A focused service for life-science teams that need AI-assisted support around Informed Consent Forms (ICFs), patient recruitment content, translation handovers, redaction and human review — without losing traceability or accountability.
There's nothing new to learn. Simply upload your documents and let AI handle the repetitive drafting and document assembly. You stay in control of the final review, revisions, and decisions. What once took hundreds of hours and thousands of dollars now takes days - at a fraction of the cost, with the same or improved quality.
In testing on suitable document workflows, AI-assisted preparation cut drafting and revision effort by at least 75%.
Protocol, templates, local requirements and client rules.
Structured document preparation from approved material.
Qualified reviewers add comments and decisions.
Changes are implemented visibly with rationale.
Revisions are checked against source documents.
The service turns an unclear document process into a visible operating model: what goes in, what AI may help with, what must be reviewed, and how the decision trail is captured.
Measured against source files during Weiser Systems testing.
Improved after expert comments were incorporated and checked.
Reviewer feedback is checked against the source files. AI-assisted revisions are paired with confirmatory or explanatory comments, plus confidence levels where useful, so reviewers can see what changed and why.
Teams compare files manually, track questions across emails, repeat checks, and struggle to see which document changed, why, and who still needs to review it.
The workflow assistant prepares structured checks, change summaries, source references and review handovers — while final judgement remains with qualified people.
Every AI-supported step is scoped: allowed inputs, forbidden decisions, human review points, acceptance criteria and audit notes are defined before the pilot starts.
The first engagement tests one document family in one context so the team can judge workload impact, errors, usability and whether scaling is justified.
Complex clinical documents often repeat the same structures, terms, review patterns and country-specific adaptation rules. Once mapped, those patterns can support faster, more consistent document work.
The goal is not a loose AI text. The output is prepared so a team can review, challenge and approve it using familiar document practices.
Patient-facing trial documents often move through many hands: study teams, reviewers, legal, privacy and local approval processes. The opportunity is not “let AI write it”. The opportunity is to make the workflow easier to see, check and hand over.
Main (Adult, Parent/Guardian or Legally Acceptable Representative), Pregnancy and Newborn Follow-Up, ancillary consents and data privacy consents/authorisations — with careful versioning, review considerations and local adaptation support.
Common examples include: study posters, leaflets, website content, pre-screening questionnaires and doctor-to-patient letters or emails. Recruitment content and materials can be tailored to meet client specifications with the trial population in mind, supporting the work needed to achieve target recruitment numbers.
Common examples include: study guides, visit reminders, patient ID cards, physician referral materials and eligibility criteria checklists. Retention and site support content can be tailored to the trial’s needs, helping support patient and site engagement throughout the study.
AI can assist end-to-end ICF creation, from Global Master ICF development through implementation of country requirements for local adaptation.
AI can also support ICF revision following expected events that affect consent language, including protocol amendments and local submission queries.
Weiser Systems focuses on structured support around document handling: starting with creation, document sweeps with consistency checks, source file linking, guiding and explanatory review notes for optimal operational visibility and clarity. Final content decisions stay with qualified client teams and approved review processes.
Compare drafts, surface changed sections and prepare review notes that humans can validate.
Keep claims and changes tied to approved source material instead of free-form generation.
Expose unresolved questions, owners and next actions before work disappears into email chains.
Create working copies and review prompts that respect data boundaries and privacy constraints.
A narrow pilot is easier to plan, build, validate, document and improve. The goal is to identify whether AI support can improve creation and document handling: for a clearer, faster and more reliable workflow without weakening quality, consistency and human accountability.
Identify document types, inputs, owners, handovers, review gates, translation steps, redaction points and approval requirements.
Set data boundaries, source rules, human review responsibilities, audit notes and what the AI system is explicitly not allowed to decide.
Build a limited workflow assistant for checklists, summaries, version comparison, source-backed notes and question tracking.
Test outputs with real users, capture errors and workload impact, then decide whether the workflow deserves broader rollout.
For clinical trial submissions, ethics committee query implementation and resubmission windows can be short e.g., strict turnaround times for EU CTIS Part II considerations. The practical pressure is clear: document update, review, approvals, translation and redaction need a workflow that exposes bottlenecks early.
Send one example document family or process description. We will help identify where controlled AI support may reduce manual effort without compromising review discipline.