Decommissioning Legacy Labs: How to Cut Costs Without Losing Data Intelligence
The Hidden Value in “Dark Data” Pharmaceutical companies often sit on petabytes of “Dark Data” information generated in failed trials, retired lab applications, and completed projects. This data is often ignored or deleted to save space. This is a strategic error. Research shows that “unexplored” areas of the genome and historical failure data often hold […]
Beyond Storage: Building a Data Fabric for AI-Driven Drug Discovery
The “Silo” Problem Data fragmentation is the number one blocker for AI adoption in Pharma. Even industry giants like Novartis have publicly noted the extreme difficulty of cleaning and linking heterogeneous data across a global organization. Valuable data sits trapped in different formats (structured SQL vs. unstructured pathology images), different legacy applications (old ELNs vs. […]
Stop Re-Inventing the Wheel: How Semantic Content Libraries Accelerate Drug Repurposing
The Value of “Old” Drugs Discovering a new chemical entity (NCE) is risky 90% fail. Drug Repurposing (finding new uses for existing drugs) is the strategic shortcut. These drugs have already passed toxicity screens; their safety profiles are known. A famous example of this is Baricitinib. Originally a rheumatoid arthritis drug, it was identified by […]
Why You Don’t Need a “Big Pharma” Budget for Quantum Drug Discovery
The Cost Barrier is Gone For decades, high-fidelity molecular modeling was a luxury reserved for the “Big Pharma” elite. Developing a new drug costs nearly $2 billion, and a significant portion of that budget goes into massive High-Performance Computing (HPC) clusters required to run complex simulations. Small biotechs and startups were forced to rely on […]
AI Data Management for Drug Discovery: Accelerating R&D with Solix EAI Pharma
What is AI Data Management in Life Sciences? We are living in the “Decade of Data.” The biomedical domain has seen an explosion of information, driven by the plummeting cost of Next Generation Sequencing (NGS), the digitization of health records, and the rise of wearable sensors. However, for most Pharma organizations, this data is a […]
Why GenAI Fails in Drug Discovery and How Semantic Data Fixes It
Introduction: The Promise vs. The Reality of Pharma AI The pharmaceutical industry is currently navigating a paradoxical “drug drought.” Over the last decade, R&D investment has skyrocketed, yet the return on investment (ROI) for the top pharmaceutical companies has plummeted dropping from roughly 10% in 2010 to under 2% recently. The industry is desperate for […]