01The problem
Every run creates evidence.Most of it is lost.
Batch records, sensor data, assays and decisions scatter across a dozen systems. Each new campaign starts again from a spreadsheet.
THE AI-NATIVE BIOPROCESS PLATFORM
Turn process data into better bioprocess decisions.
Connected data. Scientific models. Human-governed AI.
For process development, MSAT and manufacturing teams: compare batches, investigate variability and test scale-up scenarios with connected evidence, scientific models and AI. Your scientists review the findings and decide what happens next.
SOC 2 compliantHuman-governedReal-time ready
02ConnectBioMedAna Hub
Give every runa scientific memory.
Hub connects process, lab and manufacturing data into one record, with its context and provenance attached.
Explore BioMedAna Hub03PredictBioMedAna Twin
See the next runbefore you make it.
Twin combines physics, biology and your process history to predict yield, quality and scale-up behavior, with uncertainty you can review.
Explore BioMedAna Twin04ActAssist & Agents
A team of specialists,on demand.
Ask a scientific question. Specialist agents analyze, model and draft the work in parallel, with every source cited.
Explore Assist & Agents05GovernBioMedAna OS
Move fast.Stay in control.
OS keeps access, lineage, model versions and human approval on every step, across sites and partners.
Explore BioMedAna OS06Decide
One connected platform.Better bioprocess decisions.
Evidence, models, agents and governance working as one, so your scientists decide with confidence.
THE PLATFORM IN ACTION
Follow the evidence.
Scroll into the work.
Five connected moments. Scroll through the platform—from source evidence to model scenarios and agent-prepared work. Each card brings the next step into view.
Skip product journey ↓THE INTELLIGENCE JOURNEY01 / 05 ↓ SCROLL TO EXPLORE
01 / CONNECT · BIOMEDANA HUB
↗Give every run a scientific memory.
Fragmented records become connected evidence. Source context stays attached.
BioMedAna HUB● LIVE · ILLUSTRATIVE WORKSPACE
HUB / CONNECTEXAMPLE DATA
Bioreactor DCS1,240
LIMS386
ELN94
Historian5,120
BioMedAna Hub
Example runs0
Feed conditions0
Source lineage0%linking…
RUN / PROCESSCONDITIONFINAL TITEREVIDENCE
LINEAGE · R001
- ✓DCS export · run_R001.csv
- ✓Feed log · v3
- ✓HPLC titer · A-221
- → Context: control · 2 L · 14 d
Illustrative data · expert review requiredHUB / 01
02 / INVESTIGATE · BIOMEDANA HUB
↗Follow the signal. Find the context.
Align batch trajectories, feed events and assay results before drawing a conclusion.
BioMedAna HUB● LIVE · ILLUSTRATIVE WORKSPACE
HUB / INVESTIGATEEXAMPLE DATA
Example runs0
Feed conditions0
Delayed-feed difference−0.0%vs control
TITER TRAJECTORIES Hover to inspect · click a condition to toggle
│ feed start
FINAL TITER g/L
KEY OBSERVATIONTrajectories diverge after the delayed feed start (day 6).Next: check glucose and lactate profiles for R009.
Association in illustrative data; not a root-cause conclusion.
Illustrative data · expert review requiredHUB / 02
03 / SIMULATE · BIOMEDANA TWIN
↗Explore the process before the next run.
Compare model scenarios, assumptions and uncertainty before committing material.
BioMedAna TWIN● LIVE · ILLUSTRATIVE WORKSPACE
TWIN / SIMULATEEXAMPLE DATA
Predicted final titer5.59 g/L
Uncertainty± 0.22
Evidence rangeWithinsupported by prior runs
PROCESS RESPONSE Live scenario vs saved scenarios A–C
SCENARIO INPUTS auto-exploring · drag to take over
● Inside the evidence range
- Growth: logistic kinetics fitted to 12 runs
- Feed: daily bolus, constant composition
- Scale: 2 L fed-batch, no scale correction
Illustrative data · expert review requiredTWIN / 03
04 / COORDINATE · BIOMEDANA ASSIST & AGENTS
↗One question. The right expertise.
Assist coordinates specialists across evidence, models and scientific workflows.
BioMedAna ASSIST & AGENTS● LIVE · ILLUSTRATIVE WORKSPACE
ASSIST & AGENTS / COORDINATEEXAMPLE DATA
SCIENTIFIC REQUEST
“”
01Data readinessCheck context
Queued
02Hybrid modelingCompare scenarios
Queued
03Study designPrepare a DoE
Queued
04Scientific reviewFlag evidence gaps
Queued
- ACTIVITY
- Waiting for the request…
OUTPUTS FOR REVIEW
▤ Model configuration ↗▤ Scenario comparison ↗▤ Study proposal ↗Illustrative data · expert review requiredASSIST & AGENTS / 04
05 / DECIDE · BIOMEDANA ASSIST & AGENTS
↗Turn the work into a reviewable next step.
A study proposal, its assumptions and its evidence—ready for your experts.
BioMedAna ASSIST & AGENTS● LIVE · ILLUSTRATIVE WORKSPACE
ASSIST & AGENTS / DECIDEEXAMPLE DATA
Study factors0
Conditions in study0
Review statusDraft
CANDIDATE STUDY Predicted titer · click to include or exclude
FEED START (DAY)FEED RATE (g/L/day) →
Day 3, 3 g/L/day: predicted 5.3 ± 0.30 g/L (illustrative)
REVIEW GATEReady for a scientist.
Ready for a scientist.
Not the bioreactor.
Confirm safe ranges, controls, randomization and statistical power.
Illustrative data · expert review requiredASSIST & AGENTS / 05
SOFT SENSORS
Predict between measurements.
See process changes sooner.
Estimate titer, cell growth, metabolites and selected quality indicators using biology, physics and process data. Explore an interactive prediction example and upstream, downstream and quality applications.
See BioMedAna Soft Sensors in action ↗MODALITY-NATIVE SCIENCE
Shared platform.
Different science.
Process topology, scientific vocabulary, CPPs, CQAs, assays, kinetics and scale rules change by modality. BioMedAna is designed to preserve that difference.
Skip modality journey ↓8 MODALITIES. ONE CONNECTED PLATFORM.01 / 08 ↓ SCROLL TO EXPLORE Explore this modality Explore this modality Explore this modality Explore this modality Explore this modality Explore this modality Explore this modality Explore this modality
01CHO · mAb
Monoclonal antibodies
Growth, metabolism, feeding, mass transfer, titer and CQAs.
PROCESS OUTCOMES TO EVALUATETiter · recovery · product quality
Evidence
Cell growth and viability
Model
Culture kinetics and hybrid prediction
Decision
Compare media and feed strategies
02CHO · Microbial
Recombinant proteins
Expression, purification, potency and product-quality attributes.
PROCESS OUTCOMES TO EVALUATEExpression · soluble yield · potency
Evidence
Host, expression conditions and induction
Model
Expression and productivity relationships
Decision
Compare expression conditions
03CAR-T · TIL · NK
Cell therapies
Starting-material variability, expansion, phenotype and potency.
PROCESS OUTCOMES TO EVALUATECell yield · viability · phenotype
Evidence
Donor and material provenance
Model
Expansion and variability analysis
Decision
Investigate donor and batch variability
04AAV · Lentiviral
Gene therapies and viral vectors
Transfection, vector yield, capsid quality and robustness.
PROCESS OUTCOMES TO EVALUATEVector yield · purity · potency
Evidence
Cell line, seed train and reagent context
Model
Production and process sensitivity
Decision
Compare transfection and harvest conditions
05Bacterial · Yeast
Microbial and precision fermentation
Substrate kinetics, OUR/OTR, feed, heat and productivity.
PROCESS OUTCOMES TO EVALUATEBiomass · titer · productivity
Evidence
Strain, substrate and inoculum history
Model
Growth and substrate-consumption kinetics
Decision
Compare feeding strategies
06ASO · siRNA
RNA and oligonucleotides
Synthesis, purification, impurities, yield and quality.
PROCESS OUTCOMES TO EVALUATEYield · purity · impurity profile
Evidence
Synthesis cycles, reagents and material lots
Model
Reaction efficiency and loss analysis
Decision
Investigate step-dependent yield losses
07Small molecule · Reaction kinetics
Chemical & pharmaceutical APIs
Reaction networks, dosing, conversion, selectivity, impurities and crystallization.
PROCESS OUTCOMES TO EVALUATEConversion · selectivity · yield · impurities
Evidence
API product and route version
Model
Stoichiometric and Arrhenius reaction kinetics
Decision
Compare temperature and dosing strategies
08VAX · Cell culture
Viral vaccines
Cell-bank and seed-virus lineage, infection kinetics, harvest timing, recovery and inactivation evidence.
PROCESS OUTCOMES TO EVALUATEInfectious titre · cell-specific yield · recovery
Evidence
Cell-bank, seed-virus lot and passage genealogy
Model
Data-driven titre trajectories with held-out run evaluation
Decision
Compare infection conditions and harvest windows
HYBRID INTELLIGENCE
Physics constrains.
Data grounds.
AI learns.
ACROSS THE LIFECYCLE
From early development
to commercial manufacturing.
Specialist agents, scientific models and human expertise across biological development, process optimization, scale-up, manufacturing, Quality and CMC.
Biological development
Advance promising candidates
Clone and strain comparison, expression and productivity analysis, biological pathway investigation and evidence-backed candidate selection.
WORK YOU CAN REVIEWCandidate evidence
Process development
Focus experimentation
DoE analysis, media and feed strategies, upstream and downstream optimization, chromatography analysis and next-experiment recommendations.
WORK YOU CAN REVIEWExperiment planning
Characterization + scale-up
Explore before committing
Hybrid-model simulations, sensitivity analysis, operating windows, scale-dependent behavior and process-risk assessment.
WORK YOU CAN REVIEWScenario analysis
Transfer + manufacturing
Strengthen process performance
Comparability, site readiness, PAT and Raman signal analysis, batch investigations, equipment-event correlation and continued process verification.
WORK YOU CAN REVIEWBatch investigation
Quality + CMC
Build review-ready evidence
OOS/OOT support, assay trends, deviations, CAPA follow-up, change-impact analysis, evidence mapping and submission-document consistency.
WORK YOU CAN REVIEWEvidence review
Across the lifecycle
Coordinate specialist work
Deep analysis, investigations, simulation workflows and recommendations, shaped by modality-specific biology, analytical methods and quality attributes.
WORK YOU CAN REVIEWConnected execution
Connected evidence. Scientific models. Coordinated agents. Human oversight.
SCIENTIFIC EVIDENCE
Built on science.
Open to scrutiny.
Published research explores hybrid modeling, process prediction and digital twins. Read the studies, their scope and their limitations behind these approaches.
Research combines process knowledge and data-driven models to predict CHO culture performance.
A microalgal study explores hybrid modeling and transfer learning when new experimental data are limited.
These are independent studies of the underlying methods, not validation of BioMedAna performance.
Explore the scientific evidence ↗INTEGRATIONS
Meet the process
where it already lives.
BioMedAna connects across equipment, laboratory, manufacturing and enterprise environments using the protocols and interfaces already in place — a governed intelligence layer above the existing technology estate, not a rip-and-replace program.
INTEGRATION PROTOCOLS
OPC-UAOPC-DASQLAPIsSCADAFile-basedSFTP
SYSTEM CATEGORIES
BioreactorsDownstreamELNLIMSMESHistoriansPLM
REPRESENTATIVE ECOSYSTEM
CytivaApplikonSartoriusRepligenBenchlingLabWareRevvityTulipKörberINFORS HT
Vendor names are shown as representative examples of the bioprocess technology landscape. Specific connectivity depends on the available interface, protocol, data access and customer environment.
TRUST
Scientific velocity.
Without losing control.
BioMedAna is SOC 2 compliant and designed around access control, provenance, model lifecycle, auditability and human approval.
Explore trust & compliance ↗01Evidence lineage
Trace conclusions back to source records.
02Human governance
Review and approval before consequential action.
03Enterprise controls
RBAC, audit trails and controlled environments.
Start with one decision
Book a tailored demonstration.
Bring us the process question you cannot answer fast enough. We will map the evidence, modality context and intelligence path required to support it.
Or write to hello@biomedana.ai