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.

Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automated text mining with limited manual curation, opening up new opportunities for generating and modeling chemical toxicology data.

The influence of oxygen and carbon dioxide on diving behaviour of tufted ducks, Aythya fuligula.

While optimal diving models focus on the diver's oxygen (O(2)) stores as the predominant factor influencing diving behaviour, many vertebrate species surface from a dive before these stores are exhausted and may commence another dive well after their O(2) stores have been resaturated. This study investigates the influence of hypoxia and also hypercapnia on the dive cycle of tufted ducks, Aythya fuligula, in terms of surface duration and dive duration. The birds were trained to surface into a respirometer box after each dive to a feeding tray so that rates of O(2) uptake (VO2) and carbon dioxide output (VCO2) at the surface could be measured. Although Vco2 initially lagged behind Vo2, both respiratory gas stores were close to full adjustment after the average surface duration, indicating that they probably had a similar degree of influence on surface duration. Chemoreceptors, which are known to influence diving behaviour, detect changes in O(2) and CO(2) partial pressures in the arterial blood. Thus, the need to restore blood gas levels appears to be a strong stimulus to continue ventilation. Mean surface duration coincided with peak instantaneous respiratory exchange ratio due to predive anticipatory hyperventilation causing hypocapnia. For comparison, the relationship between surface duration and O(2) uptake in reanalysed data for two grey seals indicated that one animal tended to dive well after fully restocking its O(2) stores, while the other dived at the point of full restocking. More CO(2) is exchanged than O(2) in tufted ducks during the last few breaths before the first dive of a bout, serving to reduce CO(2) stores and suggesting that hypercapnia rather than hypoxia is more often the limiting factor on asphyxia tolerance during dives. Indeed, according to calculations of O(2) stores and O(2) consumption rates over modal diving durations, a lack of O(2) does not seem to be associated with the termination of a dive in tufted ducks. However, factors other than CO(2) are also likely to be important, and perhaps more so, such as food density and rate of food ingestion. Because some predictive success has been demonstrated for optimal diving models, they should continue to incorporate O(2) stores as a variable, but their validity is likely to be improved by also focusing on CO(2) stores.