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Farmak

Updating the operating model

Industry
Pharmaceuticals
Public information as of
January 2026

A4BEE prepared this analysis from publicly available sources. It reflects our own reading of Farmak's published strategy and is not endorsed by, or produced in cooperation with, Farmak. Company website

Strategic priorities

Farmak operates across 4 stated priorities, with the most concrete near-term plan anchored on global manufacturing expansion.

Strategic acquisition of Polish pharmaceutical company and expansion of Barcelona facility to diversify geopolitical risk and increase EU manufacturing footprint for 80+ country distribution network.

Complete digitalization of batch documentation and production records through SAP S/4HANA implementation targeting 2026 completion, replacing fragmented legacy systems with a unified Group-wide ERP.

Implementation of sustainability roadmap aligned with ESRS and CSRD requirements, including real-time monitoring of water, natural gas, and electricity consumption across all manufacturing sites.

Challenges we see

  • Digital Integration

    IT/OT Integration Gap

    While Farmak is investing heavily in SAP S/4HANA modernization, a critical gap exists between the top-floor ERP systems and shop-floor PLC/SCADA layers managing reactors and micronization equipment.

    Data from 6,300L reactors and micronization mills is manually transcribed or isolated in historian databases, preventing real-time production visibility and compromising the Electronic Dossier initiative.

  • Digital Manufacturing

    Laboratory Data Fragmentation

    QC laboratories utilize advanced NMR spectroscopy, X-ray powder diffractometers, and climate chambers, but instrument data integration into a unified LIMS is incomplete.

    Scientists spend disproportionate time on manual data entry and Excel management, complicating ALCOA+ data integrity standards and increasing FDA audit risk following the 2018 VAI status.

  • Operations Integration

    Multi-Site Acquisition Integration

    Recent acquisition of Polish pharmaceutical company and expansion of Spanish manufacturing creates standardization friction across diverse IT/OT stacks and legacy systems.

    The pace of integrating acquired facilities into Group SAP and data standards will drive synergy realization and shape compliance consistency across EU operations.

  • Operations Manufacturing

    Predictive Maintenance Deficit in High-Risk Units

    Plant 21 (hydrogenation) and Plant 13 operate high-pressure autoclaves with reactions ranging from -80C to 200C, representing the most complex and valuable production capabilities.

    Current SCADA systems provide reactive alarms without predictive insights, where high-value batches of tamsulosin and zolpidem APIs to unplanned downtime and yield losses.

  • ESG Compliance

    ESG Data Collection Complexity

    Farmak has completed ESG analysis to align with CSRD requirements and is building a roadmap to monitor sustainability indicators across the entire supply chain including supplier conduct.

    Manual collection of environmental metrics across Ukrainian, Czech, Polish, and Spanish sites creates reporting gaps and accuracy risks that could undermine CSRD compliance deadlines.

Opportunities, by urgency and business impact

Each bubble is one opportunity, numbered to match the list below. Further right means it bites sooner; higher means a bigger effect on the business. A bigger bubble means a bigger implementation effort.

Source: A4BEE analysis of public sources

  1. Real-Time Production Visibility

    The gap between SAP S/4HANA ERP and shop-floor equipment creates data latency that prevents the Electronic Dossier from achieving true real-time production intelligence.

    Deploy an Industrial Data Platform that bridges the "last mile" between reactors, micronization mills, and the ERP layer, converting messy OT data into clean, structured inputs for automated batch documentation.

  2. FDA-Ready Data Integrity

    The 2018 FDA inspection resulted in VAI status indicating "minimally acceptable" documentation practices, while QC lab instruments remain disconnected from unified data systems.

    Implement Lab Digitalization that automates data extraction from NMR, XRD, and other analytical instruments directly into audit-ready digital chains satisfying ALCOA+ standards with zero manual transcription.

  3. Unified Multi-Site Operations

    Newly acquired Polish facility and expanding Spanish operations use different IT/OT stacks that must be standardized to the Group SAP S/4HANA environment without replacing all legacy hardware.

    Apply MTP-based modular production standards and vendor-agnostic connectivity to rapidly onboard acquired facilities into the Group data pool while preserving functional legacy equipment.

  4. High-Risk Unit Optimization

    High-pressure hydrogenation in Plant 21 and Grignard reactions in Plant 13 carry significant batch loss risk, yet monitoring relies on reactive SCADA alarms without predictive intelligence.

    Deploy AI-driven process monitoring and computer vision (foam detection) to provide predictive anomaly detection, optimizing catalyst separation and reducing unplanned downtime in high-value API production.

  5. Automated ESG Reporting

    CSRD compliance requires comprehensive tracking of water, natural gas, electricity, and supplier sustainability metrics across four countries, currently managed through manual organizational measures.

    Implement IoT-based energy monitoring with AI-driven optimization targeting 5-10% reduction in resource consumption while automating the data collection pipeline for ESRS-compliant sustainability reporting.

What we'd propose

  • Enterprise AI

    Industrial Data Platform for Electronic Dossier

    A unified data backbone connecting shop-floor equipment to SAP S/4HANA, enabling the Electronic Dossier of the Series through automated, real-time production data capture and contextualization.

    • Ontology layer

      A shared semantic model so lab, process, and quality data describe the same things the same way.

      DETAIL

    • Predictive models

      Models trained on the historical data plane that flag deviations before they become scrap.

      DETAIL

    • Decision surfaces

      Single pane of glass that surfaces model output to the right role at the right moment.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Enterprise AI
  • Digital Lab

    QC Lab Digitalization & ALCOA+ Compliance

    Complete digitalization of QC laboratory workflows connecting analytical instruments to a unified LIMS layer, ensuring FDA-ready data integrity and eliminating paper-based documentation risks.

    • Unified data backbone

      Connect instruments and LIMS into a single data spine so QC and CDMO records are queryable across sites.

      DETAIL

    • Paperless workflows

      Move lab execution from paper to instrument-captured records with full audit trail.

      DETAIL

    • Continuous QC release

      Review-by-exception dashboards that flag only the records needing scientist attention.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Digital Lab
  • Digital CDMO

    Multi-Site IT/OT Integration Framework

    Standardized integration architecture enabling rapid onboarding of acquired facilities into Group-wide digital standards through MTP-based modularity and vendor-agnostic connectivity patterns.

    • OT/IT convergence

      Pull sensor and controller data off the line into a shared data plane in real time.

      DETAIL

    • Batch intelligence

      Golden-batch comparison and deviation detection running on the same data plane.

      DETAIL

    • Production release flow

      Closed-loop between QA, MES, and ERP so batch record review and release follow the data, not the paperwork.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Digital CDMO
  • Digital Lab

    AI-Powered Process Monitoring for High-Risk Units

    Predictive analytics and computer vision solution for Plant 21 hydrogenation and Plant 13 synthesis units, transforming reactive alarm management into proactive batch optimization.

    • Unified data backbone

      Connect instruments and LIMS into a single data spine so QC and CDMO records are queryable across sites.

      DETAIL

    • Paperless workflows

      Move lab execution from paper to instrument-captured records with full audit trail.

      DETAIL

    • Continuous QC release

      Review-by-exception dashboards that flag only the records needing scientist attention.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Digital Lab
  • Enterprise AI

    ESG Data Platform & Energy Optimization

    IoT-enabled sustainability monitoring platform providing automated CSRD-compliant reporting and AI-driven energy optimization across all manufacturing facilities.

    • Ontology layer

      A shared semantic model so lab, process, and quality data describe the same things the same way.

      DETAIL

    • Predictive models

      Models trained on the historical data plane that flag deviations before they become scrap.

      DETAIL

    • Decision surfaces

      Single pane of glass that surfaces model output to the right role at the right moment.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Enterprise AI

Digital maturity: today and target

Scored out of 100 across six dimensions. The target is what Farmak's own published ambition implies — not a perfect score.

Source: A4BEE analysis of public sources
IT/OT Convergence 35 → 80
SAP S/4HANA rollout underway but shop-floor integration remains manual; target requires unified data platform
Data Integrity & Compliance 45 → 90
FDA VAI status indicates gaps; target requires automated ALCOA+ enforcement across all QC operations
Predictive Analytics 25 → 70
Current SCADA provides reactive alarms only; target requires ML-based anomaly detection in critical units
Cross-Site Standardization 30 → 85
Acquired facilities operate on different systems; target requires MTP-based plug-and-produce modularity
ESG Data Automation 20 → 75
Manual sustainability tracking; target requires IoT-enabled real-time monitoring and automated reporting
R&D Digitalization 40 → 80
Advanced instruments exist but workflow automation limited; target requires Digital Lab integration

Check this yourself

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Related reading

This is an independent analysis prepared by A4BEE from publicly available information as of January 2026. It reflects A4BEE's own interpretation and opinion, is not affiliated with, endorsed by, or verified with Farmak, and may be incomplete or inaccurate. All company names and trademarks are the property of their respective owners. To request a correction or removal, contact [email protected].