The Hidden Cost Shock After AI DeploymentIn early pilots, AI systems seem to be economically efficient on the surface. Traffic volumes are low, use cases are narrowly defined, and teams closely ...

There is no timeline yet to the implementation of the law allowing President Ferdinand Marcos, Jr. to suspend or reduce excise tax on fuel amid exponential rise in oil prices due to the Middle East ...

Bringing a single drug to market can take more than a decade and cost billions of dollars, with fewer than one in ten candidates successfully reaching approval. Against this backdrop, generative AI is ...

Artificial intelligence is fundamentally changing how software is built. It is moving beyond just speeding up tasks. AI is ...

Machine learning has moved past its initial experimental phase. In earlier years, development often focused on creating the ...

A global survey of more than 100 COOs at manufacturers with revenues of more than $1 billion found that 93% plan to increase investment in AI and digital technologies over the next five years. The ...

Combining the industry’s most compact cyclotron with an upright positioning system creates a proton therapy system small enough to fit into a linac vault ...

Celonis' Christoph Schettler declares that the era of reactive supply chains is over. As geopolitical disruptions in critical ...

The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...

As the AI era becomes increasingly shaped by foundation models, the pharmaceutical industry is entering a new phase of opportunity for discovery, design, and decision-making driven by AI for science.

In the race of innovative drug R&D, whether for antibodies, peptides, or novel binding proteins, the efficiency of early-stage molecule discovery is always the key factor determining project success ...