Labratory automation, tablet computer at lab
Laboratory Informatics

Strategy & Guidance

Digital Strategies for Laboratories
Digitalization of scientific processes in laboratories is a hot topic. Many laboratories have embarked on their digital journey towards Lab of The Future (LoTF) and buzzwords such as Artificial Intelligence (AI), Machine Learning (ML), Advanced Analytics, Augmented Reality (AR), Mixed Reality (MR) and Internet of Things (IoT) are frequently used in articles, white papers and on conferences. But the reality is, that many pharmaceutical and biotech organizations have not yet established a digital strategy for reaching their vision of LoTF. Below are summarized some of the common drivers for initiating a digital strategy in order to improve efficiency in laboratories.

Increase innovation and reduce time-to-market
Scientific advances within R&D and drug discovery has led to innovative explorations within fields such as gene therapy, personalized medicine, bioinformatics, immunotherapy, drug delivery etc. Pharmaceutical and biotech companies are pressured on patent expirations and want to reduce time-to-market. There is a need to speed up the drug development process and discover new therapeutics.

Productivity and data democratization
Increasing productivity in laboratories is key to stay in business. The constant pursuit for improving key performance indicators such as turnaround time of tests are affecting laboratories. To improve business processes and work smarter, there is a need to democratize data by eliminating data siloes and making data available.

Connectivity and advanced analytics
Many organizations are looking into data standardization in order to harmonize scientific data flow across instruments and applications. The purpose of introducing data standards and communication standards when integrating instruments, devices and applications is to facilitate seamless flow of data across platforms and to enable advanced analytics.

Security and Regulatory Compliance
Securing data assets is key. Compliance is a license to operate in life sciences and many companies are experiencing an increasing regulatory focus on data integrity, computerized systems and security related to both laboratory applications and scientific instruments.


How NNIT can support your laboratories with a digital strategy, NNIT have supported pharmaceutical and biotech companies with defining digital strategies for laboratories.

NNIT can support your laboratories by creating:

  • Digital IT strategy and roadmap for LoTF

- Process Mapping & Gap Analysis
- Lab IT Strategy

 

  • Architectural vision

- IT Architecture Strategy & Design
- IT Landscape Roadmap


Digital IT strategy and roadmap for LoTF

NNIT has experience facilitating laboratory IT strategy workshops and providing roadmaps for laboratories in the pharmaceutical and biotech industry. NNIT can support you by facilitating process mapping workshops with different laboratory departments and stakeholders to understand their current As-Is situation (where are we today?) and future To-Be state (where do we want to be in the future?). Solutions to the gaps will be identified as part of the strategy and will form the foundation for creating the lab IT landscape roadmap which will include project prioritization and sequence.

Architectural vision
Many laboratories have not yet established an architectural vision to support their digital strategy of LoTF. Furthermore, many laboratories are not challenging the architectures behind their laboratory informatics applications, which often results in a gap between the system that is implemented and the digital strategy and vision that the organization has defined.

NNIT can help you define an architectural vision for your future laboratory IT capabilities that is tied together with your organization's overall digital strategy. We will analyze your organization's current laboratory application landscape and architectural set-up and identify which gaps to close in order to fulfill the vision. Based on this we will provide an architectural roadmap. Examples of topics that will be analyzed include:

  • Shall we abandon costly legacy systems with extensive life cycle maintenance and instead implement modern systems from a market leader?
  • Shall we upgrade current systems for compliance and performance reasons?
  • Shall data flow across systems to improve automation and data democratization?
  • Shall we establish data Intelligence to ensure correct reporting to authorities?

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