JIB.tools 2.0 - A Bioinformatics Registry for Journal Published Tools with Interoperability to bio.tools.

JIB.tools 2.0 is a new approach to more closely embed the curation process in the publication process. This website hosts the tools, software applications, databases and workflow systems published in the Journal of Integrative Bioinformatics (JIB). As soon as a new tool-related publication is published in JIB, the tool is posted to JIB.tools and can afterwards be easily transferred to bio.tools, a large information repository of software tools, databases and services for bioinformatics and the life sciences. In this way, an easily-accessible list of tools is provided which were published in JIB a well as status information regarding the underlying service. With newer registries like bio.tools providing these information on a bigger scale, JIB.tools 2.0 closes the gap between journal publications and registry publication. (Reference: https://jib.tools).

History and Future of KALIS: Towards Computer-assisted Decision Making in Prescriptive Medicine.

With an increasing older population in Germany and the need for polypharmacy to treat multimorbid patients computer-assisted decision making on an individual level is increasingly important to reduce prescription errors and adverse drug reactions. While current systems focus on guidelines and prescribing information, molecular information is equally important for explanation and discovery of drug-related problems. Based on the existing KALIS system and newer projects like PIMBase, a new concept for the KALIS-2 system is presented. Improvements to the modularisation of components enable future extension and greater maintainability. Interoperability with available electronic health records standards and protocols allows the integration and communication with existing workflows for healthcare professionals. Finally, new visualisation modes empower the user to explore and analyze the patient situation in an individual patient subgraph. For offline use and dialogue between patient and general practitioner, the results can be printed out using a new reporting tool. The adherence to findings from previous decision support systems and reasons for their failed adoption is an important task in the development of KALIS-2.

Data-Driven Assessment of Potentially Inappropriate Medication in the Elderly.

Multimorbid patients taking polypharmacy represent a growing population at high risk for inappropriate prescribing. Various lists for identifying potentially inappropriate medication are spread across scientific journals and difficult to access. To address this ongoing need, a new database named PIMBase is developed which integrates these well-known lists and unifies their rating scales. The analysis of the pharmacovigilance data reveals the benefits of combining the lists. PIMBase is meant to be a web-based system and starting point for the data-driven assessment of polypharmacy to identify inappropriate medication and to improve the quality of prescribing. PIMBase is available at https://pimbase.kalis-amts.de.

GenCoNet - A Graph Database for the Analysis of Comorbidities by Gene Networks.

The prevalence of comorbid diseases poses a major health issue for millions of people worldwide and an enormous socio-economic burden for society. The molecular mechanisms for the development of comorbidities need to be investigated. For this purpose, a workflow system was developed to aggregate data on biomedical entities from heterogeneous data sources. The process of integrating and merging all data sources of the workflow system was implemented as a semi-automatic pipeline that provides the import, fusion, and analysis of the highly connected biomedical data in a Neo4j database GenCoNet. As a starting point, data on the common comorbid diseases essential hypertension and bronchial asthma was integrated. GenCoNet (https://genconet.kalis-amts.de) is a curated database that provides a better understanding of hereditary bases of comorbidities.

KALIS - An eHealth System for Biomedical Risk Analysis of Drugs.

BACKGROUND: In Germany, adverse drug reactions and events cause hospitalizations, which lead to numerous thousands of deaths and several million Euros in additional health costs annually. OBJECTIVES: Approximately one in two deaths could be avoided by an appropriate system for risk analysis of drugs. METHODS: The integration and storage of several data sources from life sciences are an ongoing need to address various questions with respect to drug therapy. A software architecture for data integration was implemented in order to build up a new data warehouse named KALIS-DWH, which includes pharmacological, biomolecular and patient-related data. RESULTS: Based on this comprehensive KALIS-DWH, an eHealth system named KALIS for biomedical risk analysis of drugs was implemented. The task-specific modules of KALIS offer efficient algorithms for analyzing medication and supporting decision-making in drug therapy. CONCLUSION: KALIS is meant to be a web-based information system for health professionals and researchers. KALIS provides comprehensive knowledge and modules for risk analysis of drugs, which can contribute to minimizing prescribing errors.

KATIS: An eHealth System for Complementary Medicine.

BACKGROUND: Much of the information on the complementary medicine is spread across literature and the internet. However, various literature and web resources provide information just of one specialist field. In addition, these resources do not allow users to search for suitable therapies based on patient-specific indications. OBJECTIVES: Aggregating knowledge about complementary medicine into one database makes the search more efficient. METHODS: Data integration is a promising method for providing well-based knowledge. Therefore, integrative methods were used to create the database ALTMEDA, which includes complementary and drug-related data. RESULTS: Based on this comprehensive database ALTMEDA, the new eHealth system KATIS and the corresponding app ALMEKO for the mobile usage were implemented. CONCLUSION: KATIS is a web-based system for complementary medicine. KATIS provides knowledge about ten different specialist fields, which enables users not only to look up a particular complementary therapy, but also to find suitable therapies for indications more efficiently. [http://www.komplementäre-medizin.de].

GraphSAW: a web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data.

BACKGROUND: Adverse drug reactions are one of the most common causes of death in industrialized Western countries. Nowadays, empirical data from clinical studies for the approval and monitoring of drugs and molecular databases is available. METHODS: The integration of database information is a promising method for providing well-based knowledge to avoid adverse drug reactions. This paper presents our web-based decision support system GraphSAW which analyzes and evaluates drug interactions and side effects based on data from two commercial and two freely available molecular databases. The system is able to analyze single and combined drug-drug interactions, drug-molecule interactions as well as single and cumulative side effects. In addition, it allows exploring associative networks of drugs, molecules, metabolic pathways, and diseases in an intuitive way. The molecular medication analysis includes the capabilities of the upper features. RESULTS: A statistical evaluation of the integrated data and top 20 drugs concerning drug interactions and side effects is performed. The results of the data analysis give an overview of all theoretically possible drug interactions and side effects. The evaluation shows a mismatch between pharmaceutical and molecular databases. The concordance of drug interactions was about 12% and 9% of drug side effects. An application case with prescribed data of 11 patients is presented in order to demonstrate the functionality of the system under real conditions. For each patient at least two interactions occured in every medication and about 8% of total diseases were possibly induced by drug therapy. CONCLUSIONS: GraphSAW (http://tunicata.techfak.uni-bielefeld.de/graphsaw/) is meant to be a web-based system for health professionals and researchers. GraphSAW provides comprehensive drug-related knowledge and an improved medication analysis which may support efforts to reduce the risk of medication errors and numerous drastic side effects.

Identifying adverse drug reactions and drug-induced diseases using network-based drug mapping.

Drugs are essential for the prevention and treatment of diseases. However, co-administration of multiple drugs may cause serious adverse drug reactions, which are usually known but sometimes unknown. Package inserts of prescription drugs are supposed to contain risks and side effects, but such information is not necessarily complete. At the core of efforts to improve prescription quality, there is reliance on the extent and quality of information used for decision of a medical doctor. To address this on-going need, GraphSAW provides users a comprehensive view on drug-related pharmacological and molecular information. The features of GraphSAW allow users to analyze drug cocktails for adverse drug reactions and drug-induced diseases. Network visualization by drug mapping enables exploring associative networks of drugs, pathways, and diseases to fully understand effects of drugs in an intuitive way. GraphSAW is meant to be a platform and starting point for health professionals and researchers for educational and scientific research in order to achieve substantial improvements in patient safety.