According to ClinicalTrials.gov, there are 3,046 multi-country trials being conducted this year.
While many trials remain localized within a single country, there has been a definitive movement towards conducting trials in multiple countries, especially for larger, later-stage trials. This is driven by the positives that multi-country trials offer, like faster patient recruitment, lower costs in some regions, and the need for diverse patient populations..
However, behind the scenes, a critical bottleneck has been slowing many trials down. This bottleneck is the translation process that’s required to make trials work across multiple languages, locales, and regulatory bodies/organizations.
Why translations are critical to study startup timelines
Traditionally, getting a clinical study ready for multiple languages involved a series of long, linear processes that was heavily on manual work and interpretation between multiple parties. This is because every document and its multitude of cultural nuances had to be first translated, then reviewed, and then finally migrated over to the sites responsible for running the trial. Regulatory compliance and accuracy added to the complexity, as regulators required that documentation must easily be understood by every locale and dialect it affected.
In the past, linear and sequential processes mandated that teams from different organizations. For instance, the process for verifying that translated content appeared correctly in the study build often involved generating and reviewing countless screenshots, a notoriously time-consuming task that added to the overall "screenshot madness."
Additionally, organizations would spend significant time on email exchanges, scheduling, and tracking progress through manual coordination. The process also involved resource-intensive reviews, with multiple rounds often necessary across several teams to catch errors and ensure consistency.
This current way of doing things leads to longer timelines and consumes valuable resources, pushing back the go-live dates for critical studies.
AI-powered efficiencies vastly accelerate the translation process
Thankfully, the introduction of artificial intelligence (AI) has marked a pivotal shift in how organizations can tackle translations.
Updated capabilities like Lionbridge Aurora’s parallel processing, enables the simultaneous batch processing of multiple languages, eliminating the sequential, step-by-step approach that was a notorious time constraint.
This benefit, when combined with advanced clinical trial platforms (such as Medable’s AI-enhanced platform) substantially reduces the resources and time needed in creating and reviewing screenshots. In the past, this process once involved multiple teams and disparate systems. Today, it now requires only one to two teams operating within a unified platform, demonstrating
Similar to how the best eCOA systems remove COA deployment from the critical path, AI-driven translation and localization has redefined what’s possible for translations.
For instance, Medable’s Translation and Localization Engine has already reduced translation cycle times from 12–16 days to just 4 days per batch, a 75% improvement. Additionally, localization timelines shrank from 12 days to just 4–7 days per locale, while review cycles dropped from 3–4 rounds to just 1–2, resulting in up to 25% cost savings.
These gains are possible because AI-powered translations instantly convert content from any format to any language. Translated materials are prepared for validation within minutes, significantly reducing operational delays. Again, these efficiencies translate into faster trial readiness, lower operational costs, and accelerated access to global markets.
Additionally, there is a steep drop in the amount of manual effort and errors produced by Medable’s Translation and Localization Engine. This is because automation is able to better manage key localization steps and validate migrated content against original trial source materials. This significantly minimizes human error while ensuring accuracy and regulatory compliance.
When looking through a wider lens, AI-enabled translations help enhance cross-user visibility through improved workflow transparency. This leads to better alignment between building teams and translation teams, fostering more agile and collaborative working environments.
In fact, a recent collaboration between Medable and Lionbridge exemplifies how advanced AI tools are effectively dismantling traditional translation bottlenecks.The impact of this AI-powered approach is undeniable. However, it’s also not the complete picture, as AI-powered translations have improved in their capabilities since the release of Medable and Lionbridge’s case study.
If we look at the the Medable and Lionbridge case study, the adoption of these new tools led to:
- A remarkable 43% reduction in overall translation timelines,
- 55% shorter timelines for screenshot review rounds with Medable Studio,
- 54% reduction in emails between Lionbridge and Medable, a testament to the streamlined communication, and
- Significant resource optimization, with Medable reducing the number of teams involved from 2-3 to 1-2, and using a single platform instead of multiple platforms.
Thus, by effectively eliminating translation bottlenecks, AI is providing scalable and repeatable efficiencies for global studies. This translates to earlier trial launches and a significant enhanced competitive advantage for sponsors, as well as maximized resource allocation due to a notable reduction in communication touchpoints.
Conclusion: AI-powered translations are much more than an incremental improvement
By shattering long-standing bottlenecks, AI is making the translation process faster and more efficient. In turn, this accelerates the delivery of life-changing treatments to patients worldwide.
As we move forward, this innovative approach is more than an incremental improvement. Instead, it moves Medable’s vision of a one day trial startup one step closer towards reality.
