Intravenous (IV) infusion remains the predominant delivery route for oncology monoclonal antibodies, but it requires prolonged chair time and substantial infusion-unit resources. Hyaluronidase-facilitated subcutaneous (SC) formulations aim to shorten administration (minutes vs hours), improve convenience, and potentially expand outpatient or home-based delivery, while preserving exposure, efficacy, and safety. We conducted a narrative review of published clinical studies, major congress presentations, trial registries, and Food and Drug Administration (FDA)/European Medicines Agency (EMA) regulatory documents describing development of hyaluronidase-facilitated SC formulations for seven oncology antibodies (trastuzumab, rituximab, daratumumab, atezolizumab, nivolumab, pembrolizumab, and amivantamab). We extracted evidence on formulation strategy, pharmacokinetic (PK) bridging, efficacy comparability, safety/immunogenicity, and regulatory pathways supporting IV→SC approval. Across programs, PH20-based recombinant hyaluronidases, including human hyaluronidase PH20 (rHuPH20) and berahyaluronidase alfa, transiently depolymerize SC hyaluronan, enabling delivery of multi-milliliter injections and high fixed doses. Development strategies converged on PK-anchored bridging, typically targeting non-inferior SC/IV geometric-mean ratios for both initiation and maintenance exposure (e.g., cycle-1 area under the curve [AUC]/average plasma concentration [Cavg] and minimum plasma concentration [Cmin]/trough concentration [Ctrough]), supported by population PK to ensure covariate coverage. We highlight a pragmatic evolution in trial design: earlier conversions often paired PK with direct clinical activity confirmation in sensitive settings, whereas more recent programs increasingly use prespecified PK non-inferiority as the confirmatory backbone with efficacy as supportive reassurance-enabling use of an approved SC formulation across multiple indications. In pivotal bridging trials, SC regimens generally met or exceeded exposure targets and demonstrated efficacy consistent with IV comparators (treatment effects clustering around unity; Δ ≈ 0; hazard ratio/relative risk ≈ 1). Safety profiles were broadly similar; SC administration was associated with fewer administration-related reactions for several agents, while injection-site reactions were usually mild. Immunogenicity, including anti-hyaluronidase antibodies, did not show consistent clinically meaningful effects on PK or outcomes. Hyaluronidase-facilitated IV→SC conversion has become a reproducible, model-informed, PK-driven development paradigm. By synthesizing study-design choices, formulation pathways, and extrapolation logic across seven approved antibodies-including the recent IO and targeted-therapy wave-this review builds upon a previously described clinical bridging concept and provides a comprehensive updated overview including the most recently approved products, with a practical framework to guide future IV→SC transitions in oncology.

Physiologically based pharmacokinetic models are a valuable tool for simulating antidepressant pharmacokinetics in patient groups that are often underrepresented in clinical trials. Clinical data on antidepressant use in vulnerable populations such as geriatric patients or pregnant women remain limited, making safe and personalized treatment challenging. The objective of this review was to systematically evaluate existing physiologically based pharmacokinetic models for antidepressants, their applications, and the modeling software platforms used, in order to identify relevant research gaps and highlight future needs for model development. A scoping review was conducted in accordance with Preferred Reporting Items for Scoping Reviews (PRISMA-ScR) guidelines. Seven electronic databases were systematically searched. Data on the modeled drug, model applications, and software platforms were extracted and evaluated. A total of 60 studies met the inclusion criteria. The availability of physiologically based pharmacokinetic models across antidepressants was heterogeneous. Paroxetine, fluvoxamine, and venlafaxine were most frequently modeled (n = 10 each), whereas few or no models exist for substances such as mirtazapine (n = 1) or milnacipran (n = 0). The main application areas were drug-drug interactions (n = 18), pregnancy (n = 14), and drug-(drug-)gene interactions (n = 13). Pediatric populations and specific ethnic groups were rarely addressed. SimCyp® Simulator was the most used modeling platform, followed by PK-Sim®/Mobi®, GastroPlus®, and R®/RStudio®. Although physiologically based pharmacokinetic models for antidepressants are increasingly available, they focus on a limited number of drugs and applications. Substantial evidence gaps remain, particularly for vulnerable patient populations.

Dolutegravir-based regimens are part of the preferred regimens in all populations living with HIV, but dolutegravir's pharmacokinetics can vary greatly with factors such as drug-drug interactions (DDIs) and age. For example, DDIs between dolutegravir and rifamycins in countries with a high burden of HIV/tuberculosis co-infection present a major challenge. Attaining therapeutic concentrations is crucial for virologic success and to prevent resistance. Understanding dolutegravir pharmacokinetics and its sources of variability is essential to ensure adequate exposure in all individuals. Population pharmacokinetic (PopPK) modeling is a powerful tool for characterizing medication disposition. In this review, we aim to synthesize existing dolutegravir PopPK models, highlighting key pharmacokinetic parameters and covariate effects. A literature search was done on Medline and Embase databases from inception to November 18th, 2025. This review included 23 studies: 15 in adults, 4 in pediatrics, 2 in pregnancy (mothers and their newborn), and 2 in term neonates. Almost all models included allometric scaling, with body weight especially, on apparent clearance (CL/F) and/or apparent volume of distribution (Vd/F) parameters. When considering differences in body size, CL/F and Vd/F were similar across populations. The absorption rate constant (ka) was higher in adults and presented high variability across populations. Other common covariates in adults and pediatrics were co-medications and background antiretrovirals. Data and tested covariates were limited in pregnant women and neonates. Study simulations and predefined target values indicated adequate recommended dolutegravir doses. Further characterization of dolutegravir PopPK in populations at risk of altered concentrations (e.g., preterm neonates, pediatrics, pregnancy, obesity, and older adults) is crucial to better understand dolutegravir pharmacokinetics in these populations as data are still limited.

Bioequivalence studies are important for a generic drug to enter the market. These studies mainly examine various pharmacokinetic parameters like Cmax, AUC0-T and AUC0-∞. But at times, these parameters might not be sufficient to pick up essential kinetics. It is even possible to undertake the additional parameter along with the traditional pharmacometrics. This article gives an overview of one such parameter, partial area under the curve (pAUC), which captures specific time intervals of clinical relevance. The pAUC is especially useful for comparing specific formulations, determining bioequivalence in early or late stages, and assessing medicines with time-dependent therapeutic windows. When employed correctly, pAUC improves our understanding of temporal drug behaviour beyond what total AUC can provide, allowing for more precise and clinically meaningful pharmacokinetic assessments. This article is a review that describes how pAUC has been used in specific regulatory guidelines for drug products that have time-dependent exposures, which may impact the drug's pharmacodynamic properties. These product guidances have been issued by the US Food and Drug Administration (FDA), Health Canada, and European Medicines Agency (EMA). This article presents various viewpoints about pAUC in the mindset of regulators, researchers, and industrial experts.

Oral tyrosine kinase inhibitors and poly (adenosine diphosphate-ribose) polymerase inhibitors are widely used across solid tumors and hematologic malignancies and are typically administered at fixed doses. However, substantial interindividual pharmacokinetic variability results in heterogeneous systemic exposure, potentially leading to underexposure with reduced antitumor efficacy or overexposure with preventable toxicity. Therapeutic drug monitoring and model-informed precision dosing have emerged as complementary strategies to individualize dosing and optimize the exposure-response balance in routine oncology practice. This narrative problem-oriented review evaluates the clinical applicability of therapeutic drug monitoring and model-informed precision dosing for selected oral targeted agents, including epidermal growth factor receptor, anaplastic lymphoma kinase, BCR-ABL, vascular endothelial growth factor receptor, mitogen-activated protein kinase kinase, and multi-kinase inhibitors, as well as poly(adenosine diphosphate-ribose) polymerase inhibitors. For each agent, we assessed the presence of clinically meaningful exposure-response or exposure-toxicity relationships, the availability of validated assays, and the existence of actionable concentration thresholds. We also integrated an updated therapeutic drug monitoring usefulness score to contextualize the strength of recommendation. High-level evidence, including prospective interventional studies, supports exposure-guided dosing for imatinib and sunitinib, demonstrating improved molecular or clinical outcomes when predefined trough concentration targets are achieved. For alectinib, cabozantinib, trametinib, and lenvatinib, consistent exposure-response or exposure-toxicity relationships and pragmatic concentration thresholds support selective implementation, although randomized validation remains limited. For agents such as osimertinib, brigatinib, olaparib, and niraparib, monitoring appears most clinically relevant in toxicity-driven scenarios rather than for efficacy optimization. In contrast, lorlatinib currently lacks a clearly defined therapeutic window, limiting routine applicability. Across drugs, steady-state trough concentration remains the default sampling strategy. Clinical scenarios warranting measurement include early or unexpected disease progression, recurrent or severe adverse events, suspected drug-drug interactions, altered absorption, organ dysfunction, or concerns regarding adherence. Model-informed precision dosing extends conventional monitoring by integrating patient-specific covariates with pharmacokinetic models to simulate individualized dosing regimens. In conclusion, therapeutic drug monitoring and model-informed precision dosing are ready for selective clinical adoption in a subset of oral targeted therapies. Future prospective trials integrating pharmacometric tools with patient-centered outcomes are required to refine exposure targets and expand evidence-based implementation.