R&D IT executives in pharmaceutical (pharma) and biopharmaceutical (biopharma) companies are all striving to provide their scientists and technical staff with the best tools and systems. As Michael Shanler of Gartner, Inc. observed, “Many IT, R&D and supply chain leaders have a strong desire for better integration, integration standards and common data models. Ultimately, this can lead to improved quality, efficiency and innovation.”[1] These leaders believe that streamlined workflows and timely, enhanced access to data and information will make their scientists more productive and innovative in their quest to discover, optimize and deliver the next effective and targeted therapeutic agent.

But they face several challenges in achieving these goals. As R&D companies have grown and evolved, so have the informatics systems that they use to capture data, control and track samples and requests and extract actionable information. A typical informatics environment may contain a mix of home-grown tools, commercial systems, non-scientific data repositories and even Microsoft Excel files on individuals’ computers. Data definitions are inconsistent, systems don’t communicate cleanly and links between them are fragile or non-existent. As Shanler points out, “Scientific innovation is being crushed under the weight of so many disparate and non-communicative systems, and the costs of maintaining yesterday’s status quo for laboratory informatics are dangerous. The status quo is still one of complication, redundancy and complexity. It is unsustainable.”[2]

So even “business as usual” is becoming untenable. The pace of scientific change is accelerating far beyond the capabilities of static legacy data management systems. These tend to be niche solutions focused on a particular task or workflow, and they tend to be inflexible and cannot adapt easily to changed requirements or types of data. Michael Elliott of Atrium Research highlights the problem: “The rapid scientific advancement in areas such as next generation sequencing (NGS), precision medicine and next generation biologics increases the volume, variety and complexity of data sets. Informatics architectures must be more adaptive than they are today.”[3]

Informatics solutions should make life easier by removing barriers to progress and supporting a company’s unique workflows and disciplines. Based on our experience working with multiple pharma and biopharma companies, we have identified a set of five common, critical challenges facing R&D and IT leaders.

Managing New Science

New scientific developments and analytical techniques in R&D such as NGS and biotherapeutics (biologics) bring new workflows and data for capture, storage, management, search, analysis and reporting to the lab. Scientists are creating new entities and generating reams of corresponding novel data, but organizing and managing this new data be problematic.

IT staff attempting to extend existing data management architectures to work with new technologies and entities may find these integrations difficult. Older systems aren’t easily adaptable (e.g., can’t cope with experimental complexity and changeability in NGS LIMS) and are ill equipped to handle new entity types (e.g., protein structures for biologics registration). Niche solutions may appear to solve the problem of evolving needs, but only add to complexity by requiring point-to-point integrations with custom connectors that slow time to value and complicate ongoing maintenance.

Dealing with Change

Valuable IT resources are squandered on simply keeping existing informatics systems running. Requests to change a current workflow or capture and index new types of data increase the IT maintenance backlog, so essential workflow modifications and change orders can take weeks or months to get attention from IT (or a third party vendor).

Science, analytical techniques and experiment design are evolving rapidly. A request to modify a workflow (e.g., to add new data-driven options for samples going through a process) should occur in a matter of hours rather than weeks or months. The same is true when capturing a new attribute-value pair (e.g., a new parameter from a modified assay) or extending user permissions and roles when a new Contract Research Organization (CRO) comes on-board.

Integrating Old and New Systems

New informatics systems need to interchange data with current systems. For example, importing sample data from an inventory system, synchronizing with entity identification data from a corporate chemical or biological registry, or pulling assay requests and status from a LIMS. If any of these systems operates in a silo, access to essential data may require a custom coded connector. Custom coding takes time, adds to the maintenance burden and makes system upgrades problematic and disruptive.

Collaboration and Externalization

Companies externalizing their R&D activities need new communication and data exchange capabilities to collaborate effectively and securely with partners including CROs, academia and smaller biotech firms. Legacy in-house informatics systems may not be adaptable enough to deal with the changing web of partner organizations. In contrast, cloud-based collaboration platforms with strong security and user and group permissions can help companies to manage their rapidly evolving externalized workspaces.

Harmonization and Simplification

Organizations can enhance productivity and insights by simplifying and streamlining processes, and increasing access to well integrated data. As noted by Michael Elliott, “Time and again we find that efficiency gains in one group are wasted due to a lack of systemic optimization across departmental barriers”[4]. Disparate, stand-alone applications and silos of inconsistent data slow productivity, stifling efficiency and hampering decision-making. Maintaining disconnected legacy systems drains crucial IT resources better deployed on new applications.

Informatics Challenges

Our solutions address the five challenges discussed above to improve productivity, ease communication and deliver better scientific outcomes while simplifying informatics systems deployment, maintenance and upgrades. Solutions provide management with a holistic view of the R&D process, while empowering researchers with the capabilities they need to perform their science.

Solutions are built on Thermo Fisher™ Platform for Science™ software using a single technology stack. This enables clients to add new capabilities to support activities across the value chain rapidly. IT staff and power users can easily define and add new workflows, datatypes and apps to the system via configuration, with no custom code; and with no custom coding, system upgrades are quick and straightforward and total cost of ownership is lower than with traditional LIMS. As discussed in Scientific Computing World, “[Core system’s] configurability also means that the platform can address some of the major informatics bottlenecks in the life sciences – and particularly the bioindustries – in areas such as NGS, proteomics, genomics, clinical diagnostics and agbiotech. Traditional LIMS just don’t have the flexibility or data models to manage complex datasets in these emerging fields.”[5]

Pharma and biopharma leaders are overcoming these informatics challenges with solutions from Thermo Fisher Scientific. Learn how.

[1] Michael Shanler, Gartner, Inc., Research Note G00277468, 27 July 2015
[2] Michael Shanler, Gartner, Inc., Research Note G00251083, 26 September 2013
[3] Michael H. Elliott, Atrium Research & Consulting LLC, European Pharmaceutical Review Informatics in-depth focus, 3 September 2015
[4] Michael H. Elliott, Atrium Research & Consulting LLC, European Pharmaceutical Review Informatics in-depth focus, 3 September 2015
[5] Sophia Ktori, Scientific Computing World, Transforming Informatics with a marketplace in the cloud, June/July 2015