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Polpharma CDMO

Updating the operating model

Public information as of
January 2026

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

Strategic priorities

Polpharma CDMO operates across 4 stated priorities, with the most concrete near-term plan anchored on innovation as portfolio driver.

Focusing on "Hard-to-Make" Generics (H2M Gx), complex technologies like nano-milling, and the development of High Potency APIs (HPAPI) to target oncology and chronic disease markets.

Gaining efficiency through the "Production System" initiative (ongoing since 2020) and OPEX programs designed to eliminate eight types of manufacturing waste (DOWNTIME methodology).

Transitioning to a hybrid commercial model and prioritizing Day-1 launches to outgrow the broader healthcare market across 40+ global countries.

Challenges we see

  • IT Infrastructure Digital

    Legacy IT and MES Integration

    The Starogard Gdanski facility is transitioning from manual records to Werum's PAS-X Manufacturing Execution System (MES) to ensure compliance and shorten cycle times across 100+ diverse products.

    Data islands still hold back process intelligence; maintaining GxP compliance across diverse process variations (ampoules, vials, solid forms) adds technical debt that slows digital transformation.

  • Digital Transformation Labor

    Organizational Structural Rigidity

    Markus Sieger notes that traditionally hierarchical European pharmaceutical organizations are slow to adapt to new business models compared to digital-native sectors.

    Without an end-to-end approach to organizational readiness, isolated digital investments underdeliver; currently 57% of lab staff cite limited technical knowledge as a primary barrier to transformation.

  • Manufacturing Safety Regulatory

    High-Potency API (HPAPI) Safety Risks

    The "Prometheus" facility expansion targets substances with an Occupational Exposure Limit (OEL >= 10 ng/m3), requiring high-performing containment systems.

    Handling extremely harmful substances requires redundant safety protocols and isolator technology to prevent employee exposure and industrial accidents at the Starogard hub.

  • Supply Chain Energy

    Supply Chain Energy Volatility

    Polpharma is heavily reliant on coal-based energy at the Starogard plant and is currently phasing it out for biomass and gas-fired steam production.

    Dramatically increasing energy costs and the "magnitude of commitment" to drug security (1 in 3 packages in hospitals) make the plant vulnerable to energy commodity shortages.

  • Workforce Development Training

    Workforce Digital Readiness Gap

    Traditional onboarding for complex API machinery is slow; only 5% of pharmaceutical staff feel "highly prepared" for digital transformation according to industry surveys.

    The knowledge gap slows adoption of advanced manufacturing technologies; 57% of staff report limited technical knowledge as a primary barrier to digital tool utilization.

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. Manual Shift Handovers and Maintenance Tracking

    Fragmented communication during shift changes and manual reporting of equipment failures lead to 10-15% longer repair times and "lost" data across production units.

    Scaling the Electronic Shift Handover (ESH) and Maintenance modules to provide online calculated KPIs and real-time failure repair analytics across all facilities.

  2. HPAPI Market Expansion Constraints

    Global HPAPI demand is rising to $51.53 billion by 2030, but entry requires high-tech containment and specialized cryogenic infrastructure (-80C).

    use the new "Prometheus" facility to double production capacity and provide clinical-to-commercial scale services for highly active substances.

  3. Training Lag for Complex Processes

    Traditional onboarding for complex API machinery is slow; only 5% of pharmaceutical staff feel "highly prepared" for digital transformation, creating operational bottlenecks.

    Implementing AR and Digital Twins (Microsoft HoloLens) for virtual retooling and maintenance training, reducing human error by 30%.

  4. Data Island Fragmentation

    Critical process data remains trapped in legacy SCADA systems, paper records, and disparate databases, preventing advanced analytics and real-time process intelligence.

    Building an ontology-based data platform to unify R&D and manufacturing data for AI-ready regulatory submissions and automated OPV reporting.

  5. OT Cybersecurity Vulnerabilities

    Legacy PLCs and SCADA systems lack Zero Trust architecture; cloud-based OT asset inventory (ThingWorx) implementation is incomplete, exposing critical manufacturing systems.

    Implementing IEC 62443 compliant security architecture with Zero Trust principles to protect the OT layer while enabling secure data flow to IT systems.

What we'd propose

  • Digital CDMO

    Digital Manufacturing & OT Retrofitting

    Accelerating Industry 4.0 by retrofitting legacy API machinery with IoT gateways to enable real-time connectivity, predictive maintenance, and eliminating data islands across the Starogard facility.

    • 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

    BioTech Lab & Immersive Training Platform

    Building AR/VR environments for safe technician training in high-potency and cryogenic zones, reducing risk exposure and accelerating onboarding for complex API manufacturing processes.

    • 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

    Industrial Data Platform & Analytics

    Constructing ontology-based data platforms to unify R&D and manufacturing data across the Starogard facility for AI-ready regulatory submissions and automated Ongoing Process Verification.

    • 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 CDMO

    OT Cybersecurity & Zero Trust Architecture

    Implementing IEC 62443 compliant security architecture with Zero Trust principles to protect legacy PLCs and SCADA systems while enabling secure IT/OT convergence for the pharmaceutical manufacturing environment.

    • 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

    MES Integration & Process Orchestration

    Accelerating the transition from manual records to fully digital MES-driven operations by integrating Werum PAS-X with shop floor equipment and building unified process orchestration across 100+ product variations.

    • 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 maturity: today and target

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

Source: A4BEE analysis of public sources
Data Interoperability 65 → 95
Polpharma has a "world-class data architecture" vision but still struggles with data islands in legacy manufacturing units requiring unified platform deployment.
Asset Performance Management 55 → 90
Electronic Shift Handover (ESH) has reduced failure repair times by 10-15%, but predictive maintenance is not yet universal across all production lines.
Workforce Digital Readiness 43 → 85
57% of staff report lack of technical knowledge; culture shift from hierarchy to collaboration is the primary hurdle requiring immersive training programs.
OT Cybersecurity 60 → 95
Cloud-based OT asset inventory (ThingWorx) is under implementation, but legacy PLCs require Zero Trust architecture and IEC 62443 compliance.
Sustainability Transparency 50 → 90
41% GHG reduction achieved through energy transition, but Scope 3 emissions and green chemistry monitoring require automated data chains.
Process Automation 58 → 92
MES implementation ongoing with PAS-X, but manual records persist in many areas; full electronic batch record deployment needed across all product types.

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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 Polpharma CDMO, 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].