Where Can a Chinese Clinical Development Team Start With an AI Workflow?

For a Chinese clinical development team beginning with AI, I suggest a public trial-design comparison in one indication. It addresses a real need, allows bounded inputs and gives clinical, statistical, regulatory and operational staff a common result to discuss.

Choose an existing question, such as treatment line, population or primary outcome for the next study. “See what AI can do” is not a sufficient goal. Define the deliverable: a sourced design matrix and one page of questions still open for your program.

First, fix a small source set.

Begin with three to five relevant studies and record identifiers, sources, versions and retrieval dates. The CDE public information platform is a starting point for Chinese drug trials, supplemented by international records, papers and accessible protocols. Sources differ in coverage and currency; a registry summary is not a full protocol.

Second, extract predefined fields.

Include populations, prior treatment, groups, comparators, primary outcomes, assessments and consequential eligibility clauses. Preserve wording or locations and mark unknown information. Do not guess to complete a table. Standardizing between Chinese and English should retain originals, particularly thresholds, timing and negation.

Third, build a difference matrix.

Compare clauses and designs before considering why they differ. Histology, treatment context, testing and outcome populations may matter. A difference is not automatically a judgment of treatment superiority. Express implications as questions, such as whether your program requires the same test and why.

Fourth, assign focused cross-functional review.

Clinical staff confirm population and treatment context; statisticians check outcome and analysis questions; regulatory staff assess regional evidence and communication needs; operations examine records and execution. Return corrections and their basis to the same record.

China’s current Good Clinical Practice standard assigns medical judgments and decisions to qualified clinicians. Organizing public evidence does not change that responsibility. Expansion into formal research or patient-related work requires reevaluating purpose, procedures and data arrangements; the initial material pilot cannot validate every setting.

Fifth, evaluate representative cases.

Include long clauses, exceptions, missing information and version differences. Define what must be correct, especially clauses affecting populations or interpretation. Measure extraction, checking and rework together, and record failed source locations. Faster drafting is one observation; usefulness of the accepted deliverable is a separate judgment.

A short internal pilot can establish the task and sources, complete an initial extraction and review, then test repeatability with new or updated material. Duration depends on workload. This is a proposed process, not a claim of measured savings or faster enrollment in a real Chinese team.

Sixth, decide whether to continue and how to update.

A workflow with reliable clauses, accessible evidence and manageable review can be formalized. If most output needs rebuilding or errors are hard to detect, revise scope and method first. Assign update and version ownership so the table stays relevant.

There is no need to score the entire program initially. The matrix provides checkable design facts and connects them to open decisions. Accountable functions and governance still make those decisions.

Once repeatable, the workflow can extend to literature tables, protocol consistency and update tracking. Redefine inputs, purpose and acceptance at each expansion. A clear chain from sources to questions creates a stronger basis for lasting clinical development tools.