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Step Pharma SAS

Data integration for oncology trials

A precision oncology biotech advancing its pipeline with clinical data integration and GMP documentation

Industry
Biotechnology (Precision Oncology)
Headquarters
Paris, France
Public information as of
January 2026

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

Strategic priorities

Step Pharma SAS is a French precision oncology biotech advancing dencatistat through Phase 1b/2 trials targeting lymphoma, solid tumours and myeloproliferative neoplasms. The company closed a EUR 38M Series C and EUR 2.5M EIC Accelerator grant, specifically earmarked for CMC manufacturing scale-up and pivotal toxicology studies. The pipeline-in-a-product strategy spans three therapeutic areas with CTPS2-null solid tumour expansion into endometrial cancer and multiple myeloproliferative neoplasm indications. Strategic differentiators include the Concr biomarker partnership for patient stratification, FDA Orphan Drug Designation for T-cell lymphoma and approximately 70 patent documents providing IP protection. The immediate challenge is executing multi-site Phase 1/2 trials across France, the UK and the US while simultaneously building CMC manufacturing capabilities for registrational-quality clinical supply.

The defining challenge is clinical data fragmentation. Step Pharma operates Phase 1/2 trials across multiple countries with diverse hospital sites including NEXT Oncology in Texas and UK clinical centres, generating heterogeneous clinical datasets that must be harmonised for regulatory submissions. Without a unified data platform, inconsistencies between clinical sites could delay regulatory filings and compromise dose-escalation data critical for Phase 2 advancement. Beyond clinical operations, the EIC grant specifically funds the transition from small-batch early-phase clinical supply to scalable GMP manufacturing — a transition that requires systematic CMC documentation infrastructure that does not currently exist.

The biomarker partnership with Concr creates an additional data integration challenge: biomarker data from patient stratification must flow directly into clinical trial datasets to validate the CTPS2-null selection hypothesis. Without integrated data infrastructure, the biomarker-driven precision medicine strategy cannot demonstrate the patient selection benefit that differentiates Step Pharma's approach.

Challenges we see

  • Digital Integration

    Clinical trial data fragmentation across France, UK and US hospital sites

    Step Pharma operates Phase 1/2 trials across multiple countries with diverse hospital sites — NEXT Oncology in Texas, UK clinical centres — generating heterogeneous clinical datasets. Without a unified data platform, inconsistencies between sites could delay regulatory filings and compromise dose-escalation data.

    Where clinical data is fragmented by site and country, the regulatory submission dataset must be reconciled manually from incompatible formats. A unified clinical data platform means the submission dataset is generated from consistent source data.

  • Operations Regulatory

    Manual CMC documentation for early-phase supply not scaling to registrational quality

    The EIC Accelerator grant funds the transition from small-batch early-phase clinical supply to scalable GMP manufacturing. Current CMC documentation is manual and optimised for early-phase supply; registrational-quality GMP requires systematic documentation infrastructure that must be built.

    Where CMC documentation is manual and early-phase, the documentation infrastructure for registrational supply must be built from scratch. GMP documentation platform means the infrastructure is ready when the first registrational batch is manufactured.

  • Digital Integration

    Biomarker data from Concr partnership not integrated into clinical trial datasets

    The Concr biomarker partnership provides CTPS2-null patient stratification for the clinical trial programme. Without integrated data infrastructure, biomarker data and clinical outcome data exist in separate systems, preventing the integrated analysis that validates the precision medicine hypothesis.

    Where biomarker data and clinical data are in separate systems, the precision medicine value proposition cannot be demonstrated statistically. Integrated biomarker-clinical platform means the CTPS2-null selection benefit is quantifiable.

  • Digital Operations

    Preclinical data modelling capability not yet developed for pipeline expansion

    Pipeline expansion into endometrial cancer and additional myeloproliferative neoplasm indications requires preclinical data modelling to prioritise indications and design clinical trial endpoints. Current preclinical data is not in a modelling-ready format.

    Where preclinical data is not in a modelling-ready format, the indication prioritisation decisions are made without the quantitative support that modelling would provide. Preclinical data platform means the modelling capability is ready when the pipeline expansion decisions are made.

  • Digital Regulatory

    Clinical IP protection requiring enhanced cybersecurity for multi-jurisdictional trial data

    Clinical trial data spanning France, the UK and the US contains valuable IP around the CTPS2-null mechanism and patient selection biomarkers. Multi-jurisdictional data flows create cybersecurity exposure that standard hospital network protections do not address.

    Where clinical IP is distributed across hospital networks in multiple jurisdictions, the data governance requirements of each country must be met individually. Multi-jurisdiction data governance platform means the IP protection is consistent across all trial sites.

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. Unified clinical data platform for multi-site trial harmonisation

    Clinical trial data is fragmented across hospital sites in France, the UK and the US with no common data model. Site-to-site inconsistencies could delay regulatory filings and compromise the dose-escalation data critical for Phase 2 advancement.

    Deploy a unified clinical data platform that ingests and normalises data from all trial sites into a common data model, enabling consistent regulatory submissions and real-time trial monitoring across all geographies.

    • Step Pharma clinical operations assessment, 2025

  2. GMP documentation platform for CMC manufacturing scale-up

    Current CMC documentation is manual and optimised for early-phase supply. Registrational-quality GMP requires systematic documentation infrastructure that must be built in parallel with the manufacturing scale-up funded by the EIC grant.

    Deploy a GMP documentation platform that captures manufacturing data, batch records and quality data in a validated, audit-ready format as the CMC scale-up progresses toward registrational-quality clinical supply.

    • Step Pharma CMC readiness assessment, 2025

  3. Biomarker-clinical data integration for precision medicine validation

    Biomarker data from the Concr partnership and clinical outcome data exist in separate systems. Without integrated data infrastructure, the CTPS2-null patient selection benefit cannot be quantified for regulatory submissions or partner presentations.

    Build an integrated biomarker-clinical data platform that combines CTPS2-null selection data with clinical outcome data, enabling the statistical analysis that demonstrates the precision medicine value proposition.

    • Step Pharma precision medicine assessment, 2025

  4. Preclinical data modelling platform for pipeline expansion decisions

    Pipeline expansion into endometrial cancer and additional myeloproliferative neoplasm indications requires preclinical data modelling that is not currently available. Current preclinical data is not in a modelling-ready format.

    Build a preclinical data modelling platform that ingests historical preclinical data into a modelling-ready environment, enabling indication prioritisation and clinical trial endpoint design for the pipeline expansion programme.

    • Step Pharma preclinical capabilities assessment, 2025

  5. Multi-jurisdiction clinical data governance and IP security platform

    Clinical trial data across France, the UK and the US contains valuable CTPS2-null IP. Multi-jurisdiction data governance requirements create inconsistent protection unless addressed systematically.

    Implement multi-jurisdiction data governance that provides consistent IP protection and regulatory compliance across all trial sites, satisfying each country's data requirements while maintaining a unified security posture.

    • Step Pharma cybersecurity assessment, 2025

What we'd propose

  • Enterprise AI

    Unified clinical data platform for Step Pharma multi-site trials

    We design and deploy a unified clinical data platform for Step Pharma that ingests and normalises data from all trial sites in France, the UK and the US into a common CDISC CDASH data model, enabling consistent regulatory submissions and real-time trial monitoring across all geographies.

    • Multi-site EDC integration

      Data from every trial site flowing to one platform

      Build data integration pipelines from all trial site EDC systems — Medidata Rave, Oracle Inform, REPLY® — into the unified clinical data platform, normalising data to CDISC CDASH/SDTM standards from the point of collection.

    • Real-time trial monitoring dashboard

      Trial progress visible across all sites in real time

      Deliver real-time trial monitoring dashboards that give Step Pharma clinical operations teams live visibility into enrollment, data completeness and protocol deviation rates across all active trial sites.

    • Regulatory submission dataset automation

      SDTM datasets generated directly from the platform

      Build automated SDTM dataset generation that creates submission-ready CDISC SDTM datasets directly from the clinical data platform, reducing the manual mapping effort that currently precedes every regulatory submission.

    • Regulatory submission timeline shortened by automated SDTM generation from consistent source data.
    • Clinical data quality improved by normalisation at ingestion rather than retrospective reconciliation.
    • Trial oversight transformed from periodic site reports to real-time dashboards.

    We've done this before

    See how we do Enterprise AI
  • Digital Lab

    GMP documentation platform for Step Pharma CMC manufacturing scale-up

    We deploy a GMP documentation platform for Step Pharma that captures manufacturing data, batch records and quality data in a validated, audit-ready format as the CMC scale-up progresses from early-phase supply to registrational-quality GMP manufacturing.

    • Electronic batch record system

      GMP batch records completed electronically at each manufacturing campaign

      Implement electronic batch record capture that records all critical manufacturing parameters, material inputs and quality test results at each CMC manufacturing campaign, generating audit-ready batch records without paper documentation.

    • CMC regulatory submission documentation

      CMC sections of IND and CTA applications assembled automatically

      Build CMC regulatory submission documentation automation that assembles the manufacturing and quality sections of IND and CTA applications from the GMP documentation platform, ensuring consistency between the filing and the manufacturing record.

    • Equipment calibration and maintenance tracking

      GMP equipment status always current and audit-ready

      Deploy equipment calibration and maintenance tracking that keeps all GMP manufacturing equipment status current, with automated alerts for upcoming calibrations and maintenance that could affect GMP compliance.

    • Registrational CMC readiness demonstrated by having GMP documentation infrastructure in production before the first registrational batch.
    • Regulatory inspection risk reduced by audit-ready batch records maintained continuously rather than assembled retrospectively.
    • Manufacturing team time recovered from paper documentation management.

    We've done this before

    See how we do Digital Lab
  • Enterprise AI

    Biomarker-clinical data integration platform for precision medicine validation

    We build an integrated biomarker-clinical data platform for Step Pharma that combines Concr CTPS2-null selection data with clinical outcome data, enabling the statistical analysis that quantifies the precision medicine value proposition for regulatory submissions and partnership discussions.

    • Biomarker data integration pipeline

      Concr biomarker data flowing into the clinical data platform

      Build data integration pipelines that ingest Concr CTPS2-null biomarker selection data and clinical outcome data into a unified analytical environment, enabling integrated analysis that was previously impossible with data in separate systems.

    • Precision medicine statistical analysis platform

      CTPS2-null selection benefit quantified statistically

      Develop precision medicine statistical analysis that quantifies the CTPS2-null patient selection benefit, generating the evidence required for regulatory submissions and partnership discussions.

    • Patient stratification decision support

      Site investigators supported by biomarker-based patient pre-screening

      Build patient stratification decision support that provides site investigators with biomarker-based pre-screening tools, ensuring only CTPS2-null selected patients are enrolled and the trial's precision medicine hypothesis is preserved.

    • Precision medicine value proposition quantified statistically for regulatory and partnership use.
    • Clinical trial efficiency improved by ensuring only CTPS2-null selected patients are enrolled.
    • Concr partnership value demonstrated by integrated data analysis that validates the biomarker approach.

    We've done this before

    See how we do Enterprise AI
  • Enterprise AI

    Preclinical data modelling platform for pipeline expansion

    We build a preclinical data modelling platform for Step Pharma that ingests historical preclinical data into a modelling-ready environment, enabling indication prioritisation for the endometrial cancer and myeloproliferative neoplasm expansion programme.

    • Preclinical data standardisation and ingestion

      All historical preclinical data in one modelling-ready environment

      Ingest all historical preclinical data — efficacy studies, toxicology reports, PK/PD datasets — into a standardised, modelling-ready data environment that enables quantitative analysis across the full historical dataset.

    • Indication prioritisation modelling

      Pipeline expansion decisions supported by quantitative models

      Build indication prioritisation models that use the standardised preclinical data to rank endometrial cancer and myeloproliferative neoplasm indications by probability of clinical success, providing the quantitative basis for pipeline expansion decisions.

    • Clinical trial endpoint modelling

      Optimal endpoints identified before Phase 2 design begins

      Develop clinical trial endpoint models that use preclinical data to identify the optimal primary and secondary endpoints for each expansion indication, improving the probability of regulatory success at Phase 2.

    • Pipeline expansion decisions grounded in quantitative analysis rather than qualitative judgment.
    • Phase 2 design improved by preclinical endpoint modelling before the trial begins.
    • Institutional knowledge preserved in a structured data environment rather than in individual documents.

    We've done this before

    See how we do Enterprise AI
  • Enterprise AI

    Multi-jurisdiction clinical data governance for Step Pharma trial sites

    We implement multi-jurisdiction clinical data governance for Step Pharma's trial sites across France, the UK and the US, providing consistent IP protection and regulatory compliance across all geographies while satisfying each jurisdiction's specific data requirements.

    • GDPR and HIPAA compliant data architecture

      Clinical IP protected under all three jurisdictions' requirements

      Architect a data governance framework that satisfies GDPR, UK GDPR and HIPAA requirements simultaneously, ensuring clinical IP is protected across all trial sites without creating conflicting data handling procedures.

    • Clinical data access governance

      Every data access logged and auditable

      Build clinical data access governance that logs every access to clinical trial data with user identity, timestamp and purpose, providing the audit trail required for regulatory inspections and IP protection.

    • Cross-border data transfer compliance

      France-UK-US data flows documented and compliant

      Implement cross-border data transfer compliance that documents and controls data flows between France, the UK and the US trial sites, ensuring each transfer meets the applicable regulatory requirements.

    • Clinical IP protected consistently across all trial jurisdictions without conflicting procedures.
    • Regulatory inspection readiness demonstrated by comprehensive data access audit trails.
    • Partner and investor confidence strengthened by professional data governance infrastructure.

    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 Step Pharma SAS's own published ambition implies — not a perfect score.

Source: A4BEE analysis of public sources
Clinical Data Integration 20 → 85
Clinical trial data is fragmented across hospital sites in France, the UK and the US with no common data model. No unified clinical data platform exists.
CMC Documentation 25 → 80
CMC documentation is manual and optimised for early-phase supply. No GMP documentation platform is deployed. Registrational-quality documentation infrastructure must be built.
Biomarker Data Integration 15 → 75
Concr biomarker data and clinical outcome data exist in separate systems. No integrated biomarker-clinical data platform is deployed.
Preclinical Data Modelling 15 → 70
No preclinical data modelling capability exists. Current preclinical data is not in a modelling-ready format.
Clinical IP Security 30 → 75
Clinical IP is distributed across hospital networks in multiple jurisdictions. No systematic multi-jurisdiction data governance platform is deployed.
IT Architecture 30 → 70
IT infrastructure is optimised for early-phase operations. EIC-funded CMC scale-up and pipeline expansion require scalable cloud-based architecture that must be designed and implemented.

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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 Step Pharma SAS, 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].