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PharmaInformatic (www.pharmainformatic.com) provides cheminformatic services and predictive tools to improve drug discovery and preclinical compound selection. Specialised expert systems in different therapeutic areas help to discover and validate hits, followed by selection and prioritisation of suitable compounds. Novel predictive tools prioritise derivatives even of different lead structures and select the most promising drug candidates for further development. Based on our large database of clinical trials and pharmacokinetic data, ADMET-profiles are generated to identify potential risks in order to reduce clinical failures.
The company has developed a unique integrated platform that contains millions of substances together with experimental data and thousands of 3D-models of biomolecules. Proprietary methods based on chemInformatics and bioInformatics allow the prediction of biological activity of a substance and its pharmacological properties. MolScore-products increase the hit-rate, save time and reduce costs up to 80% through focussed screening campaigns. PharmaInformatic uses a proprietary rule based docking method combined with predictive methods like neural networks, decision trees and pharmacophore modelling. Extremely large structure-activity relationships (SAR) and structure-property relationships (SPR) with up to hundreds of thousands compounds allow the description of useful chemical space within a specific therapeutic area.
Our platform technology enables us to develop expert systems in nearly all therapeutic areas, like infectious diseases (antibacterial, antiviral, antifungal), cardiovascular disease, CNS-drugs, inflammation, pain, metabolic disease, cancer. These expert systems help to identify, validate, prioritise and select the most suitable compounds within that therapeutic area.
PharmaInformatic´s in-house ADME/Tox-database contains an impressive and continuously increasing amount of pharmacokinetic data obtained from diverse clinical candidates. A variety of reliable tools to predict ADME/Tox-properties like bioavailability, clearance, elimination half life, absorption, P-gp transport, volume of distribution, plasma protein binding, blood brain barrier permeability, CNS activity, solubility, log P, log D, toxicity, hepatotoxicity, carcinogenicity, mutagenicity, drug-drug interaction, type of elimination can be derived from this unique data collection. A combination of multiple models identifies potential risks in order to reduce clinical failures and prioritise compounds with the maximum possibility of success in human trials.
Products and Service
helps to identify and prioritise promising drug candidates with the maximum possibility of success in human trials. The expert system is based on a variety of reliable models. Extremely large structure-activity relationships (SAR) with up to hundreds of thousands compounds allow the estimation of useful drug-like chemical space. Structure-property relationships (SPR) which are derived from PharmaInformatic´s large in-house ADME/Tox-database can be applied to predict ADMET properties and to identify potential risks in order to reduce clinical failures.
detects antibacterial drug candidates. The expert system identifies novel antibiotic substances at the earliest stage through analysing the chemical structure of a drug candidate, its ADME characteristics and its molecular targets.
detects antiviral drug candidates. The expert system combines different strategies of drug research, so that structural patterns of virus-specific and target-specific inhibitors will be recognised.
Tailor-made expert systems
PharmaInformatic develops tailor-made expert systems. These predictive tools can be used to discover drug candidates in customer-specific therapeutic areas or can be derived from PharmaInformatic´s large in-house ADME/Tox-database to predict pharmacokinetic parameters (ADMET-profiling).
Keywords: ADME/Tox, Drug Discovery, Virtual Screening, Cheminformatic Tools for Compound Selection and Lead Prioritisation