The intersection of AI and drug development has ushered in a transformative era, revolutionizing the way researchers approach biomarker/target identification, drug/target interactions, and drug-like molecule design. AI in the life sciences seeks to unravel intricate biological phenomena through systematic assimilation, analysis, and interpretation of expansive and diverse datasets.
With the rise of new technologies and predictive analytics capable of handling the huge amounts of data within and across existing information systems, Industry 4.0 has been thriving in many sectors, such as industrial automation, financial technology, retail, and semiconductors. But the health sector in general,
Industry 4.0 applications in biopharma involve the complete spectrum of data science throughout the entire product life cycle of many disparate entity types. Tools such as digitalization, modern data science, and the industrial internet of things (IIoT) exist now, and examples from other industries such as Siri and Alexa, face identification, and self-driving cars can guide their...
