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GlobalPharma

Updating the operating model

Industry
Biotechnology
Public information as of
January 2026

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

Strategic priorities

GlobalPharma operates across 4 stated priorities, with the most concrete near-term plan anchored on operational excellence in manufacturing.

use Industry 4.0 technologies to maintain the "shortest lead times" promise while managing 14 different production forms across high-mix, low-volume operations.

Transforming the government-recognized R&D facility in Suchedniów into a fully integrated digital ecosystem to reduce prototype-to-production latency for 1,500+ implemented projects.

Meeting CSRD 2024 reporting requirements through automated energy, water, and waste data collection pipelines across Polish manufacturing sites.

Challenges we see

  • Operations Manufacturing

    High-Mix Production Changeover Inefficiency

    GPCM operates 12-14 different production forms including tablets, capsules, softgels, BOV sprays, and lozenges across Suchedniów and Ostrów Lubelski sites. Each changeover requires manual cleaning validation and line clearance procedures.

    Without MTP standards or "Plug & Produce" modularity, frequent changeovers drive significant OEE degradation and manufacturing downtime, directly impacting the "shortest lead times" value proposition.

  • Digital Integration

    R&D-to-Production Translation Loss

    GPCM has implemented 1,500 projects, but the transition from lab recipe to production floor involves paper-based work instructions and manual data transfer.

    "Golden Batch" data generated in R&D is not effectively used to drive production floor PID controllers, creating a digital friction that increases rework rates and slows time-to-market.

  • Digital Integration

    Siloed Quality Control Data Systems

    Rigorous microbiological purity and physicochemical testing data remains trapped in LIMS systems disconnected from the ERP and MES platforms.

    Data silos slow real-time "Batch Release by Exception," increasing lead times and creating regulatory risk during MoH inspections for Class II medical devices.

  • ESG Regulatory

    CSRD ESG Reporting Infrastructure Gap

    NEUCA Group must comply with mandatory CSRD reporting starting 2024, requiring granular carbon, water, energy, and waste data from GPCM manufacturing facilities.

    Current sites lack IoT infrastructure to automate collection of utility data, forcing reliance on manual Excel tracking that is error-prone and audit-risky.

  • Digital Operations

    OT Cybersecurity Vulnerabilities

    As GPCM expands connectivity to NEUCA Group network for ESG reporting and centralized management, legacy equipment at Suchedniów becomes exposed.

    Many production machines lack modern security protocols, creating attack vectors as the IT/OT convergence accelerates without proper "Zero Trust" architecture.

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. Manufacturing Margin Compression

    Despite 37.9% YoY revenue growth (PLN 315.5m in 1H 2024), the NEUCA Manufacturing segment shows operating profit pressure (PLN 19.3m to PLN 17.1m in 1H 2023), indicating inefficiency in production operations.

    Implement real-time OEE monitoring and predictive maintenance on high-value production lines (particularly BOV technology) to identify and eliminate sources of margin leakage.

  2. High R&D Project Turnover Complexity

    Managing 1,500+ implemented projects with constant lab setup/teardown creates "Innovation Latency"—extended time from concept in Suchedniów to registered product across 55+ markets.

    Deploy automated "Digital Resurrection" strategy for lab workflows, enabling rapid connectivity of diverse instruments (Beckman Coulter, etc.) into a central Industrial Data Platform.

  3. Manual Quality Control Workflows

    BOV technology for nasal sea waters and ear sprays requires sophisticated pressure and filling controls. Manual visual inspection creates inconsistent batch quality and contamination risk.

    Implement non-invasive Computer Vision systems for real-time foam management and fill-level verification, reducing rejects while maintaining 24/7 autonomous monitoring.

  4. Regulatory ESG Data Collection

    CSRD compliance requires automated tracking of energy consumption, water usage, and waste metrics across both manufacturing sites—data currently collected manually in spreadsheets.

    Build an Industrial Data Platform with IoT sensors to automate ESG metrics collection, providing auditable real-time dashboards for NEUCA Group sustainability reporting.

  5. Fragmented IT/OT Architecture Post-Acquisition

    Recent acquisition of P.P.H. "EWA" S.A. creates a fragmented IT/OT landscape with disparate quality systems, communication protocols, and data formats between GPCM and EWA manufacturing sites.

    Harmonize quality systems through a unified Industrial Data Platform, enabling synchronized production schedules between API synthesis and finished formulation across the vertically integrated supply chain.

What we'd propose

  • Digital CDMO

    BOV Line Digital Manufacturing Retrofit

    Comprehensive Industry 4.0 retrofit of Bag-on-Valve production lines at Suchedniów, implementing automated data acquisition, real-time OEE monitoring, and predictive maintenance capabilities.

    • 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
  • Enterprise AI

    ESG Industrial Data Platform

    End-to-end IoT infrastructure and cloud-based data platform for automated collection, aggregation, and reporting of sustainability metrics across all GPCM manufacturing sites.

    • 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

    Digital Lab R&D Integration

    Unified digital ecosystem connecting Suchedniów R&D laboratory instruments, workflows, and data systems into a central platform that accelerates prototype-to-production cycles.

    • 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

    Computer Vision Quality Assurance

    Non-invasive AI-powered visual inspection system for BOV filling lines, automating quality control for foam detection, fill-level verification, and packaging integrity.

    • 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
  • Enterprise AI

    High-Availability IT/OT Architecture

    Enterprise-grade infrastructure modernization transitioning GPCM from legacy standalone workstations to a resilient, clustered architecture with smooth failover and centralized management.

    • 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 GlobalPharma's own published ambition implies — not a perfect score.

Source: A4BEE analysis of public sources
Data Connectivity 35 → 85
Production equipment largely disconnected; LIMS siloed from ERP/MES; manual USB transfers still common
Process Automation 40 → 80
High reliance on manual changeover procedures and visual quality inspection; limited closed-loop control
Analytics & Intelligence 30 → 75
"Golden Batch" data underutilized; real-time KPIs unavailable; post-hoc Excel analysis dominates
Cybersecurity 25 → 70
Legacy equipment lacks modern protocols; IT/OT convergence creating vulnerabilities; no Zero Trust architecture
Regulatory Compliance 45 → 90
Strong GMP/ISO certifications but paper-based processes for MDR devices; manual CSRD data collection
Scalability & Modularity 35 → 80
No MTP standards; complex multi-site coordination post-EWA acquisition; limited Plug & Produce capability

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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 GlobalPharma, 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].