Developing a pragmatic consensus procedure supporting the ICH S1B(R1) weight of evidence carcinogenicity assessment.

The ICH S1B carcinogenicity global testing guideline has been recently revised with a novel addendum that describes a comprehensive integrated Weight of Evidence (WoE) approach to determine the need for a 2-year rat carcinogenicity study. In the present work, experts from different organizations have joined efforts to standardize as much as possible a procedural framework for the integration of evidence associated with the different ICH S1B(R1) WoE criteria. The framework uses a pragmatic consensus procedure for carcinogenicity hazard assessment to facilitate transparent, consistent, and documented decision-making and it discusses best-practices both for the organization of studies and presentation of data in a format suitable for regulatory review. First, it is acknowledged that the six WoE factors described in the addendum form an integrated network of evidence within a holistic assessment framework that is used synergistically to analyze and explain safety signals. Second, the proposed standardized procedure builds upon different considerations related to the primary sources of evidence, mechanistic analysis, alternative methodologies and novel investigative approaches, metabolites, and reliability of the data and other acquired information. Each of the six WoE factors is described highlighting how they can contribute evidence for the overall WoE assessment. A suggested reporting format to summarize the cross-integration of evidence from the different WoE factors is also presented. This work also notes that even if a 2-year rat study is ultimately required, creating a WoE assessment is valuable in understanding the specific factors and levels of human carcinogenic risk better than have been identified previously with the 2-year rat bioassay alone.

In silico approaches in carcinogenicity hazard assessment: case study of pregabalin, a nongenotoxic mouse carcinogen.

In silico toxicology protocols are meant to support computationally-based assessments using principles that ensure that results can be generated, recorded, communicated, archived, and then evaluated in a uniform, consistent, and reproducible manner. We investigated the availability of in silico models to predict the carcinogenic potential of pregabalin using the ten key characteristics of carcinogens as a framework for organizing mechanistic studies. Pregabalin is a single-species carcinogen producing only one type of tumor, hemangiosarcomas in mice via a nongenotoxic mechanism. The overall goal of this exercise is to test the ability of in silico models to predict nongenotoxic carcinogenicity with pregabalin as a case study. The established mode of action (MOA) of pregabalin is triggered by tissue hypoxia, leading to oxidative stress (KC5), chronic inflammation (KC6), and increased cell proliferation (KC10) of endothelial cells. Of these KCs, in silico models are available only for selected endpoints in KC5, limiting the usefulness of computational tools in prediction of pregabalin carcinogenicity. KC1 (electrophilicity), KC2 (genotoxicity), and KC8 (receptor-mediated effects), for which predictive in silico models exist, do not play a role in this mode of action. Confidence in the overall assessments is considered to be medium to high for KCs 1, 2, 5, 6, 7 (immune system effects), 8, and 10 (cell proliferation), largely due to the high-quality experimental data. In order to move away from dependence on animal data, development of reliable in silico models for prediction of oxidative stress, chronic inflammation, immunosuppression, and cell proliferation will be critical for the ability to predict nongenotoxic compound carcinogenicity.

ChEMBL: towards direct deposition of bioassay data.

ChEMBL is a large, open-access bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012, 2014 and 2017 Nucleic Acids Research Database Issues. In the last two years, several important improvements have been made to the database and are described here. These include more robust capture and representation of assay details; a new data deposition system, allowing updating of data sets and deposition of supplementary data; and a completely redesigned web interface, with enhanced search and filtering capabilities.

The ChEMBL database in 2017.

ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 and 2014 Nucleic Acids Research Database Issues. Since then, alongside the continued extraction of data from the medicinal chemistry literature, new sources of bioactivity data have also been added to the database. These include: deposited data sets from neglected disease screening; crop protection data; drug metabolism and disposition data and bioactivity data from patents. A number of improvements and new features have also been incorporated. These include the annotation of assays and targets using ontologies, the inclusion of targets and indications for clinical candidates, addition of metabolic pathways for drugs and calculation of structural alerts. The ChEMBL data can be accessed via a web-interface, RDF distribution, data downloads and RESTful web-services.

SureChEMBL: a large-scale, chemically annotated patent document database.

SureChEMBL is a publicly available large-scale resource containing compounds extracted from the full text, images and attachments of patent documents. The data are extracted from the patent literature according to an automated text and image-mining pipeline on a daily basis. SureChEMBL provides access to a previously unavailable, open and timely set of annotated compound-patent associations, complemented with sophisticated combined structure and keyword-based search capabilities against the compound repository and patent document corpus; given the wealth of knowledge hidden in patent documents, analysis of SureChEMBL data has immediate applications in drug discovery, medicinal chemistry and other commercial areas of chemical science. Currently, the database contains 17 million compounds extracted from 14 million patent documents. Access is available through a dedicated web-based interface and data downloads at: https://www.surechembl.org/.

Chemical databases: curation or integration by user-defined equivalence?

There is a wealth of valuable chemical information in publicly available databases for use by scientists undertaking drug discovery. However finite curation resource, limitations of chemical structure software and differences in individual database applications mean that exact chemical structure equivalence between databases is unlikely to ever be a reality. The ability to identify compound equivalence has been made significantly easier by the use of the International Chemical Identifier (InChI), a non-proprietary line-notation for describing a chemical structure. More importantly, advances in methods to identify compounds that are the same at various levels of similarity, such as those containing the same parent component or having the same connectivity, are now enabling related compounds to be linked between databases where the structure matches are not exact.

UniChem: extension of InChI-based compound mapping to salt, connectivity and stereochemistry layers.

UniChem is a low-maintenance, fast and freely available compound identifier mapping service, recently made available on the Internet. Until now, the criterion of molecular equivalence within UniChem has been on the basis of complete identity between Standard InChIs. However, a limitation of this approach is that stereoisomers, isotopes and salts of otherwise identical molecules are not considered as related. Here, we describe how we have exploited the layered structural representation of the Standard InChI to create new functionality within UniChem that integrates these related molecular forms. The service, called 'Connectivity Search' allows molecules to be first matched on the basis of complete identity between the connectivity layer of their corresponding Standard InChIs, and the remaining layers then compared to highlight stereochemical and isotopic differences. Parsing of Standard InChI sub-layers permits mixtures and salts to also be included in this integration process. Implementation of these enhancements required simple modifications to the schema, loader and web application, but none of which have changed the original UniChem functionality or services. The scope of queries may be varied using a variety of easily configurable options, and the output is annotated to assist the user to filter, sort and understand the difference between query and retrieved structures. A RESTful web service output may be easily processed programmatically to allow developers to present the data in whatever form they believe their users will require, or to define their own level of molecular equivalence for their resource, albeit within the constraint of identical connectivity.

Chondroprotective effects of zoledronic acid on articular cartilage in dogs with experimentally induced osteoarthritis.

OBJECTIVE: To assess effects of zoledronic acid on biomarkers, radiographic scores, and gross articular cartilage changes in dogs with induced osteoarthritis. ANIMALS: 21 purpose-bred hound-type dogs. PROCEDURES: The left stifle joint of each dog was examined arthroscopically to determine initial articular cartilage status, which was followed by cranial cruciate ligament (CrCL) transection to induce osteoarthritis. Dogs were assigned to 3 groups (control group, low dose [10 µg of zoledronic acid/kg], or high dose [25 µg of zoledronic acid/kg). Treatments were administered SC every 3 months for 1 year beginning the day after CrCL transection. Serum and synovial fluid samples and radiographs were obtained 0, 1, 3, 6, 9, and 12 months after transection. At 12 months, each joint was scored for cartilage defects. Serum and synovial fluid biomarkers of bone and cartilage turnover (bone-specific alkaline phosphatase, type I and II collagen, carboxy-propeptide of type II collagen, and chondroitin sulfate 846) were analyzed with ELISAs. RESULTS: The high-dose group had fewer total articular defects and lower severity scores in CrCL-transected stifle joints than did the control group. In addition, the high-dose group had significantly less change in collagenase cleavage of type I or II collagen in the synovial fluid at 1 and 3 months after CrCL transection than did the control group and also had greater changes in bone-specific alkaline phosphatase in synovial fluid at 3 months after CrCL transection than did the control group. CONCLUSIONS AND CLINICAL RELEVANCE: Zoledronic acid had a chondroprotective effect in dogs with a transected CrCL.

The ChEMBL bioactivity database: an update.

ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 Nucleic Acids Research Database Issue. Since then, a variety of new data sources and improvements in functionality have contributed to the growth and utility of the resource. In particular, more comprehensive tracking of compounds from research stages through clinical development to market is provided through the inclusion of data from United States Adopted Name applications; a new richer data model for representing drug targets has been developed; and a number of methods have been put in place to allow users to more easily identify reliable data. Finally, access to ChEMBL is now available via a new Resource Description Framework format, in addition to the web-based interface, data downloads and web services.

UniChem: a unified chemical structure cross-referencing and identifier tracking system.

UniChem is a freely available compound identifier mapping service on the internet, designed to optimize the efficiency with which structure-based hyperlinks may be built and maintained between chemistry-based resources. In the past, the creation and maintenance of such links at EMBL-EBI, where several chemistry-based resources exist, has required independent efforts by each of the separate teams. These efforts were complicated by the different data models, release schedules, and differing business rules for compound normalization and identifier nomenclature that exist across the organization. UniChem, a large-scale, non-redundant database of Standard InChIs with pointers between these structures and chemical identifiers from all the separate chemistry resources, was developed as a means of efficiently sharing the maintenance overhead of creating these links. Thus, for each source represented in UniChem, all links to and from all other sources are automatically calculated and immediately available for all to use. Updated mappings are immediately available upon loading of new data releases from the sources. Web services in UniChem provide users with a single simple automatable mechanism for maintaining all links from their resource to all other sources represented in UniChem. In addition, functionality to track changes in identifier usage allows users to monitor which identifiers are current, and which are obsolete. Lastly, UniChem has been deliberately designed to allow additional resources to be included with minimal effort. Indeed, the recent inclusion of data sources external to EMBL-EBI has provided a simple means of providing users with an even wider selection of resources with which to link to, all at no extra cost, while at the same time providing a simple mechanism for external resources to link to all EMBL-EBI chemistry resources.

ChEMBL: a large-scale bioactivity database for drug discovery.

ChEMBL is an Open Data database containing binding, functional and ADMET information for a large number of drug-like bioactive compounds. These data are manually abstracted from the primary published literature on a regular basis, then further curated and standardized to maximize their quality and utility across a wide range of chemical biology and drug-discovery research problems. Currently, the database contains 5.4 million bioactivity measurements for more than 1 million compounds and 5200 protein targets. Access is available through a web-based interface, data downloads and web services at: https://www.ebi.ac.uk/chembldb.

Collation and data-mining of literature bioactivity data for drug discovery.

The challenge of translating the huge amount of genomic and biochemical data into new drugs is a costly and challenging task. Historically, there has been comparatively little focus on linking the biochemical and chemical worlds. To address this need, we have developed ChEMBL, an online resource of small-molecule SAR (structure-activity relationship) data, which can be used to support chemical biology, lead discovery and target selection in drug discovery. The database contains the abstracted structures, properties and biological activities for over 700000 distinct compounds and in excess of more than 3 million bioactivity records abstracted from over 40000 publications. Additional public domain resources can be readily integrated into the same data model (e.g. PubChem BioAssay data). The compounds in ChEMBL are largely extracted from the primary medicinal chemistry literature, and are therefore usually 'drug-like' or 'lead-like' small molecules with full experimental context. The data cover a significant fraction of the discovery of modern drugs, and are useful in a wide range of drug design and discovery tasks. In addition to the compound data, ChEMBL also contains information for over 8000 protein, cell line and whole-organism 'targets', with over 4000 of those being proteins linked to their underlying genes. The database is searchable both chemically, using an interactive compound sketch tool, protein sequences, family hierarchies, SMILES strings, compound research codes and key words, and biologically, using a variety of gene identifiers, protein sequence similarity and protein families. The information retrieved can then be readily filtered and downloaded into various formats. ChEMBL can be accessed online at https://www.ebi.ac.uk/chembldb.

The orphan G protein-coupled receptor GPR40 is activated by medium and long chain fatty acids.

GPR40 is a member of a subfamily of homologous G protein-coupled receptors that include GPR41 and GPR43 and that have no current function or ligand ascribed. Ligand fishing experiments in HEK293 cells expressing human GPR40 revealed that a range of saturated and unsaturated carboxylic acids with carbon chain lengths greater than six were able to induce an elevation of [Ca(2+)](i), measured using a fluorometric imaging plate reader. 5,8,11-Eicosatriynoic acid was the most potent fatty acid tested, with a pEC(50) of 5.7. G protein coupling of GPR40 was examined in Chinese hamster ovary cells expressing the G alpha(q/i)-responsive Gal4-Elk1 reporter system. Expression of human GPR40 led to a constitutive induction of luciferase activity, which was further increased by exposure of the cells to eicosatriynoic acid. Neither the constitutive nor ligand-mediated luciferase induction was inhibited by pertussis toxin treatment, suggesting that GPR40 was coupled to G alpha(q/11.) Expression analysis by quantitative reverse transcription-PCR showed that GPR40 was specifically expressed in brain and pancreas, with expression in rodent pancreas being localized to insulin-producing beta-cells. These data suggest that some of the physiological effects of fatty acids in pancreatic islets and brain may be mediated through a cell-surface receptor.