1 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Digital Transformation in the Lab:

Bridging Analog Islands in a Digital Ocean

Accenture Life SciencesPatient Inspired. Outcomes Driven.

2 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

About the ResearchAccenture surveyed 128 leaders in the life sciences industry to understand the extent to which pharmaceutical companies have undergone digital transformation, from the maturity of digital strategies to the level of implementation of digital technologies within labs.

Who do our 128 respondents work for?

Where are their companies headquartered?

What are their primary responsibilities?

86%

52%

70%

8%

26%

30%

6%

20%2%

Sponsor

in North America

Preclinical development

Manufacturing

Medical device manufacturer

CRO

in Western Europe

Early research/discovery

Clinical development

of respondents were Director-level or higher.

of respondents were in either executive management or R&D management.

69% 55% 2 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

3 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

The therapies that bring life-changing benefits to patients around the world are developed in thousands of labs across the life sciences ecosystem – from academia and nationally funded institutes to global pharmaceutical and biotechnology companies. Yet, most of these labs and the instruments within them remain disconnected, serving as analog islands in a digital ocean. We envision a future of interconnected labs, brought together and powered by waves of advances in digital technologies that are turning the tide of innovation.

3 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

4 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Navigating the wave of New ScienceBreakthrough science that can transform the treatment of patients is powered by millions of scientists and analysts working in research and development (R&D) and quality control (QC) laboratories around the globe. Today’s scientists live in a digitally connected world; however, when they step into their laboratories, they typically encounter a work environment that looks and operates much as it did in the last century.

Across science-driven industries, the convergence of science and technology has helped create more novel products, faster than ever before. By embracing the potential of New Science1—therapies and medicines that combine the best in science and digital health technology—innovative biopharmaceutical companies can offer better patient outcomes, improve patient engagement, and generate new growth to combat the compressive disruption that is impacting many of today’s life sciences companies.

Accenture research predicts New Science therapies will represent 54% of sales between 2017 and 2022, up from 47% between 2012 and 2017. Leaders in this space are investing heavily in emerging technologies to improve clinical outcomes and the patient experience, and connecting with an ecosystem of partners to accelerate innovation.2 With every advancement, New Science increases the pressure on the laboratory to adapt to these more complex discovery pathways and QC scenarios.

The pace of innovation in the life sciences industry is accelerating3, and significant investment needs to be made for the laboratory to keep up. The priority? Transforming labs to become digitally enabled, globally connected powerhouses capable of breakthrough innovation at scale. And yet, Accenture research found that, of 128 industry leaders surveyed, 40% had not embarked on applying digital to R&D or QC labs, and 37% more were still in pilot mode (see Figure 1). Yet the evidence for a positive return on investment is strong: 70% of respondents who have scaled up report achieving or exceeding expected business value.

Of those that are scaling up, a full 70% view these efforts as successful or extremely successful, indicating that those who do scale are realizing real business benefit.

Where are you in your digital journey? In Accenture’s research, we found that only 23% are committed to deploying digital labs.

Figure 1. Running aground in the pilot phase

37%

40%

13%

10%

Piloting

Not started

Scaling up

Already have digital technologies in widespread use

63% of those piloting have been for six months or more.

5 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

DATA COMPLEXITY VOLUME, VELOCITY, VARIETY

Staying afloat in a post-digital worldWaves of technological change are sweeping across virtually every industry. $1.25 trillion will be spent on digital transformation globally in 20194, surging to $1.97 trillion in 2022. By some estimates, more than 80% of the world’s population is now digitally connected. Digital products are everywhere, and we are in an era where our workforce is comprised of digital natives who expect to live, learn, and work in a digitally enabled world.

In the present reality, the use of digital technology is no longer a competitive advantage- it is the price of admission for doing business.5 But up to now, the life sciences lab has been slow to adapt to the pace of change in an increasingly digital world.

The time for large-scale digital transformation of R&D and QC labs in pharma and biotech is now. We’re seeing an unprecedented convergence of elevated business expectations, increased data complexity and dramatic changes in technology and science. Taken together, these drivers present the industry with an extraordinary opportunity for visionary leadership in this critically important area (see Figure 2).

Figure 2. Key drivers of digital transformation in the labDigital technology is essential to meeting today’s business demands and dealing with the resultant data tsunami.

BUSINESS EXPECTATIONS

NEW TECHNOLOGY & SCIENCE LANDSCAPE

Advanced analytics.

Robotics & RPA.

IoLT enabled instruments.

AR/VR/XR.

In Silico experimentation.

Advanced simulation.

Machine Learning, AI and Cognitive Computing.

Limitless scalability.

Innovate rapidly.

Deliver consistently.

Improve ROI on capital investments.

Convert Data Insights.

Implement adaptable processes.

Improve regulatory compliance.

Collaborate broadly.

Data volumes are rising.

Labs generate data faster.

Greater burden on scientists.

Novel and breakthrough ideas.

Collaboration is the norm.

Demonstrated reproducibility.

6 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

The big challenge? Navigating oceans of informationAn unprecedented number of novel drugs and therapeutic modalities are being explored today.6 From immunology and oncology to rare diseases and the next generation of anti-infectives, patients are benefiting from advances in science and technology not previously seen at this scale.

These innovations, while incredibly exciting, have also exposed a fundamental weakness in laboratory operations within the pharma industry: the collective inability to harness the power of the oceans of data we generate. Whether in labs engaged in research, or in labs generating and analyzing clinical data, the volume, velocity, and variety of data being generated by scientists is overwhelming the systems required to support it. Up to 70% of experimentation is not reproducible, often due to the inability to find the original research data, or because the experimental conditions (metadata) are inconsistently or inadequately documented.7

Unless we act now to bring order to this chaos, we are likely to miss the current opportunity to successfully scale scientific advances and improve the lives of people everywhere.

The good news? A systematic approach to how we produce and consume scientific, operational, clinical, and other patient-related data has been shown to have significant positive impacts—for both patients and biopharma companies.

And it all begins in the lab.

6 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

7 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Isolated environments = disconnected systems

Connected data: a key to transformation

These days, most R&D and QC lab technology systems are transactional. Designed to address a specific need—whether it’s lab data collection, data storage, analytics, or visualization—these systems largely remain disparate and disconnected.

The reason? Most research scientists, who are valued for their independent and creative thinking, have been given the freedom to choose the instruments and technologies they need to conduct experiments and test hypotheses. While that freedom makes sense in practice, it has given rise to a complex process of data collection in which there is no standard for identifying, labeling, or storing the information. It’s not uncommon, for example, to see significant differences in data collection processes between small-molecule discovery teams and their large-molecule counterparts, or between groups in different therapeutic areas or geographies.

Complicating this diverse environment, many companies have grown through acquisition, bolting together different technologies and lab approaches to create an intractable, patchwork data landscape.

To overcome these historical challenges and become truly data-driven enterprises, life sciences companies must adopt an end-to-end data strategy and then execute against it—connecting data from disparate sources like labs, collaborators, and the real world to generate insights.

Some companies are already taking this approach. Roche, in its 2018 annual report8, confirmed their commitment to becoming a data-driven enterprise by publicly stating that they are adding data management as an area of expertise along with pharmaceuticals and diagnostics. To substantiate that claim, in February 2018, Roche completed the acquisition of Flatiron Health9—a market leader in oncology-specific electronic health record (EHR) software, as well as in the curation and development of real-world evidence (RWE) for cancer research.

Novartis is another frontrunner in the race to become data-driven. It aims to move parts of its clinical trial pipeline from the physical lab to the virtual lab, using data as driver—a vision that is in lockstep with regulatory trends in the US. The US 21st Century Cures Act, supported by the FDA’s drive to accelerate breakthrough therapies for life-threatening or irreversibly debilitating conditions, foresees that by 2022, “data summaries,” rather than full clinical trials, will be used to support the approval of certain therapies for new indications.10

8 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Downstream challenges The need for a new, holistic, data-driven approach extends beyond the R&D lab to manufacturing quality control. Relying on QC, manufacturers must demonstrate to regulators that they can consistently produce a product to required quality, safety, and efficacy standards.

As the industry moves to more complex products and a more diverse mix of product types, QC has become more challenging. With New Science dominating the pipeline of innovative products, the volume and variety of QC testing has dramatically increased.

To put this into perspective, the world’s best-selling drug 10 years ago was Pfizer’s cholesterol-fighting treatment, Lipitor11, with an active pharmaceutical ingredient (API) of 33 carbon atoms. Today, the best-seller is Abbvie’s Humira, an anti-inflammatory treatment with 6,428 carbon atoms. Even more complex and personalized treatments such as cell and gene therapies are now gaining traction and this additional complexity will challenge QC laboratories further.

Like the science it is enabling, laboratory technology does not stand still. The analytical methods with which a drug is QC-tested are constantly evolving. Academic groups and vendors like Thermo Fisher Scientific, Waters Corporation and Agilent are constantly innovating new techniques for detailed analysis of tiny variations, such as post-translational modifications, that can occur in a biologic drug. As these techniques become peer- and industry-recognized, pressure increases for the industry to adopt these methods as well.

Against this fast-moving backdrop, the objectives of digital transformation in QC should be to increase productivity, improve right-first-time rates, manage cost, and shorten lead times for batch release. Above all, these transformations need to ensure agility in adapting to new products and test methods and drive effective collaboration with colleagues in R&D, manufacturing, and across a complex supply chain.

8 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

9 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Navigating toward success in a data-driven world The life sciences industry is at an inflection point. Companies throughout the industry now recognize that to remain competitive they need to make better use of all their data assets. To be a leader in this new data-driven world, life sciences companies must fundamentally transform how they create, manage, and effectively use all the data that is generated in labs across their ecosystem—from internal labs to the many partners with whom the they collaborate—to become a truly data-driven “digitally transformed lab” (see Figure 3).

Technologies such as extended reality, artificial intelligence/machine learning (AI/ML) and Internet of Things (IoT) are mature and affordable enough today to enable real transformation of the lab.

Achieving this outcome requires a thoughtful approach anchored by an effective, sustainable, and comprehensive data strategy. With this foundation, companies can harness new digital technologies as the drivers for successful transformation. Careful planning is essential in order to avoid creation of new data silos with unintended consequences.

Figure 3. Architecture of a digitally transformed lab

AI/ML Taming the data deluge Benefits every scientist and analyst

EXTENDED REALITY

“Collaborate to innovate”The end of distance and the beginning of “Labs Without Borders”

COMPREHENSIVEDATA STRATEGY

Data-enabled processes FAIR data standards, governance, provenance and data integrity

PLATFORM ARCHITECTURES

Do more science by spending less time/money on systems integration & maintenance

INTERNET OF LAB THINGS (IoLT)

From instruments to insights seamless connection across instruments, robots, and humans

10 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Stages on the journey to the digital labIn an industry where lives depend on the quality of product and process, a change of this magnitude should be managed with risk and human factors in mind. We believe digital transformation of the lab should be pursued in three clear phases (see Figure 4).

The first phase is “foundational,” where the emphasis is on doing the basics brilliantly. Priorities here include simplifying the application landscape, deploying automation, connecting all instruments, and capturing data digitally. These foundational actions are necessary to make possible the transformational work that follows.

The next phase is “transformational.” A clear trend that we see in the modern digital lab is moving away from isolated and monolithic systems (LIMS, ELN, SDMS) toward a cloud-based, multi-vendor platform approach that delivers “connected capabilities” formerly provided by one or more of these traditional systems. For instance, sample and test management, once provided by LIMS, would be a capability offered on the same platform as experiment planning and design. The goal of the “transformational” phase is to bring the lab into “the new” by implementing a harmonized digital platform upon which true business transformation may occur. This platform for transformation should include core services including a common user interface, enhanced security, data access, and instrument integration, which in turn enable analytics-powered insights, ecosystem collaboration, and enhanced workflow and compliance (see Figure 5).

• Simplify your application landscape

• Become compliant and secure

• Capture all the data digitally

• Tactical applications of automation

• Re-imagine & optimize workflows

• Harmonize your data platform• Build end-to-end “data supply

chain”• Use analytics to gain insights• Build robust collaborations

• Implement whole lab automation

• Leverage AI to gain new insights

• Implement in silico methods and simulation

FOUNDATIONALDO THE BASICS BRILLIANTLY

TRANSFORMATIONALDATA-DRIVEN WAYS OF WORKING

ASPIRATIONALREDEFINE YOUR LAB

Figure 4.

11 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Figure 6. Areas of focus for innovation

Figure 5. The fully integrated digital lab enables better science

How is the industry faring on this journey? We asked industry leaders what operational challenges / business problems they’re trying to solve with digital in the lab. The top area of focus reported (see Figure 6) is achieving operational improvements (foundational and transformational) and less so on business challenges (aspirational).

With this data-driven infrastructure in place, the final, “aspirational” phase allows new scientific business models to be realized leveraging a redefined lab environment powered by an end-to-end data supply chain, deeper adoption of AI, whole lab automation, and implementation of in silico methods and simulations.

60%

59%

44%

43%

33%

Increased lab throughout, instrument utilization & maintenance

Assisting/augmenting staff in performing their work in the lab

Identifying potential drug candidates faster

Identifying opportunities to fail faster with non-viable drug candidates

Faster release of higher quality batches

Ecosystem for innovative software

applications

Foundational data, workflow, and decision

support capabilities

Scientific platform services built on a scalable, secure, and compliant

cloud infrastructure

Specialized Workflow, Advanced

Analytics & Visualization

Solutions

Cloud Infrastructure

Digital Laboratory Data Management CapabilitiesInstrument Integration, Data Ingestion, Data Enrichment, Relationship Linking

Standardization, Data Pipelining, Context Linking, IP Protection

Research Workflow Capabilities

Comprehensive Search

Data Visualization

Comprehensive Workflow Management

Instrument Integration & Automation

Sample & Reagent Management

Data Security, IP Protection

Experiment Data Capture

Comprehensive Reporting

Entity Registration

Data Access for Analytics/ Modeling

Experiment Planning/Design

Seamless Collaboration

12 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

A look to the horizon: the digital lab of the future The modern digital lab will truly transform how innovative biopharmaceutical products are created and brought to market. Researchers will leverage prior research from internal collaborators and external partners, real world evidence, and public research efforts to quickly identify novel disease targets, as well as potential new therapeutics and therapeutic pathways. Much of this will occur digitally, using models supported by AI/ML and digital twins, significantly reducing the amount of follow-up work that needs to be done in the physical lab.

Within the R&D lab, previously inaccessible complex and miniaturized assays will become routine and fully automated, and the entire discovery process will result in accelerated insights, greatly reduced time to move promising new therapeutics into the clinical trials phase, and increased likelihood of clinical success for those that do enter the clinical pipeline. The laboratory will be a familiar and comfortable work environment for the scientists, functioning much in the same way as their digitally connected lives outside of the lab.

In the QC lab, the use of extended reality (XR) will become commonplace to facilitate tech transfer, train, and provide technical support on new methods, and guide lab staff as they execute those methods. High levels of assay automation will further increase quality and reduce the variability of QC operations, leading to higher right-first-time rates on assay execution. The digitally lean QC lab, guided by an integrated manufacturing and QC “control tower,” will provide real-time predictive analytics that make the entire manufacturing and QC process transparent, reducing the process control efforts of manufacturing and lab personnel, who will instead focus on anticipating and preventing negative events, rather than reacting to events after they occur. This in turn will result in improved visibility to QC lab performance, asset utilization, and resource scheduling to support longer-range strategic lab planning.

12 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

13 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Charting your course to digital lab excellenceFor those still contemplating whether to embark on the journey, the digital transformation of the lab can start sooner than they might think. Not everyone is setting sail from the same port, nor will everyone’s journey follow the same course. However, the formula to reach your new digitally enabled destination is the same. And for those who have embarked on the journey some time ago but find themselves adrift and searching for direction, adopting this formula can get you back on course (see Figure 7).

Figure 7. Navigation points for your digital lab journey

DIGITAL AWARENESS

DIGITAL STRATEGY

DIGITAL FOUNDATION

DIGITAL LEADER

DIGITAL MASTERYBe best-in-class and harvest the fruits of the digital revolution

Understand where you stand on digitization

Plan your way to become a leader in applying digital innovation

Implement the digital ground layer (ELN, LIMS, data and knowledge systems)

Transform into a digital enterprise and stay ahead on the race to operational excellence

14 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

Companies should place their digital bets within a formalized innovation framework that:

• Defines what success looks like through a laboratory innovation “North Star,” tied to strategic objectives and focused on delivering value to the business.

• Establishes a robust digital laboratory innovation pipeline (see Figure 8) that is continually refreshed and prioritized to stay relevant. Pipeline initiatives should be aligned with strategic priorities for lab innovation, such as connecting the lab, improving user experience, and collaborating with internal and external partners. Firmly tie each initiative in the pipeline to expected business value, and identify metrics in advance that will clearly measure the business value delivered.

• Encourages quickly scaling the laboratory solutions that work. Identify key business KPIs for pilots and build in measurement of those KPIs. Identify a plan for quickly integrating pilots that meet or exceed business objectives into lab operations across the enterprise; harvest learnings from those that don’t.

• Identifies the leaders and the teams within the labs that can serve as “lighthouses”: those that are suited to prove out digital experiments, such as low risk or “green field” sites that are safe and relatively quick places to experiment, or labs that are open to new ways of working.

• Leverages a trusted transformation partner. The application of digital technologies within the lab is still in its early stages in most life sciences companies, and few have scaled to drive true transformation. Those just getting started or struggling to build momentum should tap into the experience of organizations that have demonstrated success with digital transformation not only within life sciences, but also in other industries.

For life sciences companies, achieving, and sustaining competitive advantage in a world of constant change demands immediate, continual, and large-scale transformation of lab operations and scientific data management. Those that commit first to doing the basics brilliantly, and then to leveraging today’s digital technologies to transform and redefine their laboratories, will be in the best position to adapt and thrive.

Figure 8. Taking an agile approach to lab innovationA digital lab innovation pipeline to evaluate, incubate, and industrialize laboratory innovation at scale

New ideas & emerging technology Ready soon Ready now Lab Scale Pilot Platform integration

Roll-out to X# of Labs

.

ESTABLISH A DIGITAL LAB INNOVATION PIPELINE

Ideate Evaluate Incubate Industrialize Scale

15 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

For Accenture’s survey of 128 industry leaders, we defined digital platforms as a foundational technology that enhances an organization’s digital processes and capabilities and that allows for the creation of new services facilitating an exchange between producers and consumers of information. Digital platforms connect both people and/or things to provide data-driven intelligence as well as actions that extend the digital business ecosystem.

Definitions provided to survey respondents:

Digitalization (Digital herein): Digitalization is leveraging technology to change a business model or process to invoke new value-producing capabilities. It is not simply moving from analog to digital.

Adoption: Adoption occurs when a digital technology has been implemented either in part or in full and is being used so that the expected value from the revamped business model or process is being achieved to a measurable degree.

Survey specific: For this survey we refer to biopharma laboratory data. This data could include any or all the following examples:

• laboratory & scientific data management

• digital methods used to collect lab data (IOLT)

• integrate lab/scientific data with other enterprise data (data virtualization, big data technology, AI/ML)

• support lab & scientific workflows and workers (cloud, platform, wearables/AR/VR, robotics)

• provide confirmation of data and product integrity (blockchain)

Definitions for digital transformation survey:

15 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

16 | Digital Transformation in the Lab: Bridging Analog Islands in a Digital Ocean

PATRICK PIJANOWSKIManaging DirectorAccenture Scientific Informatics Servicespatrick.pijanowski@accenture.com

BRIAN POTTERManaging DirectorAccenture Scientific Informatics Servicesr.brian.potter@accenture.com

MARK FISHManaging DirectorAccenture Scientific Informatics ServicesEuropem.fish@accenture.com

KAILASH SWARNAIndustry Principal DirectorAccenture Scientific Informatics Services

BARRY HEAVEYManaging DirectorAccenture Industry X.0, Life Sciencesbarry.heavey@accenture.com

Copyright © 2020 Accenture. All rights reserved.Accenture and its logo are trademarks of Accenture.

This document makes descriptive reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by Accenture and is not intended to represent or imply the existence of an association between Accenture and the lawful owners of such trademarks.

About Accenture Life SciencesAccenture’s Life Sciences group is committed to helping our clients make a meaningful impact on patients’ lives by combining new science with leading edge technology to revolutionize how medical treatments are discovered, developed and delivered to people around the world. We provide end-to-end business services as well as individual strategy, consulting, digital, technology and operations projects around the globe in all strategic and functional areas—with a strong focus on R&D, Sales & Marketing, Patient Services and the Supply Chain. We have decades of experiences working with the world’s most successful companies to innovate and improve their performance across the entire Life Sciences value chain. Accenture’s Life Sciences group connects more than 15,000 skilled professionals in over 50 countries who are personally committed to helping our clients achieve their business objectives and deliver better health and economic outcomes.

About AccentureAccenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions–underpinned by the world’s largest delivery network–Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With approximately 505,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com.

@AccentureLifeSci

/accenture_life_sciences

About Accenture Scientific Informatics ServicesAccenture Scientific Informatics Services combines scientific and laboratory informatics expertise with strategic and business consulting capabilities, industry platforms, innovation approach, and global scale to revolutionize how scientific and laboratory processes are conducted. We work with our clients to streamline technology and processes, and harness the power of data, to remain competitive within today’s changing scientific informatics ecosystem.

Contacts

1 https://www.accenture.com/us-en/insights/life-sciences/new-science

2 https://www.accenture.com/kr-en/~/media/accenture/next-gen/value-of-digital/pdf/accenture-capturing-100-billion-opportunity-life-sciences-digital-transformation.pdf

3 Ibid.4 www.idc.com/getdoc.jsp?containerId=prUS444403185 www.accenture.com/us-en/insights/technology/

technology-trends-2019?src=SOMS6 New Modalities, Technologies, and Partnerships in Probe

and Lead Generation: Enabling a Mode-of-Action Centric Paradigm, Eric Valeur and Patrick Jimonet, Journal of Medicinal Chemistry 2018 61 (20), 9004-9029

7 https://www.nature.com/articles/sdata2019218 https://www.roche.com/investors/annualreport18.html9 https://www.roche.com/media/releases/med-

cor-2018-02-15.htm10 https://www.pbs.org/newshour/health/wins-loses-21st-

century-cures-act11 https://www.kiplinger.com/slideshow/investing/T027-S001-

the-15-all-time-best-selling-prescription-drugs/index.html

References