Communicating Drug Discovery Data Efficiently and Effectively
Jonathan Davies and Andrew Lemon,
IDBSDate Posted: Thursday, February 01, 2007
Drug discovery generates vast amounts of multidisciplinary data which needs to be captured, consistently organized and shared effectively across an organization.
In this poster, we present IDBS’ ActivityBase™ — a single, integrated framework that brings together biological and chemical information. The software integrates with Oracle®, the industry standard relational database and familiar Microsoft® applications such as Word and Excel.
With all discovery data in one system, the communication of information between scientists is simplified — enabling better, faster decisions — and the need for IT support to integrate disparate systems is eliminated.
IDBS is also pioneering software to predict drug efficacy and safety based on pre-clinical data, complementing the scientific expertise of researchers. By predicting potential problems with compounds earlier in the discovery process, costs are cut and efficiency is boosted.
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Intelligent K-Means Clustering in a Multiple Endpoint Environment
The main success of QSAR predictive technology is mainly related to the modelling of the single activity/property endpoint in chemical space. Unfortunately an optimisation of the targeted endpoint may result in losing other desired properties, for example, toxicity is increased or solubility reduced. Because of this, attempts have been made in the last few years to model chemical space against multiple endpoints.
Simplifying the Flow of Drug Discovery Data
Regardless of research disciplines, scientists need to easily reach the information pertinent to their research. Ideally this data access is easy. Researchers also need the ability to ‘move the data around’ to gain a better view or different perspective. This data manipulation needs to be straightforward. Incorporating the varying views and information required by different scientific disciplines is a considerable challenge.
Screening Solution: ActivityBase™
The data management needs of discovery biology are complex and varied. The experimental data that is captured, stored and analyzed ranges from high volume, routine screening data through to low throughput, non-routine test management data that underpins pre-clinical research. ActivityBase™ is a data management system that integrates research data in a structured and scalable environment, providing secure management of a discovery organization’s principle asset – data.
Achieving Ultra High Performance Screening
High throughput (HT) and Ultra High Throughput (UHT) screening remains a valuable and necessary approach to modern drug discovery. Successful application of HTS requires accurate and meaningful handling of the experimental results. This means capturing vast data volumes generated by HTS and UHTS programmes and subsequent validation and verification. Decision making regarding HTS data can be supported via comprehensive and intuitive visualization of results.
Study Management in Late Stage Discovery and Preclinical Research
Organizations need to streamline their operations by managing the entire lifecycle of an experiment - from design to final publication of data. Organizations require the full benefits of IP protection, with the ability to access a solution for data capture, reduction, statistical analysis, charting and data curation. Researchers want a familiar notebook interface that they can use to create and manage study reports and publish data to corporate warehouses and document systems.
Related news from our archive
University of Louis Pasteur Chose IDBS to Show in Silico Predictive Technology
The University will use the PredictionBase™ suite from IDBS to focus on the application of cheminformatics within drug discovery.
Biopharmaceutical Company Introduces Activitybase XE to Improve Screening Efficiency
IDBS’s long time ActivityBase user, Organon introduces the XE module into its Molecular Pharmacology departments in Oss and Newhouse.
University of Louis Pasteur Chose IDBS to show in Silico Predictive Technology
The University will use the PredictionBase suite from IDBS to focus on the application of cheminformatics within drug discovery.