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Pharma & Life Sciences

Faster to Patients. Fix the Data First.

We help pharma, biotech and life sciences companies connect R&D, clinical, quality and commercial data, automate GxP-regulated work and use AI with full audit trails, so teams can focus on getting therapies to patients.

Talk to UsWays to Start
Most pharma AI projects stall at validation, not at the model. We start by making the data ALCOA+ compliant and traceable, then automate the work that slows every submission, batch release and launch.
Our point of view
Clinicians reviewing information on a tablet beside a computer

$2.67Baverage cost to take a drug from discovery to launch

2.9%R&D return when GLP-1 drugs are excluded

Pharma Now

What Is Changing in Life Sciences

Development costs are rising, returns are concentrated, and AI is moving faster than proof of value. These are the pressures shaping technology decisions in pharma today.

Strategic Priorities

The Problems Life Sciences Leaders Bring to Us

Six recurring issues we hear from R&D, quality, regulatory and commercial leaders. Each one maps to the capabilities further down this page.

  • P01

    Slow Path to Submission

    eCTD dossiers are assembled by hand from trial, safety and CMC data.

    We often hear“Every submission is a fire drill.”

  • P02

    Siloed R&D and Clinical Data

    EDC, CTMS, eTMF and safety systems don’t share a common data model.

    We often hear“We can’t see one trial end to end.”

  • P03

    AI Stuck at Validation

    CSV/CSA, 21 CFR Part 11 and audit-trail requirements stop pilots going live.

    We often hear“We have pilots, not production.”

  • P04

    Quality Still on Paper

    Batch records, deviations and CAPA run outside the eQMS.

    We often hear“Batch release waits on a binder.”

  • P05

    Disconnected Commercial Data

    HCP, market access and field data live in separate tools.

    We often hear“Medical and sales see different doctors.”

  • P06

    Specialist Skills Gap

    Validation, data and platform engineers are hard to hire at pace.

    We often hear“We can’t staff the roadmap.”

Sub-Segments

Who We Work With in Life Sciences

Each segment runs different systems and carries different regulatory weight. We shape teams and compliance to each one.

  • Scientist working with samples in a life sciences lab

    Large Pharma

    Global R&D, manufacturing, commercial

    Connect R&D, quality and commercial data across regions and GMP sites.

    • CIO
    • CDO
    • R&D IT
    • Quality
  • Lab technician at a monitor in a laboratory

    Biotech

    Pipelines, first approvals and launches

    Build GxP-ready data, systems and teams for a first submission and launch.

    • CTO
    • Clinical Operations
    • Commercial Lead
  • Pharmacy worker checking stock on warehouse shelves

    CROs & CDMOs

    Trials and manufacturing for sponsors

    Run trials and batches for many sponsors on one validated platform.

    • COO
    • Quality Head
    • IT Director
  • Doctor reviewing a digital health app on a tablet with a patient

    MedTech & Diagnostics

    Devices, diagnostics, connected products

    Build secure, compliant products and the data platforms behind them.

    • CTO
    • VP Engineering
    • Regulatory Affairs

Value Chain & Use Cases

Where We Help Across the Pharma Value Chain

Use cases we deliver at each stage, tagged by the capability behind them.

  1. Research & Discovery

    • Research data platform with LIMS and ELN integrationData
    • Literature and target-insight assistantAI

  2. Clinical Development

    • Trial data hub across EDC, CTMS and eTMFData
    • Site selection and enrolment forecastingAI

  3. Regulatory & Safety

    • eCTD dossier and RIM workflowsAutomation
    • Pharmacovigilance case intake and triageAI

  4. Manufacturing & Quality

    • Electronic batch records connected to MESAutomation
    • eQMS deviation, CAPA and change controlPlatforms

  5. Supply Chain

    • DSCSA / EU FMD serialization and cold-chain visibilityData
    • Demand and supply forecastingAI

  6. Commercial & Medical

    • Field CRM and HCP 360Platforms
    • Compliant MLR content approval workflowsAutomation

Sample Engagements

What Working With Us Could Look Like

Typical projects based on the problems above, with realistic scope and timelines.

Two lab staff reviewing results on a laptopIllustrative engagement

Biotech

One Clinical Data Hub for a Phase III Biotech

Situation
Trial data sits across EDC, CTMS and spreadsheets, and status reports take a week to build.
What we would do
A governed trial data model, source integrations with audit trails, and live dashboards for clinical operations.
  • Dailytrial status (target)
  • 14–18 wksto go-live

Capabilities

Capabilities Mapped to Your Priorities

See which of our practices answers each priority, so you know where to start.

  • Data & Analytics

    Platforms, integration and BI

    1. Slow Path to Submission: supporting
    2. Siloed R&D and Clinical Data: primary fit
    3. AI Stuck at Validation: supporting
    4. Quality Still on Paper: not a main fit
    5. Disconnected Commercial Data: primary fit
    6. Specialist Skills Gap: not a main fit

  • AI & Automation

    GenAI, agents, ML and RPA

    1. Slow Path to Submission: primary fit
    2. Siloed R&D and Clinical Data: not a main fit
    3. AI Stuck at Validation: supporting
    4. Quality Still on Paper: primary fit
    5. Disconnected Commercial Data: supporting
    6. Specialist Skills Gap: not a main fit

  • Cloud & App Modernization

    Validated migration and re-architecture

    1. Slow Path to Submission: not a main fit
    2. Siloed R&D and Clinical Data: supporting
    3. AI Stuck at Validation: not a main fit
    4. Quality Still on Paper: supporting
    5. Disconnected Commercial Data: not a main fit
    6. Specialist Skills Gap: not a main fit

  • Enterprise Platforms

    Salesforce, SAP, ServiceNow

    1. Slow Path to Submission: not a main fit
    2. Siloed R&D and Clinical Data: not a main fit
    3. AI Stuck at Validation: not a main fit
    4. Quality Still on Paper: supporting
    5. Disconnected Commercial Data: primary fit
    6. Specialist Skills Gap: not a main fit

  • Security & Governance

    Data integrity, Part 11 controls, AI risk

    1. Slow Path to Submission: supporting
    2. Siloed R&D and Clinical Data: not a main fit
    3. AI Stuck at Validation: primary fit
    4. Quality Still on Paper: supporting
    5. Disconnected Commercial Data: not a main fit
    6. Specialist Skills Gap: not a main fit

  • Specialist Talent

    Validation, data and platform engineers

    1. Slow Path to Submission: not a main fit
    2. Siloed R&D and Clinical Data: supporting
    3. AI Stuck at Validation: supporting
    4. Quality Still on Paper: not a main fit
    5. Disconnected Commercial Data: not a main fit
    6. Specialist Skills Gap: primary fit
  1. P01 Slow Path to Submission
  2. P02 Siloed R&D and Clinical Data
  3. P03 AI Stuck at Validation
  4. P04 Quality Still on Paper
  5. P05 Disconnected Commercial Data
  6. P06 Specialist Skills Gap

How We Work

Five Steps From Idea to Validated Results

Discuss Your Life Sciences Priorities

  1. Assess

    Understand goals, systems, data and regulatory scope, and agree what success means.

  2. Prioritise

    Score use cases by value, data readiness and validation risk, and pick the first one.

  3. Integrate & Build

    Connect the data the first use case needs, with GxP controls and audit trails built in.

  4. Validate

    Qualify the solution (IQ/OQ/PQ) with GAMP 5-aligned documentation and a traceability matrix.

  5. Scale

    Roll out to more teams, sites and products, hand over, or let us run it for you.

FAQs

Questions Life Sciences Teams Ask Us

Still have a question?

Talk to someone who knows life sciences systems, regulations and teams.

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Do your solutions support 21 CFR Part 11 and EU Annex 11?

We design for compliant electronic records, e-signatures and audit trails, and deliver validation documentation into your quality system.

How do you validate systems and AI before they go live?

We follow a risk-based CSV/CSA approach aligned to GAMP 5, with IQ/OQ/PQ evidence and human review built into every AI workflow.

How do you protect data integrity and patient privacy?

Builds follow ALCOA+ principles, with access controls, encryption and audit trails. Data stays in your environment, aligned to GDPR and HIPAA.

Can you integrate with our eQMS, LIMS, MES, EDC and eTMF?

Yes, through standard APIs and validated data pipelines, connected to the systems your teams already use.

What is the fastest way to get started?

A short assessment that maps your systems, data and regulatory scope, then one validated use case delivered first.

Let’s Build Together

Build More Connected Life Sciences Systems

Connect R&D, clinical and commercial data, take manual work off regulated teams and use AI you can validate.

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  • Connected Data
  • GxP-Ready Automation
  • Validated AI
  • Specialist Talent