Besides being time-consuming, drug development is an expensive and risky business, with a clinical trial failure rate of up to 90% and average cost of USD 2.6 billion.
While AI cannot replace clinical studies as a vital step in safe drug development, it can help focus resources onto the most promising compounds, which accelerates processes, reduces risk of failure and cuts costs. AI-based drug-discovery applications use machine learning to identify candidates and predict their interactions in vivo, enabling the research team to better prioritize their efforts.
Once a product is ready to move from bench to bedside, AI can help select sites and support the process of identifying the right patients for a clinical trial. A world leading analytics provider in healthcare, has seen enrolment rates to clinical trials increase more than 20% and automatic processing of adverse drug reactions in 70% of cases.
AI isn’t just being used in early research and to plan clinical studies. Natural language processing (NLP) is also increasingly finding its way into medical applications. NLP can be used to search, analyze and interpret large amounts of patient data. Data sources can be as diverse as discussions in public health forums, social media posts or electronic health records. For example, large pharmaceutical companies already gained a label expansion for the drugs, partially based on NLP analysis. Data for the analysis was sourced from electronic health records and three databases containing post-marketing reports of real-world use of the drug in male patients. Real-world evidence is also supporting clinical studies. By serving as a synthetic control arm, it’s especially useful in the case of rare conditions where traditional patient recruitment would take too long. Speeding up the clinical trial benefits both patients and drug developers.
Considering the huge impact that AI can have on R&D and the large investments made by pharma companies, it’s surprising that pharmaceutical companies are generally hesitant adopters. A 2019 review paper found that just 18 AI-related patent applications had been submitted by the top 20 pharma companies (by revenue) in recent years, compared to thousands by technology companies. In terms of investment in AI, the healthcare industry will rank behind banking, manufacturing, retail and the public sector in 2021 according to Atos, a global leader in digital transformation.