Population pharmacokinetics and pharmacodynamics of BYL719, a phosphoinositide 3-kinase antagonist, in adult patients with advanced solid malignancies.

AIMS: The aim was to characterize the population pharmacokinetics of BYL719 in cancer patients and assess the time course of tumour response in relation to drug exposure and dosing schedule. METHODS: Plasma samples and longitudinal tumour size measurements were collected from 60 patients with advanced solid malignancies who received oral BYL719 once daily (30-450 mg) or twice daily at 120 mg or 200 mg. Non-linear mixed effect modelling was employed to develop the population pharmacokinetic and pharmacodynamic model. RESULTS: The pharmacokinetics were best described by a one compartment disposition model and transit compartments accounting for the lag time in absorption. The typical population oral clearance and volume of distribution estimates with their between-subject variability (BSV) were 10 l h(-1) (BSV 26%) and 108 l (BSV 28%), respectively. The estimated optimal number of transit compartments was 8.1, with a mean transit time to the absorption compartment of 1.28 h (BSV 32%). The between-occasion variability in the rate and extent of absorption was 46% and 26%, respectively. Tumour growth was modelled using a turnover model characterized by a zero order growth rate of 0.581 cm week(1) and a first order death rate of 0.0123 week(-1) . BYL719 inhibited tumour growth with an IC50 of 100 ng ml(-1) (BSV 154%). Model-based predictions showed potential for additional anti-tumour activity of twice daily dosing at total daily dose below 400 mg, but a loss of efficacy if administered less frequently than once daily. CONCLUSIONS: The proposed model provides a valuable approach for planning future clinical studies and for designing optimized dosing regimens with BYL719.

Phase I, dose-escalation study of BKM120, an oral pan-Class I PI3K inhibitor, in patients with advanced solid tumors.

PURPOSE: This phase I dose-escalation study investigated the maximum-tolerated dose (MTD), safety, preliminary activity, pharmacokinetics (PK), and pharmacodynamics of BKM120, a potent and highly specific oral pan-Class I PI3K inhibitor. PATIENTS AND METHODS: Thirty-five patients with advanced solid tumors received daily BKM120 12.5 to 150 mg. Dose escalation was guided by a Bayesian logistic regression model with overdose control. Assessments included archival tumor molecular status, response by Response Evaluation Criteria in Solid Tumors (RECIST), positron emission tomography tracer uptake ([(18)F]fluorodeoxyglucose positron emission tomography [FDG-PET]), fasting plasma C-peptide, and phosphorylated ribosomal protein S6 (pS6) in skin biopsies. RESULTS: Overall, treatment was well tolerated. Dose-limiting toxicities were grade 2 mood alteration (80 mg), grade 3 epigastralgia, grade 3 rash, grade 2 and grade 3 mood alteration (100 mg), and two grade 4 hyperglycemia (150 mg). The MTD was 100 mg/d. Frequent treatment-related adverse events included rash, hyperglycemia, diarrhea, anorexia, and mood alteration (37% each); nausea (31%); fatigue (26%); pruritus (23%); and mucositis (23%). BKM120 demonstrated rapid absorption, half-life of ∼40 hours, ∼three-fold steady-state accumulation, dose-proportional exposure, and moderate interpatient variability. One patient demonstrated a confirmed partial response (triple-negative breast cancer); seven patients (20%) were on study for ≥ 8 months. BKM120 demonstrated dose-dependent pharmacodynamic effects on [(18)F]FDG-PET, fasting C-peptide, fasting blood glucose, and pS6. No significant trends were seen to correlate tumor molecular alterations with clinical activity. CONCLUSION: This study demonstrates feasibility and proof-of-concept of class I PI3K inhibition in patients with advanced cancers. BKM120, at the MTD of 100 mg/d, is safe and well tolerated, with a favorable PK profile, clear evidence of target inhibition, and preliminary antitumor activity.

Towards a better prediction of peak concentration, volume of distribution and half-life after oral drug administration in man, using allometry.

BACKGROUND: It is imperative that new drugs demonstrate adequate pharmacokinetic properties, allowing an optimal safety margin and convenient dosing regimens in clinical practice, which then lead to better patient compliance. Such pharmacokinetic properties include suitable peak (maximum) plasma drug concentration (C(max)), area under the plasma concentration-time curve (AUC) and a suitable half-life (t(½)). The C(max) and t(½) following oral drug administration are functions of the oral clearance (CL/F) and apparent volume of distribution during the terminal phase by the oral route (V(z)/F), each of which may be predicted and combined to estimate C(max) and t(½). Allometric scaling is a widely used methodology in the pharmaceutical industry to predict human pharmacokinetic parameters such as clearance and volume of distribution. In our previous published work, we have evaluated the use of allometry for prediction of CL/F and AUC. In this paper we describe the evaluation of different allometric scaling approaches for the prediction of C(max), V(z)/F and t(½) after oral drug administration in man. METHODS: Twenty-nine compounds developed at Janssen Research and Development (a division of Janssen Pharmaceutica NV), covering a wide range of physicochemical and pharmacokinetic properties, were selected. The C(max) following oral dosing of a compound was predicted using (i) simple allometry alone; (ii) simple allometry along with correction factors such as plasma protein binding (PPB), maximum life-span potential or brain weight (reverse rule of exponents, unbound C(max) approach); and (iii) an indirect approach using allometrically predicted CL/F and V(z)/F and absorption rate constant (k(a)). The k(a) was estimated from (i) in vivo pharmacokinetic experiments in preclinical species; and (ii) predicted effective permeability in man (P(eff)), using a Caco-2 permeability assay. The V(z)/F was predicted using allometric scaling with or without PPB correction. The t(½) was estimated from the allometrically predicted parameters CL/F and V(z)/F. Predictions were deemed adequate when errors were within a 2-fold range. RESULTS: C(max) and t(½) could be predicted within a 2-fold error range for 59% and 66% of the tested compounds, respectively, using allometrically predicted CL/F and V(z)/F. The best predictions for C(max) were obtained when k(a) values were calculated from the Caco-2 permeability assay. The V(z)/F was predicted within a 2-fold error range for 72% of compounds when PPB correction was applied as the correction factor for scaling. CONCLUSIONS: We conclude that (i) C(max) and t(½) are best predicted by indirect scaling approaches (using allometrically predicted CL/F and V(z)/F and accounting for k(a) derived from permeability assay); and (ii) the PPB is an important correction factor for the prediction of V(z)/F by using allometric scaling. Furthermore, additional work is warranted to understand the mechanisms governing the processes underlying determination of C(max) so that the empirical approaches can be fine-tuned further.

Effects of antibodies induced by a conjugate vaccine on 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone absorptive transport, metabolism, and proliferation of human lung cells.

One of the most abundant and potent lung carcinogen is the nicotine-derived tobacco-specific nitrosamine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). The monoclonal antibody P9D5 induced with a NNK-conjugate vaccine was used to investigate the ability of NNK-specific antibodies to modulate NNK-induced adverse effects as well as its absorptive transport and metabolism in two lung cancer cell lines (Calu-3 and NCI-H82). Transport experiments in Calu-3 cells with a 50-fold molar excess of apical P9D5 increased the recovery of coadministered apical NNK, with a concomitant decrease in NNK transepithelial transport of more than 50% compared to controls. In contrast, basolateral P9D5 did neither influence transepithelial transport of NNK nor its disappearance from the apical compartment. Calu-3 cells were also found to reduce NNK to NNAL and a 65-fold molar excess of NNK-specific antibody inhibited this metabolic conversion by 46 and 54% compared to irrelevant control antibody after 48 and 72 hr, respectively. The biological relevance of NNK redistribution by antibody was demonstrated by reversion of NNK-induced cell proliferation in NCI-H82 cells. Repartitioning of tobacco carcinogens by antibody may reduce their early effective peak concentrations in susceptible target organs and thus relieve overloaded local DNA repair mechanisms and diminish carcinogen-induced cell proliferation. These in vitro data therefore suggest that a prophylactic antibody response may be associated with a reduced risk of cancer.

Cardio-vascular safety beyond hERG: in silico modelling of a guinea pig right atrium assay.

As chemists can easily produce large numbers of new potential drug candidates, there is growing demand for high capacity models that can help in driving the chemistry towards efficacious and safe candidates before progressing towards more complex models. Traditionally, the cardiovascular (CV) safety domain plays an important role in this process, as many preclinical CV biomarkers seem to have high prognostic value for the clinical outcome. Throughout the industry, traditional ion channel binding data are generated to drive the early selection process. Although this assay can generate data at high capacity, it has the disadvantage of producing high numbers of false negatives. Therefore, our company applies the isolated guinea pig right atrium (GPRA) assay early-on in discovery. This functional multi-channel/multi-receptor model seems much more predictive in identifying potential CV liabilities. Unfortunately however, its capacity is limited, and there is no room for full automation. We assessed the correlation between ion channel binding and the GPRA's Rate of Contraction (RC), Contractile Force (CF), and effective refractory frequency (ERF) measures assay using over six thousand different data points. Furthermore, the existing experimental knowledge base was used to develop a set of in silico classification models attempting to mimic the GPRA inhibitory activity. The Naïve Bayesian classifier was used to built several models, using the ion channel binding data or in silico computed properties and structural fingerprints as descriptors. The models were validated on an independent and diverse test set of 200 reference compounds. Performances were assessed on the bases of their overall accuracy, sensitivity and specificity in detecting both active and inactive molecules. Our data show that all in silico models are highly predictive of actual GPRA data, at a level equivalent or superior to the ion channel binding assays. Furthermore, the models were interpreted in terms of the descriptors used to highlight the undesirable areas in the explored chemical space, specifically regions of low polarity, high lipophilicity and high molecular weight. In conclusion, we developed a predictive in silico model of a complex physiological assay based on a large and high quality set of experimental data. This model allows high throughput in silico safety screening based on chemical structure within a given chemical space.

Predicting oral clearance in humans: how close can we get with allometry?

BACKGROUND: Oral clearance (CL/F) is an important pharmacokinetic parameter and plays an important role in the selection of a safe and tolerable dose for first-in-human studies. Throughout the pharmaceutical industry, many drugs are administered via the oral route; however, there are only a handful of published scaling studies for the prediction of oral pharmacokinetic parameters. METHODS: We evaluated the predictive performances of four different allometric approaches -- simple allometry (SA), the rule of exponents, the unbound CL/F approach, and the unbound fraction corrected intercept method (FCIM) -- for the prediction of human CL/F and the oral area under the plasma concentration-time curve (AUC). Twenty-four compounds developed at Johnson and Johnson Pharmaceutical Research and Development, covering a wide range of physicochemical and pharmacokinetic properties, were selected. The CL/F was predicted using these approaches, and the oral AUC was then estimated using the predicted CL/F. RESULTS: The results of this study indicated that the most successful predictions of CL/F and the oral AUC were obtained using the unbound CL/F approach in combination with the maximum lifespan potential or the brain weight as correction factors based on the rule of exponents. We also observed that the unbound CL/F approach gave better predictions when the exponent of SA was between 0.5 and 1.2. However, the FCIM seemed to be the method of choice when the exponent of SA was <0.50 or >1.2. CONCLUSIONS: Overall, we were able to predict CL/F and the oral AUC within 2-fold of the observed value for 79% and 83% of the compounds, respectively, by selecting the allometric approaches based on the exponents of SA.

Physiologically based approaches towards the prediction of pharmacokinetics: in vitro-in vivo extrapolation.

In adapting to the challenge to make more informed selection of compounds for development, the pharmaceutical industry is increasingly embracing the application of mechanism-based models and prediction tools for prediction of pharmacokinetic parameters. This review first outlines the concepts and application of the major physiologically based prediction tools to extrapolate clearance, tissue distribution, and rate and extent of absorption from minimal in vitro or animal in vivo input data. Finally, the ability of these prediction tools, when placed within a generic whole body physiologically based model of pharmacokinetics, to predict plasma concentration-time profiles is briefly discussed.

Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs.

The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics.

The prediction of drug metabolism, tissue distribution, and bioavailability of 50 structurally diverse compounds in rat using mechanism-based absorption, distribution, and metabolism prediction tools.

The aim of this study was to assess a physiologically based modeling approach for predicting drug metabolism, tissue distribution, and bioavailability in rat for a structurally diverse set of neutral and moderate-to-strong basic compounds (n = 50). Hepatic blood clearance (CL(h)) was projected using microsomal data and shown to be well predicted, irrespective of the type of hepatic extraction model (80% within 2-fold). Best predictions of CL(h) were obtained disregarding both plasma and microsomal protein binding, whereas strong bias was seen using either blood binding only or both plasma and microsomal protein binding. Two mechanistic tissue composition-based equations were evaluated for predicting volume of distribution (V(dss)) and tissue-to-plasma partitioning (P(tp)). A first approach, which accounted for ionic interactions with acidic phospholipids, resulted in accurate predictions of V(dss) (80% within 2-fold). In contrast, a second approach, which disregarded ionic interactions, was a poor predictor of V(dss) (60% within 2-fold). The first approach also yielded accurate predictions of P(tp) in muscle, heart, and kidney (80% within 3-fold), whereas in lung, liver, and brain, predictions ranged from 47% to 62% within 3-fold. Using the second approach, P(tp) prediction accuracy in muscle, heart, and kidney was on average 70% within 3-fold, and ranged from 24% to 54% in all other tissues. Combining all methods for predicting V(dss) and CL(h) resulted in accurate predictions of the in vivo half-life (70% within 2-fold). Oral bioavailability was well predicted using CL(h) data and Gastroplus Software (80% within 2-fold). These results illustrate that physiologically based prediction tools can provide accurate predictions of rat pharmacokinetics.

Immunopropylactic approaches against chemical carcinogenesis.

Immunoprophylactic strategies using carcinogen-specific antibodies have so far received little attention. This may be due to experimental difficulties of in vivo chemical carcinogenesis models, which conveniently use excessive doses of carcinogen, which do not reflect environmental exposure and which cannot be matched by molar equivalents of antibodies. However, more recent studies have now demonstrated that both mucosal and systemic antibodies may afford protection against low doses of environmental carcinogens, at least when stoichiometry between carcinogen and antibody is respected. Mucosal antibodies could decrease both systemic uptake and metabolic activation at the site of entry. Systemic antibodies may change the kinetics of carcinogen metabolism and redistribute carcinogens within the organism. Antibody-mediated redistribution may favor metabolism in less sensitive distal organs and thus result in lower concentrations of adduct-forming species at mucosal surfaces and other sensitive cells. This may be accomplished by avoiding threshold concentrations of carcinogens required for triggering carcinogen-mediated cytochrome P450 induction and tumor promotion. Studies at immunoprophylactic intervention in carcinogenicity are discussed.

Specific antibody modulates absorptive transport and metabolic activation of benzo[a]pyrene across Caco-2 monolayers.

It has been shown that oral anticarcinogen antibodies can decrease intestinal absorption of procarcinogens. So far, no attempts have been made to understand the potential modulatory effect of such antibodies on metabolic activation at mucosal surfaces. Moreover, the influence of naturally induced serosal-specific antibodies on absorptive transport of carcinogens remains unknown. In this study, the prototype food carcinogen benzo[a]pyrene (B[a]P) and a specific monoclonal antibody were used to address these questions in a bicompartmental model of polarized intestinal cells (Caco-2). Apical (i.e., luminal) administration of a 30-fold molar excess antibodies increased about 25-fold recovery of unmetabolized B[a]P, concomitantly with a decrease of 80% in both absorptive transport and formation of phenol metabolites. Interestingly, when metabolism was slowed down by antibodies, cross-reactive antibodies also increased at least 5-fold the extracellular levels of the 7,8-diol-B[a]P, interrupting subsequent activation steps. On the other hand, basolateral antibodies changed by 8-fold the rate of carcinogen appearance in the basolateral compartment, albeit without interfering with the apical cellular uptake or sequestration of either B[a]P or 7,8-diol-B[a]P by apical antibodies. Furthermore, basolateral antibodies reduced exposure of Caco-2 monolayers to B[a]P as demonstrated by a 50% decrease in apical efflux of 3-OH-B[a]P. These data show for the first time that both luminal and serosal antibodies may reduce the carcinogenic process by preventing high local concentrations, which would overload DNA repair mechanisms. This study also sheds light on the relevance of both naturally induced and immunoprophylactic antibodies against polycyclic aromatic hydrocarbon carcinogens.

Modulation of the metabolism and adverse effects of benzo[a]pyrene by a specific antibody: a novel host factor in environmental carcinogenesis?

The influence of specific antibodies on molecular and cellular mechanisms of activation, detoxification and biological activity of the ubiquitous carcinogen benzo[a]pyrene (B[a]P) was investigated using a monoclonal antibody. The antibody was shown to decrease cellular uptake and metabolic activation of B[a]P as demonstrated by higher recovery of unmetabolized B[a]P and decreased formation of end-point phenol metabolites in two types of target cells. Furthermore, strong antibody reactivity with 7,8-diol-B[a]P provided a second chance for interrupting metabolic activation by sequestration of this intermediate metabolite in the extracellular space. The biological relevance of B[a]P and 7,8-diol-B[a]P redistribution by antibody was demonstrated by reversion of B[a]P-induced inhibition of proliferation of human peripheral blood lymphocytes and by inhibition of CYP 1A1 induction in HepG2 cells. Remarkably, the antibody was still protective against B[a]P-induced immunotoxicity even after delayed addition, suggesting a more important role of metabolites in immunotoxicity than has been appreciated so far. Although B[a]P is activated to 7,8-diol-B[a]P in the same cells that are inhibited by this metabolite, the antibody completely restored lymphocyte proliferation indicating that extracellular trapping of the 7,8-diol-B[a]P is biologically highly effective. Thus, repartitioning of both B[a]P and its metabolites by the antibody may reduce their effective concentration in susceptible target organs and therefore relieve overloaded DNA repair mechanisms and inhibit carcinogen-induced P450 induction. These in vitro data also suggest that a natural or prophylactic antibody response against carcinogens may be associated with a reduced risk of cancer.