Nilotinib, a second-generation tyrosine kinase inhibitor, has demonstrated clinical activity in chronic myeloid leukemia. As an exposure–response relationship has been observed for nilotinib, its therapeutic drug monitoring could be a valuable tool in clinical practice. Therefore, the aim of this study was to develop and validate a selective and precise high performance liquid chromatography–ultraviolet method for the measurement of nilotinib in plasma from patients with cancer. After protein precipitation extraction with acetonitrile, nilotinib and rilpivirine were separated using isocratic elution on a Tracer Excel 120 ODS C18 column using a mobile phase consisting of a mixture of potassium dihydrogen phosphate-buffered solution (pH 5.5; 0.037 M)–methanol–acetonitrile (45:45:10, v/v/v), pumped at a flow rate of 1.7 mL·min⁻¹. A wavelength of 254 nm was selected for the quantification of the analyte and the internal standard (IS). The technique was validated following the guidelines for the validation of analytical methods of regulatory agencies (Food and Drug Administration (FDA) and the European Medicines Agency (EMA)). Linearity was established in a concentration range between 125 and 7000 ng/mL. The detection limit was 90 ng/mL, and the lower limit of quantification was 125 ng/mL. For all concentrations in the calibration curve, the intraday and interday coefficients of variation were less than 4.1%. Median recovery of nilotinib from plasma was ≥65.1% (±21.4%). The method described is sensitive, selective, reproducible, and rapid, and can be used for the accurate determination of nilotinib in human plasma for pharmacokinetics studies and for therapeutic drug monitoring (TDM) of nilotinib in routine clinical practice.

To develop and internally validate a population pharmacokinetics model for cisplatin and assess its prediction capacity for personalising doses in cancer patients. Cisplatin plasma concentrations in forty-six cancer patients were used to determine the pharmacokinetic parameters of a two-compartment pharmacokinetic model implemented in NONMEN VI software. Pharmacokinetic parameter identification capacity was assessed using the parametric bootstrap method and the model was validated using the nonparametric bootstrap method and standardised visual and numerical predictive checks. The final model's prediction capacity was evaluated in terms of accuracy and precision during the first (a priori) and second (a posteriori) chemotherapy cycles. Mean population cisplatin clearance is 1.03 L/h with an interpatient variability of 78.0%. Estimated distribution volume at steady state was 48.3 L, with inter- and intrapatient variabilities of 31,3% and 11,7%, respectively. Internal validation confirmed that the population pharmacokinetics model is appropriate to describe changes over time in cisplatin plasma concentrations, as well as its variability in the study population. The accuracy and precision of a posteriori prediction of cisplatin concentrations improved by 21% and 54% compared to a priori prediction. The population pharmacokinetic model developed adequately described the changes in cisplatin plasma concentrations in cancer patients and can be used to optimise cisplatin dosing regimes accurately and precisely.

We describe a clinical case of an 84-year-old man diagnosed with non-small cell lung carcinoma and epidermal growth factor receptor mutation, who was treated with erlotinib, with doses adjusted by therapeutic drug monitoring. This case involved a clearance fluctuation leading to over-therapeutic drug concentrations of erlotinib and toxicity. The intrapatient and interpatient variability of erlotinib, in addition to other factors such as age or variations in liver clearance, create situations that are challenging in clinical practice. During treatment, erlotinib serum concentrations were measured, and the dose was accordingly adjusted. The erlotinib dose required to reduce toxicity (rash grade III) and maintain effective plasma concentrations, as well as clinical and radiological responses, was 50% of the initial dose, underscoring the relevance of therapeutic drug monitoring for tyrosine kinase inhibitors in routine clinical practice.

Meningiomas are the most common intracranial tumours, yet the molecular programs underlying WHO grade 1 subtypes—particularly transitional diploid tumours—remain insufficiently defined, partly due to the scarcity of biologically faithful in vitro models. Here, we report the establishment of a long-term, genetically unmanipulated grade 1 meningioma cell line (H8T-MG) maintained under normoxic conditions in serum-containing, growth-factor-supplemented medium, together with a complementary long-term primary culture (H16T-MG), and provide an integrated descriptive and functional characterization of these models, combined with a subtype-restricted transcriptomic analysis of diploid transitional grade 1 tumours versus normal meninges. Both cultures preserved the dual meso-neuroectodermal identity characteristic of meningothelial cells, exhibiting stable adherent growth, preserved contact inhibition and a coherent immunocytochemical profile, expressing vimentin, α-SMA, nestin, connexin-43 and cannabinoid receptors—reported here for the first time in grade 1 meningioma cultures—highlighting cannabinoid-related pathways as potential targets for exploration. Transcriptomic analysis identified 51 differentially expressed genes, revealing a coherent inflammatory–metabolic programme characterised by downregulation of IL-17 and TNF signalling, cytokines and chemokines (IL6, CCL2, SELE, S100A8), together with reduced extracellular-matrix and cytoskeletal activity. In parallel, the enrichment of arachidonic acid metabolism, cytochrome-P450/xenobiotic pathways, retinol metabolism and oxidative/epoxygenase activity indicated a lipid/xenobiotic-oriented metabolic shift distinctive of this subtype. Protein–protein interaction analysis identified four hub genes—ASPN, SELE, ACKR1 and ABCB1—integrating ECM remodelling, endothelial–immune modulation and xenobiotic transport, reinforcing an immune-attenuated, metabolically adapted tumour landscape. Collectively, these findings provide the first integrated in vitro and transcriptomic characterisation of diploid transitional meningiomas, underscore the value of biologically stable models for early-stage meningioma research, and support the value of histological and ploidy stratification in grade 1 meningioma biology.