Linguamatics, the leader in natural language processing (NLP)-based text mining, announced that the Federal Drug Administration’s (FDA) Center for Drug Evaluation and Research (CDER) has licensed its 12E text mining platform as a discovery and decision support tool to supplement laboratory research efforts on drug safety. The FDA will use the platform to review published literature and drug product labels to address key biomedical issues, including mechanisms of drug toxicity and disease processes. In addition to document retrieval, the 12E platform can identify, extract, synthesize, and analyze relevant facts and relationships (e.g., between genes and diseases, drugs and side effects). Customers include top tier commercial, academic, and governmental organizations, including 9 of the top 10 global pharmaceutical companies. The 12E platform is available both as an in-house or cloud-based system.
Typical applications in pharmaceutical, biotechnology, and healthcare include:
• Mapping gene-disease relationships and identifying potentially novel therapeutic targets
• Biomarker discovery
• Drug repurposing
• Drug safety
• Patent analysis
• Clinical trial site selection and study design
• Mining electronic medical records to improve prediction of health outcomes
• Translational medicine
• Competitive intelligence
• Social media mining
• Subjective data mining (sentiment analysis, key opinion mining)
Sources: BioSpace and Business Weekly
Zebrafish offer a nonclinical model for the high-throughput screening of drug compounds, including toxicity assessment, with resolution at the cellular level in living vertebrate organisms. These small, freshwater, tropical fish share genetic and biochemical similarity to humans, in addition to similar organ system development. Vertebrate disease models (e.g., Parkinson’s, epilepsy, wound repair) are available , as are 3-D image resolution and data analysis capabilities. Live-imaging options, unparalleled in other vertebrate organisms, are possible using the transparent larvae. Furthermore, live-cell microscopy can provide views of the inner complexity and workings at the cellular level. For purposes of disease modeling, researchers can create and screen genetic mutants in the zebrafish that are linked to human immune diseases. Neurological assessments using the live, transparent, zebrafish larvae allow visualization of the mechanisms of myelination. In conclusion, the zebrafish preclinical model owes much of its popularity to the transparent nature and relevant ease of imaging of vertebrate larvae. Optimization of data analyses for these varied indications is ongoing.
Source: Genetic Engineering and Biotechnology News
As brought to my attention by Sanchayita Kar, Founder and President, SciClips has created a unique and comprehensive database on therapeutic drug targets (~4000) that have been reported in US patents or US/International patent applications. The drug targets are classified according to specific drug (e.g., small molecule, protein, antibody, siRNA, miRNA, etc.) and disease types. Assays and methods utilized for characterizing each drug target are listed as well. In addition, all the drug targets are linked to PubMed (articles), Google Scholar (articles), GeneBank (nucleotide sequence), UniProt (protein sequence), USPTO database (full text patents/patent applications), WO(PCT) database (full text international patent applications), and Google Patents (full text US patents). This multifaceted database may be useful in the determination of potential mechanisms for target-organ toxicity.
SciClips is a web-based platform for open innovation and information sharing on topics such as stem cells, proteomics, biomarkers, metabolomics, and drug discovery. This innovative platform promotes the sharing of ideas through multidisciplinary and global approaches that can be utilized for research or product development without any licensing agreements or fees.
Despite greater emphasis on safety as a result of attrition, the application of toxicology (~6% of the total R&D budget) to the preclinical drug development process has remained largely unchanged for over 30 years! For this reason, the impetus to reduce safety risks early has been slow to evolve, with limited resources specifically dedicated to this endeavor. Revolutionizing the way that toxicology is applied, such as moving from a hazard identification and risk assessment preclinical paradigm to one that reduces or eliminates risk prior to major expenditures, may provide a means of narrowing the productivity gap within the biopharmaceutical industry. This paper suggests a strategy for the integration of toxicology into early drug development (discovery phase) through identification of potential safety issues related to therapeutic use, target selection, and compound selection, with a primary emphasis on new chemical entities. Information gained may also guide the appropriate selection of the toxicological species used to support clinical trials. Assays predictive of target organ effects (insufficiently discussed, in my opinion, in the present article) vs. assays designed to look at specific mechanisms of drug-induced toxicities at the intracellular level are presented relative to the need for development of high throughput safety screens.
In conclusion, the preclinical toxicology strategy needs to accommodate the unique attributes of the target, the compound, and the therapeutic application, along with assays that are “fit-for-purpose” for that specific project. This paper provides an overview of safety issues for initial exploration and cites possible techniques available to address them in the preclinical space.
Source: Pharmaceutical Outsourcing
Although drugs are usually targeted to be selective for a single protein, it is recognized that other proteins may also be affected, a phenomenon called polypharmacology. While off-target interactions can cause potentially harmful side-effects, in some cases, an effect on an unintended target might suggest new disease indications for established drugs.
Chemoinformatics, statistical programs, and experimental techniques are being utilized by Brian Shoichet of the University of California San Francisco to predict off-target interactions. Similarities between 3665 (existing and experimental) drugs and a set of over 65,000 known ligands to protein receptors in the body were examined. In addition, the ligands were arranged into around 250 classes depending on the type of receptor to which they bind. This exhaustive survey yielded hundreds of previously unrecognised potential interactions between drugs and protein receptors in the body. A number of these potential interactions were confirmed by laboratory experiments, including identification of the key receptor that binds the hallucinatory drug dimethyltryptamine.
These new computational techniques should not only prove valuable to pharmaceutical companies to both expand existing pipelines and to reap additional benefits from current compounds, they should also aid researchers to anticipate and avoid unanticipated adverse events.
Source: Chemistry World