Mechanistic Artificial Intelligence for Personalized Drug Therapy: Integrating Pharmacokinetics, Pharmacodynamics, Therapeutic Drug Monitoring, and Multiomic Systems Biology

Abstract

Interindividual variability in drug response remains a major challenge in clinical pharmacology despite substantial advances in therapeutic drug monitoring (TDM), pharmacogenomics, pharmacokinetics/pharmacodynamics (PK/PD), and model-informed precision dosing (MIPD). Although these approaches have improved individualized therapy, clinically important variability in efficacy and toxicity persists because drug response is determined not only by systemic exposure but also by target engagement, disease biology, compensatory pathways, organ function, immune status, and dynamic patient-specific molecular states. Recent advances in multiomics, systems pharmacology, and artificial intelligence (AI) provide an opportunity to integrate these complementary biological and clinical dimensions within more comprehensive precision pharmacotherapy frameworks. This narrative review examines the evolving integration of PK, PD, TDM, pharmacometrics, multiomic technologies, mechanistic AI, and systems pharmacology across drug development and clinical care. Particular emphasis is placed on the limitations of exposure-based dosing alone, the biological determinants of interindividual variability, the transition from conventional TDM toward adaptive model-informed monitoring, and emerging approaches for integrating molecular and clinical data to support individualized therapeutic decision-making. Operon™ is discussed as an illustrative example of an internally operated mechanistic systems biology platform to demonstrate how biologically informed computational frameworks may integrate pharmacological and multiomic information within drug development workflows. The review further examines applications in polypharmacy, drug–drug interaction assessment, clinical trial enrichment, regulatory science, and adaptive dosing, while emphasizing that analytical validity, clinical validity, clinical utility, prospective validation, transparency, and clearly defined contexts of use remain essential prerequisites for clinical implementation. Collectively, these developments support a transition from concentration-guided dosing toward mechanism-informed precision pharmacotherapy that integrates drug exposure with biological response and clinical outcomes while maintaining rigorous standards for validation and regulatory acceptance.