The emerging discipline of systems pharmacology aims to combine analysis and computational modeling of cellular regulatory networks with quantitative pharmacology approaches to drive the drug discovery processes, predict rare adverse events, and catalyze the practice of personalized precision medicine. Here, we introduce the concept of enhanced pharmacodynamic (ePD) models, which synergistically combine the desirable features of systems biology and current PD models within the framework of ordinary or partial differential equations. ePD models that analyze regulatory networks involved in drug action can account for a drug’s multiple targets and for the effects of genomic, epigenomic, and posttranslational changes on the drug efficacy. This new knowledge can drive drug discovery and shape precision medicine.

BACKGROUND-Malignant brain tumors are among the most challenging to treat and at present there are no uniformly successful treatment strategies. Standard treatment regimens consist of maximal surgical resection followed by radiotherapy and chemotherapy. The limited survival advantage attributed to chemotherapy is partially due to low CNS penetration of antineoplastic agents across the blood-brain barrier (BBB).OBJECTIVE-The objective of this paper is to review recent approaches to deliver anticancer drugs into primary brain tumors. CONCLUSION-Analysis of the available data indicates that novel approaches may be useful for CNS delivery, yet an appreciation of pharmacokinetic issues, and improved knowledge of tumor biology will be needed to significantly impact drug delivery to the target site. METHODS-Both

To evaluate the toxicity, pharmacological and biological properties of ATN-161, a five -amino-acid peptide derived from the synergy region of fibronectin, adult patients with advanced solid tumours were enrolled in eight sequential dose cohorts (0.1 -16 mg kg À1 ), receiving ATN-161 administered as a 10-min infusion thrice weekly. Pharmacokinetic sampling of blood and urine over 7 h was performed on Day 1. Twenty-six patients received from 1 to 14 4-week cycles of treatment. The total number of cycles administered to all patients was 86, without dose-limiting toxicities. At dose levels above 0.5 mg kg À1 , mean total clearance and volume of distribution showed dose-independent pharmacokinetics (PKs). At 8.0 and 16.0 mg kg À1 , clearance of ATN-161 was reduced, suggesting saturable PKs. Dose escalation was halted at 16 mg kg À1 when drug exposure (area under the curve) exceeded that associated with efficacy in animal models. There were no objective responses. Six patients received more than four cycles of treatment (4112 days). Three patients received 10 or more cycles (X280 days). ATN-161 was well tolerated at all dose levels. Approximately, 1/3 of the patients in the study manifested prolonged stable disease. These findings suggest that ATN-161 should be investigated further as an antiangiogenic and antimetastatic cancer agent alone or with chemotherapy.

A simple viscometric method was used to quantify mucin-polymer bioadhesive bond strength. Viscosities of 15% (w/v) porcine gastric mucin dispersions in 0.1 N HCl (pH 1) or 0.1 N acetate buffer (pH 5.5) were measured with a Brookfield viscometer in the absence (eta m) or presence (eta t) of selected neutral, anionic, and cationic polymers (0.1-2.5%, w/v). Viscosity components of bioadhesion (eta b) were calculated from the equation, eta t = eta m + eta p + eta b, where eta p is the viscosity of corresponding pure polymer solution as measured by an Ostwald viscometer. The forces of bioadhesion (F) were calculated from the equation, F = eta b sigma, where sigma is the rate of shear/sec. eta b's and F's for polyelectrolytes, e.g., polyacrylic acid, cationic gelatin, and chitosan were always higher in acetate buffer than in HCl. Validity of the technique and the effect of ionic charge, polymer conformation, and rate of shear on eta b and F are discussed, as is a comparison of this method to other methods for evaluating bioadhesive materials.

Difficulties in direct measurement of drug concentrations in human tissues have hampered the understanding of drug accumulation in tumors and normal tissues. We propose a new system analysis modeling approach to characterize drug distribution in tissues based on human positron emission tomography (PET) data. The PET system analysis method was applied to temozolomide, an important alkylating agent used in the treatment of brain tumors, as part of standard temozolomide treatment regimens in patients. The system analysis technique, embodied in the convolution integral, generated an impulse response function that, when convolved with temozolomide plasma concentration input functions, yielded predicted normal brain and brain tumor temozolomide concentration profiles for different temozolomide dosing regimens (75-200 mg/m 2 /d). Predicted peak concentrations of temozolomide ranged from 2.9 to 6.7 Mg/mL in human glioma tumors and from 1.8 to 3.7 Mg/mL in normal brain, with the total drug exposure, as indicated by the tissue/ plasma area under the curve ratio, being about 1.3 in tumor compared with 0.9 in normal brain. The higher temozolomide exposures in brain tumor relative to normal brain were attributed to breakdown of the blood-brain barrier and possibly secondary to increased intratumoral angiogenesis. Overall, the method is considered a robust tool to analyze and predict tissue drug concentrations to help select the most rational dosing schedules. [Cancer Res 2009;69(1):120-7]