Comparisons between in vitro whole cell imaging and in vivo zebrafish-based approaches for identifying potential human hepatotoxicants earlier in pharmaceutical development.

Drug-induced liver injury (DILI) is a major cause of attrition during both the early and later stages of the drug development and marketing process. Reducing or eliminating drug-induced severe liver injury, especially those that lead to liver transplants or death, would be tremendously beneficial for patients. Therefore, developing new pharmaceuticals that have the highest margins and attributes of hepatic safety would be a great accomplishment. Given the current low productivity of pharmaceutical companies and the high costs of bringing new medicines to market, any early screening assay(s) to identify and eliminate pharmaceuticals with the potential to cause severe liver injury in humans would be of economic value as well. The present review discusses the background, proof-of-concept, and validation studies associated with high-content screening (HCS) by two major pharmaceutical companies (Pfizer Inc and Jansen Pharmaceutical Companies of Johnson & Johnson) for detecting compounds with the potential to cause human DILI. These HCS assays use fluorescent-based markers of cell injury in either human hepatocytes or HepG2 cells. In collaboration with Evotec, an independent contract lab, these two companies also independently evaluated larval zebrafish as an early-stage in vivo screen for hepatotoxicity in independently conducted, blinded assessments. Details about this model species, the need for bioanalysis, and, specifically, the outcome of the phenotypic-based zebrafish screens are presented. Comparing outcomes in zebrafish against both HCS assays suggests an enhanced detection for hepatotoxicants of most DILI concern when used in combination with each other, based on the U.S. Food and Drug Administration DILI classification list.

Developing timely insights into comparative effectiveness research with a text-mining pipeline.

Comparative effectiveness research (CER) provides evidence for the relative effectiveness and risks of different treatment options and informs decisions made by healthcare providers, payers, and pharmaceutical companies. CER data come from retrospective analyses as well as prospective clinical trials. Here, we describe the development of a text-mining pipeline based on natural language processing (NLP) that extracts key information from three different trial data sources: NIH ClinicalTrials.gov, WHO International Clinical Trials Registry Platform (ICTRP), and Citeline Trialtrove. The pipeline leverages tailored terminologies to produce an integrated and structured output, capturing any trials in which pharmaceutical products of interest are compared with another therapy. The timely information alerts generated by this system provide the earliest and most complete picture of emerging clinical research.

Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development.

External content sources such as MEDLINE(®), National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions. The value of the sites for industry, however, is limited by the use of the public internet, the limited synonyms, the rarity of batch searching capability and the disconnected nature of the sites. Fortunately, many sites now offer their content for download and we have developed an automated internal workflow that uses text mining and tailored ontologies for programmatic search and knowledge extraction. We believe such an efficient and secure approach provides a competitive advantage to companies needing access to the latest information for a range of use cases and complements manually curated commercial sources.

"Seeing is believing": perspectives of applying imaging technology in discovery toxicology.

Efficiency and accuracy in addressing drug safety issues proactively are critical in minimizing late-stage drug attritions. Discovery toxicology has become a specialty subdivision of toxicology seeking to effectively provide early predictions and safety assessment in the drug discovery process. Among the many technologies utilized to select safer compounds for further development, in vitro imaging technology is one of the best characterized and validated to provide translatable biomarkers towards clinically-relevant outcomes of drug safety. By carefully applying imaging technologies in genetic, hepatic, and cardiac toxicology, and integrating them with the rest of the drug discovery processes, it was possible to demonstrate significant impact of imaging technology on drug research and development and substantial returns on investment.