Safety testing of metabolites: Expectations and outcomes

Exploration of 3,6-dihydroimidazo(4,5-d)pyrrolo(2,3-b)pyridin-2(1H)-one derivatives as JAK inhibitors using various in silico techniques

This study focuses on understanding the structural features of 3,6-dihydroimidazo(4,5-d)pyrrolo(2,3-b)pyridin-2(1H)-one (dpp) derivatives to computationally identify new JAK inhibiting compounds. For the purpose, a novel virtual screening strategy, with 2D and 3D-QSAR (CoMFA and CoMSIA), data mining, pharmacophore modeling, ADMET prediction, multi-targeted protein-based docking and inverse QSAR, was employed. The 2D-QSAR equations developed for the JAK3, JAK2 and JAK1 involved five physicochemical descriptors. These descriptors correlate with the anti-RA activity with R² values for JAK3, JAK2 and JAK1 are 0.9811, 0.8620 and 0.9740, respectively. The 3D-QSAR studies such as CoMFA and CoMSIA carried out through PLS analysis of the training set of JAK3, JAK2 and JAK1, gave Q² values as 0.369, 0.476 and 0.490; [Formula: see text] values as 0.863, 0.684 and 0.724 and, F values as 23.098, 28.139 and 31.438, respectively. The contour maps produced by the CoMFA and CoMSIA models were used to understand the importance of hydrogen bond donor, acceptor, hydrophobic, steric and electrostatic interactions. The molecular docking studies of these selected compounds with various JAK proteins were carried out and the protein-ligand interactions were also studied. The study concluded that dpp15(s) is a highly potent JAK inhibitor with a very good predicted IC₅₀ value.

Using Physiologically Based Pharmacokinetic (PBPK) Modeling to Evaluate the Impact of Pharmaceutical Excipients on Oral Drug Absorption: Sensitivity Analyses

Drug solubility, effective permeability, and intestinal metabolism and transport are parameters that govern intestinal bioavailability and oral absorption. However, excipients may affect the systemic bioavailability of a drug by altering these parameters. Thus, parameter sensitivity analyses using physiologically based pharmacokinetic (PBPK) models were performed to examine the potential impact of excipients on oral drug absorption of different Biopharmaceutics Classification System (BCS) class drugs. The simulation results showed that changes in solubility had minimal impact on C_max and AUC_0-t of investigated BCS class 1 and 3 drugs. Changes in passive permeability altered C_max more than AUC_0-t for BCS class 1 drugs but were variable and drug-specific across different BCS class 2 and 3 drugs. Depending on the drug compounds for BCS class 1 and 2 drugs, changes in intestinal metabolic activity altered C_max and AUC_0-t. Reducing or increasing influx and efflux transporter activity might likely affect C_max and AUC_0-t of BCS class 2 and 3 drugs, but the magnitude may be drug dependent. Changes in passive permeability and/or transporter activity for BCS class 2 and 3 drugs might also have a significant impact on fraction absorbed and systemic bioavailability while changes in intestinal metabolic activity may have an impact on gut and systemic bioavailability. Overall, we demonstrate that PBPK modeling can be used routinely to examine sensitivity of bioavailability based on physiochemical and physiological factors and subsequently assess whether biowaiver requirements need consideration of excipient effects for immediate release oral solid dosage forms.

Metabolite Kinetics: The Segregated Flow Model for Intestinal and Whole Body Physiologically Based Pharmacokinetic Modeling to Describe Intestinal and Hepatic Glucuronidation of Morphine in Rats In Vivo

We used the intestinal segregated flow model (SFM) versus the traditional model (TM), nested within physiologically based pharmacokinetic (PBPK) models, to describe the biliary and urinary excretion of morphine 3β-glucuronide (MG) after intravenous and intraduodenal dosing of morphine in rats in vivo. The SFM model describes a partial (5%-30%) intestinal blood flow perfusing the transporter- and enzyme-rich enterocyte region, whereas the TM describes 100% flow perfusing the intestine as a whole. For the SFM, drugs entering from the circulation are expected to be metabolized to lesser extents by the intestine due to the segregated flow, reflecting the phenomenon of shunting and route-dependent intestinal metabolism. The poor permeability of MG crossing the liver or intestinal basolateral membranes mandates that most of MG that is excreted into bile is hepatically formed, whereas MG that is excreted into urine originates from both intestine and liver metabolism, since MG is effluxed back to blood. The ratio of MG amounts in urine/bile [Formula: see text] for intraduodenal/intravenous dosing is expected to exceed unity for the SFM but approximates unity for the TM. Compartmental analysis of morphine and MG data, without consideration of the permeability of MG and where MG is formed, suggests the ratio to be 1 and failed to describe the kinetics of MG. The observed intraduodenal/intravenous ratio of [Formula: see text] (2.55 at 4 hours) was better predicted by the SFM-PBPK (2.59 at 4 hours) and not the TM-PBPK (1.0), supporting the view that the SFM is superior for the description of intestinal-liver metabolism of morphine to MG. The SFM-PBPK model predicts an appreciable contribution of the intestine to first pass M metabolism.

Fixing clearance as early as lead optimization using high throughput in vitro incubations in combination with exact mass detection and automatic structure elucidation of metabolites

New enabling MS technologies have made it possible to elucidate metabolic pathways present in ex vivo (blood, bile and/or urine) or in vitro (liver microsomes, hepatocytes and/or S9) samples. When investigating samples from high throughput assays the challenge that the user is facing now is to extract the appropriate information and compile it so that it is understandable to all. Medicinal chemist may then design the next generation of (better) drug candidates combining the needs for potency and metabolic stability and their synthetic creativity. This review focuses on the comparison of these enabling MS technologies and the IT tools developed for their interpretation.

In vitro bioactivation of a selective estrogen receptor modulator (2S,3R)-(+)-3-(3-hydroxyphenyl)-2-[4-(2-pyrrolidin-1-ylethoxy)phenyl]-2,3-dihydro-1,4-benzoxathiin-6-ol (I) in liver microsomes: formation of adenine adducts

As part of our efforts to develop safer selective estrogen receptor modulators (SERMs), compound I {(2S,3R)-(+)-3-(3-hydroxyphenyl)-2-[4-(2-pyrrolidin-1-ylethoxy)-phenyl]-2,3-dihydro-1,4-benzoxathiin-6-ol} was previously identified as a lead for further development. Subsequent studies showed that compound I is genotoxic in both in vitro Chinese hamster ovary (CHO) cells and in vivo mouse studies. To better understand the possible mechanisms for the observed genetoxicity effects, in vitro incubations of I with liver microsomes of human, monkey, and mouse in the presence of adenine were performed, which led to the detection of five adenine adducts. The formation of these adducts was NADPH-dependent, suggesting the involvement of oxidative bioactivation catalyzed by cytochrome P450 enzymes. The mechanism for the formation of the major adenine adduct (A1) involves the formation of a reactive ring-opened para-quinone intermediate. The formation of four other adenine adducts may involve the formation of a reactive epoxide or ortho-quinone intermediate. Furthermore, incubations of compound I with human hepatocytes showed dose-dependent DNA damages in Comet assays. All of the above suggest that some reactive metabolites of compound I, formed through bioactivation mechanisms, have a potential to interact with DNA molecules in vitro and in vivo. This may be one of the causes of the genotoxicity observed preclinically both in vitro and in vivo. This case study demonstrated an approach using in vitro DNA trapping assays for assessing the genotoxicity potential of drug candidates.

In vivo-formed versus preformed metabolite kinetics of trans-resveratrol-3-sulfate and trans-resveratrol-3-glucuronide

Metabolites in safety testing have gained a lot of attention recently. Regulatory agencies have suggested that the kinetics of preformed and in vivo-formed metabolites are comparable. This subject has been a topic of debate. We have compared the kinetics of in vivo-formed with preformed metabolites. trans-3,5,4'-Trihydroxystilbene [trans-resveratrol (RES)] and its two major metabolites, resveratrol-3-sulfate (R3S) and resveratrol-3-glucuronide (R3G) were used as model substrates. The pharmacokinetics (PK) of R3S and R3G were characterized under two situations. First, the pharmacokinetics of R3S and R3G were characterized (in vivo-formed metabolite) after administration of RES. Then, synthetic R3S and R3G were administered (preformed metabolite) and their pharmacokinetics were characterized. PK models were developed to describe the data. A three-compartment model for RES, a two-compartment model for R3S (preformed), and an enterohepatic cycling model for R3G (preformed) was found to describe the data well. These three models were further combined to build a comprehensive PK model, which was used to perform simulations to predict in vivo-formed metabolite kinetics. Comparisons were made between in vivo-formed and preformed metabolite kinetics. Marked differences were observed in the kinetics of preformed and in vivo-formed metabolites.

The early estimation of circulating drug metabolites in humans

INTRODUCTION

An evolution in bioanalytical methodologies to identify and quantify drug metabolites has led to a wealth of biotransformation information during preclinical and early clinical testing phases. However, this abundance of metabolism data has not clarified how to select the most important circulating human metabolites for safety assessment. Consequently, more stringent regulatory expectations for a comprehensive approach to human metabolism have led pharmaceutical sponsors to employ a variety of novel methods to estimate circulating drug metabolites in humans and animals.

AREAS COVERED

This review provides context for 'why' human circulating metabolites must be qualified for safety in animals. A detailed overview is also presented concerning 'where,' 'how' and 'when' to conduct these assessments during drug development.

EXPERT OPINION

A human metabolite qualification strategy is now a required element of the drug safety package submitted with a new drug application (NDA). The important question is whether or not this additional information, about metabolite safety, is making human drugs any safer. Currently, this is a debatable issue, especially because stand-alone metabolite testing is fraught with its own challenges. As drug development moves into the twenty-first century, there is a pressing need for more sophisticated methodologies to address human drug and metabolite safety.

Definition of metabolism-dependent xenobiotic toxicity with co-cultures of human hepatocytes and mouse 3T3 fibroblasts in the novel integrated discrete multiple organ co-culture (IdMOC) experimental system: results with model toxicants aflatoxin B1, cyclophosphamide and tamoxifen

The integrated discrete multiple organ co-culture system (IdMOC) allows the co-culturing of multiple cell types as physically separated cells interconnected by a common overlying medium. We report here the application of IdMOC with two cell types: the metabolically competent primary human hepatocytes, and a metabolically incompetent cell line, mouse 3T3 fibroblasts, in the definition of the role of hepatic metabolism on the cytotoxicity of three model toxicants: cyclophosphamide (CPA), aflatoxin B1 (AFB) and tamoxifen (TMX). The presence of hepatic metabolism in IdMOC with human hepatocytes was demonstrated by the metabolism of the P450 isoform 3A4 substrate, luciferin-IPA. The three model toxicants showed three distinct patterns of cytotoxic profile: TMX was cytotoxic to 3T3 cells in the absence of hepatocytes, with slightly lower cytotoxicity towards both 3T3 cells and hepatocytes in the IdMOC. AFB was selective toxic towards the human hepatocytes and relatively noncytotoxic towards 3T3 cells both in the presence and absence of the hepatocytes. CPA cytotoxicity to the 3T3 cells was found to be significantly enhanced by the presence of the hepatocytes, with the cytotoxicity dependent of the number of hepatocytes, and with the cytotoxicity attenuated by the presence of a non-specific P450 inhibitor, 1-aminobenzotriazole. We propose here the following classification of toxicants based on the role of hepatic metabolism as defined by the human hepatocyte-3T3 cell IdMOC assay: type I: direct-acting cytotoxicants represented by TMX as indicated by cytotoxicity in 3T3 cells in the absence of hepatocytes; type II: metabolism-dependent cytotoxicity represented by AFB1 with effects localized within the site of metabolic activation (i. e. hepatocytes); and type III: metabolism-dependent cytotoxicity with metabolites that can diffuse out of the hepatocytes to cause toxicity in cells distal from the site of metabolism, as exemplified by CPA.

Physiologically-based pharmacokinetic modeling for absorption, transport, metabolism and excretion

The seminal paper on the liver physiologically-based pharmacokinetic (PBPK) model by Rowland et al. (J Pharmacokinet Biopharm 1:123-136, 1973) that described the influence of blood flow, intrinsic clearance, and binding on hepatic clearance had inspired further development of PBPK modeling of the liver, kidney and intestine as well as whole body. Shortly thereafter, a series of papers from Pang and Rowland compared the well-stirred and parallel-tube liver models and sparked further development on clearance concepts in the liver, including those described by the dispersion model. From 2005 onwards, several seminal papers by Rodgers and Rowland, in their recognition of the binding of molecules to tissue acidic and neutral phospholipids, improved the methodology in providing estimates of the tissue-to-plasma coefficient and rendering easy calculation of these hard-to-get constants. The improvement has strongly consolidated the basic premise on PBPK modeling and simulations and these basics have allowed scientists to focus on other important variables: membrane barriers, and transporter and enzyme and their heterogeneities that further impact drug disposition. In particular, the PBPK models have delved into sequential metabolism and futile cycling to illustrate how transporters and enzymes could affect the metabolism of drugs and metabolites. PBPK models that are especially pertinent to metabolite kinetics are being utilized in drug studies and risk assessment. These types of PBPK modeling reveal differences in kinetics between the formed vs. preformed metabolite, showing special considerations for membrane barriers, and the influence of competing pathways and competing organs.

Overview of metabolite safety testing from an industry perspective

Regulatory guidelines on MIST were initially established in 2005 and finalized in 2008 by the US FDA and this has led to much discussion and debate on how to apply these recommendations in today’s resource-constrained pharmaceutical environment. There are four aspects of MIST that impact on the field of bioanalysis: definition of a disproportionate human metabolite, establishment of nonclinical (animal) safety coverage for important human metabolites, degree of rigor in validation of bioanalytical methods to quantify metabolites when synthetic standards are available, and semiquantitation of metabolites when synthetic standards are not available. In this manuscript, each of these points has been addressed from a pharmaceutical industry standpoint, including a perspective on the necessary convergence of the fields of metabolite safety testing and bioanalysis.

A radiocalibration method with pseudo internal standard to estimate circulating metabolite concentrations

Background: It has become important for metabolism scientists to identify and quantify prominent circulating human metabolites in order to develop a metabolite safety-qualification package that meets regulatory standards. Often these metabolites cannot be analyzed using traditional bioanalytical methods because a standard is not available. Results: A radiocalibration method is described that can estimate circulating metabolite concentrations in nonradioactive human and animal plasma. The key to this method is application of a pseudo internal standard (PIS) that is present in both radioactive reference and nonradioactive (i.e., unknown) samples. Metabolite exposure in the unknown samples is estimated from measured PIS exposure using a relative molar ratio established between the metabolite and PIS (usually parent drug). Conclusion: Two case studies demonstrate that the method can be used to establish human metabolite safety coverage in animal plasma and method validation is demonstrated by comparing estimated metabolite concentrations in human plasma with concentrations obtained directly using a metabolite calibration curve.

Site of metabolism prediction on cytochrome P450 2C9: a knowledge-based docking approach

A novel structure-based approach for site of metabolism prediction has been developed. This knowledge-based method consists of three steps: (1) generation of possible metabolites, (2) docking the predicted metabolites to the CYP binding site and (3) selection of the most probable metabolites based on their complementarity to the binding site. As a proof of concept we evaluated our method by using MetabolExpert for metabolite generation and Glide for docking into the binding site of the CYP2C9 crystal structure. Our method could identify the correct metabolite among the three best-ranked compounds in 69% of the cases. The predictive power of our knowledge-based method was compared to that achieved by substrate docking and two alternative literature approaches.

Metabolites in safety testing

Traditionally, only circulating concentrations of parent drug have been measured in the rodent and nonrodent test species used for drug safety assessments and served as an index of systemic exposure for comparisons to human exposures. Circulating concentrations of metabolites have generally only been measured in specialized circumstances (e.g., parent compound was extensively metabolized). Measurement of only the parent compound is usually sufficient when the metabolite profile in humans is similar to that in at least one of the animal species used in the nonclinical safety assessment. However, it is possible that metabolites formed in humans might not be present in the rodent and nonrodent test species used for drug safety assessments or the metabolites are formed at disproportionately higher concentrations in humans than in the animal test species. Generally, metabolites identified only in human plasma or metabolites present at disproportionately higher concentrations in humans than in any of the animal test species should be considered for safety assessment. The Center for Drug Evaluation and Research (CDER) published a Guidance for Industry on Safety Testing of Drug Metabolites that provides current thinking within CDER on the nonclinical safety assessment of human drug metabolites derived from drug products. The CDER guidance defines human metabolites that can raise a safety concern as those formed at greater than 10% of parent drug systemic exposure at a steady state. By contrast, the more recent International Conference on Harmonization: Guideline on Nonclinical Safety Studies for the Conduct of Human Clinical Trials and Marketing Authorization for Pharmaceuticals (ICH M3[R2]) describes the threshold as 10% of total drug-related exposure. Where they differ, the ICH guidance supersedes the CDER Guidance. The purpose of this article is to provide a perspective on the important details of these guidances from a regulatory review standpoint, as well as discuss some concerns that have arisen from the regulated industry regarding the CDER guidance. Such issues include parent drug that is extensively metabolized, metabolism by intestinal bacteria and metabolites formed by nonclinical test species but not humans.