Clinical Micro-Dose Studies to Explore the Human Pharmacokinetics of Four Selective Inhibitors of Human Nav1.7 Voltage-Dependent Sodium Channels.

BACKGROUND: The emergence of genetic data linking Nav1.7 sodium channel over- and under- expression to human pain signalling has led to an interest in the treatment of chronic pain through inhibition of Nav1.7 channels. OBJECTIVE: We describe the pharmacokinetic (PK) results of a clinical microdose study performed with four potent and selective Nav1.7 inhibitors and the subsequent modelling resulting in the selection of a single compound to explore Nav1.7 pharmacology at higher doses. METHODS: A clinical microdose study to investigate the intravenous and oral PK of four compounds (PF-05089771, PF-05150122, PF-05186462 and PF-05241328) was performed in healthy volunteers. PK parameters were derived via noncompartmental analysis. A physiologically-based PK (PBPK) model was used to predict exposure and multiples of Nav1.7 50 % inhibitory concentration (IC50) for each compound at higher doses. RESULTS: Plasma clearance, volume of distribution and bioavailability ranged from 45 to 392 mL/min/kg, 13 to 36 L/kg and 38 to 110 %, respectively. The PBPK model for PF-05089771 predicted a 1 g oral dose would be required to achieve exposures of approximately 12× Nav1.7 IC50 at maximum concentration (C max), and approximately 3× IC50 after 12 h (minimum concentration [C min] for a twice-daily regimen). Lower multiples of Nav1.7 IC50 were predicted with the same oral doses of PF-05150122, PF-05186462, and PF-05241328. In a subsequent single ascending oral dose clinical study, the predictions for PF-05089771 compared well with observed data. CONCLUSION: Based on the human PK data obtained from the microdose study and subsequent modelling, PF-05089771 provided the best opportunity to explore Nav1.7 blockade for the treatment of acute or chronic pain conditions.

Pharmacokinetics, distribution, and metabolism of [14C]sunitinib in rats, monkeys, and humans.

Sunitinib is an oral multitargeted tyrosine kinase inhibitor approved for the treatment of advanced renal cell carcinoma, imatinib-refractory gastrointestinal stromal tumor, and advanced pancreatic neuroendocrine tumors. The current studies were conducted to characterize the pharmacokinetics, distribution, and metabolism of sunitinib after intravenous and/or oral administrations of [(14)C]sunitinib in rats (5 mg/kg i.v., 15 mg/kg p.o.), monkeys (6 mg/kg p.o.), and humans (50 mg p.o.). After oral administration, plasma concentration of sunitinib and total radioactivity peaked from 3 to 8 h. Plasma terminal elimination half-lives of sunitinib were 8 h in rats, 17 h in monkeys, and 51 h in humans. The majority of radioactivity was excreted to the feces with a smaller fraction of radioactivity excreted to urine in all three species. The bioavailability in female rats was close to 100%, suggesting complete absorption of sunitinib. Whole-body autoradioluminography suggested radioactivity was distributed throughout rat tissues, with the majority of radioactivity cleared within 72 h. Radioactivity was eliminated more slowly from pigmented tissues. Sunitinib was extensively metabolized in all species. Many metabolites were detected both in urine and fecal extracts. The main metabolic pathways were N-de-ethylation and hydroxylation of indolylidene/dimethylpyrrole. N-Oxidation/hydroxylation/desaturation/deamination of N,N'-diethylamine and oxidative defluorination were the minor metabolic pathways. Des-ethyl metabolite M1 was the major circulating metabolite in all three species.

Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates.

A number of computational approaches are being proposed for an early optimization of ADME (absorption, distribution, metabolism and excretion) properties to increase the success rate in drug discovery. The present study describes the development of an in silico model able to estimate, from the three-dimensional structure of a molecule, the stability of a compound with respect to the human cytochrome P450 (CYP) 3A4 enzyme activity. Stability data were obtained by measuring the amount of unchanged compound remaining after a standardized incubation with human cDNA-expressed CYP3A4. The computational method transforms the three-dimensional molecular interaction fields (MIFs) generated from the molecular structure into descriptors (VolSurf and Almond procedures). The descriptors were correlated to the experimental metabolic stability classes by a partial least squares discriminant procedure. The model was trained using a set of 1800 compounds from the Pharmacia collection and was validated using two test sets: the first one including 825 compounds from the Pharmacia collection and the second one consisting of 20 known drugs. This model correctly predicted 75% of the first and 85% of the second test set and showed a precision above 86% to correctly select metabolically stable compounds. The model appears a valuable tool in the design of virtual libraries to bias the selection toward more stable compounds.