AstraZeneca stands apart from other major pharmaceutical companies by using artificial intelligence (AI) not only in laboratories but directly within national healthcare systems. While competitors focus on internal drug development processes, AstraZeneca has deployed AI in practice, where it screens hundreds of thousands of patients. This delivers immediate public health results.
Results from the CREATE clinical study, presented by AstraZeneca at the European Lung Cancer Congress in March 2025, show a positive predictive value of 54.1% for the chest X-ray analysis tool. This tool exceeded the predetermined success threshold of 20%. In Thailand, AI has screened more than 660,000 people since 2022 and detected suspicious lung lesions in 8% of them. Thailand's National Health Security Office is now expanding the system to 887 hospitals with a budget exceeding 415 million baht (approximately CZK 274 million).
This is not merely a pilot program, but a full-scale national deployment of AI that helps detect diseases earlier.
Differences in Pharmaceutical Companies' Approaches to AI
Pfizer has accelerated drug development through its machine learning hub, where molecule identification takes about 30 days. The company used AI in the development of Paxlovid, with patient data analysis completed 50% faster than with traditional methods. Pfizer now applies AI in more than half of its clinical trials.
Novartis is collaborating with Isomorphic Labs, founded by Nobel laureate Demis Hassabis, and with Microsoft on AI-powered drug discovery. Its intelligent decision-making system uses digital twins to simulate clinical trial processes, enabling faster patient recruitment at selected sites.
Roche applies a "lab-in-the-loop" strategy, in which AI models work in conjunction with laboratory experiments. Following its acquisitions of Foundation Medicine and Flatiron Health, Roche created the largest database of clinical genomic profiles—more than 800,000 profiles across over 150 tumor types. Its goal is to achieve a 50% improvement in safety management by 2026.
AstraZeneca's Advantages in Clinical Operations
AstraZeneca runs more than 240 global trials across its development portfolio and has integrated AI into every phase. Its "intelligent protocol tool," developed with medical writers, has reduced document creation time by up to 85% in some cases. The company uses AI to detect 3D locations in CT scans, reducing the time radiologists spend on manual annotation.
AstraZeneca is introducing virtual control groups in clinical trials, where electronic health records and data from previous trials are used to simulate placebo groups. This reduces the number of patients receiving inactive treatment and changes the fundamental design of trials.
The lung cancer screening program in Thailand uses Qure.ai's qXR-LNMS tool. In December 2025, it will expand to screen 5,000 industrial workers across four Thai provinces and now also includes heart failure detection.
Accelerating Drug Development Through AI
Traditional drug development takes 10–15 years and has a 90% failure rate. AI-discovered drugs achieve an 80–90% success rate in Phase I, twice the 40–65% achieved by conventional methods currently in use. More than 3,000 AI-assisted drugs are currently in development, with over 200 approvals expected by 2030.
Pfizer is moving from molecule identification to testing in six-week cycles. Novartis analyzes 460,000 clinical trials in minutes rather than months. AstraZeneca, however, delivers an immediate impact for patients by detecting cancer in underserved populations, often before symptoms appear.
The Question of AI's Value
The World Economic Forum estimates that AI could generate USD 350–410 billion annually for the pharmaceutical industry by 2030 (approximately CZK 8–9.4 trillion). The question is whether faster drug discovery or more efficient clinical operations offer greater benefits.
Pfizer is betting on computer-aided drug design, while Novartis is focusing on AI-based trial site selection. Roche is building a proprietary data moat by integrating its pharmaceutical and diagnostics models.
AstraZeneca integrates AI into all operations—from protocol generation and patient recruitment to regulatory submissions—reducing time to market and collecting real-world evidence.
The company works with partners such as Qure.ai and Perceptra, regulators, and national systems to deploy AI where infrastructure is lacking.
AstraZeneca is targeting 20 new medicines and revenue of around USD 80 billion (approximately CZK 1.8 trillion) by 2030. Its approach to AI in clinical trials demonstrates value in the most tightly regulated phase of drug development. While competitors search for new molecules, AstraZeneca is transforming the very way trials are conducted. Victory may belong to those who deploy AI where it improves patient outcomes—at scale, under regulatory oversight, and in real-world healthcare systems. AstraZeneca currently leads this race.
Source: artificialintelligence-news.com
