The metabolic drug-drug interaction profile of Dabrafenib: in vitro investigations and quantitative extrapolation of the P450-mediated DDI risk.

Dabrafenib is a potent ATP-competitive inhibitor for the V600 mutant b-rapidly accelerated fibrosarcoma (b-raf) kinase currently approved in the United States for the treatment of metastatic melanoma. Studies were conducted in human liver microsomes, recombinant human cytochrome P450 (P450) enzymes, and human hepatocytes to investigate the potential of dabrafenib and its major circulating metabolites to perpetrate pharmacokinetic drug-drug interactions (DDIs) as well as have their own pharmacokinetics affected (victim) by coadministered drugs. Dabrafenib metabolism was mediated by CYP2C8 (56% to 67%) and CYP3A4 (24%); in addition, it has demonstrated inhibition of CYP2C8, 2C9, 2C19, 3A4 (atorvastatin), and (nifedipine), with calculated IC50 values of 8.2, 7.2, 22.4, 16, and 32 µM. It also demonstrated metabolism-dependent inhibition of CYP3A4 with a maximal inactivation rate constant of 0.040 minute(-1) and a concentration required to achieve half-maximal inactivation for CYP3A4 of 38 µM. Hydroxy-dabrafenib inhibited CYP1A2, 2C9, and 3A4 (midazolam) with calculated IC50 values of 83, 29, and 44 µM, and carboxy-dabrafenib did not inhibit any of the P450 enzymes tested. Desmethyl-dabrafenib inhibited CYP2B6, 2C8, 2C9, 2C19, and 3A4 (midazolam, atorvastatin, and nifedipine) with calculated IC50 values of 78, 47, 6.3, 36, 17, 20, and 28 µM, respectively. At 30 µM dabrafenib showed increases in CYP2B6 and CYP3A4 mRNA expression indicative of induction. The potential clinical relevance of these findings was explored by using mechanistic static mathematical models to estimate the magnitude of change (area under the curve change) as a result of P450-mediated DDI interactions. This risk-assessment approach indicated that dabrafenib is unlikely to perpetrate any in vivo DDIs by inhibition mechanisms, but is a likely inducer of CYP3A4 and a victim of CYP3A4 and CYP2C8 inhibitors. Furthermore, inclusion of the in vitro drug interaction data for dabrafenib metabolites did not impact the overall clinical risk assessment.

Inhibition of Polo-like kinase 1 prevents the growth of metastatic breast cancer cells in the brain.

Few therapeutic strategies exist for the treatment of metastatic tumor cells in the brain because the blood-brain barrier (BBB) limits drug access. Thus the identification of molecular targets and accompanying BBB permeable drugs will significantly benefit brain metastasis patients. Polo-like kinase 1 (Plk1) is an attractive molecular target because it is only expressed in dividing cells and its expression is upregulated in many tumors. Analysis of a publicly available database of human breast cancer metastases revealed Plk1 mRNA expression was significantly increased in brain metastases compared to systemic metastases (P = 0.0018). The selective Plk1 inhibitor, GSK461364A, showed substantial uptake in normal rodent brain. Using a breast cancer brain metastatic xenograft model (231-BR), we tested the efficacy of GSK461364A to prevent brain metastatic colonization. When treatment was started 3 days post-injection, GSK461364A at 50 mg/kg inhibited the development of large brain metastases 62% (P = 0.0001) and prolonged survival by 17%. GSK461364A sensitized tumor cells to radiation induced cell death in vitro. Previously, it was reported that mutations in p53 might render tumor cells more sensitive to Plk1 inhibition; however, p53 mutations are uncommon in breast cancer. In a cohort of 41 primary breast tumors and matched brain metastases, p53 immunostaining was increased in 61% of metastases; 44% of which were associated with primary tumors with low p53. The data suggest that p53 overexpression occurs frequently in brain metastases and may facilitate sensitivity to Plk1 inhibition. These data indicate Plk1 may be a new druggable target for the prevention of breast cancer brain metastases.

Utilizing drug-drug interaction prediction tools during drug development: enhanced decision making based on clinical risk.

Several reports in the literature present the utility and value of in vitro drug-metabolizing enzyme inhibition data to predict in vivo drug-drug interactions in humans. A retrospective analysis has been conducted for 26 GlaxoSmithKline (GSK) drugs and drug candidates for which in vitro inhibition parameters have been determined, and clinical drug interaction information, from a total of 46 studies, is available. The dataset, for drugs with a diverse range of physiochemical properties, included both reversible and potentially irreversible cytochrome P450 inhibitors for which in vitro inhibition parameters (IC(50) or K(I)/k(inact) as appropriate) were determined using standardized methodologies. Mechanistic static models that differentiated reversible and metabolism-dependent inhibition, and also considered the contribution of intestinal metabolism for CYP3A4 substrates, were applied to estimate the magnitude of the interactions. Several pharmacokinetic parameters, including total C(max), unbound C(max), as well as estimates of hepatic inlet and liver concentration, were used as surrogates for the inhibitor concentration at the enzyme active site. The results suggest that estimated unbound liver concentration or unbound hepatic inlet concentration, with consideration of intestinal contribution, offered the most accurate predictions of drug-drug interactions (occurrence and magnitude) for the drugs in this dataset. When used with epidemiological information on comedication profiles for a given therapeutic area, these analyses offer a quantitative risk assessment strategy to inform the necessity of excluding specific comedications in early clinical studies and the ultimate requirement for clinical drug-drug interaction studies. This strategy has significantly reduced the number of clinical drug interaction studies performed at GSK.

The conduct of in vitro studies to address time-dependent inhibition of drug-metabolizing enzymes: a perspective of the pharmaceutical research and manufacturers of America.

Time-dependent inhibition (TDI) of cytochrome P450 (P450) enzymes caused by new molecular entities (NMEs) is of concern because such compounds can be responsible for clinically relevant drug-drug interactions (DDI). Although the biochemistry underlying mechanism-based inactivation (MBI) of P450 enzymes has been generally understood for several years, significant advances have been made only in the past few years regarding how in vitro time-dependent inhibition data can be used to understand and predict clinical DDI. In this article, a team of scientists from 16 pharmaceutical research organizations that are member companies of the Pharmaceutical Research and Manufacturers of America offer a discussion of the phenomenon of TDI with emphasis on the laboratory methods used in its measurement. Results of an anonymous survey regarding pharmaceutical industry practices and strategies around TDI are reported. Specific topics that still possess a high degree of uncertainty are raised, such as parameter estimates needed to make predictions of DDI magnitude from in vitro inactivation parameters. A description of follow-up mechanistic experiments that can be done to characterize TDI are described. A consensus recommendation regarding common practices to address TDI is included, the salient points of which include the use of a tiered approach wherein abbreviated assays are first used to determine whether NMEs demonstrate TDI or not, followed by more thorough inactivation studies for those that do to define the parameters needed for prediction of DDI.

Single mutations change CYP2F3 from a dehydrogenase of 3-methylindole to an oxygenase.

Pulmonary cytochrome P450 2F3 (CYP2F3) catalyzes the dehydrogenation of the pneumotoxin 3-methylindole (3MI) to an electrophilic intermediate, 3-methyleneindolenine, which is responsible for the toxicity of the parent compound. Members of the CYP2F subfamily are the only enzymes known to exclusively dehydrogenate 3MI, without detectable formation of oxygenation products. Thus, CYP2F3 is an attractive model to study dehydrogenation mechanisms. The purpose of this study was to identify specific residues that could facilitate 3MI dehydrogenation. Both single and double mutations were constructed to study the molecular mechanisms that direct dehydrogenation. Double mutations in substrate recognition sites (SRS) 1 produced an inactive enzyme, while double mutants in SRS 4 did not alter 3MI metabolism. However, double mutations in SRS 5 and SRS 6 successfully introduced oxygenase activity to CYP2F3. Single mutations in SRS 5, SRS 6 and near SRS 2 also introduced 3MI oxygenase activity. Mutants S474H and D361T oxygenated 3MI but also increased dehydrogenation rates, while G214L, E215Q and S475I catalyzed 3MI oxygenation exclusively. A homology model of CYP2F3 was precisely consistent with specific dehydrogenation of 3MI via initial hydrogen atom abstraction from the methyl group. In addition, intramolecular kinetic deuterium isotope studies demonstrated an isotope effect ( K H/ K D) of 6.8. This relatively high intramolecular deuterium isotope effect confirmed the initial hydrogen abstraction step; a mutant (D361T) that retained the dehydrogenation reaction exhibited the same deuterium isotope effect. The results showed that a single alteration, such as a serine to isoleucine change at residue 475, dramatically switched catalytic preference from dehydrogenation to oxygenation.