AstraZeneca, Roche, Takeda, GSK tout AI tools during half-year earnings reports

Big Pharma companies are catching the artificial intelligence wave, evidenced by a number of drugmakers’ comments in their half-year earnings reports this week.

A handful of companies highlighted their AI efforts across drug development, manufacturing and commercialization, including AstraZeneca, Roche, Takeda and GSK so far. Consulting firm McKinsey & Company reported a “rapid rise” in pharma partnerships with AI companies back in October, identifying nearly 270 companies in the AI-driven drug discovery space.

Christophe Weber

“We think that all our employees eventually will have some application of AI for their jobs,” Takeda CEO Christophe Weber said on the company’s investor call, according to an AlphaSense transcript.

The Japanese pharma company is using AI on the manufacturing side to improve efficiency of its line via image recognition, on the research side to test protocols and accelerate clinical trials, and on the commercial side to optimize its digital interaction with doctors.

“This is really a very high priority for us,” Weber said.

Aradhana Sarin

Meanwhile, Roche has developed its own in-house language model similar to ChatGPT, while AstraZeneca has used AI to optimize production schedules at one of its largest global manufacturing sites in Sweden, resulting in a “90% improvement in scheduling time,” CFO Aradhana Sarin said during an investor call.

“Our ambition is to leverage many of these tools and roll them throughout our manufacturing and supply network. This is of course a journey, but the work is already underway,” she said.

Kim Branson

Kim Branson. GSK’s senior VP and global head of AI and machine learning, told Endpoints News on Friday that the pharma giant is using new technology to predict patient response, assist with enrollment and identify biomarkers. The company recently paired Phase II data from its experimental hepatitis B drug bepirovirsen with AI and machine learning to analyze five patient groups for a better understanding of how the disease manifests in different populations and how patients respond to the drug.

“Our strategy is to identify areas where we know an AI model can have a sustained…impact and focus on building a solution for those areas,” Branson said.

While AI backers tout lofty goals of slashing drug development time and revolutionizing the industry, critics have raised concerns around the accuracy of results, potential bias in algorithms, and too much hype. And as Weber pointed out on the call, AI is only as good as the data you put in.

“It’s really bad to be near the word ‘magical’ in science,” Schrödinger CEO Ramy Farid told Endpoints earlier this month. “That scares me. The more overhype, the harder you fall.”

GSK’s Branson said that the company has a VP of AI ethics and policy that serves as an “independent check” on the company’s AI programs.

While noting the potential opportunities the technology creates, Branson added, “We also need to balance the ability to move at pace but work in a regulated and ethical manner.”

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