Biopharma data lives in ERP, LIMS, MES, QMS, Veeva and a dozen vendor feeds, and each system is right about its own piece. Multishoring connects and governs that data so launch, deal and leadership decisions run on numbers people trust. We deliver on IBM Cloud Paks, alongside your Quality and CSV team, without disrupting validated systems.
We Integrate Around the Systems You Already Trust
Systems we connect
When data work becomes urgent
Our Life Sciences Data & Integration Services
Each service starts with one business outcome and one data flow, and scales once that flow runs in production. IBM Cloud Paks provide the platform. Your domain systems stay where they are.
Where Biopharma Data Breaks
These four situations usually start the conversation.
Launch Data That Arrives Late
Vendor feeds, CRM and specialty pharmacy data land on different schedules and definitions. Brand teams see the launch curve weeks after they could have reacted.
Two Companies, One Board Report
After an acquisition, combined revenue, inventory and pipeline reporting still depends on spreadsheets from both sides.
Interfaces Nobody Wants to Touch
Lab, plant and quality systems are linked point to point. Every upgrade risks a break and another round of testing.
Data You Cannot Trace
Reports and AI pilots use data whose origin, transformations and owners nobody can show when Quality or an auditor asks.
IBM Cloud Pak & Data Technologies We Implement for Life Sciences
IBM Cloud Paks are our core toolset for regulated integration, data governance and workflow. We connect them to the domain systems and data platforms you already run.
What a Governed Data Layer Changes
Launch decisions on current data
Feeds arrive with quality checks and agreed latency, so brand, sales and market access teams act on this week’s numbers.
Combined reporting from Day 1
Leadership sees both companies in one view while systems are consolidated at a safe pace.
Fewer interfaces to revalidate
Reusable integration patterns mean a system upgrade changes one connection, not twenty.
Evidence your Quality team can use
Your Quality team owns validation strategy and approval. We deliver the specifications, traceability, test evidence, lineage and audit trails they need to decide.
“When it comes to our internal IT needs, we put emphasis on reliability and competence. That’s why we collaborate with Multishoring.”
Other services
Integration Services
We plan, build and stabilize integrations between ERP, lab, plant, quality and commercial systems, starting with the flows that matter most.
Integration Maintenance
Monitoring, support and controlled change for the integrations your operations and Quality team rely on.
IBM Cloud Pak for Data
Govern, catalog and trace enterprise data so reporting and approved AI use cases start from trusted inputs.
Thank you for your interest in Multishoring.
We’d like to ask you a few questions to better understand your IT needs.
Signed, sealed, delivered!
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Life Sciences Data Integration: Questions Biopharma Teams Ask
If you don’t find the answer you’re looking for, book a 30-minute diagnostic call. No preparation needed.
What is life sciences data integration?
Life sciences data integration connects data from systems such as ERP, LIMS, MES, QMS, CRM and external vendor feeds into governed flows and a shared data layer. The goal is consistent, traceable data for reporting, operations and AI, while each specialist system stays the record for its own domain.
Which systems do you typically connect in a biopharma company?
Most often ERP (for example SAP S/4HANA), LIMS and ELN, MES and batch records, QMS, Veeva CRM and Vault, commercial data feeds such as IQVIA, 867 and specialty pharmacy data, and the data warehouse or lakehouse. Clinical systems such as CTMS or EDC are in scope when a defined use case requires them.
Can you integrate with GxP-validated systems without forcing a full revalidation?
Often the impact can be kept small, for example by reading data through approved interfaces and keeping new logic in a separate integration or data layer. Whether a change needs revalidation, and to what extent, is decided by your Quality team through a risk-based assessment. We design to minimize changes to validated systems and document every interface they need to review.
Who is responsible for computer system validation in a data integration project?
Your organization stays responsible for compliance, and your Quality and CSV team owns the validation strategy and approval. We deliver the supplier side: requirements and design specifications, traceability, test evidence, lineage, audit trails and controlled change records your team can review and reuse.
What are the FDA expectations for data integrity in integrations and reports?
The FDA expects data to be complete, consistent and accurate, often summarized as the ALCOA+ principles, and electronic records within scope of 21 CFR Part 11 need controls such as audit trails and access restrictions. Whether a specific pipeline or report falls in scope depends on its intended use. See the FDA guidance on data integrity and compliance with drug CGMP.
What is GxP data, and does all of our data need to be treated as GxP?
GxP data is data that supports regulated good practice activities, such as manufacturing, laboratory, clinical or quality records. Not all enterprise data is GxP. Commercial, finance and corporate reporting data usually is not, which is why we classify each data flow by intended use and apply GxP controls where they are required.
What data needs to be ready before a product launch?
Typically HCP and HCO master data, CRM data, specialty pharmacy and distribution (867) data, syndicated data feeds, market access data and agreed KPI definitions. Each feed needs an owner, a quality check and a latency target, so launch dashboards are trusted from the first week of sales.
How do you integrate data after a biotech acquisition?
We start with an inventory of both companies’ applications and data, then decide what to integrate, migrate or archive. An integration layer delivers combined reporting first, master data is merged with clear ownership, and system consolidation and the TSA exit follow in planned waves that protect validated records and continuity.
Why IBM Cloud Pak, and can it work with Snowflake, Databricks or Power BI?
IBM Cloud Paks combine integration, data governance and workflow on Red Hat OpenShift, which suits hybrid estates where some systems must stay on premises. They work alongside Snowflake, Databricks, Microsoft Fabric and Power BI. We integrate with the platforms you already run rather than replace them.
How long does a life sciences data integration project take?
It depends on the number of systems, the regulatory scope and the data quality we find. We avoid long discovery phases: the first goal is one production data flow with monitoring and documentation, and we give a timeline for the wider program only after assessing your environment.
How do we start working with Multishoring?
Book a 30-minute diagnostic call and tell us which launch, deal, system change or report is under the most pressure. No preparation is needed. If there is a fit, we propose a fixed-scope assessment of the systems and data flows involved before any larger commitment.