Drug-drug interaction detection software tools | Drug discovery data analysis
An important step in drug design is to check for drug-drug interactions, which can delay, decrease, or enhance absorption of either drug, or in some cases can cause adverse drug effects. Drug-drug interactions prediction software are useful for deducing novel interactions based on previous knowledge.
Retrieves drug-drug interactions (DDIs) from biomedical text. DDI employs a method that combines feature sets and partitions datasets into subsets based on their syntactic properties. It maps each candidate DDI pair into a syntactic container before generating features. This tool utilizes various natural language processing (NLP) approaches and a support vector machine (SVM) method.
Predicts drug-drug interactions via chemical-protein interactome (CPI). DDI-CPI employs in silico simulations to model the theoretical interaction profile of a small molecule across human proteome. It can give a real-time result based only on the interactome of drugs toward a representative collection of pharmacokinetic (PK) and pharmacodynamic (PD) proteins. This tool assists users to explain the potential mechanism for any molecules with a given structure.
Deduces novel drug-drug interactions (DDIs). INDI supports pharmacokinetic and pharmacodynamic DDIs. It enables the recommendation of the type of action to take upon administration of the two drugs and the inference of the cytochrome P450 (CYP) isoforms involved when the interaction is CYP-related. This tool does not consider the method of administration of the drug. It can be used for the improvement of patient treatment.
Allows to analyze the relationships between biological activities, drug-drug interactions and multiple targeting of chemical compounds. PharmaExpert permits to select compounds with the required therapeutic, without adverse effects. It can proceed to a multitargeted selection of compounds with multiple mechanisms of action. The tool assesses drug-drug interactions with regard to pharmacokinetic, pharmacodynamic, and adverse effects.
A probabilistic approach for jointly inferring unknown drug-drug interactions from a network of multiple drug-based similarities and known interactions. PSL models are easy and fast: you can define them using a straightforward logical syntax and solve them with fast convex optimization. PSL has produced state-of-the-art results in many areas spanning natural language processing, social-network analysis, and computer vision.
Explains what the interaction is, how it occurs, the level of significance (major, moderate, or minor) and usually a suggested course of action. Drug Interactions Checker is an informational resource designed to assist licensed healthcare practitioners in caring for their patients and provide consumers with drug specific information. This web app can also display any interactions between chosen drug(s) and food, beverages, or a medical condition.
Makes quantitative predictions of drug exposure e.g. in case of drug-drug interaction (DDI) even if this interaction has not been studied. DDI-Predictor is a website dedicated to quantitative prediction of the impact on drug exposure of drug-drug interactions mediated by cytochromes P450 3A4, 2D6, 2C9, 2C19 and 1A2, as well as genetic polymorphism of these cytochromes, the combined effect of drug interaction and cytochrome polymorphism, cirrhosis, and drug-drug interactions in cirrhotic patients.