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Research reveals the greatest fear of life sciences tech leaders: cyber espionage

NTT DATA finds one third of life science leaders are concerned about various cyber threats

Cyber attacks pose the greatest technology-related risk within the life sciences industry, according to a survey of senior digital leaders working for major businesses in the sector – with industrial espionage posing an even greater threat than attacks motivated by financial theft or extortion.

The findings are among those set out in a new report titled Technology-Driven Opportunities & Risks in Life Sciences, which surveyed 100 digital and data leaders within life sciences businesses and was published by international technology and life sciences innovator NTT DATA UK&I. The report also identifies concerns about both the danger of accidentally losing or releasing data, and the risks involved in deploying Artificial Intelligence (AI) and Cloud technologies.

35% of respondents said that “very substantial” effort is required to keep the risk of “cyber-attack for espionage or data theft” at an acceptable level, with 31% saying the same of “cyber-attack for extortion or financial theft”. The risk named in third place on this metric is that of “breach of security due to flawed Cloud migration”, which requires very substantial effort for 26% of respondents.

“The life sciences sector faces a heightened risk of espionage and data theft, which reflects the high value of research and trials data. In a sector where R&D costs represent a high proportion of investment, and the first organisation to register a new treatment or vaccine leads the market for the duration of the patent, this information often comprises an organisation’s greatest asset,” explained Phil Rust], Healthcare Architect & Technical Leaderat NTT DATA UK&I. “Such data is also very attractive to state-backed cyber actors – who are often better organised and resourced than other cyber criminals, and thus present a greater threat.”

Excitement over AI potential 

However, these cyber security fears are balanced by widespread optimism about the capabilities and maturity of digital and data technologies – particularly Artificial Intelligence. 35% of respondents said that predictive AI presents “very substantial opportunities” to generate revenue and savings, while 34% said the same of generative AI.

Other key findings on the use of AI in life sciences includes:

  • Asked how their organisations are allocating time and resources to AI projects, respondents generally named projects more suited to predictive AI – such as the quantitative analysis of large statistical datasets – than to ‘large language model’-based generative AI systems such as ChatGPT.
  • Some 30% stated their top priority was “data analysis to identify new conditions where there is unmet medical need”, while 21% of respondents are prioritising “data analysis to identify new molecules with therapeutic potential”. Both goals fall within the top five priorities of more than 80% of respondents.
  • Digital leaders are also pursuing AI-powered reforms to clinical trials: 66% list the processing of trials data for regulator submissions among their top five priorities; 62% include the identification of trial participants as a priority; while a further 62% are prioritising the creation of ‘digital twins’ to act as controls in ‘in silico’ computer-based trials.

Wider technologies also drawing interest

Respondents also see huge potential in some lower-profile but more mature technologies – most notably 5G, telemedicine, automation and Cloud. Some 30% of respondents believe the “use of 5G to improve data-gathering and the pace and efficiency of business processes” presents “very substantial opportunities”, putting it in third place behind the two AI technologies. On this metric, “the use of robotic process automation to perform routine administrative tasks” comes fourth, representing very substantial opportunities for 27% of respondents.

Phil adds: “The strong interest in 5G reflects its range of uses in life sciences – organisations can create private networks operating within research, treatment or production facilities, or use the technology to exchange data remotely with scientific and medical equipment such as wearable technologies.”

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