01
Learn the operating discipline
Use the Academy to build role-specific understanding of intended use, data boundaries, review, documentation, escalation and qualification.
Explore Academy curriculum →AI work authorization
Train people to use AI. Authorize the work they are allowed to perform.
Life Sciences AI Academy develops role-specific capability. GxP Frame’s AI Work Authorization Toolkit gives Quality, process and system owners a structured way to decide what an AI-supported workflow may do, what evidence it requires and when it must be restricted. The two are designed to work together.
The foundational paper
Governing AI in Pharmaceutical Operations
Brian J. Drapeau, founder and principal consultant of GxP Frame and founder of Life Sciences AI Academy, wrote this structured white paper. It introduces the AI-Supported Work Authorization Cycle: a practical method for connecting intended use, authority, evidence, human review, qualification and corrective action to a local decision about whether AI-supported work may proceed.
White paper v2.2 · September 19, 2026 · GxP Frame
Read or download
How the offerings connect
Qualification supplies capability. Authorization supplies permission.
A course completion record does not establish that a person can use a particular AI workflow within approved boundaries. The Academy prepares people to recognize limits, review outputs, document decisions and escalate. The toolkit gives the organization records and gates for deciding which work may be authorized in the first place.
02
Apply the authorization method
Use the paper and reference toolkit to structure an AI use inventory, authority envelope, gate decision and workflow evaluation.
Review the toolkit →03
Make it work in your environment
Engage GxP Frame to adapt the work products to your systems, intended uses, roles, SOPs, evidence standards and release decisions.
Discuss implementation →The method
The AI-Supported Work Authorization Cycle
The paper’s six stages answer a practical sequence of questions. The evidence and templates give those questions a repeatable home; the Academy equips people to perform the roles within that process.
- 0
Inventory and ownership
Identify the AI use, the system and process it touches, and the accountable owners before the work proceeds.
OUTPUT: Use inventory
- 1
Define the work and risk
State the intended use, source boundary, decision affected and potential consequence of failure.
OUTPUT: Intended use and risk assessment
- 2
Set authority and records
Bound what the system may read, recommend, change or approve, and preserve the decision record.
OUTPUT: Authority envelope and gate record
- 3
Test the complete workflow
Challenge the system and the people reviewing it under representative conditions before routine use.
OUTPUT: Evaluation scoring sheet
- 4
Authorize routine use and monitor
Decide whether the available results justify use, then watch the workflow for drift, incidents and workload effects.
OUTPUT: Authorized operating conditions
- 5
Change, correct and retire
Assess what changed, test the response and narrow, suspend or retire work when the evidence calls for it.
OUTPUT: Change and corrective-action evidence
Reference toolkit
Review the method in use before you license or implement it
These downloadable reference files demonstrate how the white paper is applied. They are functional or read-only examples for review and learning; they are not editable organizational records. The current source files are maintained on GxP Frame so their versions stay aligned with the paper.
Unified toolkit user guide
How the paper, templates, roles and decisions fit together.
Open PDF ↗Role quick-start cards
Practical orientation for Quality, process, system and evaluation owners.
Open PDF ↗AI Use Inventory
A functional reference copy for identifying use, ownership, system and data boundaries.
Open reference copy ↗Gate Decision Record
A read-only reference copy for recording the authorization decision and residual risk.
Open PDF ↗Workflow Evaluation Scoring Sheet
A functional reference copy for Stage 3 challenge cases, results and review conditions.
Open reference copy ↗Editable toolkit license
Start with the system. Then make the templates yours.
The editable AI Work Authorization Toolkit is licensed for one organization at $3,250. It is distinct from the Academy's self-service learning packages. The license provides editable working files that your accountable team can adapt to its own governed process.
A private implementation engagement begins with a consultation to understand the use cases, company size, existing systems and regulated-process impact. That discovery informs a scoped estimate for work that may include configuration, role qualification, evidence design, controlled rollout and end-to-end implementation support.
Start with the real workflow
Decide what needs to be learned, authorized and evidenced
The initial conversation identifies the AI-supported work, regulated context, people, systems and decision that must be defended before a proposed scope is prepared.