Future Proofing Your Lab to Match the Pace of Innovation

Posted on Lab Informatics. 30 September, 2019

The 21st century has seen a rapid increase in the pace of technological innovation in life sciences. For example, while the first mapping of the human genome in 2003 took 13 years and 3 billion dollars to accomplish, next-generation sequencing (NGS) technology now can complete the whole genome sequencing in hours for less than $1000, generating terabytes of data in just a single run.

With the digital age now in full swing, technological advancements are quickly changing the landscape for laboratories in the life science industry. Just a few examples include:

  • Improvements in wireless networks, laboratory equipment, sensor technologies, micro-electronics, informatics software and other areas have helped to spawn a digital revolution in connectivity in the modern laboratory.
  • Growing datasets from patients, caregivers, and other sources are creating massive repositories of data, providing enormous opportunities and real challenges for researchers using this data to identify and optimize potential new therapies.
  • In the last decade, cloud computing and software as a service (SaaS) products have experienced massive growth and adoption. According to a report from Grand View Research, cloud-based Laboratory Information Management Systems (LIMS) now make up the largest share of the LIMS market.
  • The rise of R&D externalization strategies and contract research organizations (CROs) in the pharmaceutical industry has resulted in widespread disbursement of data across multiple organizations, leading to a significant increase in laboratory dataflow complexity.
  • Advances in multi-attribute analytical techniques are advancing the ability to simultaneously detect, quantify, and monitor attributes in both research and development and quality control processes, significantly increasing the amount and value of data generated per experiment.

In response to these and other innovations, today’s regulators are raising the standards and scrutiny of informatics systems and demanding strong proven control of data integrity through the entire lifecycle of laboratory data.

Given the pace and form of change we have seen in the last few decades, it is quite reasonable to assume the landscape will continue to change at least as significantly through the next decade. One of the core challenges for life and data scientists in life science laboratories will be keeping up with this rapid change, especially as it extends beyond the capabilities of our current laboratory data management systems.

Forward-thinking organizations are working hard to stay ahead of technological advancements by developing strategies to future-proof their laboratories. Let’s explore some strategies for laboratories to help ensure your organization can capitalize on the rapid pace of 21st century innovation.

Considerations for Future-Proofing Your Laboratory

In the context of life science laboratories, “future-proofing” is the process of anticipating future changes in laboratory technologies and developing strategies to maximize the benefits and minimize any negative consequences from these changes. A few key recommendations include:

Create and Maintain a Laboratory Informatics Roadmap. A laboratory informatics roadmap is a plan for the evolution of the architectural aspects of systems that participate in the data lifecycle. The objective of the roadmap is to identify gaps between the organization’s business goals and the current laboratory informatics ecosystem and develop recommendations to fill those gaps. Given the ever-changing landscape of technological change, and the fact that the roadmap is targeted towards a future-state, it should not be overly prescriptive, but instead simply provide guideposts to direct technology investments. It also must be kept relatively up to date and aligned with the overall company strategy and technological landscape.

The document should include a comprehensive list of recommendations that are prioritized in terms of what must be done, should be done, and could be done, including transitional stages designed to bring business value forward, as opposed to waiting for payback until the vision is fully implemented.

Target an Integrated Laboratory Informatics Ecosystem. One critical consideration for future laboratory systems is to explicitly design for digital continuity and data integrity across the system boundaries. Integration requirements for laboratory informatics systems should span from laboratory devices and instruments through the enterprise-level systems that consume laboratory data. Ad-hoc and point to point integration approaches are not sufficiently scalable nor economically viable in an environment with the current rate of change.

Today’s technology vendors are supporting this movement towards an integrated laboratory environment by creating adaptable platforms that can host a marketplace of integrated solutions needed to drive science forward. These platforms feature interoperability to expand outwards and manage the advances in science and technology. Such a platform can bring together many disparate systems into an integrated solution that fosters digital continuity or a digital thread across the product lifecycle, provided that open integration is truly a fundamental characteristic of the platform.

Govern Your Data. Forward-thinking organizations are taking steps to harmonize and govern their data. Master data management governance is a critical component of any digital transformation: the systems must be able to share minimal but also complete common vocabulary in order to truly integrate. Making sure you are organizing data in a standardized fashion is critical to ensuring your data is fully searchable and can be exploited for collaboration and experiments in the future.

Implement Advanced Analytics. The rapid rise in the volume of data available to life science laboratories in the last decade has far outstripped the human brain’s ability to process and analyze it effectively. In order to efficiently extract useful information and insights from this abundance of information, the industry has been adopting big data approaches and applications, including artificial intelligence (AI) , machine learning (ML), and deep learning.

While machine learning and artificial intelligence are expected to make the discovery of new medicines quicker and cheaper, AI techniques are only be as good as the data they are given – clean, robust and large datasets are necessary for AI to generate effective conclusions. Companies that are considering AI and ML solutions must first ensure that their overall systems architecture is capable of providing the data needed.

Investigate the Internet of Things. Advancements in micro-electronics, sensor technologies, wireless networks, software technologies and many other areas have helped to tear down silo walls between operational technology and information technology (IT), allowing organizations to facilitate the integration of informatics software with smart, connected instruments. The building blocks of this approach can be used to allow researchers to remotely monitor instruments and run experiments, assure important samples are stored at proper temperatures, predict instrument failures, electronically capture instrument and analysis data, and drive productivity from any physical location.

Apply Cloud Computing. The security concerns that many life science laboratories initially had with cloud-based platforms and applications have for the most part been addressed. Cloud-enabled informatics software can provide many benefits: reduced costs and deployment time, demand elasticity, scalability, and the ability to interact easily and securely with multiple external partners. In addition, scientists using cloud-based applications can access data and analytics from any location or device at any time, and this effectively facilitates multidisciplinary and multisite collaborations. Given that the most innovative companies in the future will likely be the ones that develop the best collaborative frameworks, cloud-based computing is an important aspect of future-proofing your laboratory.

Make Data Integrity and Regulatory Compliance a Priority. As your day-to-day lab activities become grounded in advanced technologies, it will become more and more important to make sure that regulatory compliance and data integrity are maintained. Compliance starts with having a proper quality management system (QMS) and quality culture. Additionally, company management should be involved in both the development and implementation of a flexible, risk-based, company-wide data integrity strategy. Part of this data integrity strategy should involve working with an external consultant that has expertise in data integrity evaluations to audit your laboratory environment as needed.

Work with A Qualified Informatics Consultant. Maintaining an up-to-date awareness of emerging technologies, digital capabilities, and best practices is essential to future-proofing your life science laboratory. Additionally, growing IT maintenance costs and a high learning curve and complexity for end users are limiting factors in your laboratory’s ability to keep up with the pace of technological change. As such, it can be wise to enlist the support of a third-party informatics consultant with industry experience and expertise in laboratory informatics systems. Such a partner can offer extensive experience with current scientific developments and supply a wide range of relevant, up-to-date information that can benefit your laboratory.

Conclusion

Given the wealth of innovative technologies and digital solutions being developed to optimize drug discovery, development and manufacturing, it is more important than ever to take steps to future-proof your laboratory so that you can benefit from the coming changes. Future-proofing results in a laboratory that is adaptable and flexible and able to respond effectively to new opportunities, something that is critical to success in a notoriously competitive industry and ultimately results in more innovative and vital medicines reaching the market quickly.

To keep pace with new technology and future-proofing innovations within the pharmaceutical industry, consider partnering with a qualified laboratory informatics consultant with extensive experience in the industry. Astrix Technology Group has over 20 years’ experience helping life science companies implement and integrate cutting-edge informatics technology in the laboratory. Our experienced professionals bring together technical, strategic and content knowledge to provide effective solutions that help you turn data into knowledge, increase organizational efficiency, improve quality, facilitate regulatory compliance and future-proof your laboratory. If you have any questions about Astrix Technology Group service offerings, or would like have an initial consultation with someone to explore how to optimize your informatics strategy, don’t hesitate to contact us.

About Dale Curtis

Dale Curtis Dale Curtis Jr. is the President of Astrix Technology Group. For over 18 years, Mr. Curtis has built an impressive track record of leadership and success in delivering high quality technology and laboratory informatics solutions to scientific organizations involved in research, development, quality and manufacturing. He has a proven talent for helping these organizations deploy innovative solutions that provide a step change in business intelligence, turn data into knowledge, increase organizational and operational efficiency, improve quality and facilitate regulatory compliance.

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