In silico trial for the assessment of givinostat dose adjustment rules based on the management of key hematological parameters in polycythemia vera patients.

Polycythemia vera (PV) is a chronic myeloproliferative neoplasm characterized by excessive levels of platelets (PLT), white blood cells (WBC), and hematocrit (HCT). Givinostat (ITF2357) is a potent histone-deacetylase inhibitor that showed a good safety/efficacy profile in PV patients during phase I/II studies. A phase III clinical trial had been planned and an adaptive dosing protocol had been proposed where givinostat dose is iteratively adjusted every 28 days (one cycle) based on PLT, WBC, and HCT. As support, a simulation platform to evaluate and refine the proposed givinostat dose adjustment rules was developed. A population pharmacokinetic/pharmacodynamic model predicting the givinostat effects on PLT, WBC, and HCT in PV patients was developed and integrated with a control algorithm implementing the adaptive dosing protocol. Ten in silico trials in ten virtual PV patient populations were simulated 500 times. Considering an eight-treatment cycle horizon, reducing/increasing the givinostat daily dose by 25 mg/day step resulted in a higher percentage of patients with a complete hematological response (CHR), that is, PLT ≤400 × 109 /L, WBC ≤10 × 109 /L, and HCT < 45% without phlebotomies in the last three cycles, and a lower percentage of patients with grade II toxicity events compared with 50 mg/day adjustment steps. After the eighth cycle, 85% of patients were predicted to receive a dose ≥100 mg/day and 40.90% (95% prediction interval = [34, 48.05]) to show a CHR. These results were confirmed at the end of 12th, 18th, and 24th cycles, showing a stability of the response between the eighth and 24th cycles.

Preclinical studies in the mdx mouse model of duchenne muscular dystrophy with the histone deacetylase inhibitor givinostat.

Previous work has established the existence of dystrophin-nitric oxide (NO) signaling to histone deacetylases (HDACs) that is deregulated in dystrophic muscles. As such, pharmacological interventions that target HDACs (that is, HDAC inhibitors) are of potential therapeutic interest for the treatment of muscular dystrophies. In this study, we explored the effectiveness of long-term treatment with different doses of the HDAC inhibitor givinostat in mdx mice--the mouse model of Duchenne muscular dystrophy (DMD). This study identified an efficacy for recovering functional and histological parameters within a window between 5 and 10 mg/kg/d of givinostat, with evident reduction of the beneficial effects with 1 mg/kg/d dosage. The long-term (3.5 months) exposure of 1.5-month-old mdx mice to optimal concentrations of givinostat promoted the formation of muscles with increased cross-sectional area and reduced fibrotic scars and fatty infiltration, leading to an overall improvement of endurance performance in treadmill tests and increased membrane stability. Interestingly, a reduced inflammatory infiltrate was observed in muscles of mdx mice exposed to 5 and 10 mg/kg/d of givinostat. A parallel pharmacokinetic/pharmacodynamic analysis confirmed the relationship between the effective doses of givinostat and the drug distribution in muscles and blood of treated mice. These findings provide the preclinical basis for an immediate translation of givinostat into clinical studies with DMD patients.

Modeling of human tumor xenografts and dose rationale in oncology.

Xenograft models are commonly used in oncology drug development. Although there are discussions about their ability to generate meaningful data for the translation from animal to humans, it appears that better data quality and better design of the preclinical experiments, together with appropriate data analysis approaches could make these data more informative for clinical development. An approach based on mathematical modeling is necessary to derive experiment-independent parameters which can be linked with clinically relevant endpoints. Moreover, the inclusion of biomarkers as predictors of efficacy is a key step towards a more general mechanism-based strategy.

Population pharmacokinetic-pharmacodynamic analysis of givinostat.

BACKGROUND: Givinostat (ITF2357), an oral, synthetic histone deacetylase inhibitor, significantly improved all histological muscle biopsy parameters in a Phase II study in boys with Duchenne muscular dystrophy (DMD). RESEARCH DESIGN AND METHODS: A population pharmacokinetic (PK) model, including seven clinical studies, was developed to explore the effect of covariates on givinostat PK. The final model was qualified to simulate pediatric dosing recommendations. A PK/pharmacodynamic (PD) model was developed to simulate the link between givinostat plasma concentration and platelet time course in 10-70-kg children following 6 months of givinostat 20-70 mg twice daily. RESULTS: A two-compartment model, with first-order input with lag and first-order elimination from the central compartment, described givinostat PK, demonstrating increasing apparent clearance with increasing body weight. The PK/PD model well-described platelet count time course. Weight-based dosing (arithmetic mean systemic exposure of 554-641 ng·h/mL) produced an average platelet count decrease from baseline of 45% with maximum decrease within 28 days. After 1 week and 6 months, ~1% and ~14-15% of patients, respectively, had a platelet count <75 × 109/L. CONCLUSIONS: Based on these data, givinostat dosing will be body weight adjusted and include monitoring of platelet counts to support efficacy and safety in a Phase III DMD study.

A Dynamic Energy Budget (DEB) based modeling framework to describe tumor-in-host growth inhibition and cachexia onset during anticancer treatment in in vivo xenograft studies.

Cancer anorexia-cachexia syndrome (CACS) is a very severe complication of cancer for which an adequate therapeutic strategy has not yet been defined. Recently, a notable number of new animal models of human CACS has been made available for translational purposes. Under the assumption that tumor-induced adaptations of host metabolism and tumor-host energetic competition play a major role in CACS (together with possible toxicities induced by the anticancer treatment), we developed a new Dynamic Energy Budget (DEB)-based framework, modeling tumor-in-host growth dynamics and cachexia onset in preclinical animal models during anticancer treatments. The tumor-in-host modeling approach was successfully applied on a multitude of in vivo preclinical studies involving different host species, tumor cell lines, type of anticancer agents and experimental settings among which standard xenograft studies. Obtained results strongly suggested the adoption of the tumor-in-host DEB-based approach in the preclinical oncological setting for a joint assessment of drug efficacy and toxicity and for a better design of the experiments. Further applications of the DEB-based approach to the context of poly-targeted combination therapy, anti-cachectic treatments and preclinical to clinical translation are under investigation with extremely encouraging preliminary results.

In Vitro-In Vivo Correlation (IVIVC) Population Modeling for the In Silico Bioequivalence of a Long-Acting Release Formulation of Progesterone.

Health authorities carefully evaluate any change in the batch manufacturing process of a drug before and after regulatory approval. In the absence of an adequate in vitro-in vivo correlation (Level A IVIVC), an in vivo bioequivalence (BE) study is frequently required, increasing the cost and time of drug development. This study focused on developing a Level A IVIVC for progesterone vaginal rings (PVRs), a dosage form designed for the continuous delivery in vivo. The pharmacokinetics (PK) of four batches of rings charged with 125, 375, 750 and 1500 mg of progesterone and characterized by different in vitro release rates were evaluated in two clinical studies. In vivo serum concentrations and in vitro release profiles were used to develop a population IVIVC progesterone ring (P-ring) model through a direct differential-equation-based method and a nonlinear-mixed-effect approach. The in vivo release, Rvivo(t), was predicted from the in vitro profile through a nonlinear relationship. Rvivo(t) was used as the input of a compartmental PK model describing the in vivo serum concentration dynamics of progesterone. The proposed IVIVC P-ring model was able to correctly predict the in vivo concentration-time profiles of progesterone starting from the in vitro PVR release profiles. Its internal and external predictability was carefully evaluated considering the FDA acceptance criteria for IVIVC assessment of extended-release oral drugs. Obtained results justified the use of the in vitro release testing in lieu of clinical studies for the BE assessment of any new PVRs batches. Finally, the possible use of the developed population IVIVC model as a simulator of virtual BE trials was explored through a case study.

A Tumor-in-Host DEB-Based Approach for Modeling Cachexia and Bevacizumab Resistance.

Adequate energy intake and homeostasis are fundamental for the appropriate growth and maintenance of an organism; the presence of a tumor can break this equilibrium. Tumor energy requests can lead to extreme weight loss in animals and cachexia in cancer patients. Angiogenesis inhibitors, acting on tumor vascularization, counteract this tumor-host energy imbalance, with significant results in preclinical models and more limited results in the clinic. Current pharmacokinetic-pharmacodynamic models mainly focus on the antiangiogenic effects on tumor growth but do not provide information about host conditions. A model that can predict energetic conditions that provide significant tumor growth inhibition with acceptable host body weight reduction is therefore needed. We developed a new tumor-in-host dynamic energy budget (DEB)-based model to account for the cytostatic activity of antiangiogenic treatments. Drug effect was implemented as an inhibition of the energy fraction subtracted from the host by the tumor. The model was tested on seven xenograft experiments involving bevacizumab and three different tumor cell lines. The model successfully predicted tumor and host body growth data, providing a quantitative measurement of drug potency and tumor-related cachexia. The inclusion of a hypoxia-triggered resistance mechanism enabled investigation of the decreased efficacy frequently observed with prolonged bevacizumab treatments. In conclusion, the tumor-in-host DEB-based approach has been extended to account for the effect of bevacizumab. The resistance model predicts the response to different administration protocols and, for the first time, the impact of tumor-related cachexia in different cell lines. Finally, the physiologic base of the model strongly suggests its use in translational human research. SIGNIFICANCE: A mathematical model describes tumor growth in animal models, taking into consideration the energy balance involving both the growth of tumor and the physiologic functions of the host.

Bee Visitation and Fruit Quality in Berries Under Protected Cropping Vary Along the Length of Polytunnels.

Wild and managed bees provide effective crop pollination services worldwide. Protected cropping conditions are thought to alter the ambient environmental conditions in which pollinators forage for flowers, yet few studies have compared conditions at the edges and center of growing tunnels. We measured environmental variables (temperature, relative humidity, wind speed, white light, and UV light) and surveyed activity of the managed honey bee, Apis mellifera L.; wild stingless bee, Tetragonula carbonaria Smith; and wild sweat bee, Homalictus urbanus Smith, along the length of 32 multiple open-ended polyethylene growing tunnels. These were spaced across 12 blocks at two commercial berry farms, in Coffs Harbour, New South Wales and Walkamin, North Queensland, Australia. Berry yield, fresh weight, and other quality metrics were recorded at discrete increments along the length of the tunnels. We found a higher abundance and greater number of flower visits by stingless bees and honey bees at the end of tunnels, and less frequent visits to flowers toward the middle of tunnels. The center of tunnels experienced higher temperatures and reduced wind speed. In raspberry, fruit shape was improved with greater pollinator abundance and was susceptible to higher temperatures. In blueberry, per plant yield and mean berry weight were positively associated with pollinator abundance and were lower at the center of tunnels than at the edge. Fruit quality (crumbliness) in raspberries was improved with a greater number of visits by sweat bees, who were not as susceptible to climatic conditions within tunnels. Understanding bee foraging behavior and changes to yield under protected cropping conditions is critical to inform the appropriate design of polytunnels, aid pollinator management within them, and increase economic gains in commercial berry crops.

PHA-739358, a potent inhibitor of Aurora kinases with a selective target inhibition profile relevant to cancer.

PHA-739358 is a small-molecule 3-aminopyrazole derivative with strong activity against Aurora kinases and cross-reactivities with some receptor tyrosine kinases relevant for cancer. PHA-739358 inhibits all Aurora kinase family members and shows a dominant Aurora B kinase inhibition-related cellular phenotype and mechanism of action in cells in vitro and in vivo. p53 status-dependent endoreduplication is observed upon treatment of cells with PHA-739358, and phosphorylation of histone H3 in Ser(10) is inhibited. The compound has significant antitumor activity in different xenografts and spontaneous and transgenic animal tumor models and shows a favorable pharmacokinetic and safety profile. In vivo target modulation is observed as assessed by the inhibition of the phosphorylation of histone H3, which has been validated preclinically as a candidate biomarker for the clinical phase. Pharmacokinetics/pharmacodynamics modeling was used to define drug potency and to support the prediction of active clinical doses and schedules. We conclude that PHA-739358, which is currently tested in clinical trials, has great therapeutic potential in anticancer therapy in a wide range of cancers.

Development and validation of in silico models for estimating drug preformulation risk in PEG400/water and Tween80/water systems.

Solubility is one of the most important properties of drug candidates for achieving the targeted plasma concentrations following oral dosing. Furthermore, the formulations adopted in the in vivo preclinical studies, for both oral and intravenous administrations, are usually solutions. To formulate compounds sparingly soluble in water, pharmaceutically acceptable cosolvents or surfactants are typically employed to increase solubility. Compounds poorly soluble also in these systems will likely show severe formulation issues. In such cases, relatively high amount of compounds, rarely available in the early preclinical phases, are needed to identify the most appropriate dosing vehicles. Hence, the purpose of this study was to build two computational models which, on the basis of the molecular structure, are able to predict the compound solubility in two vehicle systems (40% PEG400/water and 10% Tween80/water) used in our company as screening tools for anticipating potential formulation issues. The two models were developed using the solubility data obtained from the analysis of approximately 2000 chemically diverse compounds. The structural diversity and the drug-like space covered by these molecules were investigated using the ChemGPS methodology. The compounds were classified (high/low preformulation risk) based on the experimental solubility value range. A combination of descriptors (i.e. logD at two different pH, E-state indices and other 2D structural descriptors) was correlated to these classes using partial least squares discriminant (PLSD) analysis. The overall accuracy of each PLSD model applied to independent sets of compounds was approximately 78%. The accuracy reached when the models were used in combination to identify molecules with low preformulation risk in both systems was 83%. The models appeared a valuable tool for predicting the preformulation risk of drug candidates and consequently for identifying the most appropriate dosing vehicles to be further investigated before the first in vivo preclinical studies. Since only a small number of 2D descriptors is need to evaluate the preformulation risk classes, the models resulted easy to use and characterized by high throughput.

Evaluation of a basic physiologically based pharmacokinetic model for simulating the first-time-in-animal study.

The objective of this study was to evaluate a physiologically based pharmacokinetic (PBPK) approach for predicting the plasma concentration-time curves expected after intravenous administration of candidate drugs to rodents. The predictions were based on a small number of properties that were either calculated based on the structure of the candidate drug (octanol:water partition coefficient, ionization constant(s)) or obtained from the typical high-throughput screens implemented in the early drug discovery phases (fraction unbound in plasma and hepatic intrinsic clearance). The model was tested comparing the predicted and the observed pharmacokinetics of 45 molecules. This dataset included six known drugs and 39 drug candidates from different discovery programs, so that the performance of the model could be evaluated in a real discovery case scenario. The plasma concentration-time curves were predicted with good accuracy, the pharmacokinetic parameters being on average two- to three-fold of actual values. Multivariate analysis was used for identifying the candidate properties which were likely associated to biased predictions. The application of this approach was found useful for the prioritization of the in vivo pharmacokinetics screens and the design of the first-time-in-animal studies.

1,4,5,6-tetrahydropyrrolo[3,4-c]pyrazoles: identification of a potent Aurora kinase inhibitor with a favorable antitumor kinase inhibition profile.

The optimization of a series of 5-phenylacetyl 1,4,5,6-tetrahydropyrrolo[3,4-c]pyrazole derivatives toward the inhibition of Aurora kinases led to the identification of compound 9d. This is a potent inhibitor of Aurora kinases that also shows low nanomolar potency against additional anticancer kinase targets. Based on its high antiproliferative activity on different cancer cell lines, favorable chemico-physical and pharmacokinetic properties, and high efficacy in in vivo tumor models, compound 9d was ultimately selected for further development.

Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents.

The available mathematical models describing tumor growth and the effect of anticancer treatments on tumors in animals are of limited use within the drug industry. A simple and effective model would allow applying quantitative thinking to the preclinical development of oncology drugs. In this article, a minimal pharmacokinetic-pharmacodynamic model is presented, based on a system of ordinary differential equations that link the dosing regimen of a compound to the tumor growth in animal models. The growth of tumors in nontreated animals is described by an exponential growth followed by a linear growth. In treated animals, the tumor growth rate is decreased by a factor proportional to both drug concentration and number of proliferating tumor cells. A transit compartmental system is used to model the process of cell death, which occurs at later times. The parameters of the pharmacodynamic model are related to the growth characteristics of the tumor, to the drug potency, and to the kinetics of the tumor cell death. Therefore, such parameters can be used for ranking compounds based on their potency and for evaluating potential differences in the tumor cell death process. The model was extensively tested on discovery candidates and known anticancer drugs. It fitted well the experimental data, providing reliable parameter estimates. On the basis of the parameters estimated in a first experiment, the model successfully predicted the response of tumors exposed to drugs given at different dose levels and/or schedules. It is, thus, possible to use the model prospectively, optimizing the design of new experiments.

Histological effects of givinostat in boys with Duchenne muscular dystrophy.

Duchenne Muscular Dystrophy (DMD) is caused by mutations in the dystrophin gene leading to dystrophin deficiency, muscle fiber degeneration and progressive fibrotic replacement of muscles. Givinostat, a histone deacetylase (HDAC) inhibitor, significantly reduced fibrosis and promoted compensatory muscle regeneration in mdx mice. This study was conducted to evaluate whether the beneficial histological effects of Givinostat could be extended to DMD boys. Twenty ambulant DMD boys aged 7 to <11 years on stable corticosteroid treatment were enrolled in the study and treated for ≥12 months with Givinostat. A muscle biopsy was collected at the beginning and at the end of treatment to evaluate the amount of muscle and fibrotic tissue. Histological effects were the primary objectives of the study. Treatment with Givinostat significantly increased the fraction of muscle tissue in the biopsies and reduced the amount of fibrotic tissue. It also substantially reduced tissue necrosis and fatty replacement. Overall the drug was safe and tolerated. Improvement in functional tests was not observed in this study, but the sample size of the study was not sufficient to draw definitive conclusions. This study showed that treatment with Givinostat for more than 1 year significantly counteracted histological disease progression in ambulant DMD boys aged 7 to 10 years.

Dose escalation study of intravenous estramustine phosphate in combination with Paclitaxel and Carboplatin in patients with advanced prostate cancer.

PURPOSE: The purpose is to determine a safe weekly dose of i.v. estramustine phosphate (EMP) to combine with weekly paclitaxel and monthly carboplatin in patients with advanced prostate cancer. EXPERIMENTAL DESIGN: Patients with advanced prostate cancer (castrate and noncastrate) were administered escalating doses of weekly 1-h infusion of i.v. EMP (500-1000-1500 mg/m(2)) in combination with weekly paclitaxel (100 mg/m(2) over 1 h) and i.v. carboplatin (area under the curve 6 mg/ml-min every 4 weeks). Four weeks of therapy were considered one cycle. In the first three cohorts, EMP was given i.v. 3 h before paclitaxel. Cohorts 4 and 5 reversed the administration order: EMP (doses 1000-1500 mg/m(2)) was given immediately after the end of paclitaxel infusion. Plasma levels of EMP and its metabolites, estramustine and estromustine, were monitored at time 0, at 120 min, and approximately at 20, 21, and 168 h from the start of EMP infusion. Paclitaxel concentrations were determined at basal (0), 30, 60, 90, and 120 min and 18 h after the start of paclitaxel infusion, and a concentration-time curve was estimated. Pharmacokinetic evaluation was performed in cycles 1 and 2 during the first week of therapy. RESULTS: Nineteen patients were entered on the initial three dose levels (cohorts 1-3). Dose-limiting transient hepatic toxicity was encountered in cohort 3 (EMP = 1500 mg/m(2)). An additional 13 patients were treated with paclitaxel (100 mg/m(2)) first, followed by i.v. EMP at 1000 mg/m(2) (cohort 4), and 1500 mg/m(2) (cohort 5). No dose-limiting toxicities were seen, and cohort 5 was determined safe for Phase II studies. Thromboembolic events were observed in 9% of patients (no prophylactic coumadin was used). Plasma concentrations of EMP and metabolites increased proportionally with dose. In all cohorts, there was a slight decrease in EMP and estramustine plasma concentrations between cycles 1 and 2. Although not significant, higher levels of estromustine at cycle 2 were observed in comparison to cycle 1. Decreased clearance of paclitaxel leading to higher than expected paclitaxel plasma concentrations was observed during the first cycle of therapy. Paclitaxel plasma concentrations were lower during cycle 2. In 17 patients with androgen-independent disease, 59% had >/=50% posttherapy decline in PSA and 22% showed measurable disease regression. CONCLUSIONS: The regimen of weekly i.v. EMP in combination with paclitaxel and carboplatin can be safely administered with hepatic toxicity being transient and reversible. Pharmacokinetic results suggest that EMP competitively inhibits the biotransformation of paclitaxel after the first administration. This effect is counterbalanced, after repeated administrations, by a possible induction of the metabolic system caused by EMP. Phase II testing is ongoing to evaluate the efficacy of this combination.

The effects of degree of hepatic or renal impairment on the pharmacokinetics of exemestane in postmenopausal women.

PURPOSE: Two studies were conducted to compare the pharmacokinetics and tolerability of exemestane in postmenopausal subjects with various degrees of impairment of hepatic or renal function with those in healthy postmenopausal subjects. METHODS: All subjects were postmenopausal females. In study 1, nine subjects had normal hepatic function (Child-Pugh grade A), and nine had moderately (grade B) and eight severely (grade C) impaired hepatic function. In study 2, six subjects had normal renal function, and six moderately (creatinine clearance, CrCL, 30-60 ml/min per 1.73 m(2)) and seven severely (CrCL <29 ml/min per 1.73 m(2)) impaired renal function. Each subject took a single oral dose of 25 mg exemestane. Samples of plasma (to 168 h after dosing) and urine (to 72 h in study 1, or 96 h in study 2) were taken for pharmacokinetic analysis. Safety and tolerability were assessed by monitoring vital signs, laboratory safety tests, ECG and adverse events. RESULTS: Exposure to exemestane was increased two- to threefold in patients with hepatic impairment. Thus, the geometric mean AUC(0- infinity ) values were 41.71 (90% CI 32.2 to 54.0), 99.02 (76.5 to 128.2) and 118.59 ng.h/ml (90.2 to 156.0) in healthy subjects, and in patients with moderate and severe hepatic impairment, respectively ( P<0.01). C(max) also increased twofold. Compared with healthy subjects, patients with hepatic impairment had lower apparent oral clearance and apparent volume of distribution of exemestane. Renal impairment was also associated with two- to threefold increases in AUC(0- infinity ): 34.64 (90% CI 23.9 to 50.2), 94.10 (64.9 to 136.4) and 65.52 ng.h/ml (46.5 to 92.4) in healthy subjects, and in patients with moderate and severe hepatic impairment, respectively ( P<0.05). C(max) did not change significantly. Apparent oral clearance was directly correlated with CrCL ( r(2)=0.43). Exemestane was tolerated well, with no safety concerns. CONCLUSIONS: Oral clearance of exemestane was reduced in the presence of significant hepatic or renal disease. However, in view of the relatively large safety margin and the mild nature of the side effects of exemestane, the therapeutic implications of these changes in pharmacokinetics are considered minor and of no clinical significance.

In vitro cell growth pharmacodynamic studies: a new nonparametric approach to determining the relative importance of drug concentration and treatment time.

PURPOSE: The effect of an anticancer treatment on tumor cell proliferation in vitro can be described as a three-dimensional surface where the inhibitory effect is related to drug concentration and treatment time. The analysis of this kind of response surface could provide critical information: for example, it could indicate whether a prolonged exposure to a low concentration of an anticancer agent will produce a different effect from exposure to higher concentrations for a shorter period of time. The parametric approach available in the literature was not flexible enough to accommodate the behavior of the response surface in some of the data sets collected as part of our research programs. Therefore, a new, general, nonparametric approach was developed. METHODS: The response surface of the inhibition of cell-based tumor growth was described using a radial basis function neural network (RBF-NN). The RBF-NN was trained using regularization theory, which provided the initialization of a constrained quadratic optimization algorithm that imposes monotonicity of the surface with respect to both concentration and exposure time. RESULTS: In the two analyzed cases (doxorubicin and flavopiridol), the proposed method was accurate and reliable in describing the inhibition surface of tumor cell growth as a function of drug concentration and exposure time. Residuals were small and unbiased. The new method improved on the parametric approach when the relative importance of drug concentration and exposure time in determining the overall effect was not constant across the experimental data. CONCLUSIONS: The proposed RBF-NN can be reliably applied for the analysis in cell-based tumor growth inhibition studies. This approach can be used for optimizing the administration regimens to be adopted in vivo. The use of this methodology can be easily extended to any cell-based experiment, in which the outcome can be seen as a function of two experimental variables.

Assessment of normal and tumor tissue uptake of MAG-CPT, a polymer-bound prodrug of camptothecin, in patients undergoing elective surgery for colorectal carcinoma.

PURPOSE: MAG-camptothecin (MAG-CPT) is the lead compound of a novel drug delivery system in which an active cytotoxic moiety, camptothecin (CPT), is covalently linked to a soluble polymeric carrier (MAG) to form an inactive prodrug. The mechanism of action of CPT remains unaltered, but the delivery system is thought to allow the carrier-bound drug to accumulate in tumor tissues and release the active CPT locally. This proof-of-concept clinical study was designed to determine whether MAG-CPT was preferentially delivered to or retained in tumor tissue compared to adjacent normal tissue or plasma, and to estimate the degree of intratissue release of CPT. METHODS: This was an open, non-randomized study in ten adult patients scheduled for elective surgery for colorectal cancer. Patients received a single dose of 60 mg/m2 (CPT equivalent) of MAG-CPT 24 h, 3 days or 7 days prior to surgery. Plasma, tumor, and adjacent normal tissue samples were collected simultaneously at the time of surgery and analyzed for MAG-bound and released CPT concentrations. RESULTS: MAG-bound and free CPT concentrations in plasma, tumor, and normal tissue achieved equilibrium by 24 h after dosing, declining in parallel up to 7 days after dosing. MAG-bound CPT was delivered to similar levels to tumor and normal tissue. At 24 h after dosing, the mean+/-SD MAG-bound CPT concentrations were 861+/-216 ng/g in tumor and 751+/-215 ng/g in adjacent normal tissue, and free CPT concentrations were lower in tumor than in normal tissue (12.2+/-4.7 ng/g and 21.9+/-6.7 ng/g, respectively). At 24 h after dosing, mean+/-SD ratios of MAG-bound and free CPT in tumor and plasma were 0.13+/-0.03 and 0.22+/-0.09, respectively, and the ratios did not change for up to 7 days after dosing, indicating a lack of preferential retention of MAG-bound CPT or release of free CPT in tumor. These results are in marked contrast to previous data from animal tumor xenograft studies, where MAG-CPT levels were higher in tissue than in plasma at 3 and 7 days after a single i.v. dose. CONCLUSIONS: Delivery of CPT to the target tumor tissue is achievable by means of the MAG-CPT polymer-bound delivery system, with the equilibrium between plasma and tumor tissue concentrations of released CPT being established within 24 h after dosing. However, preferential retention of MAG-bound or released CPT in the tumor relative to normal tissue or plasma was not detected during the 7 days after dosing. The methods employed in our study could be of use in making "go/no-go" decisions on further development of anticancer drugs.

A4S: a user-friendly graphical tool for pharmacokinetic and pharmacodynamic (PK/PD) simulation.

Effective communication of PK/PD principles and results in a biomedical research environment remains a significant challenge which can result in lack of buy-in and engagement from scientists outside the modeling and simulation communities. In our view, one of the barriers in this area is a lack of user-friendly tools which allow "non experts" to use PK/PD models without the need to develop technical skills and expertise in advanced mathematical principles and specialist software. The costs of commercial software may also prevent large-scale distribution. One attempt to address this issue internally in our research organizations has resulted in the development of the A4S ("Accelera for Sandwich") software, which is a simple-to-use, menu-drive Matlab-based PK/PD simulator targeted at biomedical researchers with little PK/PD experience.

Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth after administration of an anti-angiogenic agent, bevacizumab, as single-agent and combination therapy in tumor xenografts.

PURPOSE: Pharmacokinetic-pharmacodynamic (PK-PD) models able to predict the action of anticancer compounds in tumor xenografts have an important impact on drug development. In case of anti-angiogenic compounds, many of the available models show difficulties in their applications, as they are based on a cell kill hypothesis, while these drugs act on the tumor vascularization, without a direct tumor cell kill effect. For this reason, a PK-PD model able to describe the tumor growth modulation following treatment with a cytostatic therapy, as opposed to a cytotoxic treatment, is proposed here. METHODS: Untreated tumor growth was described using an exponential growth phase followed by a linear one. The effect of anti-angiogenic compounds was implemented using an inhibitory effect on the growth function. The model was tested on a number of experiments in tumor-bearing mice given the anti-angiogenic drug bevacizumab either alone or in combination with another investigational compound. Nonlinear regression techniques were used for estimating the model parameters. RESULTS: The model successfully captured the tumor growth data following different bevacizumab dosing regimens, allowing to estimate experiment-independent parameters. A combination model was also developed under a 'no-interaction' assumption to assess the effect of the combination of bevacizumab with a target-oriented agent. The observation of a significant difference between model-predicted and observed tumor growth curves was suggestive of the presence of a pharmacological interaction that was further accommodated into the model. CONCLUSIONS: This approach can be used for optimizing the design of preclinical experiments. With all the inherent limitations, the estimated experiment-independent model parameters can be used to provide useful indications for the single-agent and combination regimens to be explored in the subsequent development phases.