Population Pharmacokinetics of Ranibizumab Delivered via the Port Delivery System Implanted in the Eye in Patients with Neovascular Age-Related Macular Degeneration.

The port delivery system with ranibizumab (PDS) is designed to continuously deliver ranibizumab to maintain therapeutic drug concentrations in the vitreous of the eye for an extended duration. The PDS has been evaluated for the treatment of neovascular age-related macular degeneration in the Ladder (PDS 10, 40, and 100 mg/mL, with refill exchanges as needed, versus monthly intravitreal ranibizumab 0.5 mg), Archway (PDS 100 mg/mL with 24-week refill exchanges, versus monthly intravitreal ranibizumab 0.5 mg), and ongoing Portal (PDS 100 mg/mL with 24-week refill exchanges) clinical trials. Data from Ladder, Archway, and Portal were used to develop a population pharmacokinetics (PK) model to estimate the ranibizumab release rate from the PDS implant, describe ranibizumab PK in serum and aqueous humor, and predict the concentration in vitreous humor. A model was developed to adequately describe the serum and aqueous humor PK data, as suggested by goodness-of-fit plots as well as visual predictive checks. In the final model, the first-order implant release rate was estimated to be 0.00654 (1/day), corresponding to a half-life of 106 days, consistent with the implant release rate determined in vitro. The model-predicted vitreous concentrations achieved with PDS 100 mg/mL given every 24 weeks were below the intravitreal peak concentration and above the intravitreal trough concentration of ranibizumab over the entire 24-week refill interval. The results demonstrate a durable release of ranibizumab from the PDS with a half-life of 106 days, providing vitreous exposure to ranibizumab for at least 24 weeks that is within the range of exposure for monthly intravitreal treatment.

Pharmacokinetic/Pharmacodynamic Analysis of Savolitinib plus Osimertinib in an EGFR Mutation-Positive, MET-Amplified Non-Small Cell Lung Cancer Model.

Osimertinib is a third-generation, irreversible, oral EGFR tyrosine kinase inhibitor (TKI) recommended as first-line treatment for patients with locally advanced/metastatic EGFR mutation-positive (EGFRm) non-small cell lung cancer (NSCLC). However, MET amplification/overexpression is a common acquired osimertinib resistance mechanism. Savolitinib is an oral, potent, and highly selective MET-TKI; preliminary data suggest that combining osimertinib with savolitinib may overcome MET-driven resistance. A patient-derived xenograft (PDX) mouse model with EGFRm, MET-amplified NSCLC was tested with a fixed osimertinib dose [10 mg/kg for exposures equivalent to (≈)80 mg], combined with doses of savolitinib (0-15 mg/kg, ≈0-600 mg once daily), both with 1-aminobenzotriazole (to better match clinical half-life). After 20 days of oral dosing, samples were taken at various time points to follow the time course of drug exposure in addition to phosphorylated MET and EGFR (pMET and pEGFR) change. Population pharmacokinetics, savolitinib concentration versus percentage inhibition from baseline in pMET, and the relationship between pMET and tumor growth inhibition (TGI) were also modeled. As single agents, savolitinib (15 mg/kg) showed significant antitumor activity, reaching ∼84% TGI, and osimertinib (10 mg/kg) showed no significant antitumor activity (34% TGI, P > 0.05 vs. vehicle). Upon combination, at a fixed dose of osimertinib, significant savolitinib dose-related antitumor activity was shown, ranging from 81% TGI (0.3 mg/kg) to 84% tumor regression (15 mg/kg). Pharmacokinetic-pharmacodynamic modeling showed that the maximum inhibition of both pEGFR and pMET increased with increasing savolitinib doses. Savolitinib demonstrated exposure-related combination antitumor activity when combined with osimertinib in the EGFRm MET-amplified NSCLC PDX model.

A pharmacokinetic-pharmacodynamic model for the MET tyrosine kinase inhibitor, savolitinib, to explore target inhibition requirements for anti-tumour activity.

BACKGROUND AND PURPOSE: Savolitinib (AZD6094, HMPL-504, volitinib) is an oral, potent, and highly MET receptor TK inhibitor. This series of studies aimed to develop a pharmacokinetic-pharmacodynamic (PK/PD) model to link inhibition of MET phosphorylation (pMET) by savolitinib with anti-tumour activity. EXPERIMENTAL APPROACH: Cell line-derived xenograft (CDX) experiments using human lung cancer (EBC-1) and gastric cancer (MKN-45) cells were conducted in athymic nude mice using a variety of doses and schedules of savolitinib. Tumour pMET changes and growth inhibition were calculated after 28 days. Population PK/PD techniques were used to construct a PK/PD model for savolitinib. KEY RESULTS: Savolitinib showed dose- and dose frequency-dependent anti-tumour activity in the CDX models, with more frequent, lower dosing schedules (e.g., twice daily) being more effective than intermittent, higher dosing schedules (e.g., 4 days on/3 days off or 2 days on/5 days off). There was a clear exposure-response relationship, with maximal suppression of pMET of >90%. Data from additional CDX and patient-derived xenograft (PDX) models overlapped, allowing calculation of a single EC50 of 0.38 ng·ml-1 . Tumour growth modelling demonstrated that prolonged, high levels of pMET inhibition (>90%) were required for tumour stasis and regression in the models. CONCLUSION AND IMPLICATIONS: High and persistent levels of MET inhibition by savolitinib were needed for optimal monotherapy anti-tumour activity in preclinical models. The modelling framework developed here can be used to translate tumour growth inhibition from the mouse to human and thus guide choice of clinical dose and schedule.

Population exposure-safety analysis of cediranib for Phase I and II studies in patients with cancer.

AIMS: A multistudy analysis of cediranib, a potent, selective inhibitor of all three vascular endothelial growth factor receptors (VEGFR-1, -2 and -3), was conducted to establish population exposure-safety models for the relationship of cediranib exposure to the safety endpoints, diastolic and systolic blood pressure (DBP and SBP) and diarrhoea in cancer patients. These models were applied to predict safety outcomes for different cediranib dose regimens. METHODS: Models for hypertension and diarrhoea were constructed based on data from 10 Phase I and three Phase II studies comprising 631 cancer patients following cediranib once-daily oral dosing. Daily DBP and SBP were simultaneously characterized using indirect response models for predicted cediranib concentration-time courses, while daily diarrhoea events were modelled as ordered categorical variables with a proportional odds model with a Markov element for predicted average cediranib concentrations. RESULTS: For 20 mg cediranib once-daily oral administration, the mean increase in DBP and SBP was predicted to be 7 (95% CI 3-13) and 8 mmHg (95% CI 3-16), respectively, while the probability of mild diarrhoea, but not the severity, was predicted to increase over time. Severe diarrhoea was predicted to be resolved rapidly upon discontinuation of cediranib treatment. CONCLUSIONS: Maximum blood pressure increase was observed within the first few days of cediranib treatment, consistent with the pharmacokinetic profile of cediranib reaching steady state in about 5 days. The probability of diarrhoea increased with cediranib concentration but was far more dependent on the status of diarrhoea predicted on the previous day.

Predictions of in vivo prolactin levels from in vitro K(i) values of D(2) receptor antagonists using an agonist-antagonist interaction model.

Prolactin elevation is a side effect of all currently available D(2) receptor antagonists used in the treatment of schizophrenia. Prolactin elevation is the result of a direct antagonistic D(2) effect blocking the tonic inhibition of prolactin release by dopamine. The aims of this work were to assess the correlation between in vitro estimates of D(2) receptor affinity and pharmacokinetic-pharmacodynamic model-based estimates obtained from analysis of clinical data using an agonist-antagonist interaction (AAI) model and to assess the value of such a correlation in early prediction of full prolactin time profiles. A population model describing longitudinal prolactin data was fitted to clinical data from 16 clinical phases 1 and 3 trials including five different compounds. Pharmacokinetic data were modeled for each compound and the prolactin model was both fitted in per-compound fits as well as simultaneously to all prolactin data. Estimates of prolactin elevating potency were compared to corresponding in vitro values and their predictability was evaluated through model-based simulations. The model successfully described the prolactin time course for all compounds. Estimates derived from experimental preclinical data and the model fit of the clinical data were strongly correlated (p<0.001), and simulations adequately predicted the prolactin elevation in five out of six compounds. The AAI model has the potential to be used in drug development to predict prolactin response for a given exposure of D(2) antagonists using routinely produced preclinical data.

Semiparametric distributions with estimated shape parameters.

PURPOSE: To investigate the use of adaptive transformations to assess the parameter distributions in population modeling. METHODS: The logit, box-cox, and heavy tailed transformations were investigated. Each one was used in conjunction with the standard (exponential) transformation for PK and PD parameters. The shape parameters of these transformations were estimated to allow the parameter distributions to more accurately resemble a wider range of parameter distributions. The transformations were tested both in simulated settings where the true distributions were known and in 30 models developed from real data. RESULTS: In the simulated setting the transformations were better than the standard lognormal distribution at characterizing the true distributions. Improvement could also be seen in objective function value (OFV) and in simulation based diagnostics. In the real datasets, significant model improvement based on OFV could be seen in 22, 18, and 22 out of the 30 models for the three transformations respectively. CONCLUSION: Transformations with estimated shape parameters are a promising approach to relax the often erroneous assumption of a known shape of the parameter distribution. They offer a simple and straightforward way of handling and characterizing parameter distributions.