Thermo Fisher and OpenAI Team Up to Accelerate Drug Development and Clinical Trials

Thermo Fisher partners with OpenAI to embed AI in development and operations, speeding trials and cutting costs. ChatGPT Enterprise helps faster decisions and cleaner execution.

Thermo Fisher partners with OpenAI to speed drug development

Thermo Fisher Scientific announced a collaboration with OpenAI to apply practical AI across product development, service delivery, customer engagement and operations. The goal: shorten clinical timelines, cut waste, and move effective therapies to patients faster and at lower cost.

The company will embed OpenAI APIs into core workflows and launch ChatGPT Enterprise to colleagues. The focus is on execution-ready use cases that improve cycle time, decision quality and scale.

Where AI lands first

PPD clinical research: Apply advanced models to reduce clinical trial cycle time and speed market entry.
Early kill signals: Use model-driven evidence to flag therapies unlikely to succeed so teams can reallocate resources sooner.
Accelerator Drug Development: Integrate AI across early development, Phase I-III, clinical manufacturing and supply, and commercialization for a more streamlined end-to-end path.
Workforce enablement: Roll out ChatGPT Enterprise to build fluency and consistent usage across teams.

Why this matters for product, science and clinical leaders

Faster decisions: Summarize protocols, prior art, safety signals and site performance in minutes, not weeks.
Higher kill-rate on weak assets: Data-driven triage helps stop low-probability programs earlier.
Cleaner execution: Standardized assistants cut handoffs, reduce rework and improve documentation quality.
Scale without bloat: AI co-pilots let small teams manage larger portfolios without proportional headcount increases.

How to capture value quickly

Define guardrails: Lock down data access, PII handling and traceability; require human-in-the-loop for high-risk outputs.
Start with narrow workflows: Protocol authoring, CSR drafting, site feasibility summaries and risk reports are high-yield pilots.
Measure what matters: Track cycle time, query volume, deviation rate, edit distance to final submission and cost per page.
Plug into existing tools: Embed AI in eTMF, CTMS, LIMS/ELN and QMS to avoid context switching.
Create validated prompts and templates: Version-controlled prompts, reference datasets and evaluation suites improve reliability.
Upskill teams: Train PMs, statisticians, medical writers and CRAs on repeatable patterns for review and signoff.

What leaders said

Marc Casper, Thermo Fisher's Chairman, President and CEO, said AI paired with the company's Mission is a catalyst to move scientific progress faster and deliver impact for customers, patients and society.

Brad Lightcap, COO at OpenAI, noted that integrating OpenAI directly into Thermo Fisher workflows can cut through complexity, compress timelines and improve how quickly medicines reach people.