English
翻訳会社
tradução em papel
empresa de traducción
traduzione cartacea
Papierübersetzung
traduction papier
papieren vertaling
ترجمه مقاله
แปลกระดาษ
бумажный перевод
ترجمة ورقية
makale çeviri
Tradutor de Artigos
學術翻譯
학술출판번역
论文翻译
AI Translation Pipeline for Delivering Clinical Evidence to Japanese Physicians
How Ulatus engineered a custom AI-orchestrated translation pipeline to deliver 4.16+ million words of evidence-based clinical content from English to Japanese in just 1.5 months.
Client Testimonial
This was the first time we were bringing content of this scale and sensitivity into Japanese for our platform, and the stakes were high: physicians would be relying on this material for real diagnostic and treatment decisions. Ulatus identified a structural problem in our source files that we hadn't fully anticipated, engineered a fix for it before translation even began, and still delivered over four million words within an extremely tight timeline without compromising the accuracy our reputation depends on.
Global Publisher of Evidence-Based Clinical Decision Support Content
Project Summary
About the Company, Their Requirements, and Why
The client is a global publisher of evidence-based clinical decision support content, relied on by physicians and healthcare institutions around the world to guide diagnostic and treatment decisions at the point of care. Its content is written and continuously updated by physician-authors and peer-reviewed by practicing clinicians across dozens of specialties, which makes clinical and terminological accuracy non-negotiable in any language the content is published in.
The client was preparing to make a large body of this clinical content available in Japanese for the first time, so that physicians in Japan could access the same depth of evidence-based guidance already trusted by clinicians elsewhere. The scope covered 600+ clinical topic reviews (in effect, 600+ full-length clinical papers) spanning 18 therapeutic areas including infectious diseases, pulmonary and critical care medicine, neurology, nephrology and hypertension, hematology, rheumatology, endocrinology, cardiovascular medicine, gastroenterology, and pediatrics, among others.
Because this content would ultimately be sold to and relied upon by practicing physicians, the client set requirements that went well beyond typical translation quality bars: physician-level review of every translated topic, zero tolerance for drug name, dosage, or unit errors, strict preservation of the source formatting and cross-referencing structure, and full delivery of all 4.16+ million words within just 1.5 months.
Challenges We Faced During the Project
A Source Format That Actively Worked Against Translation
The client's source files were delivered as structured XML paired with reference PDFs. On paper, XML should be a translation-friendly format; however, the XML files we received had source content that was entirely fragmented, with formatting and structural elements interwoven throughout the text. Fed directly into an AI translation engine, this fragmentation caused each isolated segment to be translated in isolation from the others, producing output that was grammatically broken and, in places, meaningless.
Volume and Velocity at a Scale That Left No Margin
4.16+ million words across 600+ full clinical topics, spread across 18 different therapeutic areas, had to be translated, reviewed, and finalized in six weeks. That pace ruled out any workflow that depended on manual, segment-by-segment fixes to the underlying structural problem: the fix had to be systematic and automated from the outset.
Physician Reviewers Instead of Linguists
The client required every translated topic to be reviewed by a physician rather than a professional linguist, given the clinical nature of the content. This meant sourcing a panel of doctors across 18 specialties, and coordinating their already demanding schedules against a fixed delivery calendar. Physician reviewers bring deep clinical judgment but not the same trained eye for target-language fluency and register that a dedicated linguist would apply, and the project timeline did not allow for a second, dedicated linguistic review pass after physician revisions before delivery.
Zero Tolerance for Clinical Error
Because the finished Japanese content would be published for physicians to consult when making real diagnostic and treatment decisions, any drug name, dosage, unit, or clinical value that was mistranslated, omitted, or altered had the potential to cause real-world harm. With a compressed timeline and a physician-led (rather than linguist-led) review step, the risk of an error slipping through to publication was a constant, serious concern.
Solutions Provided by Ulatus
The solution came together in five parts. At the center was a single AI-orchestrated workflow that carried each of the 600 topics through AI translation, physician review, and AI audit as one continuous pipeline, with segments routed automatically between steps rather than handed off manually.
Re-Engineering the Source Files Before Translation Even Began
Rather than translating the broken XML segmentation as-is, our development team built a custom conversion pipeline that transformed each XML file, reconstructing every full text string as a single, coherent translation segment instead of a scattered chain of fragments. Formatting and structural elements (bold, italic, subscript, superscript, drug-name flags, inline layout hints, citation references, and cross-references to other topics) were preserved using a custom token system, so AI and physician reviewers could see and translate clean, complete sentences while every underlying tag stayed intact and traceable. Once review was complete, the same pipeline ran in reverse, reinserting every formatting tag, citation, and cross-reference into its correct position so the client received files structurally identical to what they had sent us, just fully translated.
A Purpose-Built Clinical Glossary Before a Single Word Was Translated
To ground the AI translation step in accurate, standardized medical terminology from the outset, we built a dedicated English-Japanese glossary using the MedDRA terminology dictionary as its clinical backbone, applied through Ulatus proprietary GlossaryX360 multilingual terminology tool. GlossaryX360 draws on a repository of 150,000+ terms across 10+ languages and automatically applies domain-specific terminology to documents based on their subject matter, meaning every drug name, clinical term, and unit of measure was translated consistently before a linguist or physician ever touched the file.
AI Translation on Clean, Whole-Sentence Segments
With properly reconstructed sentences and a domain-specific glossary in place, the AI translation step produced dramatically better first-pass output than the original broken-segment approach: Japanese sentences that read naturally and followed correct grammatical structure, instead of translations built from disconnected fragments. This gave physician reviewers a genuinely usable starting point rather than text that needed to be reverse-engineered before it could even be assessed for clinical accuracy.
Building and Coordinating a Physician Review Panel Under a Fixed Deadline
Our project management team recruited and scheduled a panel of physicians matched to each of the 18 therapeutic areas in scope, and coordinated their reviews against the project's six-week delivery calendar. Balancing the availability of busy, in-demand medical professionals against a fixed schedule required constant, hands-on coordination, but it ensured every topic was reviewed by someone with genuine clinical authority in that specialty.
An AI Orchestration Layer as the Safety Net Behind Physician Review
Because the timeline did not allow for a separate linguistic review pass after physician revisions, we introduced an AI audit step to close that gap. Every physician-reviewed segment was run through an AI audit that scored it across fluency, meaning, technical terminology, completeness, tag integrity, drug name accuracy, dosage accuracy, mistranslation risk, and omissions. An AI orchestration layer sat on top of this scoring, automatically routing any segment that fell below the quality threshold back to the physician panel for a second, targeted review, giving the project a systematic quality safety net without adding a full additional review cycle to an already tight schedule.
Project Overview
Translated 4.16+ million words across 600+ clinical topic reviews spanning 18 therapeutic areas, from English into Japanese, within a 1.5-month turnaround.
Built a custom XML engineering pipeline that repaired broken source segmentation while preserving every formatting tag, citation, and cross-reference in the original file structure.
Deployed a dedicated English-Japanese clinical glossary built on the MedDRA dictionary through Ulatus proprietary GlossaryX360 terminology tool (150,000+ terms, 10+ languages) to ground AI translation in accurate, consistent terminology.
Recruited and coordinated a panel of physicians across 18 specialties to review translated content against a fixed delivery schedule.
Introduced an AI audit layer to systematically re-check physician-reviewed content for fluency, terminology, tag integrity, drug and dosage accuracy, and completeness, routing flagged segments back for a second physician pass.
Enabled the client's first-ever release of translated evidence-based clinical content of this scale onto its platform for Japanese physicians.
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