The scale of the difficulties is revealed in research commissioned by Aspen Technology, a global leader in asset optimisation software, among 300 pharmaceutical industry decision-makers in the UK, US, Germany, France, Spain and Sweden.
Nearly half (49%) of all executives surveyed say their company has no overarching strategy for AI. Nearly a third (31%) say they lack consistent data structures that make implementation easier or have high levels of unstructured data that are more complex to handle.
More than four-in-ten (43%) pharma executives believe that if companies in their industry fail to learn the lessons of AI and 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 three-in-ten executives (30%) say their companies struggle with data that is held in separate, siloed systems, while more than a quarter (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%).
“There is no shortage of smarter, better ways for pharma companies to use technology,” said Leitham. “Best of all, these solutions are available now, they are being adopted, and they are helping companies get ahead.”