Pharma · Development

Personalized Solutions for Pharma Development

We help development teams turn promising research into scalable, validated processes through tailored organizational, digital and technical solutions.

01 · the phase

Development is where promising science meets process reality, and where scale-up surprises, tech-transfer overhead and validation rework eat timelines. We know these bottlenecks and prove which one is worth moving with a 4-week PoC, before it threatens a Phase-III milestone.

02 · what we hear

Key challenges, and how AI-driven transformation helps.

  • Scale-up risk
    Challenge

    Successful early R&D still carries a real risk of failing to scale, and technology transfer can hide the exact issues that lead to failure at Phase III.

    How we help

    We identify the risk areas along technology transfer that would otherwise surface at Phase III, and provide a validation-ready path built for successful scaling.

  • Mapping data across targets
    Challenge

    Large volumes of sequences and structures cannot easily be mapped across similar targets, so relationships that would speed development stay hidden.

    How we help

    We develop knowledge graphs that amalgamate and analyse the various layers of data, helping pinpoint which sequences and structures connect to new disease-related targets.

03 · the framework

One offering, three implementation fields.

Organizational Implementation

Change that the organization actually adopts, not a reorg on paper.

  • Processes, roles and responsibilities
  • Ways of working and operational flows
  • Internal collaboration across functions
  • Change management and adoption

Digitalization, AI & Software

Tailored software, AI workflows and automation, fit to your situation, not off the shelf.

  • Custom software development
  • AI applications and automation
  • Data platforms and interfaces
  • Digital workflows, internal tools, system integration

Evaluation, Hardware & Optimization

What to optimize, what to buy, what to build, and which partners to bring in.

  • Evaluation of existing processes
  • Process optimization
  • Hardware selection and evaluation
  • Make-or-buy decisions, partner integration

04 · use cases

What a 4-week PoC could target.

Automated compound handling

A platform for powder weighing and liquid handling, built for throughput.

We own the system specifications and the functional-design phase, architect the high-throughput solution, and reconcile business and technical requirements with stakeholders, designed for global rollout with safety and priority handling built in.

What good looks like

  • Higher daily processing capacity
  • Standardized order processing across the department globally
  • Safer handling, reduced operator exposure

Process data model & ontology

A shared data model that survives tech transfer between sites.

We define a focused data model and an agreed ontology, an end-to-end view of what data exists and how it should be structured to be FAIR, consistent and reusable across development and tech transfer.

What good looks like

  • Aligned definitions across sites
  • Reduced redundancy and rework
  • A future-proof, AI-ready data blueprint

Throughput & variability automation

Automate repetitive steps to lift capacity and cut variability.

We identify the highest-leverage manual steps and automate them, standardizing process execution so throughput rises and batch-to-batch variability falls.

What good looks like

  • More daily capacity from the same team
  • Standardized, repeatable execution
  • Lower variability batch to batch

Equipment make-or-buy evaluation

Decide which development tooling to buy, build or skip.

Vendor-agnostic assessment and selection based on pre-defined criteria, with a costed recommendation and an integration path for the right partners.

What good looks like

  • A defensible buy / build / skip decision
  • Costed options and an integration plan
  • Right-sized partner selection

Scale-up data pipeline

Surface scale-up surprises early, not in Phase III.

We instrument pilot-batch and process data so deviations and scale-up risks become visible early, with a clear data flow from bench to pilot.

What good looks like

  • Earlier detection of scale-up risk
  • A connected bench-to-pilot data view
  • Fewer late, costly surprises

05 · proof

Work, re-framed for this phase.

Automated Compound Hub · Swiss biopharma client

Process standardization and throughput at scale, a fully automated compound hub that took daily capacity 5×. The same discipline that de-risks a scale-up.

Background
Growing global volume of compound orders for powder-solution production with varying priorities. The compound-management team was strained on productivity, sample tracking and prioritisation.
Solution
Personalized Solutions workshop to optimise workflows, then a fully automated platform for powder weighing and liquid handling, designed for global rollout, with throughput, safety and priority handling built in.
Results · 12 mo. after engagement
Daily processing capacity up by more than 500%. Lab processes automated and optimised. Global standardisation of order processing across the department.
inite's role
inite provided a Scientific Business Analyst and Solution Architect. Owned system specifications and the functional-design phase. Architected the high-throughput solution. Negotiated with stakeholders to reconcile business and technical requirements.

“Inite contributed significantly to the success of our projects with excellent and well-founded analyses. Their structure and committed way of working was greatly appreciated by the team.”

Compound Management Director · Global Pharma Company

Digital Biorepository · Swiss pharma client

A standardized, FAIR-ready data model across sites, the structural backbone validated development depends on.

Background
Cross-site collaboration on bio-sample management, biosamples (cells, proteins, plasmids, antibodies) distributed across multiple locations with no clear structure. Tracing, accessing and collecting the right samples was slow; scientific productivity was capped.
Solution
A global virtual + physical solution to handle, search and retrieve biosamples. Secure cross-site sharing, AI-contextualised digital + physical storage, and an integrated request → register → store workflow.
Results · 12 mo. after engagement
Remote and centralised access to bio samples. Faster data access. Lower experiment time and cost. ~35% efficiency improvement.
inite's role
inite concepted, designed and managed the full DBR implementation across life-science, IT and business domains. Delivered a standardised Bio-Sample Data Model aligned with FAIR principles. Aligned multiple sites and functions on a single workflow.

“Inite positively influenced a change of mindset and supported us to approach the task with fresh thinking. Their approach allowed the team to imagine solutions in an unlimited way rather than being held back by constraints and obstacles.”

Global Process Owner, Biosample Management · Global Pharma Company

06 · why inite

What every client comes to us for, whatever their field.

  1. AI that delivers on your goals.

    No slide decks, no chatbots. Working tools in your team’s hands, not another strategy workshop.

  2. Buy, build, or skip.

    Straight advice on what is worth building, buying, or leaving, carried from pilot through to production.

  3. Startup speed. Corporate delivery.

    Startup pace with the rigour your regulated world needs. Tailored rollout, at a speed that fits you.

Turn promising research into scalable, validated development processes.

Book a call

Pick the conversation that fits where you are. Both are free 30-minute calls. No deck, no pitch.