Background for AI Pharma
    AI for Pharma

    AI Agents That Accelerate Drug Discovery

    Alice Labs builds production-ready AI agents for pharmaceutical companies: clinical trial optimization that reduces enrollment time by 30-50%, molecular modeling that screens thousands of candidates in hours instead of months, and lab automation agents that streamline GxP-compliant workflows. Deployed within your security perimeter, compliant with HIPAA, GDPR, and FDA 21 CFR Part 11.

    HIPAA & GxP Compliant
    Private Infrastructure
    30-90 Day Delivery
    Senior-Only Team

    Part of the team that delivers

    An experienced team with broad AI and tech backgrounds from leading companies

    Linus Ingemarsson, Co-founder & AI Consultant

    Linus

    Co-founder & AI Consultant

    Alice, CEO & Co-founder

    Alice

    CEO & Co-founder

    Jens, AI Consultant

    Jens

    AI Consultant

    Eric, Co-founder & AI Consultant

    Eric

    Co-founder & AI Consultant

    Lisa, Project Lead & Implementation

    Lisa

    Project Lead & Implementation

    Results From Our Clients

    Verified outcomes from completed AI implementations

    AI AgentFood & Grocery

    AI Agent for Order Management

    Ljusgårda (Supernormal Greens)

    $250K/year saved
    • 83% cost reduction
    • 70-80% automation
    • 6-week implementation
    AI AutomationPublic Sector

    Document Automation: 60h → 3min

    Public Sector

    6,400–8,000 h/year freed
    • 95% time reduction
    • 60h → 3min/doc
    • 1000+ hours/month saved
    AI SEOMedia & Publishing

    AI-Driven SEO Rewrite: +2,092% Clicks

    Media Company

    +2,092% clicks
    • 178 articles rewritten
    • +330% daily increase
    • 141 → 3,091 clicks

    Top AI Use Cases in Pharma

    Where AI agents deliver the highest ROI in pharmaceutical R&D

    1. Molecular Modeling & Drug Candidate Screening

    Traditional drug screening takes 4-6 years in preclinical phases. AI agents analyze molecular structures, predict binding affinities, simulate ADMET properties, and rank thousands of candidates — reducing preclinical timelines to 18-24 months.

    Key Deliverables:

    Protein structure prediction
    Binding affinity modeling
    ADMET property optimization
    Lead compound ranking

    2. Clinical Trial Optimization

    80% of clinical trials fail to meet enrollment deadlines. AI agents analyze patient databases, predict enrollment velocity, optimize site selection, and enable adaptive trial designs — cutting recruitment time by 30-50% and reducing protocol deviations by 40%.

    Key Deliverables:

    Patient matching & recruitment
    Adaptive trial design
    Site performance prediction
    Real-time safety monitoring

    3. Pharmacovigilance & Safety Monitoring

    Post-market safety monitoring traditionally relies on manual case processing with 6-12 month detection lag. AI agents analyze real-world evidence, FAERS reports, and social media signals in real-time — detecting safety signals in days, not months.

    Key Deliverables:

    Real-time adverse event detection
    Automated case processing
    Signal detection & analysis
    PBRER/PSUR auto-drafting

    Built for Regulated R&D

    GxP-Compliant AI

    GAMP 5 validated, FDA 21 CFR Part 11 compliant. Complete validation documentation and audit trails for every AI-assisted decision.

    Private RAG Pipelines

    AI agents access your proprietary research data — patents, trial protocols, safety databases — without any data leaving your environment.

    Real-Time Monitoring

    Continuous safety signal detection across clinical and post-market data. Sub-hour alert generation for critical adverse events.

    Regulatory Documentation

    Auto-generated submission packages, CSRs, and safety reports — formatted for FDA, EMA, and PMDA requirements.

    Model Context Protocol

    Secure integration with LIMS, ELN, CTMS, and legacy research systems without modifying existing infrastructure.

    Explainable Predictions

    Every molecular prediction and clinical recommendation includes feature importance, confidence intervals, and decision rationale.

    What Our Clients Say

    "We decided early on to embrace AI technology and needed a partner who could explore opportunities, propose solutions, lead change management, and build them. With Alice, we got everything in one place and have implemented multiple solutions that increased efficiency so significantly that an entire team could be reallocated."

    Andreas Wilhelmsson

    CEO & Co-founder

    Supernormal Greens / Ljusgårda

    "Alice Labs' AI training gave us all a real aha-moment, whether we were completely new to the field or experienced! The training contained a perfect balance between theory and practice. We have definitely become more efficient at work!"

    Åsa Nordin

    IT Manager

    Trollhättan Energi

    "The collaboration with Alice Labs has been easy, educational, and incredibly supportive. We engaged them to improve our processes and create more efficiency in the team, and the result truly exceeded expectations. Through their guidance, we've gained better structure, faster workflows, and more time for what actually creates results."

    Frida

    Partner Manager

    Bruce Studios

    "Fast, professional, and wonderful people. Find out for yourself <3"

    Johannes Hansen

    Founder

    Johannes Hansen AB

    Frequently Asked Questions

    Ready to Accelerate Your R&D Pipeline?

    Tell us about your challenges. We'll respond within 24 hours.

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