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RESEARCH / LITERATURE

Research Literature

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Clinical Pharmacology & Model-Informed Development 4

Duplicate DOIs are merged. This is a selected collection, not an exhaustive bibliography.

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Original research
European Journal of Drug Metabolism and Pharmacokinetics

Progesterone PopPK study combines machine-learning screening with conventional covariate modeling

Lu Wang; Jie Tang; Sufeng Zhou; Tangping Zhao; Ying Ding; Weiwei Gao; Xiaoyan Zhu; Feng Shao

A study in European Journal of Drug Metabolism and Pharmacokinetics modeled subcutaneous aqueous progesterone using single-dose crossover data from 50 healthy Chinese postmenopausal women. Machine-learning approaches screened potential covariates before conventional PopPK evaluation. Height and body-weight effects remained statistically identifiable but had limited clinical significance. Simulated repeated-dose exposure is model-derived, rather than an observed efficacy outcome in fertility patients.

Clinical Pharmacology & Model-Informed Development
Read guide →Original paper ↗

DOI: 10.1007/s13318-026-01048-4

Reviews & perspectives
Clinical Pharmacology & Therapeutics

Review identifies higher patient exposure for some drugs in chronic inflammation

Johannes Tillil; Sathej Gopalakrishnan; Jennifer Dong; Karthik Venkatakrishnan; Charlotte Kloft; Wilhelm Huisinga; Lena Klopp-Schulze

Based on the article abstract, a review of 20 approved small-molecule medicines for selected chronic inflammatory diseases found more than 25% higher exposure in patients for five medicines, using reported population pharmacokinetic analyses. The authors highlight CYP3A4 and CYP2C19 metabolism. This cross-drug review supports risk assessment, not automatic dose changes for individual patients.

Clinical Pharmacology & Model-Informed Development
Read guide →Original paper ↗

DOI: 10.1002/cpt.70535

Reviews & perspectives
The Journal of Clinical Pharmacology

Model-Informed Decision Making from Drug Discovery to Reimbursement: A Roadmap for Clinical Pharmacology in Value-Based Healthcare

Rajesh Krishna; Ananth Kadambi; Patrick Smith; Piet H van der Graaf; Fran Brown

This commentary proposes a lifecycle approach to model-informed decision-making, from discovery and dose selection to regulatory evaluation and reimbursement. It discusses quantitative methods, patient-relevant outcomes, and real-world data, alongside challenges in integration, transparency, and stakeholder acceptance. It is a conceptual roadmap, not a prospective validation of one modeling strategy.

Clinical Pharmacology & Model-Informed Development
Read guide →Original paper ↗

DOI: 10.1002/jcph.70270

Reviews & perspectives
Clinical Pharmacology & Therapeutics

From Classical PKPD to Model-Informed Drug Development: Are “Digital Twins” a New Paradigm?

Brett E Houk

This perspective examines digital-twin claims against established pharmacometric practice. It argues that individual simulation, sequential updating, and decision-focused uncertainty analysis have longstanding roots in PK/PD modeling. The author emphasizes that fundamental limits, including identifiability, remain relevant despite new terminology.

Clinical Pharmacology & Model-Informed Development
Read guide →Original paper ↗

DOI: 10.1002/cpt.70340

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