Advanced Drug Delivery for Special Patient Populations: From Physiological Barriers to Model-Informed Clinical Translation

Special patient populations - including neonates and infants, children, pregnant and lactating women, older adults, and patients with organ impairment, critical illness, obesity, or advanced malignancy - exhibit physiological characteristics that can substantially alter drug absorption, distribution, metabolism, and elimination. These differences arise across multiple levels, including organ barriers such as the blood-brain barrier, placenta, gastrointestinal tract, lung, and skin; tissue compartments such as the tumour interstitium, cerebrospinal fluid, and lymphatics; and molecular targets involving transporter and enzyme ontogeny, receptor expression, FcRn-mediated recycling, and target-mediated disposition. Conventional dosing strategies therefore frequently fail to achieve appropriate exposure and therapeutic response in these populations. Although novel drug delivery systems (NDDS), including nanoparticles, liposomes, microneedles, and other advanced formulations, continue to develop rapidly, their translation has largely focused on general adult populations. Recent advances in population pharmacokinetic/pharmacodynamic (PK/PD) modelling, physiologically based pharmacokinetic (PBPK) modelling, in vitro–in vivo correlation (IVIVC), in vitro-in vivo extrapolation (IVIVE), and microphysiological systems offer opportunities to address this limitation. However, validated and clinically relevant models for vulnerable populations remain limited, particularly where data are sparse and barrier penetration, disease-related physiology, and developmental changes interact. Further investigation is needed to establish reliable links between formulation performance, barrier transport, systemic and tissue exposure, and clinical outcomes.This Research Topic aims to advance the development and clinical translation of drug delivery systems tailored to special patient populations. We seek studies that build explicit bridges between in vitro performance and clinical exposure through biopredictive dissolution, IVIVC/IVIVE, microphysiological systems, and relevant barrier models; between preclinical in vivo findings and clinical outcomes through improved scaling of barrier penetration and careful evaluation of the limitations of conventional allometric approaches; and between healthy adult data and vulnerable populations through PBPK, population PK/PD, exposure-matching strategies, and virtual populations. We also welcome work that moves in the reverse direction, using clinical, pharmacometric, or biomarker data from special populations to guide the design and optimization of delivery systems. Particular emphasis will be placed on model qualification, uncertainty quantification, sensitivity analysis, and prospective verification as essential components of translational research rather than as secondary considerations. Multidisciplinary contributions integrating formulation science, experimental pharmacology, clinical research, and quantitative pharmacology are especially encouraged.To gather further insights into model-informed and individualized drug delivery across physiological, tissue, and target-level barriers in neonatal, pediatric, geriatric, pregnant, critically ill, obese, and organ-impaired populations, we welcome articles addressing, but not limited to, the following themes:&#8226 Novel drug delivery systems and formulations designed for special patient populations&#8226 Drug transport across the blood–brain barrier, placenta, gastrointestinal tract, lung, skin, and other physiological barriers&#8226 Delivery to tumour interstitium, cerebrospinal fluid compartments, lymphatics, and other clinically relevant tissue sites&#8226 PBPK and PK/PD models incorporating age-, disease-, pregnancy-, organ-function-, or critical-illness-specific physiological parameters&#8226 Population PK, exposure matching, virtual populations, and individualized dosing strategies&#8226 IVIVC and IVIVE frameworks linking in vitro formulation performance with clinical exposure and response&#8226 Microphysiological, organ-on-chip, barrier, and other predictive preclinical models&#8226 Biologics, antibody-drug conjugates, and other large molecules for which tissue distribution or target access limits efficacy&#8226 Transporter and enzyme ontogeny, receptor expression, FcRn-mediated recycling, and target-mediated drug disposition&#8226 Machine learning, artificial intelligence, and hybrid mechanistic-machine-learning approaches using clinical or real-world data to support individualized dosing&#8226 Model qualification, uncertainty quantification, sensitivity analysis, prospective validation, and independent verification&#8226 Experimental and clinical biomarkers that inform delivery-system design, barrier penetration, or therapeutic responseModelling studies based primarily on publicly available data are also welcome when the models are appropriately qualified and validated against independent experimental or clinical observations. Topic editors: Xiaoyu Yan, Guohua An Source: https://www.frontiersin.org/research-topics/84876/advanced-drug-delivery-for-special-patient-populations-from-physiological-barriers-to-model-informed-clinical-translation