Every deviation has a dollar cost. See it before the next batch.
FyndEm Quality predicts batch deviations from the data your PI, PAS-X, LIMS, and MES already collect — and attaches a dollar cost to every one. Across six cost drivers, three tier views, and audit-defensible CAPA narratives. Built for monoclonal antibody, plasma fractionation, vaccine, and biosimilar manufacturing.
By the time a deviation reaches CAPA, the dollar damage is already done — yield loss, make-up batch raw materials, investigation hours, lot-release delay, and schedule cascade. Plant leaders learn the cost from the quarterly review, not the alert.
⚠️ The Problem
Biologics quality systems flag deviations after they occur — and rarely quantify what each one costs. Yield shortfall, raw material write-offs for make-up batches, QA investigator hours, lot-release delays, capacity opportunity cost, and CAPA write-up overhead all accrue silently across cost centers. By the time finance reconciles them at quarter-end, tens of millions of dollars have moved without a single forecast — and the Director of Manufacturing learns the impact in the executive review, not when the decision could still be made.
✓ The FyndEm Approach
FyndEm Quality predicts deviations from process and batch data — and attaches a dollar cost to each one. Six cost drivers. Three tier views (Per Deviation, Per Batch, Per Plant). Audit-defensible CAPA narratives for upload into your existing eQMS. Operators see the cost at the moment of detection. QA and MSAT see it at batch review. The Director of Manufacturing sees the plant-level total long before the quarterly close — when the next batch can still be saved.
Four predictive capabilities that turn batch deviation management from reactive to anticipatory — and from cost-blind to dollar-quantified.
Predictive Deviation Detection
Detect process drift and parameter combinations that precede batch deviations — hours or shifts before traditional release testing or single-parameter SPC charts would catch them. Surfaces the multi-variable interactions that single-batch monitoring misses.
Cost Economics in Every Alert
Every deviation comes with a dollar cost across six drivers — yield shortfall, make-up batch, investigation, lot-release delay, schedule cascade, and CAPA write-up. Three tier views (Per Deviation, Per Batch, Per Plant), calibrated to your facility’s cost rates during configuration.
Audit-Defensible CAPA Narratives
Generate CAPA narratives from deviation context, root cause patterns, and recommended actions — formatted for upload into TrackWise, Veeva QualityDocs, or your existing eQMS. Investigator drafting time reduced. Documentation quality and consistency improved across plants.
Gold-Standard Cluster Analysis
Cluster batch outcomes against a tenant-specific gold standard — identifying which campaigns trend toward gold and which trend toward failure. Surfaces root causes hidden across bioreactors, downstream skids, and shifts that single-batch analysis cannot detect.
Designed For
Directors of Manufacturing, Plant Financial Controllers, MSAT and Process Engineering leads, and Quality (deviation/CAPA) teams in biologics manufacturing — including monoclonal antibody (mAb), plasma fractionation, vaccine, biosimilar, cell & gene therapy, and sterile fill-finish operations. Integrates with OSIsoft PI / AVEVA, PAS-X, Veeva QualityDocs, TrackWise, LIMS, and SAP / MES via standard exports — no new sensors, no system migration.
FyndEm Quality is built around a six-driver cost economics framework — the same drivers your finance team reconciles at quarter-end, surfaced in the moment a deviation is predicted.
The six cost drivers in every alert
Yield Shortfall
Lost product value when batch yields fall below the gold-standard. Per gram of mAb, per kg of albumin, per dose of vaccine.
Make-Up Batch
Raw material write-offs plus labor, utilities, and the opportunity cost of displacing the next planned campaign.
Investigation
QA investigator, manufacturing SME, and MSAT engineer hours. Major-severity investigations routinely exceed six figures.
Lot-Release Delay
Inventory carrying cost while held in QA review. Capital tied up plus downstream supply commitment risk.
Schedule Cascade
When a make-up batch displaces planned production. Counted only when a sales-committed batch is provably delayed.
CAPA Write-Up
The hidden tax. Investigator drafting, SME review, and regulatory documentation — 60+ hours per major deviation.
Three tier views, three audiences
Per Deviation
Every predicted deviation carries a projected dollar impact, surfaced on the operator’s screen at the moment of detection — turning an abstract alert into a decision with a price tag.
Per Batch
Roll-up across all deviations in a batch — total cost, driver breakdown, and attribution to recommended actions. The single view that closes a batch review with a defensible number.
Per Plant
Quarterly view across all batches, all deviations, all cost drivers — the number that goes to finance, the executive review, and the next planning cycle. Visible long before quarter-end.
Figures shown are biologics-industry-typical defaults. Calibrated to your facility’s cost rates during configuration.
Wherever a single deviation can carry six- or seven-figure cost — through lost yield, make-up batches, lot-release delays, or schedule cascade.
🧬 Monoclonal Antibody (mAb)
CHO bioreactor process drift, viable cell density and titer trajectory deviations, glycosylation pattern shifts — predicted hours before downstream release testing flags them.
🩸 Plasma Fractionation
Cohn-fraction yield, chromatography selectivity, and viral inactivation deviations — surfaced across pooling, Fr.II+III, and IVIG / albumin downstream processing.
🦠 Vaccine Manufacturing
Cell-culture and viral-propagation parameter drift — predicted from bioreactor and downstream process data, before potency assay flags it.
🔬 Biosimilars
Comparability deviation prediction against innovator-equivalent gold standards — across bioreactor, formulation, and fill-finish steps where comparability margins are tight.
💊 Sterile Fill-Finish
Aseptic process, container-closure, and vial integrity deviation prediction — with batch-level cost attribution that reflects the full downstream value at risk.
🧫 Cell & Gene Therapy
Lot-of-one production economics where every deviation carries the full batch cost. Predicted before release testing, with patient-specific schedule risk surfaced explicitly.
No new sensors. No PI replacement. No PAS-X migration. FyndEm Quality works from the data your existing systems already export — and adds a cost rate configuration layer on top.
Process Parameters
OSIsoft PI / AVEVA — bioreactor (DO, pH, VCD, temperature), chromatography skid pressures, fermentation conditions
Batch Records
PAS-X / MES electronic batch records, deviation logs, in-process control results, hold times
QC / QA Data
LIMS / TrackWise — HPLC, ELISA, potency assays, CoA, lot release testing, deviation and CAPA history
Cost Rate Configuration
Plant-level cost rates — yield value, make-up batch costs, investigation hours, capacity opportunity cost — set during configuration
Powered by CentroidAI’s behavioral intelligence engine
The same patent-pending AI architecture that predicts patient risk, donor churn, and surgeon adoption — applied to biologics manufacturing, with the dollar cost of every deviation attached.
See it applied to your batch data
Every engagement begins with a retrospective diagnostic — a run on your own historical batch and deviation data, with the dollar cost attached. See what FyndEm Quality would have predicted, and what it would have cost. No commitment required.