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.