Home All Models
Models
AURA · Education VYDE · Finance SAGE · Healthcare NOVA · Pharma ZYNC · Retail ROAM · Logistics MUSE · Media TIDE · Tourism Platform About Contact Request Demo →
VelorQ/ Models/ NOVA
🧬 Pharma

NOVA

Novel Observation & Validation Assistant

Pharmaceutical AI for drug discovery, pharmacovigilance, clinical trials, and regulatory submissions. Signal detection. Trial outcome prediction. FDA, EMA & 15+ jurisdictions.

🧬
LIVE · Pharma · Regulatory Intelligence
Signal
Pharmacovigilance Pipeline
Safety
Adverse Event Scoring
15+
Regulatory Jurisdictions
RWE
Real-World Evidence Translation
24/7
Vigilance Monitoring
KCL
SAGE Safety Link
Pharma · Overview

Pharma intelligence at the standard the industry demands.

NOVA detects pharmacovigilance signals before they become events. Predicts clinical trial outcomes. Models competitive pipeline intelligence. Supports FDA, EMA, CDSCO and 12+ other regulatory submissions.

01

Signal Strength Modelling

Composite signal score from case volume, disproportionality, clinical plausibility, temporal association.

02

Trial Outcome Prediction

Estimates endpoint achievement probability from interim data. Enables adaptive design decisions.

03

Regulatory Submission Support

FDA, EMA, CDSCO, PMDA & 11+ jurisdictions. Automated document generation and compliance checks.

Knowledge Communication Layer

What NOVA shares via KCL.

Non-classified signals flow from NOVA to sibling models — enabling cross-domain intelligence that no single-domain AI can produce.

KCL Exchange Contents

Non-classified pharmacovigilance signals · drug interaction data · trial outcome patterns · regulatory timelines

Regulatory Intelligence · NOVA Deep Analytics

NOVA detects signals early.
Prepares submissions fast.

Pharmacovigilance signal detection at scale. Clinical trial outcome prediction from interim data. Regulatory submission support across 15+ jurisdictions.

01 · SAFETY SIGNAL DETECTION

72 hours from case → regulatory submission

Composite signal score from case volume, disproportionality, clinical plausibility, temporal association — all automated.

SIGNAL STRENGTH — 12 WEEKS
THRESHOLDALERT: 70%
Signal detection engine surfaces emerging safety patterns across pharmacovigilance data streams.
02 · TRIAL OUTCOME PREDICTION

Predict endpoint achievement from interim data

NOVA models project endpoint probability from interim analyses — enabling adaptive trial design decisions.

ENDPOINT PROBABILITY BY PHASE
Phase I
Modelled
Phase II
Scored
Phase IIb
Tracked
Phase III
Flagged
Phase IV
Reported
RWE
Active
Adverse event scoring translates Phase II signals to Phase III endpoint predictions.
03 · REGULATORY COVERAGE

15+ jurisdictions supported

FDA, EMA, PMDA, CDSCO, MHRA, Health Canada, TGA, ANVISA — automated document generation tailored per regulator.

REGULATORY COVERAGE
FDA
Modelled
EMA
Scored
PMDA
Tracked
CDSCO
Flagged
MHRA
Reported
Others
Active
15+ jurisdictions supported · automated PSUR, PADER, DSUR generation workflows.
04 · KCL SAFETY FLOW

NOVA → SAGE safety signal link

NOVA's drug safety signals flow to SAGE in real time — clinicians see the latest pharmacovigilance intelligence within their care pathway tools.

KCL SIGNAL FLOW
→ SAGE
Modelled
→ AURA
Scored
→ VYDE
Tracked
→ ZYNC
Flagged
← SAGE
Reported
← HUB
Active
Real-time drug safety signals route to clinical point of care via KCL SAGE link.
Signal
Pharmacovigilance
Safety
AE Scoring
RWE
Evidence Translation
24/7
Vigilance
Use Cases

Where NOVA supports pharma.

01

Pharmacovigilance Teams

24/7 signal detection · automated PSUR / DSUR · regulatory submission prep.

PV
02

Clinical Development

Interim analysis · endpoint prediction · adaptive design recommendations.

R&D
03

Regulatory Affairs

Multi-jurisdiction submissions · compliance monitoring · change impact.

RegAff
04

Medical Affairs

Publication support · KOL intelligence · competitive landscape tracking.

MedAff
Deploy NOVA

Ready to see NOVA in production?

Request a demo tailored to your specific deployment — we'll walk you through the model, KCL integration, and onboarding timeline.