Quality Analytics
Trending that does not wait for the annual review
Litewave turns the records you already execute into structured quality data, so yield, deviations, OOS rates, supplier performance and cycle times are live all year instead of reconstructed once at review time. The same structured record is what continued process verification runs on.
Most quality data is not missing, it is unreadable
It exists. In a binder, in a scanned PDF, in a free-text deviation description, in a LIMS export nobody joins back to the batch record.
So the annual product quality review becomes archaeology: weeks of manual extraction to produce a document describing a year you can no longer do anything about. Meanwhile the signals that mattered were visible in month three. A yield trending down inside the acceptable range. One supplier assay creeping toward the limit. A deviation category quietly doubling on one line.
Our API customer put it exactly: yield varied within acceptable ranges, but the lack of integrated data made it impossible to identify the underlying drivers. That is the real cost of unstructured records. Not non-compliance. Blindness.
How it works
- Executed batch and production records
- In-process and analytical results
- Deviations, OOS and OOT records, CAPA and change control
- Complaints, returns and stability data
- Environmental monitoring and supplier CoAs
- Equipment and downtime logs, LIMS, MES and ERP exports
- Normalizes everything into one quality data model keyed to batch, product, site, line, equipment, lot and time
- Keeps every field traceable to the page it came from
- Runs statistical trending against your alert and action limits
- Evaluates variability and capability within a batch and between batches, which is what continued process verification is assessed on
- Detects drift and rising frequency before a limit is breached
- Live dashboards by product, site and line
- Drafted APQR, PQR and management review packs, every figure linked to its record
- The periodic continued process verification report drafted from the same data, against the criteria in your approved protocol
- Alerts on drift and emerging trends
- A clean export your statisticians can actually use
The questions it answers
Not "here is a dashboard", but the specific questions a quality director is already asking.
Batch and process trends
- Yield, cycle time, right-first-time, rejection and rework rate by product, line, shift and campaign
- Control charts, capability indices and rule-based signal detection against your limits
- Whether the process is still in the state of control it was validated in, batch over batch, and where it is moving if not
- Assay, impurities, dissolution, moisture and microbiological results drifting toward specification
- Which variables track most closely with yield, ranked and testable, rather than an undifferentiated wall of correlations
Deviation trends
- Frequency and category by equipment, process step, product and shift
- Recurrence detection across events that were investigated separately
- Investigation aging and closure performance against your target
- CAPA effectiveness outcomes, including the ones that did not hold
Supplier trends
- Acceptance rate and out-of-specification frequency by supplier and material
- Result drift across lots from the same supplier
- Late or missing documentation, and repeated method changes
- Supplier scorecards built from the CoA review rather than maintained by hand
Laboratory and environment
- OOS and OOT trending including invalidation rates by laboratory, analyst, method and instrument
- Environmental monitoring excursion frequency by room, grade and sample location
- Utility monitoring against the manufacturing window
- Cross-site benchmarking where the same product runs in more than one place
Continued process verification, as a byproduct rather than a project
Validation does not end when the qualification batches are released. Both regimes then ask for a standing program, and it runs on exactly the data this page already structures.
The FDA process validation guidance calls its third stage continued process verification: an ongoing program to collect and analyse product and process data, statistically trended and reviewed by trained personnel, to give continual assurance the process is still in its validated state. Annex 15 calls the same lifecycle activity ongoing process verification, and asks that product quality be monitored so a state of control is maintained with the relevant process trends evaluated.
The hard part is almost never the statistics. It is that the inputs are scattered. The FDA guidance points at yield variations, out-of-specification findings, deviation reports, complaints, batch records and incoming material records as the places variation surfaces, and asks for intra-batch as well as inter-batch variation to be scrutinised. Annex 15 expects statistical tools applied to the variability and capability of the process, under an approved protocol, with a report on the outcome. Most sites hold every one of those inputs, unjoined, across a binder, a LIMS and an eQMS.
Litewave structures those records as they are executed, so verification stops being an annual gathering exercise and becomes continuous. Annex 15 asks that ongoing verification support the validated status documented in the Product Quality Review, which is the same review this page already drafts from source, with every figure traceable back to the page it came from.
What the regulations actually ask for
Requirement
21 CFR 211.180(e)
What it obliges
An annual evaluation of records for each drug product, to determine the need for changes to specifications or procedures.
Requirement
FDA process validation guidance, Stage 3
What it obliges
Continued process verification: an ongoing program to collect and analyse product and process data, statistically trended and reviewed by trained personnel, so the process stays in its validated state.
Requirement
EU GMP Part I
What it obliges
A regular periodic Product Quality Review across batches, materials, deviations, changes and stability.
Requirement
EU GMP Annex 15, 5.28 to 5.32
What it obliges
Ongoing process verification across the lifecycle: product quality monitored so a state of control is maintained, process trends evaluated, statistical tools used where appropriate, supporting the validated status recorded in the Product Quality Review.
Requirement
ICH Q7, section 2.5
What it obliges
For API sites: regular quality reviews verifying process consistency, normally annual, covering critical in-process and test results, failed batches, critical deviations and their investigations, process and method changes, stability, returns, complaints and recalls, and whether corrective actions were adequate.
Requirement
ICH Q10
What it obliges
Monitoring of process performance and product quality as a standing element of the pharmaceutical quality system.
Requirement
21 CFR Part 117
What it obliges
Verification activities and reanalysis of the food safety plan at least every three years, or upon significant change.
Where the evidence comes from
The API deployment reports improved batch yield efficiency through performance driver identification. We have deliberately not attached a percentage to that: no yield improvement figure has been verified and published, and inventing one would be the easiest claim on this site to disprove.
Questions we get asked
Do we need to be fully digital first?
No. The structured data comes from the records you already execute, paper included. That is the point: analytics becomes a byproduct of the review rather than a separate program with its own budget.
Is this a Design of Experiments or digital twin tool?
No, and we are not trying to be one. Litewave reads the batches you have already executed, which makes it observational: it can show you that a parameter moves with yield, not that changing it causes the change. Establishing that is what a designed experiment is for, and simulating it is what a mechanistic twin is for. Both live in process development. Litewave works on the commercial record, so what it gives you is a trended, structured view of what your process has actually done, which is useful input if you later run a study and is the continued process verification layer either way.
Does this give us our continued process verification program?
It gives you the data layer underneath one. CPV under the FDA guidance and ongoing process verification under Annex 15 both run to an approved protocol with defined acceptance criteria, and the FDA guidance recommends a statistician, or someone trained in statistical process control, designs the sampling plan and the statistical methods. That stays with your quality unit. What Litewave removes is the part that actually delays these programs, which is assembling and joining the data. Trending then runs continuously against your own alert and action limits, every figure traceable to the executed record, and exports cleanly into whatever tooling your protocol specifies.
Does this replace our BI tool?
No. Litewave produces the structured, traceable quality dataset most sites do not have. You can consume it in Litewave dashboards or export it into the BI and statistics tooling you already run.
How do we defend a number that came out of an AI system?
Every figure links to the executed record and page it came from. An inspector can drill from a trend line to a scanned batch page in the same session.
Can it trend across sites running different systems?
Yes, and that is the normal case. Litewave normalizes to a common model, so a product made at two sites on two different platforms can be compared without harmonizing the platforms.
Related
Built for validated environments
Your data stays where your auditors expect it
Deploy in your environment
Your cloud, your data center, on the plant floor, or fully air-gapped. The same agents run identically in all four, because the models are open-source and served inside your perimeter, so inference never leaves it.
Your data never trains our models
Documents are never sent to third-party AI providers, and they never train a model that any other customer touches. Where a model does adapt to your site, the handwriting engine learning your operators, that loop is closed inside your deployment and what it learns stays yours.
21 CFR Part 11
Electronic records, electronic signatures and complete audit trails on every action, built to ALCOA+ data integrity principles.
EU GMP Annex 11, and building for what is next
Meets the currently effective Annex 11 expectations for computerised systems. We are building to the draft revised Annex 11 and the draft Annex 22 on AI while both remain in consultation, so nothing here is claimed as compliance with a standard that is not yet in force.
Validated like the computerised system it is
The validation documentation your quality unit needs to qualify Litewave under its own CSV or CSA procedure, risk-based and scoped with you during procurement, alongside Part 11 and Annex 11 assessments covering audit trail, electronic signature and access control.
AI governance you can inspect
Context of use, model versions, performance monitoring and change control are documented in line with the EMA and FDA guiding principles of good AI practice in drug development, so the model sits inside your quality system rather than beside it.
Advised from both sides of the inspection
A former FDA division director who edited the Investigations Operations Manual, the field guide its investigators follow on site. A former FDA investigator who then decided enforcement outcomes at CDER. A Qualified Person who certifies batch release under EU GMP. They advise in a personal capacity, and FDA does not endorse products or companies.
Evidence on every flag
Every extraction, check and recommendation links back to its source page. Nothing asserted is unverifiable.
Human in the loop by design
Agents propose, qualified people approve. Litewave never dispositions a batch on its own.
See it run on one of your own records
Bring something real. We will show you what Litewave finds in it and what it cites as evidence.