High interindividual variability (IIV) of the clinical response to epidermal growth factor receptor (EGFR) inhibitors such as osimertinib in non-small-cell lung cancer (NSCLC) might be related to the IIV in plasma exposure. The aim of this study was to evaluate the exposure–response relationship for toxicity and efficacy of osimertinib in unselected patients with advanced EGFR-mutant NSCLC. This retrospective analysis included 87 patients treated with osimertinib. Exposure–toxicity analysis was performed in the entire cohort and survival analysis only in second-line patients (n = 45). No significant relationship between occurrence of dose-limiting toxicity and plasma exposure was observed in the entire cohort (p = 0.23, n = 86). The median overall survival (OS) was approximately two-fold shorter in the 4th quartile (Q4) of osimertinib trough plasma concentration (>235 ng/mL) than in the Q1–Q3 group (12.2 months [CI95% = 8.0–not reached (NR)] vs. 22.7 months [CI95% = 17.1–34.1]), but the difference was not statistically significant (p = 0.15). To refine this result, the exposure–survival relationship was explored in a cohort of 41 NSCLC patients treated with erlotinib. The Q4 erlotinib exposure group (>1728 ng/mL) exhibited a six-fold shorter median OS than the Q1–Q3 group (4.8 months [CI95% = 3.3-NR] vs. 22.8 months (CI95% = 10.6–37.4), p = 0.00011). These results suggest that high exposure to EGFR inhibitors might be related to worse survival in NSCLC patients.

Patients treated with dabrafenib/trametinib (DAB/TRA) exhibit a large interindividual variability in clinical outcomes. The aims of this study were to characterize the pharmacokinetics of DAB, hydroxy-dabrafenib (OHD), and TRA in BRAF-mutated patients and to investigate the exposure–response relationship for toxicity and efficacy in metastatic melanoma (MM) patients. Univariate Fisher and Wilcoxon models including drug systemic exposure (area under the plasma concentration curve, AUC) were used to identify prognostic factors for the onset of dose-limiting toxicities (DLT), and Cox models for overall (OS) and progression-free survival (PFS). Seventy-three BRAF-mutated patients were included in pharmacokinetic (n = 424, NONMEM) and 52 in pharmacokinetic/pharmacodynamic analyses. Age and sex were identified as determinants of DAB and OHD clearances (p < 0.01). MM patients experiencing DLT were overexposed to DAB compared to patients without DLT (AUC: 9624 vs. 7485 ng∙h/mL, respectively, p < 0.01). Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≥ 2 and plasma ratio AUC_OHD/AUC_DAB ≥ 1 were independently associated with shorter OS (HR: 6.58 (1.29–33.56); p = 0.023 and 10.61 (2.34–48.15), p = 0.022, respectively). A number of metastatic sites ≥3 and cerebral metastases were associated with shorter PFS (HR = 3.25 (1.11–9.50); p = 0.032 and HR = 1.23 (1.35–10.39), p = 0.011; respectively). TRA plasma exposure was neither associated with toxicity nor efficacy. Our results suggest that early drug monitoring could be helpful to prevent the onset of DLT in MM patients, especially in fragile patients such as the elderly. Regarding efficacy, the clinical benefit to monitor plasma ratio AUC_OHD/AUC_DAB deserves more investigation in a larger cohort of MM patients.

Factors associated with olaparib toxicity remain unknown in ovarian cancer patients. The large inter-individual variability in olaparib pharmacokinetics could contribute to the onset of early significant adverse events (SAE). We aimed to retrospectively analyze the pharmacokinetic/pharmacodynamic relationship for toxicity in ovarian cancer patients from “real life” data. The clinical endpoint was the onset of SAE (grade III/IV toxicity or dose reduction/discontinuation). Plasma olaparib concentration was assayed using liquid chromatography at any time over the dosing interval. Trough concentrations (CminPred) were estimated using a population pharmacokinetic model. The association between toxicity and clinical characteristics or CminPred was assessed by logistic regression and non-parametric statistical tests. Twenty-seven patients were included, among whom 13 (48%) experienced SAE during the first six months of treatment. Olaparib CminPred was the only covariate significantly associated with increased risk of SAE onset (odds ratio = 1.31, 95%CI = [1.10; 1.57], for each additional 1000 ng/mL). The ROC curve identified a threshold of CminPred = 2500 ng/mL for prediction of SAE onset (sensitivity/specificity 0.62 and 1.00, respectively). This study highlights a significant association between olaparib plasma exposure and SAE onset and identified the threshold of 2500 ng/mL trough concentration as potentially useful to guide dose adjustment in ovarian cancer patients.

Patients treated with dabrafenib and trametinib for BRAF^V600-mutant melanoma often experience dose reductions and treatment discontinuations. Current knowledge about the associations between patient characteristics, adverse events (AE), and exposure is inconclusive. Our study included 27 patients (including 18 patients for micro-sampling). Dabrafenib and trametinib exposure was prospectively analyzed, and the relevant patient characteristics and AE were reported. Their association with the observed concentrations and Bayesian estimates of the pharmacokinetic (PK) parameters of (hydroxy-)dabrafenib and trametinib were investigated. Further, the feasibility of at-home sampling of capillary blood was assessed. A population pharmacokinetic (popPK) model-informed conversion model was developed to derive serum PK parameters from self-sampled capillary blood. Results showed that (hydroxy-)dabrafenib or trametinib exposure was not associated with age, sex, body mass index, or toxicity. Co-medication with P-glycoprotein inducers was associated with significantly lower trough concentrations of trametinib (p = 0.027) but not (hydroxy-)dabrafenib. Self-sampling of capillary blood was feasible for use in routine care. Our conversion model was adequate for estimating serum PK parameters from micro-samples. Findings do not support a general recommendation for monitoring dabrafenib and trametinib but suggest that monitoring can facilitate making decisions about dosage adjustments. To this end, micro-sampling and the newly developed conversion model may be useful for estimating precise PK parameters.