AI and Drug Development with Modern Clinical Trial Designs

Over the past decade, biomedical technology has been through a massive revolution, leading to innovative breakthrough treatments. At the same time, concerns have grown over the development cycle and escalating costs of drug development. To tackle cost concerns and other modern drug development challenges, new trial designs have emerged. Compared to conventional designs, modern clinical trial designs drive efficiencies. However, they also introduce complexities in the operational and statistical execution of clinical trials. These complexities impact service providers involved in trial execution, including Life sciences translation services. Large Language Models, or Artificial Intelligence are well-suited to address these challenges. AI and life sciences services can:

• Enhance speed and efficiency in language outcomes
• Ensure consistency in localized content
• Maintain style
• Facilitate strong results communication

New Trial Designs for AI and Drug Development

Conventional trial designs, characterized by randomized, double-blind comparisons of parallel treatment groups, have long been the gold standard for generating reliable and robust clinical data. Notably, their inherent limitations have been increasingly scrutinized. These limitations include:

• Long execution phases
• High costs
• Need for extensive sample sizes

Coupled with advancements in statistical software, classic trial design limitations have spurred development of alternative trial designs. These changes offer greater flexibility and efficiency in clinical trials.  

Master or Main protocols, classified as either basket, umbrella, or platform trials, are overarching protocols that contain more sub-studies. These protocols represent a paradigm shift for sponsors, regulators, and patients alike. The protocols enable parallel testing of multiple therapies and/or diseases under the same clinical infrastructure. Implementing a multinational trial protocol is both time and resource-intensive. As a result, a master protocol can deliver significant efficiencies in trial execution when its sub-studies share aspects such as

• Site selection
• Patient screening
• Data management
• Ethical or monitoring committees

Furthermore, potential to share a common control group across sub-studies may increase patient participation. This is due to a heightened likelihood of receiving the active experimental treatment.  

Adaptive trials, another modern trial design, allow for modifications during the trial execution based on accumulated data from trial participants. Such changes must be pre-defined. They require interim analyses during the trial to allow for mid-trial adaptations, such as sample size adjustments or discontinuation of certain doses. Adaptive trial designs offer high flexibility and can reduce timeline, costs, and number of patients exposed in a clinical drug development program.  

While conventional designs remain the standard, newer trial designs infuse flexibility and efficiency, accelerated enrolment, and reduced research costs. They also present fresh challenges for planning, organization, ethical surveillance, and statistical analysis. Therefore, sponsors are advised to plan language activities already during protocol development. 

AI and Drug Development Improve Trial Execution

Large Language Models (LLMs) are designed to drive efficiencies, speed, and consistency in language outcomes. They have great potential to support the preparation and efficient execution of new trial designs. Master protocols may necessitate high volumes of submission content during initial clinical trial applications (CTAs) and CTA amendments because multiple sub-studies are submitted under the same protocol. Adaptive trial designs may undergo multiple changes during trial conduct, necessitating new or repeated translations within stringent deadlines.   

Like any emerging drug development technology, the application of LLMs should be based on a risk assessment. They should also carefully consider:

• Content types
• Intended users
• Compliance aspects

The level of human intervention in translation workflows can be predetermined. A language plan can be established during the trial preparation stage while all essential clinical master documents are being developed. An obvious advantage of protocol-level language planning is that any adaptations, amendments, and new documentation after trial initiation can be expedited.  

As a leader in Large Language Models and expert in clinical trial content and requirements, Lionbridge helps trial sponsors build a language strategy that optimizes these new trial designs. 

Get in touch

Need help with your language strategy? Lionbridge has decades of experience providing clinical trial translation and Life Sciences content solutions. We’re deeply familiar with the challenges of multi-lingual clinical trials, and our team stays updated on the latest regulatory changes for clinical trials. Get in touch to learn more.