Case StudiesBiopharma

Bring R&D datato life

From multilingual collaboration across global teams to second-level search across millions of papers, NextAI turns every piece of biopharma knowledge into compounding value.

Biopharma

Biopharma R&D Challenges and the AI Path Forward

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The language wall in global R&D

Biopharma is global by nature. R&D, clinical, manufacturing, and regulatory teams are distributed worldwide, so multilingual communication is expensive and cross-border collaboration slows down. Language is not the real barrier. Efficiency is.

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Information overload in literature review

A single R&D lead may need to track hundreds of papers, guidelines, and preprints every week. Nature, Cell, and Lancet never stop updating. Teams do not have time to read everything, yet they cannot afford to miss the one critical data point.

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Knowledge gaps across CXO projects

In CRO and CDMO settings, people rotate frequently. When one key person leaves, much of the project decision history leaves with them. New team members are forced to reconstruct the logic from scratch.

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A maze of regulatory versions

FDA, EMA, and NMPA guidance updates dozens of times per year. Sales, registration, and compliance teams each maintain their own spreadsheet, and eventually no one can say with confidence which version was actually used in a submission.

Literature intelligence

AI literature interpretation hub

The platform connects PubMed, internal literature libraries, and research reports. With a multi-stage RAG plus LLM workflow, it produces a structured readout across research background, methodology, key findings, and commercialization implications in under 30 seconds.

Multilingual collaboration

Real-time multilingual workspace

Built for cross-border R&D and clinical teams, the system embeds domain terminology so that phrases such as “Adverse Event” are translated correctly every time. It plugs into Teams, WeCom, and email without changing daily habits.

Knowledge retention

CXO project knowledge base

Every meeting note, decision document, and client email is retained at the project level, so a new joiner can immediately ask why the project was designed this way, where the risks are, and what pitfalls to avoid next.

Compliance traceability

Authoritative regulatory library

The latest FDA, EMA, and NMPA documents are ingested automatically, but only versions approved by designated compliance owners can be surfaced in AI answers. Every answer includes its source and effective date.

Biopharma

How to Improve Global R&D Collaboration

Client background

An international innovative biopharma company

The client is an innovation-driven biopharma company headquartered in Shanghai, with R&D centers across China, the United States, and Europe, focused on oncology and metabolic therapeutics.

The challenge

Over the last three years, its drug pipeline expanded rapidly and cross-border collaboration tripled. R&D daily reports had to be written in English, translated into Chinese, and then rewritten again for local shareholders. Weekly clinical meetings required the same deck in two languages, and email chains were full of second-round confirmations caused by inaccurate translation. The company estimated that every employee was losing at least six hours per week to translation-heavy work.

Biopharma

Case details

From diagnosis to value delivery in one closed loop.

What we built

We built a real-time translation layer embedded directly into Outlook, Teams, and WeCom. The key was not generic translation. It was translation that understands biopharma. We injected internal term lists, abbreviation dictionaries, and product naming references, so even senior medical directors did not need to revise the output.
We also connected the client’s SharePoint literature library. Researchers writing weekly updates could simply ask, “What are the most relevant new GLP-1 publications this week?” The AI retrieved, summarized, and linked the source material entirely inside the client’s private environment.

What the client gained

Cross-border communication improved sharply, saving R&D staff more than five hours per week on translation work.
Chinese and English daily and weekly reports moved from manual reconciliation to AI-generated final drafts.
Literature tracking improved from two carefully read papers per week to browsing twenty and deeply reading five.
Company literature began to accumulate as a shared, searchable asset instead of being scattered across personal bookmarks.

Biopharma

Technical capabilities behind global R&D collaboration

Enterprise-grade security and extensibility for biopharma teams.

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Fully private deployment

Data stays inside enterprise boundaries and supports GxP-level compliance requirements.

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Dual-channel terminology management

Medical terminology can be maintained manually while also improving through AI learning as business usage evolves.

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Multi-source literature access

PubMed, Google Scholar, and internal systems connect into one unified knowledge entry point.

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Reserved APIs for R&D systems

The platform is ready to integrate with CTMS, EDC, and eTMF systems inside existing digital R&D stacks.

Biopharma

We work with both Biotech and Big Pharma. A 30-minute conversation is enough to understand your scenario.