Using Baseline Case Characteristics through Machine Learning and Ensemble Modeling: A Two-Step Approach
inferred← citeshttps://doi.org/10.1016/b978-0-323-91819-0.00004-xopenalex-snapshot
Pharmacometrics and machine learning in drug development
inferred← citeshttps://doi.org/10.1016/j.addr.2024.115503openalex-snapshot
Applications of pharmacometrics in drug development
inferred← citeshttps://doi.org/10.1016/j.apsb.2026.05.028openalex-snapshot
AI and machine learning for predicting in vitro/preclinical drug toxicities and adverse events in clinical patients
inferred← citeshttps://doi.org/10.1016/j.bnd.2025.04.001openalex-snapshot
Machine learning in early diagnosis of neurological diseases: Advancing accuracy and overcoming challenges
inferred← citeshttps://doi.org/10.1016/j.brainresbull.2025.111667openalex-snapshot
Machine learning and deep learning in clinical practice: Advancing neurodegenerative disease diagnosis with multimodal markers
inferred← citeshttps://doi.org/10.1016/j.dmpk.2024.100996openalex-snapshot
Applications of model simulation in pharmacological fields and the problems of theoretical reliability
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.121796openalex-snapshot
IDoser: Improving individualized dosing policies with clinical practice and machine learning
inferred← citeshttps://doi.org/10.1016/j.fct.2023.113920openalex-snapshot
Development of machine learning algorithms to estimate maximum residue limits for veterinary medicines
inferred← citeshttps://doi.org/10.1016/j.ijantimicag.2022.106620openalex-snapshot
Pharmacometrics in tuberculosis: progress and opportunities
inferred← citeshttps://doi.org/10.1016/j.ijantimicag.2025.107632openalex-snapshot
Machine learning in antimicrobial therapy for critically ill patients: optimizing early empirical regimens, individualized dosing, and de-escalation strategies
inferred← citeshttps://doi.org/10.1016/j.ijpharm.2025.126266openalex-snapshot
Artificial intelligence in the non-clinical laboratory: enhancing good laboratory and documentation practices
inferred← citeshttps://doi.org/10.1016/j.jhip.2026.02.007openalex-snapshot
Machine learning models for predicting pharmacokinetics and pharmacodynamics: A step toward personalized dosing
inferred← citeshttps://doi.org/10.1016/j.jpha.2026.101701openalex-snapshot
Pharmacometrics-driven dose individualization of modified-release formulations: integration of PopPK, PBPK, and PK/PD modeling
inferred← citeshttps://doi.org/10.1016/j.matpr.2021.12.101openalex-snapshot
Machine learning applications in healthcare sector: An overview
inferred← citeshttps://doi.org/10.1016/j.nexres.2026.102569openalex-snapshot
Artificial Intelligence as a Disruptive Tool in Interdisciplinary Research: Current Trends and Emerging Applications
inferred← citeshttps://doi.org/10.1016/j.phymed.2024.155479openalex-snapshot
Warfarin–A natural anticoagulant: A review of research trends for precision medication
inferred← citeshttps://doi.org/10.1016/j.procs.2023.01.405openalex-snapshot
A Big Data Approach to Explore Medical Imaging Repositories Based on DICOM
inferred← citeshttps://doi.org/10.1021/acs.jafc.5c05624openalex-snapshot
KadsuraChem: A Machine Learning-Powered LC–MS Database for Kadsura Phytochemicals and Its Role in Compound Identification of Kadsura heteroclita
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00026openalex-snapshot
AI-Based Protein Structure Prediction in Drug Discovery: Impacts and Challenges
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.3c00162openalex-snapshot
Knowledge Gaps in Generating Cell-Based Drug Delivery Systems and a Possible Meeting with Artificial Intelligence
inferred← citeshttps://doi.org/10.1039/9781837070206-00430openalex-snapshot
Machine Learning in the Optimization of Pharmacokinetic Parameters
inferred← citeshttps://doi.org/10.1080/10543406.2024.2365389openalex-snapshot
Clustering plasma concentration-time curves: applications ofunsupervised learning in pharmacogenomics
inferred← citeshttps://doi.org/10.1080/17460441.2022.1985108openalex-snapshot
Success stories of AI in drug discovery - where do things stand?
inferred← citeshttps://doi.org/10.1080/17576180.2024.2437283openalex-snapshot
Transforming drug discovery: the impact of AI and molecular simulation on R&D efficiency
inferred← citeshttps://doi.org/10.1089/omi.2022.0097openalex-snapshot
Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean
inferred← citeshttps://doi.org/10.1097/ftd.0000000000001078openalex-snapshot
Artificial Intelligence and Machine Learning Approaches to Facilitate Therapeutic Drug Management and Model-Informed Precision Dosing
inferred← citeshttps://doi.org/10.1109/iicai70155.2026.11620912openalex-snapshot
Predicting Plasma Protein Binding (Fraction Unbound) with Machine Learning Using Molecular Descriptors
inferred← citeshttps://doi.org/10.1109/tcbb.2024.3492708openalex-snapshot
AI-Based Computational Methods in Early Drug Discovery and Post Market Drug Assessment: A Survey
inferred← citeshttps://doi.org/10.1111/bcp.15289openalex-snapshot
Perspectives on the past, present, and future of pharmacometrics
inferred← citeshttps://doi.org/10.1111/bcp.15469openalex-snapshot
Use of medication data alone to identify diagnoses and related contraindications: Application of algorithms to close a common documentation gap
inferred← citeshttps://doi.org/10.1111/bcp.15623openalex-snapshot
Generative adversarial networks for modelling clinical biomarker profiles with race/ethnicity
inferred← citeshttps://doi.org/10.1111/bcp.15927openalex-snapshot
From statistical inference to machine learning: A paradigm shift in contemporary cardiovascular pharmacotherapy
inferred← citeshttps://doi.org/10.1111/bcp.16335openalex-snapshot
Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice
inferred← citeshttps://doi.org/10.1111/cts.70272openalex-snapshot
Leveraging In Silico and Artificial Intelligence Models to Advance Drug Disposition and Response Predictions Across the Lifespan
inferred← citeshttps://doi.org/10.1111/cts.70293openalex-snapshot
Predicting Vancomycin Clearance in Neonates and Infants by Integrating Machine Learning and Metabolomics With Population Pharmacokinetics
inferred← citeshttps://doi.org/10.1111/cts.70691openalex-snapshot
Deep‐Learning: An Emerging Tool to Support Model‐Informed Drug Development
inferred← citeshttps://doi.org/10.1124/jpet.122.001551openalex-snapshot
Quantitative Systems Pharmacology and Machine Learning: A Match Made in Heaven or Hell?
inferred← citeshttps://doi.org/10.1124/pharmrev.122.000715openalex-snapshot
Review of Natural Language Processing in Pharmacology
inferred← citeshttps://doi.org/10.1145/3686990openalex-snapshot
"Math is a pain!": Understanding challenges and needs of the Machine Learning community on Stack Overflow
inferred← citeshttps://doi.org/10.1186/s40779-023-00446-yopenalex-snapshot
Applications and prospects of cryo-EM in drug discovery
inferred← citeshttps://doi.org/10.1208/s12248-024-00934-6openalex-snapshot
Machine-Learning Assisted Screening of Correlated Covariates: Application to Clinical Data of Desipramine
inferred← citeshttps://doi.org/10.1208/s12248-025-01075-0openalex-snapshot
Evaluating the Impact of AI-Based Model-Informed Drug Development (MIDD): A Comparative Review
inferred← citeshttps://doi.org/10.1208/s12249-024-02901-yopenalex-snapshot
The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review
inferred← citeshttps://doi.org/10.12688/f1000research.129064.1openalex-snapshot
Progress and challenges for the application of machine learning for neglected tropical diseases
inferred← citeshttps://doi.org/10.12688/f1000research.129064.2openalex-snapshot
Progress and challenges for the application of machine learning for neglected tropical diseases
inferred← citeshttps://doi.org/10.12688/f1000research.129064.3openalex-snapshot
Progress and challenges for the application of machine learning for neglected tropical diseases
inferred← citeshttps://doi.org/10.12793/tcp.2026.34.e4openalex-snapshot
Pioneering pharmacometrics practice in Korea: an eight-year retrospective analysis of 192 projects from the first dedicated service organization (2016–2024)
inferred← citeshttps://doi.org/10.12923/cipms-2025-0020openalex-snapshot
Harnessing machine learning for predictive pharmacokinetics:revolutionizing drug development and personalized medicine
inferred← citeshttps://doi.org/10.2147/ijgm.s595659openalex-snapshot
Exploring Influencing Factors Including CYP2C19 Genotypes, and Developing a Machine Learning-Based Predictive Model for Clopidogrel Resistance in Chinese Patients with Ischemic Stroke
inferred← citeshttps://doi.org/10.2174/2666782701666220920091940openalex-snapshot
Perspectives of Artificial Intelligence (AI) in Health Care Management: Prospect and Protest
inferred← citeshttps://doi.org/10.2217/epi-2023-0177openalex-snapshot
The Relevance of Epigenetics and Epigenomics to Pharmacometrics
inferred← citeshttps://doi.org/10.22541/au.165332169.99486848/v1openalex-snapshot
Generative Adversarial Networks for Modeling Clinical Biomarker Profiles in Under-Represented Groups
inferred← citeshttps://doi.org/10.25163/angiotherapy.819488openalex-snapshot
Advances of AI-driven Drug Design and Discovery in Pharmaceuticals - Review
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-mqzjbopenalex-snapshot
Machine Learning Modeling and Insights into the Structural Foundations of Polymyxin-like Antimicrobials
inferred← citeshttps://doi.org/10.33093/ijomfa.2024.5.1.2openalex-snapshot
Enhancing Conversions and Lead Scoring in Online Professional Education
inferred← citeshttps://doi.org/10.3389/978-2-8325-4503-4openalex-snapshot
Innovative Pharmacometric Approaches to Inform Drug Development and Clinical Use
inferred← citeshttps://doi.org/10.3389/ebm.2026.10988openalex-snapshot
Training the next-generation of biomedical scientists through artificial intelligence-driven education and research in pharmacology and pharmaceutical sciences
inferred← citeshttps://doi.org/10.3389/fphar.2021.749692openalex-snapshot
Pediatric Therapeutic Drug Monitoring for Selective Serotonin Reuptake Inhibitors
inferred← citeshttps://doi.org/10.3389/fphar.2022.1016399openalex-snapshot
Applying machine learning to the pharmacokinetic modeling of cyclosporine in adult renal transplant recipients: a multi-method comparison
inferred← citeshttps://doi.org/10.3389/fphar.2022.975855openalex-snapshot
An interpretable stacking ensemble learning framework based on multi-dimensional data for real-time prediction of drug concentration: The example of olanzapine
inferred← citeshttps://doi.org/10.3389/fphar.2022.994665openalex-snapshot
Machine learning advances the integration of covariates in population pharmacokinetic models: Valproic acid as an example
inferred← citeshttps://doi.org/10.3389/fphar.2026.1963219openalex-snapshot
From time-series deep learning to physics-constrained population pharmacokinetics: AI-driven prediction of drug concentrations and exposure for model-informed dosing
inferred← citeshttps://doi.org/10.3389/fsysb.2022.1044281openalex-snapshot
Teaching computational systems biology with an eye on quantitative systems pharmacology at the undergraduate level: Why do it, who would take it, and what should we teach?
inferred← citeshttps://doi.org/10.3389/fsysb.2024.1380685openalex-snapshot
Coupling quantitative systems pharmacology modelling to machine learning and artificial intelligence for drug development: its pAIns and gAIns
inferred← citeshttps://doi.org/10.3390/antibiotics13121203openalex-snapshot
Artificial Intelligence and Machine Learning Applications to Pharmacokinetic Modeling and Dose Prediction of Antibiotics: A Scoping Review
inferred← citeshttps://doi.org/10.3390/biomedinformatics3040057openalex-snapshot
Machine Learning Models for Predicting Personalized Tacrolimus Stable Dosages in Pediatric Renal Transplant Patients
inferred← citeshttps://doi.org/10.3390/ddc4010009openalex-snapshot
A Review on Revolutionizing Healthcare Technologies with AI and ML Applications in Pharmaceutical Sciences
inferred← citeshttps://doi.org/10.3390/diagnostics15151914openalex-snapshot
Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications
inferred← citeshttps://doi.org/10.3390/oxygen4040026openalex-snapshot
Noble Gases in Medicine: Current Status and Future Prospects
inferred← citeshttps://doi.org/10.3390/ph17070925openalex-snapshot
Biosimilars in the Era of Artificial Intelligence—International Regulations and the Use in Oncological Treatments
inferred← citeshttps://doi.org/10.3390/pharmaceutics13060797openalex-snapshot
Application of Deep Neural Networks as a Prescreening Tool to Assign Individualized Absorption Models in Pharmacokinetic Analysis
inferred← citeshttps://doi.org/10.3390/pharmaceutics14081530openalex-snapshot
Machine Learning and Pharmacometrics for Prediction of Pharmacokinetic Data: Differences, Similarities and Challenges Illustrated with Rifampicin
inferred← citeshttps://doi.org/10.3390/pharmaceutics14091814openalex-snapshot
Adoption of Machine Learning in Pharmacometrics: An Overview of Recent Implementations and Their Considerations
inferred← citeshttps://doi.org/10.3390/pharmaceutics15041139openalex-snapshot
Deep Learning Methods Applied to Drug Concentration Prediction of Olanzapine
inferred← citeshttps://doi.org/10.3390/pharmaceutics15051381openalex-snapshot
Machine Learning for Exposure-Response Analysis: Methodological Considerations and Confirmation of Their Importance via Computational Experimentations
inferred← citeshttps://doi.org/10.3390/pharmaceutics16030332openalex-snapshot
Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare
inferred← citeshttps://doi.org/10.3390/pharmaceutics16121559openalex-snapshot
The Role of Pharmacometrics in Advancing the Therapies for Autoimmune Diseases
inferred← citeshttps://doi.org/10.3390/pharmaceutics17030290openalex-snapshot
Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy
inferred← citeshttps://doi.org/10.3390/pharmaceutics17101274openalex-snapshot
Pharmacometrics in the Age of Large Language Models: A Vision of the Future
inferred← citeshttps://doi.org/10.3390/pharmaceutics18070824openalex-snapshot
Beyond Body Weight: A Comprehensive Review of Allometric Scaling in Drug Development for Human Dose Predictions
inferred← citeshttps://doi.org/10.51847/1ae49rlxigopenalex-snapshot
Mechanistic Accountability in Hybrid Physiologically Based Pharmacokinetic and Machine-Learning Models for Drug Development
inferred← citeshttps://doi.org/10.51847/maxwwv33ysopenalex-snapshot
What Machine Learning Adds to Pharmacometrics—and What Mechanistic Information It Risks Removing
inferred← citeshttps://doi.org/10.51847/ppht0m5a9hopenalex-snapshot
Artificial Intelligence in Clinical Pharmacokinetics and Pharmacodynamics: A Realist Review of Contexts, Mechanisms, Outcomes, and Failure Modes
inferred← citeshttps://doi.org/10.51847/qdjn456xbwopenalex-snapshot
What Makes an Artificial Intelligence Explanation Pharmacologically Useful beyond Attractive Heatmaps and Feature-Importance Rankings?
inferred← citeshttps://doi.org/10.51847/x9byggpsgqopenalex-snapshot
Interpretable Models for Pharmacokinetic Interaction Magnitude Using Enzyme, Transporter, and Dose Features
inferred← citeshttps://doi.org/10.52783/jes.3086openalex-snapshot
Optimization of English Classroom Interaction Models Incorporating Machine Learning
inferred← citeshttps://doi.org/10.61466/ijcmr3060002openalex-snapshot
Transforming healthcare technologies through the application of artificial intelligence and machine learning in pharmaceutical sciences
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