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Biotech Software: To Build or Not to Build, That is the Question…

Explore the evolution of biotech software trends and uncover the advantages of subscribing to biotech SaaS platforms.

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Zareh Zurabyan
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Table of Contents

In-House Buildouts vs. Using Readily-Available Software and the Path towards Digital Sustainability

When considering whether to develop in-house software or purchase an off-the-shelf solution for your biotech applications (including lab operations, data analysis, or protein platform analysis), it is important to look at the history of the trends. 

A Brief History of Software as a Service (SaaS) in the Life Sciences

Early Development (Pre-Internet Era - Before the 1990s): Before the widespread adoption of the Internet in the 1990s, life science and pharma labs predominantly developed their own in-house software solutions to meet specific research needs. Custom-built software was standard, tailored to the unique requirements of each lab. Development timelines were lengthy, and costs were high due to the need for specialized expertise and infrastructure.

Proliferation of Commercial Software (1990s - 2000s): With advancements in computing technology and the availability of commercial software, many life science and pharma labs began adopting commercial off-the-shelf (COTS) software solutions in the 1990s and 2000s. These solutions offered standardized features, functionalities, and workflows, reducing the need for extensive in-house development efforts and providing cost-effective alternatives to custom-built software.

Emergence of SaaS Models (Early 21st Century—2000s): The early 21st century saw the rise of Software as a Service (SaaS) models, coinciding with the growth of the Internet and cloud computing. Labs started transitioning from on-premises software to cloud-based SaaS solutions in the 2000s to streamline research workflows, reduce IT overhead, and access specialized features and expertise. SaaS offerings provide advantages such as rapid deployment, scalability, and subscription-based pricing models.

Adoption of Biotech SaaS Solutions (Recent Years - 2010s onwards): In recent years, there has been a growing trend towards adopting specialized biotech SaaS solutions tailored to the unique needs of the life science and pharma industries. Labs increasingly recognize the benefits of leveraging ready-to-use biotech SaaS solutions, such as cost savings, rapid deployment, continuous updates, and compatibility with existing systems. This trend has accelerated since the 2010s, with widespread adoption across the industry.

5 Benefits of Subscribing to SaaS Rather Than Building In-House Software

1. Cost and Time Savings: Off-the-shelf biotech SaaS solutions eliminate the need for extensive development efforts and associated costs, such as hiring specialized developers, infrastructure setup, and ongoing maintenance. By leveraging pre-built solutions, organizations can significantly reduce upfront investment and time-to-market, allowing them to allocate resources more efficiently and focus on core research activities.

2. Access to Specialised Expertise and Features: Off-the-shelf biotech SaaS platforms are often developed by specialized vendors with domain expertise in life sciences and biotechnology. These solutions typically offer advanced features, functionalities, and workflows tailored to specific research needs, providing access to state-of-the-art technologies and methodologies that may be challenging to replicate in-house. By utilizing specialized expertise, organizations can benefit from best practices, industry standards, and cutting-edge innovations without requiring extensive internal development efforts.

3. Rapid Deployment and Scalability: Off-the-shelf biotech SaaS solutions are designed for rapid deployment and scalability, allowing organizations to rapidly implement and scale their research workflows as needed. These platforms typically offer cloud-based infrastructure, automated provisioning, and flexible pricing models, enabling seamless scalability to accommodate growing data volumes, research projects, and user requirements. By leveraging SaaS solutions, organizations can respond more effectively to changing research needs and market demands, ensuring agility and competitiveness in the dynamic biotech landscape.

4. Continuous Updates and Maintenance: Off-the-shelf biotech SaaS solutions are continuously updated and maintained by the vendor, ensuring access to the latest features, security patches, and performance optimizations. By outsourcing software maintenance and updates to the vendor, organizations can minimize the burden on internal IT teams and avoid disruptions to research workflows caused by outdated or unsupported software versions. Continuous updates also enable organizations to stay ahead of regulatory requirements, industry trends, and emerging technologies, ensuring the long-term relevance and sustainability of their research infrastructure.

5. Compatibility and Integration: Off-the-shelf biotech SaaS solutions are designed to be compatible with existing research tools, laboratory equipment, and data management systems, facilitating seamless integration and interoperability. These platforms often offer standardized data formats, APIs, and integration capabilities, enabling organizations to consolidate and streamline their research workflows across multiple applications and platforms. By leveraging compatible SaaS solutions, organizations can maximize the value of their existing investments, improve data accessibility and collaboration, and enhance overall research productivity and efficiency.

New Trend: White Label Software in Big Pharma

The trend of big pharma purchasing white-label software and using it internally reflects a strategic shift towards maintaining control over proprietary data and processes while leveraging external technology solutions. Rather than relying on third-party vendors for software development and data management, big pharma companies customize and deploy white-label software solutions internally, enabling them to safeguard sensitive data, streamline operations, and maintain a competitive edge. 

White Label Software Examples

Customized Laboratory Information Management Systems (LIMS): Big pharma companies may purchase white-label LIMS software and tailor it to their specific laboratory workflows and data management needs. By deploying customized LIMS internally, they can securely manage and track experimental data, samples, and workflows without relying on external vendors.

In-House Clinical Trial Management Platforms: Rather than outsourcing clinical trial management to third-party vendors, big pharma companies are investing in white label clinical trial management platforms that can be customised to meet their unique requirements. This allows them to control trial data, patient records, and regulatory compliance while streamlining the clinical trial process.

Proprietary Data Analytics Platforms: Big pharma companies often require advanced data analytics capabilities to analyze large-scale biological datasets, identify potential drug targets, and optimize research strategies. By purchasing white-label data analytics platforms and customizing them internally, they can leverage powerful analytics tools while protecting proprietary data and intellectual property.

Internal Collaboration and Communication Tools: To facilitate collaboration and communication among research teams, big pharma companies may adopt white-label collaboration platforms, project management tools, and communication software. These internal solutions enable secure collaboration, document sharing, and real-time communication while ensuring data privacy and confidentiality.

Regulatory Compliance and Quality Management Systems: Big pharma companies must adhere to stringent regulatory requirements and quality standards throughout drug development. By internally deploying white-label regulatory compliance and quality management systems, they can ensure compliance with regulatory guidelines, track quality metrics, and manage audit trails without exposing sensitive data to third-party vendors.

The trend of big pharma purchasing white-label software and using it internally underscores the importance of data privacy, security, and control in the highly regulated pharmaceutical industry. By customizing and deploying internal software solutions, big pharma companies can harness the benefits of external technology while safeguarding proprietary data and maintaining compliance with regulatory standards.

Digital Sustainability's 3 Main Pillars: Expand, Integrate, and Support!

To ensure sustainability (that is, maintaining optimal performance in the long term) when implementing digital tools, particularly when purchasing SaaS solutions, biotech companies should focus on the following:

Scalability: Choose SaaS solutions that offer scalability to accommodate the company's growth and evolving needs. Prioritise platforms that can seamlessly scale resources, such as storage, computing power, and user licenses, as the company expands its operations, increases data volumes, or introduces new products and services. Regularly assess scalability requirements and adjust subscription plans or configurations to support ongoing growth and innovation.

Integration and Customisation: Select SaaS solutions that offer robust integration capabilities and customization options to align with the company's existing systems, workflows, and unique requirements. Ensure that the chosen platforms support open APIs, data interoperability standards, and flexible configuration settings, allowing seamless integration with internal databases, laboratory equipment, and third-party applications. Collaborate closely with the SaaS vendor to tailor the solution to the company's specific needs, workflows, and business objectives, leveraging customization features, workflow automation tools, and professional services as needed.

Maintenance and Support: Prioritize SaaS solutions that provide reliable maintenance, support, and updates to ensure ongoing performance, security, and compliance. Choose vendors with a proven track record of delivering timely software updates, patches, and enhancements, as well as responsive customer support services and technical assistance. Establish clear service-level agreements (SLAs) and communication channels with the vendor to address any issues, resolve technical challenges, and provide training and support to end-users. Regularly review and optimize software configurations, monitor performance metrics, and conduct user feedback sessions to identify improvement areas and ensure the digital tools' long-term sustainability.

By implementing these strategies, a biotech company can scale up its operations, integrate and customize digital tools to meet its specific needs and ensure ongoing maintenance and support for sustainable digital transformation. This approach enables the company to leverage the benefits of SaaS solutions while maximizing efficiency, innovation, and competitiveness in the rapidly evolving biotech industry.

The Big But! 

If your company has a unique workflow or requires a platform or solution that cannot be fulfilled by off-the-shelf SaaS options and decides to build software in-house, integrating it with existing SaaS workflows presents a unique challenge. However, there are several steps the company can take to ensure successful integration:

1. Identify Integration Points: Analyse the in-house software's functionality and determine where it intersects with existing SaaS workflows. Identify integration points where data exchange or interaction between the in-house software and SaaS platforms is necessary.

2. Standardize Data Formats and Protocols: Establish standardized data formats, protocols, and APIs for data exchange between the in-house software and SaaS platforms. Ensure compatibility with common data standards and industry-specific formats to facilitate seamless integration and interoperability.

3. Implement Middleware or Integration Tools: Use middleware or integration tools to facilitate communication and data exchange between in-house software and SaaS platforms. Implement APIs, web services, or middleware solutions that can translate data between different systems, synchronize data in real time, and orchestrate workflows across multiple platforms.

4. Customize SaaS Platforms: Work with SaaS vendors to customize their platforms or APIs to accommodate the unique requirements of the in-house software. Collaborate closely with vendors to develop custom integrations, plugins, or extensions that enable seamless interoperability with the in-house solution while leveraging the scalability, reliability, and features of the SaaS platforms.

5. Develop Custom Connectors or Plugins: Build custom connectors, plugins, or adapters to facilitate integration between the in-house software and SaaS platforms. Develop custom scripts, APIs, or middleware components that bridge the gap between different systems, allowing data to flow bi-directionally and workflows to be synchronized effectively.

6. Implement Data Governance and Security Measures: Establish data governance policies, access controls, and security measures to protect sensitive information and ensure compliance with regulatory requirements. Implement encryption, authentication, and authorization mechanisms to secure data transmission and access between the in-house software and SaaS platforms.

7). Test and Validate Integration: Conduct thorough testing and validation of the integration between the in-house software and SaaS platforms to ensure reliability, accuracy, and performance. Test data exchange workflows, error handling mechanisms, and system interactions under various scenarios to identify and address any issues or discrepancies.

8. Provide Training and Support: Offer training and support to end-users to familiarise them with the integrated workflows and software interfaces. Provide documentation, tutorials, and user guides to help users navigate the integrated environment effectively and maximize productivity.

Conclusion

By following these steps, life science companies can effectively integrate their in-house software with existing SaaS workflows, enabling seamless data exchange, collaboration, and workflow orchestration across the organization. This approach allows the company to leverage the benefits of in-house and SaaS solutions while optimizing efficiency, innovation, and competitiveness in its operations.

However, if you're beginning your digital journey, there are many benefits to choosing a SaaS over building an in-house platform. 

In-House Buildouts vs. Using Readily-Available Software and the Path towards Digital Sustainability

When considering whether to develop in-house software or purchase an off-the-shelf solution for your biotech applications (including lab operations, data analysis, or protein platform analysis), it is important to look at the history of the trends. 

A Brief History of Software as a Service (SaaS) in the Life Sciences

Early Development (Pre-Internet Era - Before the 1990s): Before the widespread adoption of the Internet in the 1990s, life science and pharma labs predominantly developed their own in-house software solutions to meet specific research needs. Custom-built software was standard, tailored to the unique requirements of each lab. Development timelines were lengthy, and costs were high due to the need for specialized expertise and infrastructure.

Proliferation of Commercial Software (1990s - 2000s): With advancements in computing technology and the availability of commercial software, many life science and pharma labs began adopting commercial off-the-shelf (COTS) software solutions in the 1990s and 2000s. These solutions offered standardized features, functionalities, and workflows, reducing the need for extensive in-house development efforts and providing cost-effective alternatives to custom-built software.

Emergence of SaaS Models (Early 21st Century—2000s): The early 21st century saw the rise of Software as a Service (SaaS) models, coinciding with the growth of the Internet and cloud computing. Labs started transitioning from on-premises software to cloud-based SaaS solutions in the 2000s to streamline research workflows, reduce IT overhead, and access specialized features and expertise. SaaS offerings provide advantages such as rapid deployment, scalability, and subscription-based pricing models.

Adoption of Biotech SaaS Solutions (Recent Years - 2010s onwards): In recent years, there has been a growing trend towards adopting specialized biotech SaaS solutions tailored to the unique needs of the life science and pharma industries. Labs increasingly recognize the benefits of leveraging ready-to-use biotech SaaS solutions, such as cost savings, rapid deployment, continuous updates, and compatibility with existing systems. This trend has accelerated since the 2010s, with widespread adoption across the industry.

5 Benefits of Subscribing to SaaS Rather Than Building In-House Software

1. Cost and Time Savings: Off-the-shelf biotech SaaS solutions eliminate the need for extensive development efforts and associated costs, such as hiring specialized developers, infrastructure setup, and ongoing maintenance. By leveraging pre-built solutions, organizations can significantly reduce upfront investment and time-to-market, allowing them to allocate resources more efficiently and focus on core research activities.

2. Access to Specialised Expertise and Features: Off-the-shelf biotech SaaS platforms are often developed by specialized vendors with domain expertise in life sciences and biotechnology. These solutions typically offer advanced features, functionalities, and workflows tailored to specific research needs, providing access to state-of-the-art technologies and methodologies that may be challenging to replicate in-house. By utilizing specialized expertise, organizations can benefit from best practices, industry standards, and cutting-edge innovations without requiring extensive internal development efforts.

3. Rapid Deployment and Scalability: Off-the-shelf biotech SaaS solutions are designed for rapid deployment and scalability, allowing organizations to rapidly implement and scale their research workflows as needed. These platforms typically offer cloud-based infrastructure, automated provisioning, and flexible pricing models, enabling seamless scalability to accommodate growing data volumes, research projects, and user requirements. By leveraging SaaS solutions, organizations can respond more effectively to changing research needs and market demands, ensuring agility and competitiveness in the dynamic biotech landscape.

4. Continuous Updates and Maintenance: Off-the-shelf biotech SaaS solutions are continuously updated and maintained by the vendor, ensuring access to the latest features, security patches, and performance optimizations. By outsourcing software maintenance and updates to the vendor, organizations can minimize the burden on internal IT teams and avoid disruptions to research workflows caused by outdated or unsupported software versions. Continuous updates also enable organizations to stay ahead of regulatory requirements, industry trends, and emerging technologies, ensuring the long-term relevance and sustainability of their research infrastructure.

5. Compatibility and Integration: Off-the-shelf biotech SaaS solutions are designed to be compatible with existing research tools, laboratory equipment, and data management systems, facilitating seamless integration and interoperability. These platforms often offer standardized data formats, APIs, and integration capabilities, enabling organizations to consolidate and streamline their research workflows across multiple applications and platforms. By leveraging compatible SaaS solutions, organizations can maximize the value of their existing investments, improve data accessibility and collaboration, and enhance overall research productivity and efficiency.

New Trend: White Label Software in Big Pharma

The trend of big pharma purchasing white-label software and using it internally reflects a strategic shift towards maintaining control over proprietary data and processes while leveraging external technology solutions. Rather than relying on third-party vendors for software development and data management, big pharma companies customize and deploy white-label software solutions internally, enabling them to safeguard sensitive data, streamline operations, and maintain a competitive edge. 

White Label Software Examples

Customized Laboratory Information Management Systems (LIMS): Big pharma companies may purchase white-label LIMS software and tailor it to their specific laboratory workflows and data management needs. By deploying customized LIMS internally, they can securely manage and track experimental data, samples, and workflows without relying on external vendors.

In-House Clinical Trial Management Platforms: Rather than outsourcing clinical trial management to third-party vendors, big pharma companies are investing in white label clinical trial management platforms that can be customised to meet their unique requirements. This allows them to control trial data, patient records, and regulatory compliance while streamlining the clinical trial process.

Proprietary Data Analytics Platforms: Big pharma companies often require advanced data analytics capabilities to analyze large-scale biological datasets, identify potential drug targets, and optimize research strategies. By purchasing white-label data analytics platforms and customizing them internally, they can leverage powerful analytics tools while protecting proprietary data and intellectual property.

Internal Collaboration and Communication Tools: To facilitate collaboration and communication among research teams, big pharma companies may adopt white-label collaboration platforms, project management tools, and communication software. These internal solutions enable secure collaboration, document sharing, and real-time communication while ensuring data privacy and confidentiality.

Regulatory Compliance and Quality Management Systems: Big pharma companies must adhere to stringent regulatory requirements and quality standards throughout drug development. By internally deploying white-label regulatory compliance and quality management systems, they can ensure compliance with regulatory guidelines, track quality metrics, and manage audit trails without exposing sensitive data to third-party vendors.

The trend of big pharma purchasing white-label software and using it internally underscores the importance of data privacy, security, and control in the highly regulated pharmaceutical industry. By customizing and deploying internal software solutions, big pharma companies can harness the benefits of external technology while safeguarding proprietary data and maintaining compliance with regulatory standards.

Digital Sustainability's 3 Main Pillars: Expand, Integrate, and Support!

To ensure sustainability (that is, maintaining optimal performance in the long term) when implementing digital tools, particularly when purchasing SaaS solutions, biotech companies should focus on the following:

Scalability: Choose SaaS solutions that offer scalability to accommodate the company's growth and evolving needs. Prioritise platforms that can seamlessly scale resources, such as storage, computing power, and user licenses, as the company expands its operations, increases data volumes, or introduces new products and services. Regularly assess scalability requirements and adjust subscription plans or configurations to support ongoing growth and innovation.

Integration and Customisation: Select SaaS solutions that offer robust integration capabilities and customization options to align with the company's existing systems, workflows, and unique requirements. Ensure that the chosen platforms support open APIs, data interoperability standards, and flexible configuration settings, allowing seamless integration with internal databases, laboratory equipment, and third-party applications. Collaborate closely with the SaaS vendor to tailor the solution to the company's specific needs, workflows, and business objectives, leveraging customization features, workflow automation tools, and professional services as needed.

Maintenance and Support: Prioritize SaaS solutions that provide reliable maintenance, support, and updates to ensure ongoing performance, security, and compliance. Choose vendors with a proven track record of delivering timely software updates, patches, and enhancements, as well as responsive customer support services and technical assistance. Establish clear service-level agreements (SLAs) and communication channels with the vendor to address any issues, resolve technical challenges, and provide training and support to end-users. Regularly review and optimize software configurations, monitor performance metrics, and conduct user feedback sessions to identify improvement areas and ensure the digital tools' long-term sustainability.

By implementing these strategies, a biotech company can scale up its operations, integrate and customize digital tools to meet its specific needs and ensure ongoing maintenance and support for sustainable digital transformation. This approach enables the company to leverage the benefits of SaaS solutions while maximizing efficiency, innovation, and competitiveness in the rapidly evolving biotech industry.

The Big But! 

If your company has a unique workflow or requires a platform or solution that cannot be fulfilled by off-the-shelf SaaS options and decides to build software in-house, integrating it with existing SaaS workflows presents a unique challenge. However, there are several steps the company can take to ensure successful integration:

1. Identify Integration Points: Analyse the in-house software's functionality and determine where it intersects with existing SaaS workflows. Identify integration points where data exchange or interaction between the in-house software and SaaS platforms is necessary.

2. Standardize Data Formats and Protocols: Establish standardized data formats, protocols, and APIs for data exchange between the in-house software and SaaS platforms. Ensure compatibility with common data standards and industry-specific formats to facilitate seamless integration and interoperability.

3. Implement Middleware or Integration Tools: Use middleware or integration tools to facilitate communication and data exchange between in-house software and SaaS platforms. Implement APIs, web services, or middleware solutions that can translate data between different systems, synchronize data in real time, and orchestrate workflows across multiple platforms.

4. Customize SaaS Platforms: Work with SaaS vendors to customize their platforms or APIs to accommodate the unique requirements of the in-house software. Collaborate closely with vendors to develop custom integrations, plugins, or extensions that enable seamless interoperability with the in-house solution while leveraging the scalability, reliability, and features of the SaaS platforms.

5. Develop Custom Connectors or Plugins: Build custom connectors, plugins, or adapters to facilitate integration between the in-house software and SaaS platforms. Develop custom scripts, APIs, or middleware components that bridge the gap between different systems, allowing data to flow bi-directionally and workflows to be synchronized effectively.

6. Implement Data Governance and Security Measures: Establish data governance policies, access controls, and security measures to protect sensitive information and ensure compliance with regulatory requirements. Implement encryption, authentication, and authorization mechanisms to secure data transmission and access between the in-house software and SaaS platforms.

7). Test and Validate Integration: Conduct thorough testing and validation of the integration between the in-house software and SaaS platforms to ensure reliability, accuracy, and performance. Test data exchange workflows, error handling mechanisms, and system interactions under various scenarios to identify and address any issues or discrepancies.

8. Provide Training and Support: Offer training and support to end-users to familiarise them with the integrated workflows and software interfaces. Provide documentation, tutorials, and user guides to help users navigate the integrated environment effectively and maximize productivity.

Conclusion

By following these steps, life science companies can effectively integrate their in-house software with existing SaaS workflows, enabling seamless data exchange, collaboration, and workflow orchestration across the organization. This approach allows the company to leverage the benefits of in-house and SaaS solutions while optimizing efficiency, innovation, and competitiveness in its operations.

However, if you're beginning your digital journey, there are many benefits to choosing a SaaS over building an in-house platform. 

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