The discovery and development of new drugs to treat cancer and other diseases has been more reliant on information technology to collect and analyze data in a more efficient manner. This is due to the amount of data generated in one experiment today as compared to the past. When the NCI60 screen was implemented in 96 well plates 20 years ago, it was considered state of the art. Today the NCI60 generates 20,800 data points per week. In comparison, an ultra high throughput screening (uHTS) assay conducted in 1536 well plates can generate 2.2 million data points in that same period of time. With the advent of new pharmacology assays to evaluate pharmacodynamics in addition to pharmacokinetics, a simple efficacy experiment that did not take any samples from the tumor or normal tissues/fluids for analysis a few years ago, now can take up to 4000 samples that need to be analyzed in multiple assays and multiple sites. This not only creates a storage and handling issue, but also one for analysis since one is attempting to draw correlations from as many as ten different endpoints in one experiment. To solve these issues and to accelerate the implementation and integration of new IT software for data acquisition, storage and evaluation for drug discovery and development, in consultation with CaBIG, DCTD has selected CambridgeSoft, a life science enterprise solution for data and knowledge management. As a result, CambridgeSoft, modified for compatibility with CaBIG, is becoming the primary software for the collection of all data generated on Chemical Biology Consortium (CBC) projects that are conducted within the NCI, at SAIC-F, at various NCI contractors and with outside consortium members. Implementation is slow due to the limited DCTD/DTP IT resources to enable the collection of different data streams from CBC members and DCTD contractors. Our goal is to integrate additional software that will facilitate the analysis of this data from multiple streams such as Simulations Plus, Spotfire, Prous/Integrity, GVK-Bio Target and Biomarker Databases and FDA in silico toxicity prediction software, to name a few. These software packages will also be integrated to the extent possible with the Microsoft Project Enterprise server which the Project Management Office of SAIC uses to manage drug discovery and development projects for DCTD. The solution is to purchase/license new commercial off the shelf (COTS) software as indicated above and award new IT contracts or expand existing contracts through SAIC to speed up the integration process.
