Chad L. Stoner

The road map to oral bioavailability: an industrial perspective

Optimisation of oral bioavailability is a continuing challenge for the pharmaceutical and biotechnology industries. The number of potential drug candidates requiring invivo evaluation has significantly increased with the advent of combinatorial chemistry. In addition, drug discovery programmes are increasingly forced into more lipophilic and lower solubility chemical space. To aid in the use of invitro and insilico tools as well as reduce the number of invivo studies required, a team-based discussion tool is proposed that provides a road map to guide the selection of profiling assays that should be considered when optimising oral bioavailability. This road map divides the factors that contribute to poor oral bioavailability into two interrelated categories: absorption and metabolism. This road map provides an interface for cross discipline discussions and a systematic approach to the experimentation that drives the drug discovery process towards a common goal acceptable oral bioavailability using minimal resources in an acceptable time frame.

Integrated in silico-in vitro strategy for addressing cytochrome P450 3A4 time-dependent inhibition.

Throughout the past decade, the expectations from the regulatory agencies for safety, drug-drug interactions (DDIs), pharmacokinetic, and disposition characterization of new chemical entities (NCEs) by pharmaceutical companies seeking registration have increased. DDIs are frequently assessed using in silico, in vitro, and in vivo methodologies. However, a key gap in this screening paradigm is a full structural understanding of time-dependent inhibition (TDI) on the cytochrome P450 systems, particularly P450 3A4. To address this, a number of high-throughput in vitro assays have been developed. This work describes an automated assay for TDI using two concentrations at two time points (2 + 2 assay). Data generated with this assay for over 2000 compounds from multiple therapeutic programs were used to generate in silico Bayesian classification models of P450 3A4-mediated TDI. These in silico models were validated using several external test sets and multiple random group testing (receiver operator curve value >0.847). We identified a number of substructures that were likely to elicit TDI, the majority containing indazole rings. These in vitro and in silico approaches have been implemented as a part of the Pfizer screening paradigm. The Bayesian models are available on the intranet to guide synthetic strategy, predict whether a NCE is likely to cause a TDI via P450 3A4, filter for in vitro testing, and identify substructures important for TDI as well as those that do not cause TDI. This represents an integrated in silico-in vitro strategy for addressing P450 3A4 TDI and improving the efficiency of screening.

Discovery of a Series of Imidazo[4,5-b]pyridines with Dual Activity at Angiotensin II Type 1 Receptor and Peroxisome Proliferator-Activated Receptor-gamma.

Mining of an in-house collection of angiotensin II type 1 receptor antagonists to identify compounds with activity at the peroxisome proliferator-activated receptor-γ (PPARγ) revealed a new series of imidazo[4,5-b]pyridines 2 possessing activity at these two receptors. Early availability of the crystal structure of the lead compound 2a bound to the ligand binding domain of human PPARγ confirmed the mode of interaction of this scaffold to the nuclear receptor and assisted in the optimization of PPARγ activity. Among the new compounds, (S)-3-(5-(2-(1H-tetrazol-5-yl)phenyl)-2,3-dihydro-1H-inden-1-yl)-2-ethyl-5-isobutyl-7-methyl-3H-imidazo[4,5-b]pyridine (2l) was identified as a potent angiotensin II type I receptor blocker (IC(50) = 1.6 nM) with partial PPARγ agonism (EC(50) = 212 nM, 31% max) and oral bioavailability in rat. The dual pharmacology of 2l was demonstrated in animal models of hypertension (SHR) and insulin resistance (ZDF rat). In the SHR, 2l was highly efficacious in lowering blood pressure, while robust lowering of glucose and triglycerides was observed in the male ZDF rat.

Synthesis and SAR of tolylamine 5-HT6 antagonists

The synthesis and SAR of tolylamines with 5-HT(6) receptor antagonist activity is presented. The amine, core aromatic, peripheral aromatic, and ether linker moieties of HTS hit 1 were modulated and the effect on potency at 5-HT(6) examined. Tolylpiperidine ether 9h was found to possess desirable pharmacokinetic (PK) properties, and was also shown to enhance cognition in the rat novel object recognition paradigm.

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.

Discovery of a novel class of targeted kinase inhibitors that blocks protein kinase C signaling and ameliorates retinal vascular leakage in a diabetic rat model

Protein kinase C (PKC) family members such as PKCbetaII may become activated in the hyperglycemic state associated with diabetes. Preclinical and clinical data implicate aberrant PKC activity in the development of diabetic microvasculature abnormalities. Based on this potential etiological role for PKC in diabetic complications, several therapeutic PKC inhibitors have been investigated in clinical trials for the treatment of diabetic patients. In this report, we present the discovery and preclinical evaluation of a novel class of 3-amino-pyrrolo[3,4-c]pyrazole derivatives as inhibitors of PKC that are structurally distinct from the prototypical indolocarbazole and bisindolylmaleimide PKC inhibitors. From this pyrrolo-pyrazole series, several compounds were identified from biochemical assays as potent, ATP-competitive inhibitors of PKC activity with high specificity for PKC over other protein kinases. These compounds were also found to block PKC signaling activity in multiple cellular functional assays. PF-04577806, a representative from this series, inhibited PKC activity in retinal lysates from diabetic rats stimulated with phorbol myristate acetate. When orally administered, PF-04577806 showed good exposure in the retina of diabetic Long-Evans rats and ameliorated retinal vascular leakage in a streptozotocin-induced diabetic rat model. These novel PKC inhibitors represent a promising new class of targeted protein kinase inhibitors with potential as therapeutic agents for the treatment of patients with diabetic microvascular complications.

In Silico Approaches to Predict DDIs

This chapter will briefly describe in silico methodologies for the prediction of drug–drug interactions (DDIs) and highlight the broad application of computational tools to study DDIs. This chapter outlines the main methodologies currently applied including QSAR modeling, pharmacophore modeling, docking, and the combination of in silico and experimental approaches. There is an emphasis on cytochrome P450 and how in silico models are used in current drug discovery efforts to reduce the risk of DDIs. The discussion of the limitations associated with the various approaches as well as future aspects of DDI modeling and simulation can give researchers helpful guidance to this useful and growing area.