Agentic AI for Drug Development & Healthcare

Pharma & Life Sciences

AI that respects trial rigor and GxP constraints while actually reducing timelines and risk.

Pharma and life sciences teams sit at the intersection of science, regulation, and operations. You need AI that doesn't just analyze data — it designs molecules, accelerates trials, and generates regulatory evidence automatically. All while meeting GxP and validation requirements.

We build agentic AI layers around your existing data, platforms, and quality systems. Working agents for clinical development, pathology and QC, safety, and regulatory documentation — running on your infrastructure, with your data, yours to own.

Your infrastructure. Your data. Yours to own.

Why Agentic

Traditional Pharma AI
Agentic Life Sciences

Screen existing compound libraries

Generate novel molecules

Static trial protocols

Adaptive designs that adjust in real-time

Manual pathology review

Vision agents at million-image scale

Months of submission prep

Auto-generated regulatory evidence

Analysts query databases

Agents query and synthesize literature

Siloed data systems

Unified agents across discovery, clinical, and regulatory

Dashboards and reports

Agents that act and recommend

What We Build

Agentic AI systems for pharma and life sciences

Pathology at Scale

Vision agents analyzing histopathology, radiology, and microscopy — processing millions of images with consistent precision

Generative Chemistry

AI that designs novel molecular structures optimized for target binding, selectivity, and ADMET properties — not just screens existing libraries

Clinical Trial Design Agents

Scenario exploration, protocol optimization, and cohort selection against historical and synthetic data — highlighting trade-offs before a trial locks

Recruitment & Screening Agents

Combine EHR, registry, and prior trial data to identify eligible participants faster, reduce screen failures, and support adaptive designs

QC & Manufacturing Intelligence

Monitor critical quality attributes, combine sensor data with lab results, flag risk lots or drifts, and surface similar historical deviations

Regulatory Submission Agents

Pull data and narratives from source systems, structure into regional templates, and cross-check against protocol, SAP, and internal standards

Scientific Literature Agents

LLMs that query, synthesize, and monitor the scientific literature — surfacing relevant findings as they publish

Medical Affairs & HEOR Agents

Create traceable summaries, slide outlines, and evidence packs from trial outputs, publications, and RWE — always linked to source data

Regulatory Intelligence

Life sciences AI requires auditability, validation, and governance from day one.

GxP Compliance Built-In

GxP-ready

Built with validation, audit trails, and change control in mind

21 CFR Part 11 / Annex 11

Electronic records and signatures compliance

Explainability

Every model decision traceable and justifiable for regulators

Model lifecycle

Versioning, drift detection, and revalidation workflows

Data lineage

Full traceability from source to insight

Separation of modes — Clear distinction between experimental and validated deployments
Human-in-the-loop — Scientists and regulators remain in control
Innovation that passes QA and audit without turning every release into a negotiation
LIVE DEMO

Agentic AI in Action

Real AI agents working together autonomously to deliver results in your industry. Select a scenario and watch them work.

This is the exact agent architecture we deploy for clients today.

Pharma
Life Sciences — Regulatory Evidence Orchestration by paterhn
GxP validation, batch release, submission-ready documentation
Each node is an agent. Each arrow is a call. This is how production AI actually runs.
SCENARIO
Pick an industry, choose a scenario, hit Run.
INPUT PAYLOAD
protocol idNCT-2024-7829
phasePhase II
indicationOncology
request typeEvidence Compilation
STATUS
Idle
Pending
Running
Complete
ORCH
Orchestrator
ING
Ingest
PRT
Protocol
CLN
Clinical
SAF
Safety
EFF
Efficacy
REG
Regulatory
CMP
Compliance
EVD
Evidence
SUB
Submission
Orchestrator
Decision
Data
Analysis
Human

Synthetic data for privacy. Architecture identical to live client deployments.

From the Field

30%

R&D cycle time reduction

European biotech, applying AI to compound screening workflows.

Agentic screening and prioritization reduced time-to-candidate while improving hit rates.

Confidential Work

Most of our work is deep IP creation. Our clients protect what they're building. So do we.

But we can walk you through how we built it and what it achieved.

Talk to an Engineer

Technical Foundations

How we build agentic AI for pharma & life sciences — Deployed on your infrastructure: cloud, on-prem, or hybrid. GxP-validated environments supported.

$ --technical-foundations
01. Multi-modal learning
Imaging, genomics, EHR, molecular
02. Multi-agent orchestration
Trial, research, regulatory agents
03. Explainability
Traceable for regulatory review
04. Graph neural networks
Molecular property, knowledge graphs
05. MLOps / regulated deployment
GxP-compliant model lifecycle
06. Ecosystem integration
LIMS, ELN, EHR connectors
07. Generative models
Molecular generation, protein structure
08. Workflow management
Automated trial & research pipelines
09. Conversational AI
Natural language for researchers
Deployed on your infrastructure — cloud, on-prem, or hybrid. GxP-validated environments supported. Swiss/EU data residency available.
8–12 weeks

From kickoff to production system. Not a demo—a working system on your infrastructure.

20+ years shipping ML100% IP ownershipNo vendor lock-inYour infrastructure