New research reveals that 50% of European and US pharmaceutical manufacturing companies know artificial intelligence (AI) can help bring new drugs to market more rapidly and securely, but 96% face challenges with using it to derive value from their data.
49% of all executives surveyed say their company has no overarching strategy for while 31% say they lack consistent data structures that make implementation easier or have high levels of unstructured data that are more complex to handle. 43% of pharma executives believe that if companies in their industry fail to learn the lessons of AI and machine learning (ML) adoption from other sectors, they will be in severe financial trouble within two years.
“Our research shows pharma companies need to act now to tackle their data challenges and implement AI,” said David Leitham, Senior Vice President and General Manager Pharma, AspenTech. “Advances in AI will relieve the growing pressures on them, built on the ability to break down the barriers between systems and types of data within production processes and supply chains. Organisations must reimagine their digital culture and think more holistically about what data will add across all aspects of drug manufacture.”
The research reveals that 30% of executives say their companies struggle with data that is held in separate, siloed systems, while 28% suffer from a lack of digital skills or a risk-averse culture that does not foster innovation. Even the more advanced, data-driven companies in the research have a problem with risk-averse culture (43%).