Grounded in real manufacturing expertise.
BioProcessIQ is built on deep operational knowledge — not just algorithms. The following figures reflect our team's combined track record and early pilot outcomes.
Bioprocess manufacturing experience
Spanning academia, industry, laboratory, and GMP-scale production environments.
Successful manufacturing runs
Accumulated across a broad portfolio of biologic modalities and process scales.
Platform breadth
Plasmid DNA, Viral Vectors, Monoclonal Antibodies, Recombinant Proteins, and Enzymes.
Scale-up acceleration (pilot)
Reported by two biotech partners in early pilots. Results may vary by process and context.
Claims based on internal pilot data and team experience. Results may vary depending on process complexity, scale, and customer context.
The bottlenecks holding back biologics operations.
Process Delays
Late-stage bottlenecks in tech transfer, media prep, and equipment qualification slow time-to-clinic.
Low or Variable Yields
Inconsistent titers and unpredictable product quality create costly repeat batches and deviation investigations.
Supply Shortages
Raw material shortfalls and single-source critical reagents create cascading schedule risk.
Process Failures
Contamination events, equipment failures, and out-of-spec batches erode capacity and confidence.
AI built for every stage of bioprocessing.
BioProcessIQ connects batch records, equipment data, and scheduling systems into a unified intelligence layer — surfacing the right insight at the right moment.
Batch Analytics
Automated ingestion and analysis of batch records to surface trends, deviations, and root-cause signals.
Scale-Up Simulation
Model process parameter relationships from lab to pilot to GMP scale before committing to physical runs.
Scheduling Optimization
Intelligent campaign planning that accounts for equipment, personnel, materials, and regulatory hold times.
Defect Detection
Real-time monitoring of in-process controls with anomaly flagging before batches reach critical stages.
Inventory Forecasting
Predictive material requirement planning linked to production schedules and supplier lead times.
Workflow Automation
Elimination of manual data entry and disconnected spreadsheets across batch record, QC, and LIMS workflows.
AI that amplifies expertise — not replaces it.
BioProcessIQ combines machine learning models with validated bioprocess knowledge. Our system continuously learns from your batch data while ensuring that qualified personnel remain in control of every process decision.
No alert gets acted on without human review. No recommendation is generated without traceable evidence. The result is an AI co-pilot your team can trust — and your auditors can inspect.
Human-in-the-Loop
Every AI recommendation surfaces to a domain expert for review before it influences a process decision. No autonomous action on critical steps.
Evidence-Backed
Outputs are grounded in your own batch data, reference literature, and regulatory guidance — not black-box inference.
Auditable
Full data lineage and decision trails for every insight. Designed with 21 CFR Part 11 and GMP documentation requirements in mind.
Domain Expertise First
ML models are trained and validated by bioprocess engineers, not generic data scientists. The AI knows what a titer curve should look like.
Discover AI-Smart Biomanufacturing.
See how BioProcessIQ can help your team reduce batch failures, accelerate scale-up, and build the data infrastructure your biologics operations need.