Narrow Therapeutic Index Drugs: Regulatory Frameworks, Bioequivalence, and Model-Informed Precision Dosing
Background/Objectives: Narrow therapeutic index (NTI) drugs are characterized by a small margin between effective and toxic exposure. This review aimed to summarize international definitions and regulatory frameworks for NTI drugs, compare bioequivalence requirements for generic NTI products, and evaluate the role of model-informed approaches in precision dosing and lifecycle risk management. Methods: A structured literature search was conducted in PubMed, MEDLINE, Embase, Web of Science, Scopus, and the China National Knowledge Infrastructure from database inception to 30 June 2026. Official documents from major regulatory authorities were also reviewed. Evidence relating to NTI drug classification, bioequivalence, interchangeability, therapeutic drug monitoring, population pharmacokinetics, physiologically based pharmacokinetics, machine learning, and hybrid modeling was included. Results: Definitions, drug lists, study designs, and bioequivalence criteria varied substantially across jurisdictions. Several authorities use narrowed acceptance ranges, whereas China and the United States apply fully replicated crossover designs with reference-scaled average bioequivalence, average bioequivalence constraints, and within-subject variability comparisons for selected NTI drugs. Population pharmacokinetic and Bayesian approaches remain the most mature tools for therapeutic drug monitoring and individualized dosing. Physiologically based models support drug–drug interaction prediction, special-population extrapolation, virtual bioequivalence, and clinically relevant formulation specifications. Machine-learning and hybrid models improve exposure, dose, and toxicity-risk prediction, but most evidence remains retrospective and externally limited. Conclusions: NTI drug regulation and clinical management remain heterogeneous. Greater international harmonization, standardized model validation, prospective clinical evaluation, and integration of regulatory, formulation, and patient-level data are needed to support safer substitution and more reliable precision dosing.
Authors
- Libo Zhao (ORCID: https://orcid.org/0000-0002-4968-6045)
- Jueyu Li
- Yuqi Jia (ORCID: https://orcid.org/0000-0003-2869-975X)
- Zhe Wang (ORCID: https://orcid.org/0000-0002-9129-4125)
- Lei Xu (ORCID: https://orcid.org/0000-0001-7582-941X)
- Yongbo Chen
- Mengmeng Liu (ORCID: https://orcid.org/0000-0002-9872-4212)
- Haojie Xu (ORCID: https://orcid.org/0009-0007-3275-261X)
Institutions
- Peking University (CN)
- Peking University Third Hospital (CN)
Publication Details
- Journal
- Pharmaceutics
- Published
- 2026-09-20
- DOI
- https://doi.org/10.3390/pharmaceutics18091190
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 0.00