The withdrawal of torcetrapib from drug development: implications for the future of drugs that alter HDL metabolism

Omics Data Integration and Analysis for Systems Pharmacology

Systems pharmacology aims to understand drug actions on a multi-scale from atomic details of drug-target interactions to emergent properties of biological network and rationally design drugs targeting an interacting network instead of a single gene. Multifaceted data-driven studies, including machine learning-based predictions, play a key role in systems pharmacology. In such works, the integration of multiple omics data is the key initial step, followed by optimization and prediction. Here, we describe the overall procedures for drug-target association prediction using REMAP, a large-scale off-target prediction tool. The method introduced here can be applied to other relation inference problems in systems pharmacology.

Carbon-carbon bond cleavage and formation reactions in drug metabolism and the role of metabolic enzymes

Elimination of xenobiotics from the human body is often facilitated by a transformation to highly water soluble and more ionizable molecules. In general, oxidation-reduction, hydrolysis, and conjugation reactions are common biotransformation reactions that are catalyzed by various metabolic enzymes including cytochrome P450s (CYPs), non-CYPs, and conjugative enzymes. Although carbon-carbon (C-C) bond formation and cleavage reactions are known to exist in plant secondary metabolism, these reactions are relatively rare in mammalian metabolism and are considered exceptions. However, various reactions such as demethylation, dealkylation, dearylation, reduction of alkyl chain, ring expansion, ring contraction, oxidative elimination of a nitrile through C-C bond cleavage, and dimerization, and glucuronidation through C-C bond formation have been reported for drug molecules. Carbon-carbon bond cleavage reactions for drug molecules are primarily catalyzed by CYP enzymes, dimerization is mediated by peroxidases, and C-glucuronidation is catalyzed by UGT1A9. This review provides an overview of C-C bond cleavage and formation reactions in drug metabolism and the metabolic enzymes associated with these reactions.

Haemodynamic Assessment in Safety Pharmacology

Evaluation of the effects of a drug on arterial blood pressure is important in nonclinical safety pharmacology assessment. Detecting large and obvious changes in blood pressure is an unchallenging task. Detecting small changes is more difficult, and interpretation of findings requires careful risk/benefit evaluation. Detecting subtle and small changes in blood pressure is important in particular with respect to increases, since blood pressure above the normal range is associated with increased risk of stroke and sudden cardiac death. Cardiovascular safety pharmacology has been preoccupied with drug-induced changes in the electrocardiogram, and by comparison, there has been little in the way of contemporaneous improvements in the level of complexity and sophistication involved in blood pressure assessment. Thus, it is important to understand the nature of drug-induced changes in blood pressure, appreciate the plethora of agents currently used clinically (and over the counter) that alter blood pressure and understand safety pharmacology study design in order to optimize assessment of a new chemical entity (NCE) or biologic agent in this context.

Construction and analysis of a human hepatotoxicity database suitable for QSAR modeling using post-market safety data

Drug-induced liver injury (DILI) is one of the most common drug-induced adverse events (AEs) leading to life-threatening conditions such as acute liver failure. It has also been recognized as the single most common cause of safety-related post-market withdrawals or warnings. Efforts to develop new predictive methods to assess the likelihood of a drug being a hepatotoxicant have been challenging due to the complexity and idiosyncrasy of clinical manifestations of DILI. The FDA adverse event reporting system (AERS) contains post-market data that depict the morbidity of AEs. Here, we developed a scalable approach to construct a hepatotoxicity database using post-market data for the purpose of quantitative structure-activity relationship (QSAR) modeling. A set of 2029 unique and modelable drug entities with 13,555 drug-AE combinations was extracted from the AERS database using 37 hepatotoxicity-related query preferred terms (PTs). In order to determine the optimal classification scheme to partition positive from negative drugs, a manually-curated DILI calibration set composed of 105 negatives and 177 positives was developed based on the published literature. The final classification scheme combines hepatotoxicity-related PT data with supporting information that optimize the predictive performance across the calibration set. Data for other toxicological endpoints related to liver injury such as liver enzyme abnormalities, cholestasis, and bile duct disorders, were also extracted and classified. Collectively, these datasets can be used to generate a battery of QSAR models that assess a drug's potential to cause DILI.

Pharmacometabonomics and personalized medicine

BACKGROUND

Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics.

METHODS

A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmaco-metabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013.

RESULTS

Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals.

CONCLUSIONS

Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.

Crystal structures of cholesteryl ester transfer protein in complex with inhibitors

Human plasma cholesteryl ester transfer protein (CETP) transports cholesteryl ester from the antiatherogenic high-density lipoproteins (HDL) to the proatherogenic low-density and very low-density lipoproteins (LDL and VLDL). Inhibition of CETP has been shown to raise human plasma HDL cholesterol (HDL-C) levels and is potentially a novel approach for the prevention of cardiovascular diseases. Here, we report the crystal structures of CETP in complex with torcetrapib, a CETP inhibitor that has been tested in phase 3 clinical trials, and compound 2, an analog from a structurally distinct inhibitor series. In both crystal structures, the inhibitors are buried deeply within the protein, shifting the bound cholesteryl ester in the N-terminal pocket of the long hydrophobic tunnel and displacing the phospholipid from that pocket. The lipids in the C-terminal pocket of the hydrophobic tunnel remain unchanged. The inhibitors are positioned near the narrowing neck of the hydrophobic tunnel of CETP and thus block the connection between the N- and C-terminal pockets. These structures illuminate the unusual inhibition mechanism of these compounds and support the tunnel mechanism for neutral lipid transfer by CETP. These highly lipophilic inhibitors bind mainly through extensive hydrophobic interactions with the protein and the shifted cholesteryl ester molecule. However, polar residues, such as Ser-230 and His-232, are also found in the inhibitor binding site. An enhanced understanding of the inhibitor binding site may provide opportunities to design novel CETP inhibitors possessing more drug-like physical properties, distinct modes of action, or alternative pharmacological profiles.

A systems biology strategy for predicting similarities and differences of drug effects: evidence for drug-specific modulation of inflammation in atherosclerosis

Background

Successful drug development has been hampered by a limited understanding of how to translate laboratory-based biological discoveries into safe and effective medicines. We have developed a generic method for predicting the effects of drugs on biological processes. Information derived from the chemical structure and experimental omics data from short-term efficacy studies are combined to predict the possible protein targets and cellular pathways affected by drugs.

Results

Validation of the method with anti-atherosclerotic compounds (fenofibrate, rosuvastatin, LXR activator T0901317) demonstrated a great conformity between the computationally predicted effects and the wet-lab biochemical effects. Comparative genome-wide pathway mapping revealed that the biological drug effects were realized largely via different pathways and mechanisms. In line with the predictions, the drugs showed differential effects on inflammatory pathways (downstream of PDGF, VEGF, IFNγ, TGFβ, IL1β, TNFα, LPS), transcriptional regulators (NFκB, C/EBP, STAT3, AP-1) and enzymes (PKCδ, AKT, PLA2), and they quenched different aspects of the inflammatory signaling cascade. Fenofibrate, the compound predicted to be most efficacious in inhibiting early processes of atherosclerosis, had the strongest effect on early lesion development.

Conclusion

Our approach provides mechanistic rationales for the differential and common effects of drugs and may help to better understand the origins of drug actions and the design of combination therapies.

Cholesteryl ester transfer protein and its inhibition

Cholesteryl ester transfer protein (CETP) is a plasma glycoprotein that facilitates the transfer of cholesteryl esters from the atheroprotective high density lipoprotein (HDL) to the proatherogenic low density lipoprotein cholesterol (LDL) and very low density lipoprotein cholesterol (VLDL) leading to lower levels of HDL but raising the levels of proatherogenic LDL and VLDL. Inhibition of CETP is considered a potential approach to treat dyslipidemia. However, discussions regarding the role of CETP-mediated lipid transfer in the development of atherosclerosis and CETP inhibition as a potential strategy for prevention of atherosclerosis have been controversial. Although many animal studies support the hypothesis that inhibition of CETP activity may be beneficial, negative phase III studies on clinical endpoints with the CETP inhibitor torcetrapib challenged the future perspectives of CETP inhibitors as potential therapeutic agents. The review provides an update on current understanding of the molecular mechanisms involved in CETP activity and its inhibition.

High-density lipoprotein therapeutics and cardiovascular prevention

The field of cardiovascular prevention has long anticipated the evolution of high-density lipoprotein (HDL) therapy from unproven metabolic tweaking to pillar of risk reduction on par with low-density lipoprotein control. However, the convincing epidemiologic data linking HDL cholesterol (HDL-C) and cardiovascular disease risk in an inverse correlation has not yet translated into clinical trial evidence supporting linearity between HDL-C increases and risk reduction, or identifying obvious goals of therapy. Although HDL-C-increasing lifestyle maneuvers and established HDL drugs such as niacin and fibrates are likely to protect the vasculature, the negative results obtained in trials of a cholesteryl ester transfer protein inhibitor remind us that HDL-C increases are not always beneficial. It is becoming clear that a functional HDL is a more desirable target than simply increasing HDL-C levels. The larger objective of improving HDL functionality (with or without HDL-C level changes) is bound to become the guiding principle for pharmaceutical research in this area. Several new compounds currently being tested bridge the classical aim of increasing HDL-C levels with the novel target of improving HDL function.

Torcetrapib for animal and human pharmacokinetic studies: applicability of chiral and achiral methodologies

The emergence of bioanalysis as a key tool in the drug-discovery and -development process has enabled the development of sensitive, precise and specific bioanalytical methods in recent years. These methods have enabled the progress of novel chemical entities through the life cycle of drug discovery and development. The focus of this review article is on a well-known cholesteryl ester transfer protein (CETP) inhibitor known as torcetrapib. Although torcetrapib was withdrawn from clinical development, it is important to understand the various bioanalytical methodologies (chiral and achiral) that are readily available for the pharmacokinetic/pharmacodynamic characterization of the drug. Additionally, these methodologies may be applicable to the bioanalysis of the next-generation CETP inhibitors. This review covers the development and validation of assay methods that were used to obtain preclinical and clinical pharmacokinetic parameters of torcetrapib. Accordingly, methods are available for the determination of torcetrapib in various species, namely dogs, hamsters, rats, mice, monkeys and humans. Since torcetrapib is a chiral compound, methods have been developed for stereoselective bioanalysis to evaluate in vivo chiral inversion phenomena. Interestingly, torcetrapib can be analyzed by various bioanalytical options (e.g., HPLC–UV, LC–MS, LC–MS/MS and GC–MS assays) depending on the type of species under consideration with the associated sensitivity requirements. This review covers all the available methodologies for torcetrapib, providing both assay-development and -optimization strategies. It also tabulates validation parameters and enumerates the difficulties, challenges and nuances of the various published assays for torcetrapib.

Drug discovery using chemical systems biology: identification of the protein-ligand binding network to explain the side effects of CETP inhibitors

Systematic identification of protein-drug interaction networks is crucial to correlate complex modes of drug action to clinical indications. We introduce a novel computational strategy to identify protein-ligand binding profiles on a genome-wide scale and apply it to elucidating the molecular mechanisms associated with the adverse drug effects of Cholesteryl Ester Transfer Protein (CETP) inhibitors. CETP inhibitors are a new class of preventive therapies for the treatment of cardiovascular disease. However, clinical studies indicated that one CETP inhibitor, Torcetrapib, has deadly off-target effects as a result of hypertension, and hence it has been withdrawn from phase III clinical trials. We have identified a panel of off-targets for Torcetrapib and other CETP inhibitors from the human structural genome and map those targets to biological pathways via the literature. The predicted protein-ligand network is consistent with experimental results from multiple sources and reveals that the side-effect of CETP inhibitors is modulated through the combinatorial control of multiple interconnected pathways. Given that combinatorial control is a common phenomenon observed in many biological processes, our findings suggest that adverse drug effects might be minimized by fine-tuning multiple off-target interactions using single or multiple therapies. This work extends the scope of chemogenomics approaches and exemplifies the role that systems biology has in the future of drug discovery.

Both the cost to launch a new drug and the attrition rate during the late stage of the drug discovery and development process are increasing. Torcetrapib is a case in point, having been withdrawn from phase III clinical trials after 15 years of development and an estimated cost of US $800 M. Torcetrapib represents a new class of therapies for the treatment of cardiovascular disease; however, clinical studies indicated that Torcetrapib has deadly side-effects as a result of hypertension. To understand the origins of these adverse drug reactions from Torcetrapib and other related drugs undergoing clinical trials, we introduce a systematic strategy to identify off-targets in the human structural proteome and investigate the roles of these off-targets in impacting human physiology and pathology using biochemical pathway analysis. Our findings suggest that potential side-effects of a new drug can be identified at an early stage of the development cycle and be minimized by fine-tuning multiple off-target interactions. The hope is that this can reduce both the cost of drug development and the mortality rates during clinical trials.

Postprocedural high-density lipoprotein cholesterol predicts carotid stent patency at 1 year

The durability of carotid artery stenting (CAS) is affected by the occurrence of myointimal proliferation and in-stent restenosis (ISR). We aimed to identify clinical, angiographic, and laboratory predictors of ISR, paying special attention to postprocedural metabolic factors. A total of 102 consecutive patients with successful CAS for > or =70% atherosclerotic internal carotid artery stenosis were followed up with neurological assessment and duplex sonography 1 day, 1 month, and 1 year after CAS. Lipid profile and hemoglobin A(1c) were tested at the 1-month follow-up visit. Ten (10%) patients had ISR > or =50% after 1 year. Compared with patients without ISR (n = 92), patients with ISR were more often current smokers (33% vs. 70%, P = 0.034) and had significantly lower 1-month high-density lipoprotein (HDL) cholesterol: median (range) 47 (24-95) mg/dl vs. 39.5 (25-50) mg/dl, P = 0.031. Multivariate logistic regression analyses identified 1-month HDL cholesterol >45 mg/dl as the only independent predictor of carotid stent patency at 1 year (P = 0.033, OR = 0.09, 95% CI 0.01-0.83). Postprocedural HDL cholesterol levels predict carotid stent patency at 1 year. With the possibility of elevation of HDL cholesterol by lifestyle changes and medication, this finding may have implications for the future management of patients undergoing CAS.

Effect of obesity on high-density lipoprotein metabolism

Reduced levels of high-density lipoproteins (HDL) in non-obese and obese states are associated with increased risk for the development of coronary artery disease. Therefore, it is imperative to determine the mechanisms responsible for reduced HDL in obese states and, conversely, to examine therapies aimed at increasing HDL levels in these individuals. This paper examines the multiple causes for reduced HDL in obese states and the effect of exercise and diet--two non-pharmacologic therapies--on HDL metabolism in humans. In general, the concentration of HDL-cholesterol is adversely altered in obesity, with HDL-cholesterol levels associated with both the degree and distribution of obesity. More specifically, intra-abdominal visceral fat deposition is an important negative correlate of HDL-cholesterol. The specific subfractions of HDL that are altered in obese states include the HDL2, apolipoprotein A-I, and pre-beta1 subfractions. Decreased HDL levels in obesity have been attributed to both an enhancement in the uptake of HDL2 by adipocytes and an increase in the catabolism of apolipoprotein A-I on HDL particles. In addition, there is a decrease in the conversion of the pre-beta1 subfraction, the initial acceptor of cholesterol from peripheral cells, to pre-beta2 particles. Conversely, as a means of reversing the decrease in HDL levels in obesity, sustained weight loss is an effective method. More specifically, weight loss achieved through exercise is more effective at raising HDL levels than dieting. Exercise mediates positive effects on HDL levels at least partly through changes in enzymes of HDL metabolism. Increased lipid transfer to HDL by lipoprotein lipase and reduced HDL clearance by hepatic triglyceride lipase as a result of endurance training are two important mechanisms for increases in HDL observed from exercise.