Physiologically relevant binding affinity quantification of monoclonal antibody PF-00547659 to mucosal addressin cell adhesion molecule for in vitro in vivo correlation.

BACKGROUND AND PURPOSE: A monoclonal antibody (PF-00547659) against mucosal addressin cell adhesion molecule (MAdCAM), expressed as both soluble (sMAdCAM) and trans-membrane (mMAdCAM) target forms, showed over 30-fold difference in antibody-target KD between in vitro (Biacore) and clinically derived (KD,in-vivo ) values. Back-scattering interferometry (BSI) was applied to acquire physiologically relevant KD values which were used to establish in vitro and in vivo correlation (IVIVC). EXPERIMENTAL APPROACH: BSI was applied to obtain KD values between PF-00547659 and recombinant human MAdCAM in buffer or CHO cells and endogenous MAdCAM in human serum or colon tissue. CHO cells and tissue were minimally processed to yield homogenate containing membrane vesicles and soluble proteins. A series of binding affinities in serum with various dilution factors was used to estimate both KD,in-vivo and target concentrations; MAdCAM concentrations were also measured using LC-MS/MS. KEY RESULTS: BSI measurements revealed low KD values (higher affinity) for sMAdCAM in buffer and serum, yet a 20-fold higher KD value (lower affinity) for mMAdCAM in CHO, mMAdCAM and sMAdCAM in tissue. BSI predicted KD,in-vivo in serum was similar to clinically derived KD,in-vivo , and the BSI-estimated serum sMAdCAM concentration also matched the measured concentration by LC-MS/MS. CONCLUSIONS AND IMPLICATIONS: Our results successfully demonstrated that BSI measurements of physiologically relevant KD values can be used to establish IVIVC, for PF-00547659 to MAdCAM despite the lack of correlation when using Biacore measured KD and accurately estimates endogenous target concentrations. The application of BSI would greatly enhance successful basic pharmacological research and drug development.

The development and validation of a computational model to predict rat liver microsomal clearance.

As the cost of discovering and developing new pharmaceutically relevant compounds continues to rise, it is increasingly important to select the right molecules to prosecute very early in drug discovery. The development of high throughput in vitro assays of hepatic metabolic clearance has allowed for vast quantities of data generation; however, these large screens are still costly and remain dependant on animal usage. To further expand the value of these screens and ultimately aid in animal usage reduction, we have developed an in silico model of rat liver microsomal (RLM) clearance. This model combines a large amount of rat clearance data (n = 27,697) generated at multiple Pfizer laboratories to represent the broadest possible chemistry space. The model predicts RLM stability (with 82% accuracy and a kappa value of 0.65 for test data set) based solely on chemical structural inputs, and provides a clear assessment of confidence in the prediction. The current in silico model should help accelerate the drug discovery process by using confidence-based stability-driven prioritization, and reduce cost by filtering out the most unstable/undesirable molecules. The model can also increase efficiency in the evaluation of chemical series by optimizing iterative testing and promoting rational drug design.

Implementation of an ADME enabling selection and visualization tool for drug discovery.

The pharmaceutical industry has large investments in compound library enrichment, high throughput biological screening, and biopharmaceutical (ADME) screening. As the number of compounds submitted for in vitro ADME screens increases, data analysis, interpretation, and reporting will become rate limiting in providing ADME-structure-activity relationship information to guide the synthetic strategy for chemical series. To meet these challenges, a software tool was developed and implemented that enables scientists to explore in vitro and in silico ADME and chemistry data in a multidimensional framework. The present work integrates physicochemical and ADME data, encompassing results for Caco-2 permeability, human liver microsomal half-life, rat liver microsomal half-life, kinetic solubility, measured log P, rule of 5 descriptors (molecular weight, hydrogen bond acceptors, hydrogen bond donors, calculated log P), polar surface area, chemical stability, and CYP450 3A4 inhibition. To facilitate interpretation of this data, a semicustomized software solution using Spotfire was designed that allows for multidimensional data analysis and visualization. The solution also enables simultaneous viewing and export of chemical structures with the corresponding ADME properties, enabling a more facile analysis of ADME-structure-activity relationship. In vitro and in silico ADME data were generated for 358 compounds from a series of human immunodeficiency virus protease inhibitors, resulting in a data set of 5370 experimental values which were subsequently analyzed and visualized using the customized Spotfire application. Implementation of this analysis and visualization tool has accelerated the selection of molecules for further development based on optimum ADME characteristics, and provided medicinal chemistry with specific, data driven structural recommendations for improvements in the ADME profile.

Effects of organic anion, organic cation, and dipeptide transport inhibitors on cefdinir in the isolated perfused rat kidney.

Cefdinir (Omnicef; Abbott Laboratories) is a cephalosporin antibiotic primarily eliminated by the kidney. Nonlinear renal elimination of cefdinir has been previously reported. Cefdinir renal transport mechanisms were studied in the erythrocyte-free isolated perfused rat kidney. Studies were performed with drug-free perfusate and perfusate containing cefdinir alone to establish the baseline physiology and investigate cefdinir renal elimination characteristics. To investigate cefdinir renal transport mechanisms, inhibition studies were conducted by coperfusing cefdinir with inhibitors of the renal organic anion (probenecid), organic cation (tetraethylammonium), or dipeptide (glycylsarcosine) transport system. Cefdinir concentrations in biological samples were determined using reversed-phase high-performance liquid chromatography. Differences between treatments and controls were evaluated using analysis of variance and Dunnett's test. The excretion ratio (ER; the renal clearance corrected for the fraction unbound and glomerular filtration rate) for cefdinir was 5.94, a value indicating net renal tubular secretion. Anionic, cationic, and dipeptide transport inhibitors all significantly affected the cefdinir ER. With probenecid, the ER was reduced to 0.59, clearly demonstrating a significant reabsorptive component to cefdinir renal disposition. This finding was confirmed by glycylsarcosine studies, in which the ER was elevated to 7.95, indicating that reabsorption was mediated, at least in part, by the dipeptide transporter system. The effects of the organic cation tetraethylammonium, in which the ER was elevated to 7.53, were likely secondary in nature. The anionic secretory pathway was found to be the predominant mechanism for cefdinir renal excretion.