Data Academy · Tutorial 4 of 10 · Life sciences & pharma

Governed AI in life sciences & pharma

Pharmaceutical and biotech companies are using AI agents in the document- and rule-heavy work around medicines: safety case processing, quality investigations, batch release readiness, clinical supply and regulatory writing. Because these are GxP processes that regulators inspect, scale depends on validated rules, human accountability for every regulated decision and records that meet 21 CFR Part 11 and EU Annex 11.

01 What is changing

Where AI in life sciences is heading

From drafting assistants to multi-agent systems that pull from quality, safety and regulatory systems and prepare complete work products for expert review.
From isolated R&D experiments to operations, quality and safety, where workflows are repeatable and the evidence trail already exists.
From treating AI as unregulated tooling to treating any AI that influences batch release, deviations or safety reporting as a validated, computerised system.
From scattered pilots to a few end-to-end workflows redesigned around agents, with experts reviewing rather than assembling.

02 Use cases

Three use cases on the governed path

Each use case runs the same path: a business question, governed context, a deterministic rule, specialist agents, a policy check, an action and a record. How the path works →

Illustrative: names and figures are invented to show the flow.

Use case 1

Batch release readiness

Batches wait in quarantine while quality staff check records across MES, LIMS and QMS by hand, which strains supply. A readiness check that surfaces every open item early shortens release without weakening control.

“Can batch LX-2417 be put forward for certification this week, and if not, what is holding it?”Asked by a head of quality operations

Context: MES: electronic batch record for LX-2417 of Corvelan 20 mg tablets complete at the Brightmoor site
LIMS: assay, dissolution and impurities all within specification
QMS: deviation DEV-0931 (granulation room temperature above limit for 2 hours) linked to the batch, investigation open
ERP: 3 markets awaiting stock; distributor cover about 9 days
Rule: No batch is proposed for certification while any linked deviation, out-of-specification result or change control remains open or unapproved.
Decision: Propose batch for certification Severity: High
Agents: Record review agent Checks the batch record, test results and equipment logs for completeness and exceptions, citing each entry.
Deviation agent Summarises DEV-0931, comparable past deviations and their root causes to help the investigator.
Supply impact agent Shows which markets run short first if release slips, so planning can respond.
Policy: Only a Qualified Person (EU GMP Annex 16) or the authorised quality unit may certify or release a batch. Agents may not close deviations or change batch status; all records meet 21 CFR Part 11 and Annex 11.
Action: Disposition blocked pending closure of DEV-0931; batch stays in quarantine in ERP and MES, and a readiness summary is routed to the deviation owner and QP.
Data: MES electronic batch recordsLIMS results and specificationsQMS deviations, CAPA and change controlERP inventory and ordersEquipment and environmental monitoring

Use case 2

Adverse event case intake and triage

Case volumes rise while reporting deadlines are fixed. Agents that extract, code and check cases let safety physicians spend their time on causality and benefit-risk rather than data entry.

“Which new safety cases are serious and unexpected, and when is each due to regulators?”Asked by a head of pharmacovigilance

Context: Inbox: report from a hospital physician received 2 October (day 0) about a patient on Corvelan
Event: liver injury requiring hospitalisation; coded to MedDRA as drug-induced liver injury
Reference safety information: event not listed in the company core data sheet
Safety database: 3 similar reports found, none matching this patient and reporter
Rule: If the case has an identifiable patient, reporter, suspect product and event, and is serious and unlisted, set the 15-day expedited clock from day 0 and route to a safety physician; agents never assign causality.
Decision: Expedited case Severity: High
Agents: Intake agent Extracts patient, product, event and reporter details from the email and attachments into structured fields.
Coding agent Proposes MedDRA terms and checks the event against the reference safety information.
Duplicate agent Compares the case with existing reports and explains why it is or is not a duplicate.
Policy: Causality, seriousness confirmation and submission are decided by qualified safety staff under EU GVP Module VI and 21 CFR 314.80. Agents may prepare the case but not submit it.
Action: Case created in the safety database in medical review state and referred to the safety physician; submission due date set to 17 October.
Data: Safety database (ICSRs)Inbound reports (email, call centre, literature)Reference safety informationMedDRA and product dictionariesRegulatory submission tracking

Use case 3

Clinical trial site resupply

A site that runs out of investigational product misses dosing visits, while over-shipping wastes costly, short-dated kits. Resupplying on cover and expiry keeps patients on study with less waste.

“Does Site 114 on study NVX-301 need a resupply shipment now?”Asked by a clinical supply manager

Context: IRT: Site 114 on study NVX-301 has 6 kits on hand and dispenses about 2 kits a week, so cover is about 3 weeks
Depot WMS: 240 kits available with use-by dates beyond the next dispensing window
Depot to site lead time is 7 days by temperature-logged courier
Site temperature log: no excursions recorded in the last 30 days
Rule: If site cover falls below 4 weeks and depot kits have use-by dates beyond the next dispensing window, release a standard resupply of 8 kits; any temperature excursion at the site holds the shipment for review.
Decision: Site resupply Severity: Low
Agents: Forecast agent Projects kit use from enrolment and visit schedules and explains the cover estimate.
Expiry agent Selects depot kits whose use-by dates cover the coming visits, avoiding short-dated stock.
Blinding agent Checks that the shipment uses kit numbers only and reveals nothing about treatment arm.
Policy: Standard resupplies within the rule are released automatically; non-standard quantities, unblinded information or temperature issues need the clinical supply manager. Records follow ICH E6 good clinical practice.
Action: Resupply of 8 kits released automatically in IRT and sent to the depot WMS for picking and temperature-logged shipment.
Data: IRT randomisation and dispensingDepot WMS inventory and expiryStudy visit scheduleTemperature monitoringCourier shipment tracking

03 The foundation

What the agents need to understand

Core entities in the ontology

ProductBatchSpecificationDeviationCAPAStudySiteKitSafety CaseAdverse Event

Systems they come from

MES: electronic batch records, process parameters and equipment use
LIMS: samples, test results, specifications and stability data
QMS: deviations, CAPA, change control and audits
Safety database: individual case safety reports, coding and submissions
IRT and CTMS: randomisation, kit dispensing, sites and study milestones
ERP and depot WMS: inventory, orders, distribution and expiry

04 Guardrails

The controls that let it scale

Humans own GxP decisions

Batch certification, deviation closure and causality are made by qualified, named staff, never by an agent.

Validated before use

Rules and agents that influence regulated decisions are validated under a risk-based computerised system approach before going live.

Part 11 records

Every agent action produces an attributable, time-stamped record consistent with 21 CFR Part 11 and EU Annex 11.

Blinding and privacy kept

Clinical agents see only kit numbers and pseudonymised data, protecting trial blinding and GDPR obligations.

Change control for rules

Thresholds and rule changes go through change control, so inspectors can see which version decided each case.

05 Rollout

From the first use case to many

1
Pick one GxP workflow
Start where records are already structured, such as batch release readiness or case intake, and the expert reviewer is clearly named.
2
Model the business context
Define products, batches, deviations, studies and cases once, linked across MES, LIMS, QMS and the safety database.
3
Validate rules and agents
Write rules with quality and safety owners, test against historical cases and document the validation.
4
Run in review mode
Start with every output reviewed by an expert, then allow automatic release only for low-risk actions such as standard resupply.
5
Extend across the chain
Reuse the same ontology, audit trail and controls for regulatory writing, CAPA trending and commercial content review.

06 What to measure

Outcomes, not activity

Batch release cycle timeRight-first-time batch recordsRepeat deviationsOn-time expedited safety reportsSite stock-outsInvestigational product waste

07 Pitfalls

What usually goes wrong

Skipping validation. Teams treat AI as an experiment and then cannot use its output in a regulated decision; plan validation from the start.
Agents that summarise, not cite. A summary without links to the exact record cannot be inspected; require every statement to point to its source entry.
Starting in discovery only. Early research gets the attention but takes years to show value; operations, quality and safety return sooner and build trust.
Rules hidden in prompts. Thresholds buried in agent instructions escape change control; keep them as versioned rules outside the agents.

08 Diagnostics

Questions to ask your team

1
Which GxP workflow has structured records, a named reviewer and a clear rule set we could start with?
2
How will we validate an agent that influences a regulated decision, and who signs that validation?
3
Can an inspector see, for any case or batch, which rule version decided and who approved it?
4
Where do our agents touch patient or trial data, and how is blinding protected?

09 Keep going

Frequently asked

Can an agent release a batch?

No. Agents check readiness and surface open items; certification and release remain with the Qualified Person or authorised quality unit. Agents cannot change batch status.

How does this fit GxP validation?

Rules and agents that influence regulated decisions are validated like other computerised systems, with documented testing and change control. Every action produces a Part 11 compliant record.

Where should we start?

Pick a workflow with structured data and clear rules, such as safety case intake or batch release readiness. Run it with expert review on every output before allowing any automatic action.