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Celon Pharma S.A.

Lab data, shop-floor data, and a new factory

Industry
Specialty Pharmaceuticals
Headquarters
Łomianki, Poland
Public information as of
January 2026

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

Strategic priorities

Celon Pharma operates a hybrid model in which a stable generics business funds innovative R&D across oncology, neuropsychiatry and metabolic disease. 2023 revenues reached PLN 216.3 million, up 11.2 percent year on year, while the innovative segment grew 54.9 percent on R&D grant refunds and milestone payments. EBITDA climbed from PLN 6.8 million in 2022 to PLN 22.8 million in 2023, a 235.3 percent increase.

Two capital projects are reshaping the operating footprint at the same time. The EUR 23 million EBRD-financed greenfield facility in Žilina, Slovakia is being built for semaglutide pen-injector production, with construction starting in late 2025 and a 12-month build expected. In parallel, the TransformRNA mRNA platform and clinical candidates Falkieri (esketamine DPI) and CPL'36 (PDE10A inhibitor) are entering Phase III, the latter with an FDA Type B meeting in hand.

The digital implication is that the data layer has to serve three programmes at once. Research workstations generate sequence, bioprocess and SPR binding-affinity data on the R&D side. The Kazuń Nowy dry-powder-inhaler plant runs automated molding, assembly and filling. A new pen-injector line is being commissioned in Žilina. Each of those environments expects the same query to return an answer, which is what an ontology-driven data platform and IT/OT reference architecture are designed to provide.

Continuous flow chemistry developed by Krzysztof Dubiel's team at lab scale for PI3Kδ inhibitor CPL302415 intermediates, including Pd-catalysed oxidation and Claisen condensation, has improved E-factors and yields. Carrying that performance into commercial production requires Process Analytical Technology and automated control that bridge lab and plant, which the digital work programme is structured to deliver.

Challenges we see

  • Digital Integration

    Bringing mRNA and biologics research data into a shared model

    The TransformRNA mRNA platform runs Design of Experiments and Quality by Design programmes for LNP formulations across Trop2, FGFR2 and antiviral programmes. The CPL976 PD-L1/AXL bispecific antibody work adds surface-plasmon-resonance binding-affinity, conjugation and cellular-uptake data. Both sets of measurements are produced on instrument workstations that do not currently feed a shared repository.

    Where research teams each keep their own workstation files, the same compound ends up represented differently in each team. A shared ontology over sequence, construct, run, result and lot lets the same question be answered once instead of being reconstructed per group.

  • Operations Manufacturing

    Designing IT/OT for the Žilina pen-injector facility while it is still being built

    The Žilina facility is a greenfield site in CTPark Žilina Airport, with construction starting in late 2025 under an EBRD-financed EUR 23 million package. It will house pen-injector assembly, labs, packaging and storage, and must meet GMP and ISO 9001, 14001 and 45001 from day one.

    When the network and protocol decisions are taken before equipment arrives, the data path is designed rather than retrofitted. Procurement requirements written in those terms arrive with the machines instead of becoming an integration project after handover.

  • Operations Manufacturing

    Carrying continuous flow chemistry performance from lab to commercial scale

    Celon Pharma has run continuous flow reactors at lab scale for Pd-catalysed oxidation, Claisen condensation and LiAlH4 ester reduction, with documented improvements in E-factor and yield. Production-scale reactors need Process Analytical Technology and closed-loop control to keep that performance as volumes increase.

    Where the lab shows a process can be run greener and faster, the question for production is whether the analytical and control layer can sustain the same numbers. Inline spectroscopy and model-predictive control keep the running envelope visible while the reaction is in progress.

  • Compliance Regulatory

    Managing clinical data across global Phase III sites

    Falkieri and CPL'36 Phase III programmes will run across US, EU and additional sites with FDA Type B engagement, centralised monitoring expertise hired from larger sponsors, and ALCOA+ data-integrity expectations from FDA and EMA reviewers.

    Where data must be gathered across thousands of patients and several jurisdictions, the audit trail and the protocol-deviation visibility need to be properties of the system rather than properties of an individual monitor. That is the difference between an inspection that opens the system and one that opens a binder.

  • Operations Manufacturing

    Linking shop-floor signals across the Kazuń Nowy plant and the new Slovak site

    Kazuń Nowy runs fully automated inhaler molding, assembly and filling. The Žilina site will add pen-injector assembly on a separate network. EBRD-linked commitments on workforce skill development and the ISO 14001 environmental programme add site-level sustainability reporting on top of process data.

    Once a company runs two production networks in parallel, a single pane of glass over yield, quality and energy becomes the working surface for operations reviews. Without it, the two sites get reconciled by hand after the fact.

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. Bringing mRNA and biologics research data into a shared model

    mRNA sequencing and LNP-formulation data from TransformRNA, and SPR binding-affinity and conjugation data from the CPL976 programme, sit on separate instrument workstations across the Kiełpin and Warsaw research sites.

    An ontology-driven data platform over sequence, construct, run, result and lot lets both programmes load into one model, so design-of-experiments analyses and cross-programme queries run against a single source of truth.

    • Celon Pharma 2023 investor presentation, April 2024
    • Celon Pharma Deep Research Report, January 2026

  2. Designing IT/OT for the Žilina pen-injector facility before commissioning

    The EUR 23 million Žilina facility starts construction in late 2025 with a roughly 12-month build, and equipment procurement decisions taken now shape the plant's data path for the next decade.

    A reference architecture with OPC UA, network segmentation to IEC 62443, and equipment data contracts embedded in procurement means interoperability is bought with the machines rather than assembled afterwards.

    • EBRD Project Documentation, Celon Pharma Slovakia s.r.o.
    • Current Report 17/2025, Celon Pharma, agreement with general contractor

  3. Carrying continuous flow chemistry from lab to commercial scale

    Lab-scale continuous flow reactors have demonstrated improved E-factors and yields for the CPL302415 aldehyde precursor and Claisen intermediates, but production-scale reactors need Process Analytical Technology to keep that performance.

    Inline NIR, Raman and mass-spectrometry sensors with edge computing and closed-loop control keep the running envelope in view while the reaction is in progress, so lab performance transfers into production numbers.

    • DoE optimisation of aerobic flow Pd-catalysed oxidation, RSC Publishing 2022
    • Celon Pharma 2023 investor presentation, April 2024

  4. Managing clinical data across global Phase III sites

    Falkieri and CPL'36 Phase III programmes will run across thousands of patients in multiple geographies, with FDA Type B engagement, centralised monitoring expertise, and ALCOA+ data-integrity expectations.

    A clinical data platform with centralised monitoring, electronic data capture that meets ALCOA+, and built-in safety-signal dashboards gives regulators and sponsors a single, inspectable record from each site.

    • Celon Pharma, news and regulatory disclosures, 2025
    • Celon Pharma Deep Research Report, January 2026

  5. Linking shop-floor signals across the Kazuń Nowy and Žilina sites

    Kazuń Nowy runs automated inhaler molding, assembly and filling on one network; Žilina will run pen-injector assembly on another. ISO 14001 reporting and the EBRD workforce commitments add a site-level sustainability and training dimension.

    A multi-site quality cockpit with edge computing, predictive-maintenance signals and an integrated ESG dashboard gives operations a single working surface across both plants, with sustainability metrics generated as a by-product.

    • Celon Pharma 2023 investor presentation, April 2024
    • Celon Pharma Environmental Policy

What we'd propose

  • Enterprise AI

    Ontology-driven data platform for mRNA and biologics research

    A shared data model over sequence, construct, run, result and lot, with pipelines from sequencing, SPR and bioprocess instruments, so TransformRNA and CPL976 data can be queried in one place.

    • Shared research ontology

      One agreed set of terms

      Define sequence, construct, LNP formulation, run, result and lot as explicit entities with agreed relationships, so a query written once returns comparable answers across mRNA and biologics programmes instead of two dialects of the same table.

    • Instrument and workstation pipelines

      Loading data from where it lives

      Build ingestion for sequencing, SPR, bioreactor and LNP-characterisation workstations with schema validation at the boundary, so bad records fail loudly instead of arriving silently in the model.

    • DoE and cross-programme analytics

      Questions answered without IT tickets

      Expose Design-of-Experiments analyses, LNP formulation comparisons and binding-affinity queries through a self-service layer, so researchers run their own views without commissioning a new extract for each question.

    • One data model serves TransformRNA, CPL976 and the small-molecule programmes instead of three.
    • Cross-programme questions run against a single repository rather than a folder of exports.
    • New programmes and acquisitions attach to the model rather than triggering another migration.

    We've done this before

    See how we do Enterprise AI
  • Digital CDMO

    IT/OT reference architecture for the Žilina pen-injector facility

    An architecture and standards package for the Žilina greenfield: network segmentation, protocol choices and equipment data requirements agreed before procurement, so the plant's data path is designed rather than retrofitted.

    • Reference architecture for the plant

      One documented data path

      Specify how equipment, line supervision, manufacturing execution and enterprise systems connect, including the segmentation model, so every vendor on the project builds toward the same target.

    • Equipment data contracts

      What each machine must publish

      Write OPC UA information models and MQTT topic structures into procurement requirements, making interoperability a purchase condition rather than an integration project after handover.

    • Segmentation and security baseline

      IEC 62443 zones from day one

      Define zones, conduits and remote-access rules to IEC 62443 before commissioning, so the plant's security posture does not have to be re-argued later against a live production line.

    • Interoperability is bought with the equipment instead of built after commissioning.
    • Traceability from raw material to finished device is a property of the design, not a later addition.
    • The same architecture and procurement language is reusable as the Kazuń Nowy site is upgraded.

    We've done this before

    See how we do Digital CDMO
  • Digital Lab

    Process Analytical Technology for continuous flow chemistry

    An integrated PAT layer for the continuous flow reactors: inline spectroscopy at the reactor outlet, edge computing, and closed-loop control that keeps the running envelope in view while the reaction is in progress.

    • Inline spectroscopy at the reactor

      Reaction monitored in real time

      Deploy NIR, Raman or mass-spectrometry sensors at the outlet of the Pd-catalysed oxidation, Claisen condensation and ester-reduction reactors, with calibration tied to the existing lab analytics.

    • Edge computing for closed-loop control

      Parameters adjusted on the result

      Run the kinetic model on an industrial edge device and feed temperature, flow and reagent setpoints back to the reactor controllers so the system holds the optimum E-factor under normal variation.

    • Lab-to-production traceability

      The lab run and the plant run are the same record

      Capture every PAT reading with lineage back to the lab method that defined the envelope, so a scale-up question is answered by querying the same record instead of re-running the experiment.

    • Lab-scale E-factor performance transfers to production reactors.
    • Reactor operators see the same envelope the chemists see.
    • Deviations surface against the batch that is running, not the batch that already shipped.

    We've done this before

    See how we do Digital Lab
  • Digital CDMO

    Multi-site quality and ESG cockpit for Kazuń Nowy and Žilina

    A unified operations layer over both plants: edge nodes on the line, predictive-maintenance signals and an integrated ESG dashboard, so yield, quality and sustainability are visible from one working surface.

    • Edge quality nodes on the line

      Decisions made at the line

      Place industrial edge devices next to inhaler molding and pen-injector assembly, processing sensor data locally for immediate quality decisions and streaming aggregated metrics to the central cockpit.

    • Predictive maintenance on critical equipment

      Failures flagged before they stop the line

      Instrument molding, assembly and filling equipment with vibration, temperature and performance sensors so the maintenance team works from a prediction rather than a fault.

    • Integrated ESG and energy dashboard

      Sustainability generated as a by-product

      Automate energy, water and E-factor data capture for ISO 14001 and the Žilina rooftop solar PV monitoring, so the numbers that go into the annual report are produced by the line rather than assembled for it.

    • One operations surface serves both sites instead of two parallel reviews.
    • Maintenance moves from reactive to planned because the signal arrives first.
    • ESG and energy reporting is generated continuously rather than compiled at year-end.

    We've done this before

    See how we do Digital CDMO
  • Agents

    AI agents for clinical and regulatory document work

    Narrow, reviewable agents that handle the repetitive part of clinical and regulatory document work: drafting clinical study report sections, building IND and IMPD updates, and tracing every controlled document a protocol or standard change touches. A named person approves each output.

    • Drafting from source records

      First drafts from trial and lab data

      Generate first drafts of clinical study report sections, IND updates and periodic safety reports directly from the underlying trial, lab and manufacturing records, so the author edits and judges rather than assembles.

    • Template and completeness checking

      Gaps found before review

      Check a submitted document against its template and the relevant FDA or EMA checklist, returning missing or inconsistent sections before the document enters the human review queue.

    • Change-impact search across the document set

      Which documents a protocol change touches

      When a protocol, specification or standard changes, retrieve every controlled document that references it and rank them by how directly they are affected, so the update scope is known on day one.

    • Clinical and regulatory queues move faster because documents arrive complete.
    • The scope of a protocol change is established by search rather than by recollection.
    • Every output is traceable to the source records it came from and signed off by a named reviewer.

    We've done this before

    See how we do Agents

Digital maturity: today and target

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

Source: A4BEE analysis of public sources
Lab data integration 45 → 85
Design-of-Experiments and Quality-by-Design capabilities exist on the TransformRNA and CPL976 programmes, but the underlying records stay on instrument workstations. A unified research data model is the next step.
Manufacturing automation 60 → 90
Kazuń Nowy runs fully automated inhaler molding, assembly and filling. The Žilina greenfield is a chance to extend that baseline with IT/OT convergence from day one.
Clinical data management 40 → 80
Centralised monitoring expertise has been hired from larger sponsors and FDA Type B engagement is in place, but the underlying platform for global Phase III is still being assembled.
IT/OT convergence 35 → 85
The CEO has framed manufacturing as a continuous flow that needs real-time digital quality control. The current two-site footprint and the Žilina build make that an immediate programme of work.
Process Analytical Technology 50 → 85
Continuous flow chemistry at lab scale has produced documented E-factor and yield improvements. Production-scale PAT is the next layer needed to carry that performance into commercial reactors.
ESG digital enablement 40 → 75
ISO 14001 and the Sustainable Development Policy are in place, and the Žilina site adds rooftop solar PV. Per-site and per-batch energy measurement is still being assembled manually.

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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 Celon Pharma S.A., 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].