Age and dPCR can predict relapse in CML patients who discontinued imatinib: the ISAV study.

Imatinib is effective for the treatment of chronic myeloid leukemia (CML). However even undetectable BCR-ABL1 by Q-RT-PCR does not equate to eradication of the disease. Digital-PCR (dPCR), able to detect 1 BCR-ABL1 positive cell out of 10(7) , has been recently developed.

Predicting myelosuppression of drugs from in silico models.

Anticancer agents targeting proliferating cell populations in tumor as well as in normal tissues can lead to a number of side effects including hematotoxicity, a common dose-limiting toxicity associated with oncology drugs. Myelosuppression, regarded as unacceptable for other therapeutic indications, is considered a clinical risk also for new targeted anticancer drugs acting specifically on tumor cells. Thus, it becomes important not only to evaluate the potential toxicity of such new therapeutics to human hematopoietic tissue during preclinical development but also to anticipate this liability in early drug discovery.

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.

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.

Computational models for identifying potential P-glycoprotein substrates and inhibitors.

Multidrug resistance mediated by ATP binding cassette (ABC) transporters such as P-glycoprotein (P-gp) represents a serious problem for the development of effective anticancer drugs. In addition, P-gp has been shown to reduce oral absorption, modulate hepatic, renal, or intestinal elimination, and restrict blood-brain barrier penetration of several drugs. Consequently, there is a great interest in anticipating whether drug candidates are P-gp substrates or inhibitors.

Structure-based approaches to improve selectivity: CDK2-GSK3beta binding site analysis.

An evaluation and comparison of two different approaches, GRID/CPCA and GRIND/CPCA (CPCA = consensus principal component analysis; GRIND = GRid-INdependent Descriptors), suitable for visualizing the structural differences between related proteins is presented. Ten crystal structures of CDK2/cyclin A and GSK3beta solved in-house with different inhibitors were compared with the aim of highlighting regions that could be potential sites for gaining selectivity for CDK2 versus GSK3beta. The analyses pointed out remarkable differences in the backs of the CDK2-GSK3beta ATP binding pockets that guided the optimization toward a selective benzodipyrazole CDK2 inhibitor.

Virtual screening to enrich a compound collection with CDK2 inhibitors using docking, scoring, and composite scoring models.

Docking programs can generate subsets of a compound collection with an increased percentage of actives against a target (enrichment) by predicting their binding mode (pose) and affinity (score), and retrieving those with the highest scores. Using the QXP and GOLD programs, we compared the ability of six single scoring functions (PLP, Ligscore, Ludi, Jain, ChemScore, PMF) and four composite scoring models (Mean Rank: MR, Rank-by-Vote: Vt, Bayesian Statistics: BS and PLS Discriminant Analysis: DA) to separate compounds that are active against CDK2 from inactives. We determined the enrichment for the entire set of actives (IC50 < 10 microM) and for three activity subsets.

Influence of molecular flexibility and polar surface area metrics on oral bioavailability in the rat.

The relationship of rotatable bond count (N(rot)) and polar surface area (PSA) with oral bioavailability in rats was examined for 434 Pharmacia compounds and compared with an earlier report from Veber et al. (J. Med.

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.