In 2015, the debate between Single Vendor and Best of Breed approaches for Integrated Informatics Solutions (IIS) was a hot topic. Organizations had actively embraced laboratory informatics to increase laboratory efficiency and effectiveness, information availability across the enterprise, innovation and discovery, and collaboration amongst scientists and partners. Although laboratory informatics solutions enabled greater efficiency and insights, getting to the next level required implementing a fully integrated informatics solution. Organizations recognized the benefits of connecting their laboratory information systems (LIMS, ELN, SDMS, etc.), instrument systems (CDS, MS, balances, etc.), reporting and analytics tools, and business systems to achieve seamless data flow, faster data access, increased collaboration, informed decision-making, improved data integrity, and operational efficiency.

Ten years ago, fully integrated informatics solutions could be implemented by following two distinct approaches: Single Vendor or Best of Breed. The single vendor/platform approach entailed implementing a solution and architecture that came with all the informatics systems already integrated. The multivendor/best of breed approach required integrating independent informatics solutions. Integration with additional systems was supported in either approach, although with more vendors, integrations became more complex.

Fast forward to 2025, and the laboratory informatics landscape has evolved in unexpected ways. Advanced technologies, cloud computing, artificial intelligence (AI), and modular architecture choices have transformed how organizations approach integration. Today, the decision is no longer just about Single Vendor vs. Best of Breed - it's about leveraging a spectrum of new options and strategies to meet the unique needs of your organization.

Revisiting Single Vendor vs. Best of Breed in 2025

While the Single Vendor and Best of Breed approaches are still relevant, they must now accommodate the new realities of laboratory informatics. The revised lists of advantages and disadvantages for each can help inform your choices when considering the expanded range of options.

Single Vendor Approach

Advantages:

• Simplified integration and maintenance, as all components are designed to work together out of the box.
• Single point of contact for support and updates.
• Reduced IT and support costs.
• Often includes built-in AI and analytics capabilities.
• Accelerated learning curve.
• Cloud-native options provide scalability and flexibility.
• Reduced validation efforts.
• Faster rollout and deployment.

Disadvantages:

• Requirements definition and prioritization are necessary and can take time.
• Limited flexibility to incorporate specialized tools from other vendors.
• Potential vendor lock-in, especially with proprietary platforms.
• May not always offer the most advanced features for specific use cases.

Best of Breed Approach

Advantages:

• Ability to select the best tools for each specific task.
• Greater flexibility to adapt to changing needs and technologies.
• Modular architecture choices and APIs make integration easier than ever.
• Can leverage cutting-edge innovations from niche vendors.
• Flexible rollout and deployment.

Disadvantages:

• Added complexity when managing multiple vendors.
• Requirements definition and prioritization are necessary and can take time.
• Requires more effort to manage the integrations and ensure compatibility.
• Potential for higher upfront and ongoing IT, infrastructure, and support costs.
• May need to rely on third-party integration tools or consultants.
• More complex validation processes.

The Evolution of Integrated Informatics

Today, the goal of achieving an integrated informatics system remains the same: to create a unified ecosystem where data flows effortlessly through and across systems, enabling better decision-making, innovation, and collaboration. However, the choices of tools and approaches available to achieve this goal have expanded substantially. Some key advancements shaping the future of integrated informatics include:

Cloud-Native Platform-as-a-Service (PaaS)

Cloud computing has irrevocably changed laboratory informatics. Cloud-native platforms offer unparalleled scalability, flexibility, and accessibility. These platforms often have built-in integration options for popular laboratory and business systems, reducing the need for custom development. Whether you choose a single-vendor or multi-vendor approach, cloud-native systems enable real-time data sharing and collaboration for global teams. PaaS solutions provide a flexible foundation for building and integrating custom applications and reduce the time and effort required for integration.

Open-Source Solutions

Open-source laboratory informatics tools have matured and now are seen as viable alternatives to proprietary systems. These solutions can be customized to meet specific needs and integrated with other systems using open standards. Vendors now prioritize open APIs, making integrations among LIMS, ELN, SDMS, and other systems more seamless and further reducing reliance on custom-built interfaces.

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Modular and Microservices Architectures

New types of architectures have made it easier to mix and match systems from different vendors. Instead of being locked into a single vendor's ecosystem, organizations can now select solutions for specific tasks and integrate them seamlessly using APIs and middleware. This approach combines the strengths of both the Single Vendor and Best of Breed models, offering flexibility without sacrificing integration.

Low-Code/No-Code Integration Tools

These options enable IT and lab professionals to build integrations with minimal coding knowledge, making interoperability more accessible and reducing deployment time.

AI-Powered Integration Suites

Artificial intelligence is playing an increasingly important role in laboratory informatics. AI-powered integration tools can automatically map data flows, transform data, identify inconsistencies, and optimize and synchronize processes. These tools reduce the burden on IT teams when managing a multi-vendor environment and ensure that data is accurate and current across all systems.

Interoperability Standards

The adoption of industry-wide interoperability standards, such as FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, the Allotrope Simple Model, and HL7 FHIR (Fast Healthcare Interoperability Resources), has made it easier to integrate instruments and systems from different vendors. These standards ensure that data can be shared and understood across platforms, regardless of the vendor.

Hybrid Approach

The strengths of both the Single Vendor and Best of Breed models can be combined in a core platform from a single vendor and augmented with specialized tools from other vendors. This approach offers a balance of simplicity and flexibility. Hybrid Integration Platforms have emerged as a powerful middleware solution for organizations that need to connect on-premises, cloud, and edge systems. HIPs provide a unified framework for integrating data, applications, instruments, and devices, making them ideal for complex environments.

Vendor Ecosystems and Marketplaces

Many vendors now offer ecosystems and marketplaces where third-party applications can be found that easily integrate with their systems. This allows organizations to extend core system functionality without extensive customization. For example, a LIMS vendor might offer integrations with specialized AI analytics tools or electronic lab notebooks (ELNs) through its marketplace.

Making the Right Choice for Your Organization

As in 2015, the key to selecting the right approach is to understand your organization's unique needs and requirements. However, in 2025, there are additional factors to consider:

• Data Governance and Security: Ensure that your chosen approach complies with data privacy regulations and provides robust security features.
• Scalability: Consider how well the solution will meet future needs, such as increased data volumes or new laboratory workflows. These changes frequently, especially with the rise of generative AI
• ‍User Experience: Evaluate the ease of use and accessibility of the solution for your scientists and lab technicians. Without user adoption, the new functionality is useless.‍
• Total Cost of Ownership (TCO): Look beyond upfront costs and consider ongoing expenses, such as maintenance, upgrades, and integration efforts.

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Conclusion

The world of integratedinformatics has come a long way since 2015. While the Single Vendor and Best ofBreed approaches are still useful, new technologies and strategies have expandedthe possibilities for integration. Whatever you choose, alignment with yourorganization's goals, resources, and culture is paramount.

To be clear, ourintention is not to decide which approach is best for you. Rather, our goal isto provide the pros and cons of each approach and help guide you to your owndecision. As with any informatics solution selection, it is critical for you tounderstand and fully document your business and laboratory needs andrequirements. There are many factors to consider, such as your ITinfrastructure, data architecture, resource availability, and organizational culture.

We know how complexintegrated informatics plans can be. Our informatics experts will partner withyou to develop a fair evaluation of your integration options.

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Have you implemented afully Integrated Informatics Solution in 2025? What approach did you take, andwhat were the results? Share your experiences and insights in the commentsbelow!

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