6 Ways to Elevate Your Machine Translation Strategy

Future-proof your MT strategy for clinical and regulatory content with this guide.

AI Driven

With 2025 well underway, innovators in the global life sciences and pharmaceutical industries continue to question how to maximize efficiencies and reduce complexities in clinical and regulatory content development and localization. As part of the broader technological roadmap, AI and automation remain front and center as key players in taking these workflows to new heights. Here are six approaches to ensure you don’t miss a pivotal step when adapting and applying your process. 

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1. Translation Model Customization

The pharmaceutical industry commands precision and optimal quality in all content. MT models should therefore be tailored and regularly updated such that they align with industry-specific terminology and have built-in glossaries that enforce accuracy and consistency across all translated materials. Using translation memories (TMs) and engine customization with company-specific data enables teams to repurpose pre-approved translations to cut down on review cycle times and ensure content uniformity when compared to “off-the-shelf” machine translation models. 

2. Integration with Clinical & Regulatory Technologies

From a workflow perspective, MT can be integrated directly into additional content repositories, like an eTMF, RIM, web CMS, and more. This generates faster and more secure MT workflows that can be initiated from those same systems where your documents are authored and stored, in a secure “closed loop” ecosystem. In addition, integration with technologies like generative AI and natural language processing can yield more sophisticated language understanding and translation than MT alone. Explore 5 essential use cases for AI automation in regulatory content

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3. Increased Use of Multimodal Translation

With continually evolving capabilities and new use cases being identified, MT may extend beyond text to include multimodal elements, such as translating audio, images, graphs, and other visual content commonly found in pharmaceutical documents. This could enhance the overall translation of complex information and provide significant efficiencies in areas like patient recruitment and medical information, which more frequently utilize multi-channel and non-document-based content.

4. Enhanced Post-Editing Automation

Automation of post-editing processes has become more sophisticated, mitigating the need for extensive human intervention post-MT. Generative AI tools embedded within the review module leveraged by post-editors results in more streamlined workflows and rapid delivery of high-quality, fully reviewed translations.

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5. Compliance Monitoring and Reporting

MT systems have evolved to incorporate multifaceted tools, such as built-in compliance monitoring features, ensuring that translations comply with specific regulatory requirements through automated checks for terminology consistency and language compliance, for example.

6. Real-Time Collaboration Tools

The integration of real-time collaboration tools within MT platforms enhances efficiency and enables global teams to work simultaneously on translation projects. Features like live editing, instant feedback, and collaborative workflows help cut down the time needed to make documents submission-ready.

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