ximelagatran and Drug-Related-Side-Effects-and-Adverse-Reactions

The occurrence of drug-induced liver injury (DILI) presents a significant safety issue for patients and represents a major cause of regulatory action. The methods that are in current use for early detection and prediction of DILI in patients are not adequate. The liver is the major site of synthesis of endogenous metabolites, and data suggest that alterations in the profiles of endogenous metabolites ("the metabolome") may precede development of clinically overt DILI. Metabonomics involves the application of analytical technologies such as nuclear magnetic resonance and mass spectrometry to detect changes in the metabolome. In this review, we describe the emerging role of metabonomics in predicting and understanding the mechanisms underlying DILI. Recent human clinical trials of drugs, including acetaminophen (APAP) and ximelagatran, have shown that the metabonomics of biofluids (plasma and urine) collected before and immediately after dosing can identify individual patients who are likely to develop DILI. These studies support the need to include metabonomic investigations in clinical trials of potentially hepatotoxic medications.

Topics: Acetaminophen; Animals; Azetidines; Benzylamines; Chemical and Drug Induced Liver Injury; Clinical Trials as Topic; Drug-Related Side Effects and Adverse Reactions; Humans; Magnetic Resonance Spectroscopy; Mass Spectrometry; Metabolomics

Thrombin is a plasma serine protease that plays a key role in coagulation and hemostasis but also in thromboembolic diseases. Direct thrombin inhibitors could, therefore, be beneficial for future anticoagulant therapy in the prophylaxis of venous and arterial thrombosis as well as myocardial infarction. However, development of direct thrombin inhibitors has brought researchers more heartache than success. The most recent setback came this year when AstraZeneca withdrew Ximelagatran, the first orally bioavailable direct thrombin inhibitor that had received regulatory approval (France, 2003), after reports of serious hepatoxicity in a fraction of patients. This review describes the status of direct thrombin inhibitors, focusing on drug candidates that are at present in clinical trials. In addition, some more recent research strategies in the design of novel direct thrombin inhibitors are discussed, which may very well contribute to future developments of potent anticoagulants.

Topics: Animals; Anticoagulants; Azetidines; Benzylamines; Clinical Trials as Topic; Drug Design; Drug-Related Side Effects and Adverse Reactions; Hirudins; Humans; Molecular Sequence Data; Myocardial Infarction; Thrombin; Thrombosis

Drug-induced liver injury (DILI) is a leading cause of drugs failing during clinical trials and being withdrawn from the market. Comparative analysis of drugs based on their DILI potential is an effective approach to discover key DILI mechanisms and risk factors. However, assessing the DILI potential of a drug is a challenge with no existing consensus methods. We proposed a systematic classification scheme using FDA-approved drug labeling to assess the DILI potential of drugs, which yielded a benchmark dataset with 287 drugs representing a wide range of therapeutic categories and daily dosage amounts. The method is transparent and reproducible with a potential to serve as a common practice to study the DILI of marketed drugs for supporting drug discovery and biomarker development.

Topics: Animals; Benchmarking; Biomarkers, Pharmacological; Chemical and Drug Induced Liver Injury; Drug Design; Drug Labeling; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmaceutical Preparations; Reproducibility of Results; United States; United States Food and Drug Administration

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

Topics: Animals; Anti-Infective Agents; Anti-Inflammatory Agents; Chemical and Drug Induced Liver Injury; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Models, Biological; Predictive Value of Tests