Hortonworks and Revolution Analytics provide massive-scale data handling
Integrichain (Princeton, NJ), which has been one of a handful of developers of analytics services based on, among other things, commercial EDI data from pharma trading partners, is upgrading its offerings based on alliances with a pair of Big Data developers: Hortonworks (Palo Alto, CA) and Revolution Analytics (Mountain View, CA). Hortonworks, in turn, is a developer of “open source enterprise Apache Hadoop software,” and Revolution Analytics is a developer of the R programming language, which it characterizes as “the single most important tool for computational statistics, visualization and data science.”
Josh Halpern, Integrichain co-founder and EVP, provides a translation: “These IT resources are comparable to what the major Internet-based e-commerce companies, like Amazon or Facebook, use to manage their systems or mine data to find trends. In the context of pharma distribution agreements, we’re seeing instances where a pharma company wants to analyze thousands of SKUs [stockkeeping units] across thousands of customers, over a multi-year span. You can do that with existing tools, but handling massive data loads like that are becoming more and more difficult without these cutting-edge IT tools.”
In practice, Integrichain will be incorporating these IT capabilities into its Demand Networks Analytics (DNA) platform, which is used by many major pharma companies to analyze trade agreements, market trends and the like. Some new service offerings will be rolled out over the next several months, says Halpern.
Newron, Myung In Pharm Form Partnership Centered Around Treating Schizophrenia in South Korea
January 14th 2025The license agreement will feature an upcoming Phase III trial and—depending on results—the development, manufacturing, and commercialization of evenamide as a potential treatment option.
Machine Health in Pharmaceutical Production
December 2nd 2024Predictive maintenance in pharmaceutical production can help reduce downtime and increase efficiency. Grundfos Machine Health (GMH) uses artificial intelligence (AI)-driven wireless sensors to monitor motor health in real-time, identifying potential issues. This approach not only reduces maintenance costs but also ensures compliance with industry standards.