CPHI MILAN 2026 · BIOMANUFACTURING + AI
AI-Native Bioprocess Intelligence. Built for Every Modality. Measured by Outcomes.
Connect bioprocess data in days. Predict and optimize development, scale-up and manufacturing with modality-native AI. BioMedAna combines a unified data layer, a predictive digital twin and agentic scientific workflows — governed by human review at every step.
Hub in daysTwin in approximately 12 weeksEvidence-linkedHuman-governed
ONE PLATFORM6 MODALITIES · 3 CONNECTED LAYERS
mAbs
Rec. proteins
Cell therapies
Gene / viral vectors
Fermentation
RNA / oligo
BioMedAna HubConnect · standardize · contextualize
BioMedAna TwinPredict · simulate · recommend
BioMedAna OSSecure · govern · deploy
Faster decisions
Lower risk
Higher yield
Compounding knowledge
01 — START WITH YOUR OUTCOME
What Decision Does Your Team Need to Make Faster?
Every engagement starts with one bioprocess decision — not a platform migration. Pick the outcome closest to your current priority to see the actual product screen and a realistic next step.
app.BioMedAna.ai/twinBioMedAna TWIN
PROGRAMmAb IgG1 · CHO fed-batchDECISION2,000 L → 10,000 L transferOBJECTIVEQuality Objective BSCREEN01 · Process Simulation
Process Simulation
Day-by-day trajectory prediction with disclosed uncertainty
Scenario InputsCOMMERCIAL-LIKE
Scale10,000 L
Agitation57 RPM
Aeration0.206 vvm
DO setpoint45 %
Temperature37.0 → 34.5 °C
pH7.00 constant
Glucose strategyStandard fed-batch
Harvest dayDay 14
GUIDED SCENARIOSBaseline 2K transferCooler production phaseAggressive feedpH shift day 6
Predicted Trajectory±8.1% uncertainty · model v2.1
Titer (normalized)ViabilityConfidence band
Day 0Day 3Day 6Day 9Day 12Harvest
Titer2.451 g/L±0.19
Viability91.9 %
G0 / G1 / G239 / 34 / 21 %
Lactate1.8 g/L
Ammonia3.1 mM
Quality score87 / 100vs. Objective B
02 — WHY NOW
Bioprocess development is still
constrained by physical experimentation.
Complex biology makes every run valuable, but much of what is learned remains difficult to reuse. Run → analyze → learn → adjust — another physical run is required just to validate the next change, and knowledge stays fragmented across data, models and SME memory.
PROCESSOperating conditions
→BIOLOGYCell response
→QUALITYProduct outcome
03 — WHERE THE TIME GOES
Scientists spend most
of their week not doing science.
Someone exports the bioreactor data, hunts down assay results, re-aligns timestamps and rebuilds context — every single time. BioMedAna moves that work to the platform, permanently, and keeps it current.
Data preparation & huntingScience & decisions
TODAY
62%38%
Exporting, cleaning, aligning timestamps and rebuilding context by handWITH BioMedAna
18%82%
Context connected and maintained by the platform — science gets the hours backIllustrative split, based on how bioprocess teams commonly report their analysis time. Actual results depend on systems, scope and deployment.
04 — INTEGRATED PLATFORM
One Platform. From Process Data to Governed Decisions.
Four layers, one evidence chain: Hub connects and contextualizes, Twin predicts and simulates, Agents investigate and create, and OS governs and scales the whole system across sites and programs.
CONNECT AND CONTEXTUALIZE
BioMedAna Hub
Connect bioreactors, historians, ELN, LIMS, MES, lab systems, files and APIs into a modality-aware scientific record.
Time to initial value: Days
Explore Hub ↗app.BioMedAna.ai/hubBioMedAna HUB
WORKSPACEProcess Studio · 6 modality packsEVIDENCE1,057 runs · 131 source filesGOVERNANCEFull audit trail · saved viewsSCREEN01 · Modality Overview
One Evidence Chain, Six Modalities
Source file → mapping & validation → canonical record → calculation → reviewable conclusion → frozen evidence.
MODALITY PACKS6/6ACTIVE
Runs & batches1,057all packs
Designed exceptions24validation cases
Source files131import-ready
Active imports12preview & commit
Saved views19shared evidence
Audit events4,208fully traceable
Batches12
Exceptions4
Files31
Batches10
Exceptions3
Files18
Batches8
Exceptions5
Files24
Batches9
Exceptions4
Files22
Batches11
Exceptions2
Files17
Batches7
Exceptions6
Files19
05 — MODALITY-NATIVE
Shared Platform. Different Science.
BioMedAna preserves the distinct biology, CPPs, CQAs, kinetics, assays and scale rules of each modality — the same evidence chain, a different scientific record underneath.
EXAMPLE · MICROBIAL AND PRECISION FERMENTATION
Understand substrate kinetics, feed strategy, OUR/OTR, oxygen limitation and productivity across scales.
06 — SPEED AND ROI
Start Small. Deliver Measurable Value Quickly.
- Connect priority data sources and create a scientific record in days (Hub)
- Build and validate a decision-focused Twin in approximately 12 weeks
- Faster access to trusted process context — no rip-and-replace required
- Evidence-linked and human-reviewed predictive insights
Potential value: fewer manual data-preparation hours, fewer unnecessary experiments, faster investigations, reduced scale-up and transfer risk, improved yield and manufacturing performance.
Data preparation & huntingScience & decisions
TODAY
62%38%
Exporting, cleaning, aligning timestamps and rebuilding context by handWITH BioMedAna
18%82%
Context connected and maintained by the platform — science gets the hours backIllustrative split, based on how bioprocess teams commonly report their analysis time. Actual results depend on systems, scope and deployment.
120+
01Scenarios explored in silico
Feed, DO, agitation, temperature and scale combinations simulated against models and prior evidence
12
02Candidate conditions
Ranked by predicted outcome, uncertainty and engineering constraint headroom
3
03Physical runs committed
High-value experiments approved through governed scientist review
Illustrative workflow — the point is the shape: explore widely in silico, commit narrowly in the lab.
07 — FEWER, HIGHER-VALUE EXPERIMENTS
Every run should teach
the next one something.
BioMedAna uses accumulated evidence and predictive models to prioritize which experiments actually change the decision — instead of running the same class of experiment because context was lost.
08 — GOVERNANCE BY DESIGN
Scientific velocity.
Without losing control.
BioMedAna is SOC 2 compliant and built around access control, evidence lineage, model lifecycle and mandatory human review — every recommendation is traceable back to its source.
EVIDENCESource records
Runs, assays, materials — authenticated and versioned
✓Lineage attached
MODELVersioned model
Configuration, training evidence and validation history
✓Release controlled
RECOMMENDATIONProposed action
Prediction, uncertainty and constraints made explicit
✓Uncertainty shown
REVIEWHuman approval
Scientist reviews evidence before anything moves
✓Approval required
AUDIT TRAILEvery step above is recorded — who, what, when, with which evidence and model version.
09 — AUDIENCE
How Can BioMedAna Help Your Organization?
10 — QUESTIONS WE GET AT CPHI
Straight answers before the pilot.
Do we need to replace our historian, ELN, LIMS or MES?
No. BioMedAna Hub connects to the systems you already run — bioreactors, PAT, historians, ELN, LIMS, MES, lab systems, files and APIs — without a rip-and-replace migration.
How fast can we see value?
Hub can produce a governed, searchable scientific record from priority data sources in days. A decision-focused Twin is typically built and validated in approximately 12 weeks.
Does BioMedAna work for our modality?
Yes. The platform is modality-native across monoclonal antibodies, recombinant proteins, microbial and precision fermentation, cell therapies, gene therapies/viral vectors, and RNA/oligonucleotides — each with its own CPPs, CQAs, kinetics and assays.
Who reviews the model's recommendations?
Every recommendation carries its evidence, uncertainty and model version, and requires human review and approval before any action is taken. Nothing writes back to source systems unattended.
Is this only for large biologics manufacturers?
No. Biologics manufacturers, CDMOs running multiple client programs, and technology partners embedding intelligence into equipment and systems all use BioMedAna today.
What does a pilot look like?
We map one bioprocess decision — a yield question, a scale-up risk, a transfer or an investigation — and scope a bounded engagement with clear scientific and governance gates before anything scales.
Bring us one bioprocess decision
We will map the data, evidence, intelligence and execution path to a measurable outcome.
Hub in days. Twin in approximately 12 weeks. No rip-and-replace transformation.
11 — VALUE OPPORTUNITY CALCULATOR
See what BioMedAna could
return for your team.
VALUE OPPORTUNITY CALCULATOR
Model value across the bioprocess lifecycle.
Use your own operating economics or start with an illustrative regional scenario. All financial values are in USD.
Conservative assumptionsEditable inputsNo data transmitted
Presets change only the editable cost assumptions—not BioMedAna's impact percentages.
BIOMEDANA HUB
Operational speed, insight and capacity
Data foundationInsightsPlanning & DOEInvestigation & RCAReports
Lifecycle coverage and conservative impact assumptions
SCENARIO VIEW
Compare the same operating profile across regions.
Illustrative economics only. Replace them with your own values for a decision-quality estimate.
| Scenario | Annual labor cost | Hub annual value | Hours returned | Twin value opportunity |
|---|---|---|---|---|
| India | $36,000 | $52,920 | 2,822 | $490,000 |
| South Korea | $95,000 | $139,650 | 2,822 | $892,500 |
| Singapore | $130,000 | $191,100 | 2,822 | $1,109,500 |
| Japan | $115,000 | $169,050 | 2,822 | $1,001,000 |
| European Union | $110,000 | $161,700 | 2,822 | $980,000 |
| United States | $150,000 | $220,500 | 2,822 | $1,268,750 |
Transparent by design.
The calculator estimates value—not BioMedAna pricing—using the same conservative improvement assumptions and user-provided economics. Results are planning estimates, not guaranteed outcomes. A tailored business case and BioMedAna Twin require a scoped assessment.