idc techscape: worldwide life science clinical trials ... · figure 1 shows the 2015 idc techscape...
TRANSCRIPT
February 2015, IDC #254210
Industry Developments and Models
IDC TechScape: Worldwide Life Science Clinical Trials Technologies, 2015
Alan S. Louie, Ph.D.
IDC OPINION
FIGURE 1
IDC TechScape: Worldwide Life Science Clinical Trials Technologies, 2015
Note: This IDC TechScape chart is representational of various technology adoption life cycles, given IDC's current analysis of the
market. It is not a detailed or dynamic mathematical model. There is no preestablished time frame for the various adoption curves.
Source: IDC, 2015
Figure 1 shows the 2015 IDC TechScape worldwide life science clinical trials technologies.
©2015 IDC #254210 2
Technology is an integral component in the life science industry overall and especially within the
discovery research and clinical development spaces. As life science companies seek to rapidly
innovate in response to industry pressures, technology will play an increasingly important role through
both enabling and more directly supporting key industry processes integral to the complex, highly
regulated product discovery and development life cycle. In addition, new data, information, and
knowledge resources are becoming available that must be integrated into current best practices.
Technological innovation is expected to strongly contribute to the next-generation best practices
approaches that will lead the industry into the future. This IDC TechScape study focuses on
technology adoption within the life science clinical development space. It assesses key technologies
that are driving evolution beyond industry technology best practices in place today. Besides looking
more deeply into individual technologies, this document considers technology-specific analyst insights
regarding anticipated rate of adoption, potential risks impacting future success, and industry market
interest. The IDC TechScape model is designed specifically to capture progress in the adoption of
emerging disruptive technologies, mainstream technology buyer alignment with current industry best
practices, and supporting technologies that promise to deliver operational advantages to organizations
that choose to adopt them. IDC expects that life science executives will use the IDC TechScape model
to:
Assess the progress of their own technology adoption efforts in comparison with the industry
overall
Identify new technologies that should be added to consideration in their technology road map
Add new insights to increase the robustness of their own technology decision frameworks
©2015 IDC #254210 3
IN THIS STUDY
The life science R&D technologies IDC TechScape is intended to help senior executives assess their
organizations' technology landscape to determine whether their efforts are aligned with analyst's
assessment of the industry's overall technology adoption progress. While it is clear that an individual
company's tolerance for risk plays a significant role in determining its path forward, this study helps
organizations more systematically categorize and assess relevant clinical trials technologies, taking
into account adoption criteria specific to each technology.
SITUATION OVERVIEW
The life science industry is actively undergoing transformational change as it seeks to regain long-term
sustainability in the shadow of blockbuster drug revenue losses due to the patent cliff. With savings
from the elimination of excess capacity and the externalization of noncore competencies largely
complete, leading industry innovators are increasingly looking beyond their own traditional boundaries
to best practices from outside of the industry. While life science companies are historically averse to
exploring innovation from outside of the industry, the increased urgency dictated by both anticipated
and realized revenue losses has forced them to pursue opportunities to more quickly and efficiently
implement change. While still relatively slow in adoption when compared with other industries, the life
science industry has realized that there is significant potential for advances built on industry-specific
innovation and industry-agnostic innovations proven elsewhere.
Discovery research and clinical development in the life sciences are strongly supported by technology
and technological innovation. With continuing evolution in the industry, including a data explosion
fueled by the $1,000 genome and increasing access to healthcare and consumer data, the growing
need to routinely process ever-larger amounts of information and knowledge on a global basis, and an
ever-expanding global collaborative work environment, effective adoption of appropriate technologies
is the likely sole path to systematically and efficiently move companies forward.
Unlike other technology assessment frameworks, the IDC TechScape is intended to provide a visual
representation of the process of technology adoption, dividing technologies into three major categories
based on their impact on the organization and then assessing their relative maturity within their
respective categories. In addition, in reviewing specific, individual categories, additional insights
regarding the speed of adoption, technology potential for success (risk), and industry market buzz are
also considered (refer back to Figure 1).
The IDC TechScape
This IDC TechScape study focuses on different technologies used to support the clinical trials needed
to validate a potential new drug's safety and efficacy. Ranging from infrastructure technologies
supporting eClinical platforms to technologies that promise to improve operational efficiencies to
technologies that will bring new forms of patient data to trials, this IDC TechScape captures the full
spectrum of technology types that will impact the industry both now and in the future.
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This IDC TechScape provides technology buyers with a snapshot of technologies and their current
state of adoption in the life science clinical development space. Recognizing that the rate of
technology adoption can vary with organizational risk tolerance, the IDC TechScape is intended to
represent adoption progress expected for mainstream technology adopters.
The IDC TechScape is composed of three separate adoption profiles, representing technologies
supporting disruptive processes (transformational), current technology best practices (incremental),
and supportive technologies that can deliver improved operational effectiveness or efficiencies
(opportunistic).
Within each adoption profile, individual technologies are positioned relative to their adoption maturity.
IDC has identified five basic stages to technology adoption: evaluate, test, deploy, maintain, and
replace. Refer back to Figure 1, which displays the adoption curves and the relative stages of adoption
for each technology on the IDC TechScape graph.
Scope and Domain of the IDC TechScape
The core foundation of an IDC TechScape is the definition of the specific technology coverage area
within its specific use domain. The IDC TechScape is intended to provide IT and technology buyers
with a current snapshot of the user domain, which may be specific to a particular focus area or
industry. As a result, it becomes possible for specific technologies to be positioned in different places
on the IDC TechScape, depending on what user domain is being discussed. For example, while public
clouds are positioned in the deploy stage within the opportunistic category in this IDC TechScape, they
would likely be considered to be in the maintain stage within the incremental category in an IDC
TechScape focused on industry-agnostic datacenter technologies. As a result, an understanding of the
specific domain associated with an IDC TechScape figure is critical to applying the market insights
contained within.
IDC TechScape Categories and Definitions
The categories that define the three types of adoption curves in an IDC TechScape are (see Table 1):
Transformational: The transformational category includes disruptive technologies that are likely to be next generational by their potential to fundamentally transform current industry best
practices. While clearly different from current best practices, technologies that are successful in this category are likely to represent the best practice technologies of the future.
Covered technologies/processes: Adaptive trials, virtual trials, gamification, risk-based monitoring (RBM) trials, cognitive computing, mobile-linked diagnostics, and Webcam
diagnostics
Incremental: The incremental change category includes technologies that represent current
industry best practices. While different technologies can clearly be at different stages of adoption, these technologies are generally recognized as best practices currently in use in
clinical trials, with the analyst's assessment of average industry adoption for each technology represented. These technologies are expected to continue to incrementally evolve over time.
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Covered technologies/processes: Electronic data capture (EDC), eClinical solutions, electronic trial master file (eTMF), translational research, crowdsourcing, real-world
evidence (RWE) trials, and drug portfolio trials
Opportunistic: The opportunistic category includes those technologies that contribute to
industry progress but are not considered integral to current best practices. These technologies may include industry-agnostic solutions that help advance efforts but are not critical to
success. While not absolutely required, technologies in this category contribute to company success through more streamlined process execution, direct cost savings, and improved process outcomes.
Covered technologies/processes: Private clouds, BI platforms, public clouds, social media
engagement, and big data platforms
TABLE 1
IDC TechScape Technology Markers of Momentum
Curve Type Technology Stage of Adoption Speed of Adoption Risk Level Market Buzz
Transformational Adaptive trials Deploy Medium Low Medium
Virtual trials Test-deploy Medium Medium High
Gamification Test Medium Medium Medium
RBM trials Test Fast Low High
Cognitive computing Evaluate-test Slow Medium High
Mobile-linked diagnostics Evaluate Medium Low Medium
Webcam diagnostics Evaluate Slow Medium Low
Incremental EDC Maintain Medium Low Low
eClinical solutions Deploy Fast Low Medium
eTMF Test-deploy Medium Medium High
Translational research Test-deploy Medium Medium High
Crowdsourcing Test Slow Medium Medium
RWE trials Evaluate-test Slow Medium Medium
Portfolio trials Evaluate Slow High Low
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TABLE 1
IDC TechScape Technology Markers of Momentum
Curve Type Technology Stage of Adoption Speed of Adoption Risk Level Market Buzz
Opportunistic Private clouds Maintain Medium Low Medium
BI platforms Deploy-maintain Fast Medium High
Public clouds Deploy Fast Medium High
Social media
engagement
Test Slow High High
Big data platforms Evaluate-test Medium Medium Medium
Technology = Technologies supporting clinical trials in the life sciences
Stage of Adoption = Progress relative to the five stages of technology adoption (evaluate, test, deploy, maintain, or replace)
Speed of Adoption = How quickly technology adoption is moving (fast, medium, or slow)
Risk Level = The potential level of risk impacting success in technology adoption (high, medium, or low)
Market Buzz = The level of industry enthusiasm regarding the promise of a particular technology (high, medium, or low)
Source: IDC, 2015
IDC TechScape Technology Descriptions
In conjunction with each life science technology or process description, each IDC TechScape
technology includes an IDC TechScape Spotlight that is intended to provide additional analyst insights
regarding the expected momentum that a particular technology is expected to carry with it. The IDC
TechScape Spotlight is composed of three independent, analyst-determined metrics — speed, risk, and
market buzz:
Speed: How quickly technology adoption is moving (fast, medium, or slow)
Risk: The potential level of risk impacting success in technology adoption (high, medium, or
low)
Buzz: The level of industry excitement regarding the promise of a particular technology (high,
medium, or low)
©2015 IDC #254210 7
Adaptive Clinical Trials
FIGURE 2
Adaptive Clinical Trials Markers of Momentum
Source: IDC, 2015
Clinical trials that are built and performed using adaptive designs are intended to allow trial managers
to dynamically change trial conduct at any stage during an ongoing trial based on the predetermined
response to specific performance criteria. Early termination of nonresponsive trial arms and early
validation of primary endpoints are examples of adaptive trial designs. Adaptive clinical trials are
intended to allow clinical trial managers to more efficiently manage trial resources while concurrently
accelerating time to outcomes.
Virtual Clinical Trials
FIGURE 3
Virtual Clinical Trials Markers of Momentum
Source: IDC, 2015
First performed in 2011 by Pfizer in its REMOTE trial, the application of a number of technology
innovations to enable and empower a "siteless" clinical trial (i.e., participating trial patients do not need
to go to a physical trial investigator office but visit specified locally available physicians or medical
laboratories as needed) demonstrated the potential of a virtual clinical trial, despite not achieving its
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desired trial outcome. The ability to access a much larger potential trial participant pool while
maintaining required patient safety and regulatory compliance requirements is potentially a
transformative innovation that should enable increased access to a much broader potential trial
candidate population, faster overall trial enrollment, and more streamlined trial execution (allowing
trials to start earlier and finish faster). With only limited experience in the field, virtual clinical trials carry
significant unknown risk factors that limit rapid mainstream adoption at this time.
Gamification
FIGURE 4
Gamification Trials Markers of Momentum
Source: IDC, 2015
The use of gamification technology in clinical development aspires to improve stakeholder (i.e.,
patient, investigator, and clinical staff) engagement, satisfaction, and compliance using approaches
that have delivered proven results in other industry and social venues. With performance data already
captured as part of ongoing clinical data collection, it should be possible and reasonably simple to
apply game thinking and mechanics to areas that include trial patient recruitment, patient compliance,
and investigator management. As an innovation approach that seeks to leverage human nature
without adding significant new costs, the use of gamification in clinical development is primarily limited
by creativity in execution and the need to operate in a tightly regulated ecosystem.
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Risk-Based Monitoring Clinical Trials
FIGURE 5
Risk-Based Monitoring Clinical Trials Markers of Momentum
Source: IDC, 2015
With strongly supportive guidance from global regulatory bodies over the past three years, the industry
has been aggressively developing risk-based monitoring approaches to the execution of new clinical
trials. The prospect of more efficient, higher-quality, and, likely, lower-cost clinical trials is the core
benefit of the RBM approach, and sponsor companies, along with their execution partners, are
transitioning their clinical strategies and processes to accommodate this new approach. As with most
complex processes, clinical trials have a large number of core elements, key tasks, process controls,
regulatory requirements, people, and places that will need to be systematically transitioned to this new
approach while concurrently maintaining traditional efforts for trials initiated prior to the advent of RBM.
With roles expected to change with RBM, proper training and clear strategic guidance will be key to
success.
Cognitive Computing
FIGURE 6
Cognitive Computing Markers of Momentum
Source: IDC, 2015
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From a practical perspective, most people will likely view cognitive computing technology solutions as
processes that utilize IBM's Watson computer system. As a platform designed to apply an artificial
intelligence approach to complex problem solving, Watson is capable of analyzing very large amounts
of data to extract relationships and correlations relevant to a particular problem. From a clinical
development perspective, Watson can systematically examine all available data, information, and
knowledge related to a drug or medical issue and bring forth this data to potentially provide fresh
insights to ongoing industry problems. Watson has applications across the industry spectrum, ranging
from providing comprehensive literature reviews regarding a specific researcher project to identifying
potential opportunities to repurpose drugs to screening for potential new drug safety indicators, and
more. While early in its commercialization, Watson is expected to find significant utility in the life
sciences as pilot efforts begin to demonstrate value.
Mobile-Linked Diagnostics
FIGURE 7
Mobile-Linked Diagnostics Markers of Momentum
Source: IDC, 2015
As a technology that is experiencing early adoption within the healthcare-based remote patient
monitoring market, mobile-linked diagnostic technologies offer significant potential to improve the
clinical trials process through more real-time, remote access to clinical trial patient data as it is
generated. Using wireless sensors in conjunction with patient smartphones, it becomes possible to
actively monitor patient metrics without the need for patients to intervene. With several FDA-approved
mobile-linked diagnostic solutions available and many more in development, this new technological
capability promises to provide more specific data to trial investigators in real time while concurrently
enabling better patient safety through earlier identification of potential adverse events.
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Webcam Diagnostics
FIGURE 8
Webcam Diagnostics Markers of Momentum
Source: IDC, 2015
While historically used in monitoring consumer behavior for marketing purposes (e.g., tracking eye
movement in response to television commercials), the potential use of patient Webcams to monitor
and measure their capabilities and performance offers new opportunities to measure disease and/or
treatment progress. Especially relevant in areas such as CNS and potentially in conjunction with
gamification technologies, Webcam-based diagnostics offer the potential to regularly measure patient
physical responses that may be associated with disease progression. With specific Webcam-based
biomarkers still in early research stages, this application remains likely on the longer-term horizon,
although the technologies are sufficiently advanced to enable applications over the near term.
Electronic Data Capture
FIGURE 9
Electronic Data Capture Markers of Momentum
Source: IDC, 2015
EDC has been the core element in the transition from paper-based to electronically data-captured
clinical trials. IDC believes that while most of the later-stage addressable EDC market has been fully
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penetrated, some additional growth remains (primarily in Phase I and Phase IV trials and through
expanded use in the broader eClinical space) in this mature technology space.
eClinical Solutions
FIGURE 10
eClinical Solutions Markers of Momentum
Source: IDC, 2015
With the emergence of electronic alternatives to each of the processes associated with the conduct of
a clinical trial, it became possible to connect these processes to form more comprehensive eClinical
trial platforms. The ability of eClinical platforms to share data across individual processes adds
significant process efficiencies and enables earlier insights into potential drug safety issues. In
addition, with the increasing use of contract research organization (CRO) services to execute clinical
trials, preconfigured, prepackaged eClinical solution offerings are becoming more practical, especially
in the case of small- to midtier sponsors that fully rely on service providers for their trials. While best-
of-breed eClinical platform components remain a concern for specific needs or specific sponsors (e.g.,
the use of Oracle InForm or Medidata Rave EDC platforms for pivotal late-stage trials), easy-to-use,
interconnected, cost-effective, and comprehensive eClinical platforms are experiencing increased
interest as sponsor companies focus on outcomes over process.
Electronic Trial Master File
FIGURE 11
eTMF Markers of Momentum
Source: IDC, 2015
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The electronic trial master file is intended to electronically manage all trial documentation, images, and
other digital content to maintain regulatory compliance and respond to interactions with regulators.
Historically, trial master files have been paper based, requiring significant dedicated effort in response
to regulatory events (e.g., new drug filings or regulatory audits). With evolving regulatory guidelines
supporting the increased use of eTMF and other electronic content management solutions to achieve
higher levels of regulatory compliance and reduce business risk, the industry is actively transitioning
away from paper. While efforts are ongoing to standardize the eTMF requirements across the industry,
commercial eTMF solutions vary significantly and a number of different platforms are in use today.
Translational Research
FIGURE 12
Translational Research Markers of Momentum
Source: IDC, 2015
While not a specific technological innovation per se, translational research is a paradigm-changing
approach to life science research that will exploit a wide variety of technological innovations in its
execution. Translational research seeks to use data from across the life science and healthcare
ecosystems to better inform strategic decision making. As an example, by bringing in disease-specific
data from patients in a healthcare setting, it should be possible to determine whether an early-stage
disease model accurately reflects disease manifestation in humans. Exclusion of approaches whose
data are not supported reduces wasted effort that has significantly reduced the likelihood of success
and allows for resources to be better allocated. In lowering risk and increasing the likelihood of
success for efforts across the life science product life cycle, translational research promises to improve
the operational effectiveness and efficiency of the industry overall.
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Crowdsourcing
FIGURE 13
Crowdsourcing Markers of Momentum
Source: IDC, 2015
Enabled by the emergence of social media technology platforms in the consumer space,
crowdsourcing offers significant potential for a new source of funding for early-stage life science
ventures. Whether supporting early demonstration projects in discovery research or potentially
paradigm-changing approaches to clinical trial recruitment or patient compliance, crowdsourcing is a
quickly accessible resource that allows for unconventional ideas to advance. While not a substitution
for the major financial commitments required to advance promising drugs through clinical
development, this alternative financial vehicle may have a role to play in the industry as a grassroots
alternative to angel investors.
Real-World Evidence Trials
FIGURE 14
Real-World Evidence Trials Markers of Momentum
Source: IDC, 2015
While regulatory requirements necessitate the validation of drug performance separate from
complicating factors (e.g., concurrent disease management), patients in the real world (and especially
aging patients in the developed world) routinely are managing multiple medical conditions at the same
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time. For most drugs, effectiveness and safety have not been tested for concurrent unrelated drugs
being used together (unless there are obvious recognized drug interactions). While immediate and
near-term adverse drug interactions become readily apparent once drugs become commercially
available, longer-term adverse reactions are often not identified, resulting in increased negative
outcomes in the population at large that could be averted (e.g., increased potential for a cardiac event
or greater sensitivity to other diseases). With more post-approval REMS trials ongoing and the use of
advanced social media analytics, it is becoming possible to better assess drug performance in real-
world situations. While not necessarily the purview of drug companies, this research will be
increasingly enabled by big data and analytics, clinical data accessible via data transparency
initiatives, and social media data.
Portfolio Trials
FIGURE 15
Portfolio Trials Markers of Momentum
Source: IDC, 2015
As we increasingly understand disease at the molecular level, it is becoming possible to develop drugs
that specifically target disease factors specific to the individual. For many diseases, this may mean that
a portfolio of potential drugs can be identified that take into account individual disease factors
(biomarkers) that can be used to determine which drug candidate is most likely to be effective in that
individual. For complex diseases and diseases with recognized variants, this may be the best
approach possible to manage the disease overall, allowing for the approval of a portfolio of effective
drugs capable of addressing most, if not all, of the patients afflicted with the disease in a timely
fashion. While currently being performed on a piecemeal basis, a portfolio approach may be applicable
for next-generation drugs that are being applied to diseases where our growing knowledge uncovers
variations important to disease treatment. At present, however, there is no regulatory pathway to
approving this approach, a concern that will strongly slow progress in approving portfolios of drugs
over the near- to midterm.
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Private Clouds
FIGURE 16
Private Clouds Markers of Momentum
Source: IDC, 2015
As a more physically secure approach to cloud adoption (compared with public clouds), private clouds
are a technological innovation that helps extend internal IT infrastructure without raising significant
concerns over data security. While more costly, the highly risk-averse life science industry has
embraced this transitional approach to cloud adoption based on both direct cost savings and increased
agility in extending the enterprise. The life science industry continues to lag behind other industries in
the rate of cloud adoption but is slowly making the shift as access, reliability, security, and regulatory
concerns are allayed. IDC expects that the use of private clouds will grow over the near term but
diminish somewhat over the longer term as capacity shifts to more cost-effective public clouds for
noncritical efforts.
BI Platforms and Technologies
FIGURE 17
BI Platforms and Technologies Markers of Momentum
Source: IDC, 2015
As part of current efforts by the industry to transform itself, the ability to translate data into actionable
information has maintained a high priority within life science organizations. Efforts to embed analytics
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into operational platforms, expand BI across the enterprise, and bring together data from disparate
data silos within the organization are beginning to pay off, and efforts have further expanded with
access to new data resources including EMR data, healthcare payer data, and consumer social media
data. With improved access to organizational data, companies are now implementing automated
workflows capturing current industry best practices to deliver alerts to key stakeholders that can act on
the data to drive both strategic and tactical decision making. The increasing BI challenge for
organizations will be keeping up with growing data volumes, maintaining regulatory compliance with
restricted data sets, and ensuring that analytics deliver accurate insights from evolving data resources.
Public Clouds
FIGURE 18
Public Clouds Markers of Momentum
Source: IDC, 2015
While agility and cost savings remain the key benefits of shifting from on-premise and private cloud
platforms to public clouds, the primary concern with the use of public clouds continues to be in the
area of data security. In the especially risk-averse life science industry, this has greatly slowed the
adoption of public clouds in all regulated areas (e.g., clinical trials) while concurrently allowing the
largely unregulated discovery research area to quickly shift into the space. As additional security
measures are being put in place and industry fears begin to be put aside, there is an ongoing shift
toward public over private clouds. At the same time, increased externalization of the life science
enterprise is opening up new opportunities to use public clouds as the common workspace for
collaborative efforts. IDC expects the use of public clouds to continue to expand in the industry with the
limited exception of highly sensitive areas, taking capacity and costs from existing private cloud and
internal datacenter investments.
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Social Media Engagement
FIGURE 19
Social Media Engagement Markers of Momentum
Source: IDC, 2015
The use of social media by the life science industry has been greatly slowed by concerns over
potential liabilities associated with maintaining regulatory compliance. Issues as to whether companies
are responsible for reporting drug safety events posted to social media sites and potentially illegal
promotion of drugs for unapproved uses have greatly limited the industry's ability to contribute to social
media discussions to date, and regulatory agencies have only provided limited guidance as to what
companies can do. While initial investments have focused strongly on social listening in support of
brand sentiment and competitive intelligence, social media offers significant potential for the industry to
better engage with all key stakeholders, improve compliance for patients taking drugs, and accelerate
patient recruitment in clinical trials. As a technology innovation that remains early in industry adoption,
this area is expected to play a large part in the future of the industry, with most efforts yet to come.
Big Data Platforms
FIGURE 20
Big Data Platforms Markers of Momentum
Source: IDC, 2015
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For the most part, the problem of big data in the life science industry has not yet arrived, with a notable
few exceptions (e.g., ELN data management at Merck). With multiple new data resources on the near-
term horizon (e.g., genomics, EMR, social media, and payer data), the industry has recognized that it
needs to manage the big data issue proactively. With the recognition that technological advances will
likely be insufficient to deal with the rate of data growth, companies are beginning to seek ways to
mitigate big data concerns at their sources, with the hope of reducing the amount of data that needs to
be captured and shared. While it remains to be seen how successful organizations will be in managing
the anticipated big data tsunami, the industry is hopeful that big data will not become a significant
problem in the future.
FUTURE OUTLOOK
While not the simple cure for the life science industry's ills, disruptive technological innovation will be a
strong contributor and enabler of progress in the life sciences over both the near- and long term. In our
view, near-term benefits of technology innovations are mostly focused on operational performance
optimization. IDC expects that over the longer term, the impact of technology and IT will be much
greater and deeper, resulting, in some cases, in fundamental changes to current industry business
models.
Recognizing the complex nature of life science R&D and the ability of technology solutions to deliver
additional value outside of their core applications, this IDC TechScape has focused on the broad
spectrum of technology and IT innovations with a goal of highlighting both the near-term impact and
the longer-term implications of specific technology adoption. The IDC TechScape graphic is expected
to change over time, with individual technologies advancing in adoption and potentially shifting curves
as technologies currently categorized as "transformational" go mainstream and become the new
"incremental" best practices (refer back to Figure 1).
ESSENTIAL GUIDANCE
As it considers the technology and IT consumer perspectives, this IDC TechScape provides a
technology reference snapshot that enables life science technology and IT buyers to quickly assess
how their technology adoption compares with the industry overall while concurrently enabling them to
identify and investigate relevant technologies that should be on their radar today.
Domain-Specific Guidance
Top Pharmaceutical Companies
With hundreds, if not thousands, of clinical trials at all stages of progress, top pharmaceutical
companies also carry forth legacy clinical trial applications that are likely only now transitioning toward
a more unified and streamlined approach to trial execution. In addition, these companies have
significant organizationwide IT infrastructure that is also transitioning as technology enables more
powerful computing and more efficient processes with increased agility.
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Top pharmaceutical companies will likely have to directly consider and contend with all technologies
and processes described in this IDC TechScape. In addition, as many organizations increasingly
virtualize many of their processes, they will still need to deal with these technologies and processes
through their vendors and partners. Foundationally, top pharmaceutical companies should have an
extensible technology road map in place that allows them to maintain a standardized approach to their
technology implementation efforts across their broad ecosystem. Beyond these foundational efforts,
the approaches described in the General Guidance section should apply to the companies' preferred
technology adoption philosophy.
Emerging and Midtier Biopharmaceutical Companies
In most cases, emerging and midtier biopharmaceutical companies should be able to focus their
technology and process road map primarily on functional technologies and processes used in the
clinical trial space, since they have likely made only limited investments in IT infrastructure. In
differentiating these companies from top pharmaceutical companies, emerging and midtier companies
typically depend more heavily on external service providers for their clinical trial efforts (especially
contract research organizations and clinical IT service providers). The increased dependence on
external service providers suggests that vendors supporting life science clinical trials should also
examine their technology road maps relative to this IDC TechScape to ensure that they are capable of
delivering services to their customers in a timely fashion (both functional technologies as customers
increasingly demand these services and infrastructure as increasing operational efficiencies limit cost
growth).
General Guidance
Early Adopters
From an IDC perspective, early technology adopters are more aggressive than the norm, seeking to
gain early benefits from technologies that have the potential to transform the business. In addition,
these organizations routinely seek to foster an open innovation mindset in their people, enabling the
organizations to embrace rather than fear risk. Within the IDC TechScape framework, early adopters
are expected to be at par or ahead on key initiatives within both the incremental and the
transformational categories with an eye toward aggressive implementation of new technology
opportunities as they arise. IDC expects that within their core focus areas, early adopters are likely
significantly ahead of industry adoption progress, especially in the area of transformational technology
adoption:
Based on their increased risk tolerance, early technology adopters should consider emerging
transformational technologies outside of their core competencies for benefits to their organizations.
With organizational efficiency and effectiveness initiatives maturing, early technology adopters should review opportunistic technologies to ensure that progress exceeds average industry
progress with a view toward maximizing both near- and longer-term performance metrics.
Mainstream Adopters
Most organizations are likely to be in the domain of mainstream adopters, with only limited investments
in promising, but unproven, technology innovations outside of their core focus. Mainstream adopters
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are somewhat risk averse with very limited tolerance for failure. Since this IDC TechScape is
normalized to these buyers, technology adoption progress is expected to be aligned for all
technologies with mainstream adopter expectations:
Likely falling into a "fast follower" mindset, mainstream adopter companies should validate that their technology innovation initiatives, particularly with the incremental technology category,
are in line with overall average industry progress.
With a view toward longer-term opportunities, mainstream adopters should consider focusing
their technology innovation budgets on core technologies that reside in the transformational category.
Cautious Adopters
For those organizations that would be categorized as cautious adopters, technology innovation is not a
significant priority when compared with operational issues. Operational efficiency and effectiveness
are foundational drivers within these organizations, and incremental progress in technological
innovation is the norm. Cautious adopters likely lag behind their mainstream peers with regard to
adoption progress in the incremental category and may have little, if any, active technology initiatives
based on technologies residing in the transformational category. Even within the supportive
opportunistic category, cautious adopters are likely lagging behind their peers with regard to
technology adoption, with the exception of those initiatives that can clearly demonstrate near-term ROI
to support improved operational efficiency and effectiveness while concurrently raising no regulatory or
quality concerns:
With ongoing external pressures continuing to threaten the status quo, it is becoming
increasingly difficult to retain traditional business models. Cautious adopters should consider targeted technology investments in areas expected to become near-term issues (e.g., the upcoming data tsunami and effectively collaborating in an increasingly global ecosystem).
LEARN MORE
Related Research
Business Strategy: Disruptive Innovation — Transformational Change Coming in Life Science R&D (IDC Health Insights #HI251770, October 2014)
Business Strategy: Transformational Times — Preparing Life Science IT for the Age of Genomics (IDC Health Insights #HI249557, June 2014)
Cloud-Based Business Transformation: Industry Case Studies (IDC #243275, September
2013)
Perspective: Patient Centricity — The Key to the Future of the Life Science Industry (IDC
Health Insights #HI242630, August 2013)
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Appendix
Interpreting the IDC TechScape Figure
The IDC TechScape study is both a strategic planning tool and a tactical decision-making tool. It's
designed exclusively for technology professionals in IT buyer organizations. This audience includes
CIOs, IT directors, IT managers, and IT architects and IT buyers from within business lines and
functions:
Strategic planning tool. IDC TechScape research offers a view into where a technology exists within its overall adoption life cycle. Technologies in the early stages of evaluation and
deployment are riskier investments than those further along in the adoption life cycle that are already being deployed more broadly. IT strategists can use this information to decide when a technology or group of technologies might be ready for adoption, given their organizations'
preferred level of risk.
Tactical decision-making tool. Because Figure 1 provides insight into where a technology
exists within its overall adoption life cycle and its associated risk, the IDC TechScape can be used to determine whether or not a particular technology should be adopted immediately or at
some point in the future when the adoption risk is less.
IDC TechScape Methodology
This IDC TechScape explores technology and/or management arenas characterized by one or more of
the following:
A single technology that has the potential for huge positive impact in the near future
A general technology area represented by multiple different technologies such as cloud, big
data and analytics, mobility, social business, datacenter, and security
A group of technologies that must come together to support a particular business process or
objective
Supporting technologies that, while not directly driving clinical development, have the potential to create significant competitive advantage
Synopsis
This IDC study uses the IDC TechScape model to provide an assessment of both industry-specific and
industry-agnostic technology adoption supporting the worldwide life science clinical trials market. The
IDC TechScape is an evaluation model based on a comprehensive framework and a set of parameters
that assess a technology's adoption progress relative to one another and to those factors expected to
be most conducive to success in a given market over both the short- and the long term. In breaking
technologies into three major adoption categories, transformational, incremental, and opportunistic,
the IDC TechScape aspires to provide IT buyers with an industry snapshot as to where specific
technologies lie today relative to current industry best practices. In addition, the IDC TechScape
identifies technologies likely to become best practices in the future and their current state of adoption
maturity relative to each other. Within our discussions of individual technologies, we also identify our
analyst's best opinions regarding key momentum factors, highlighted as IDC TechScape Spotlights,
where we rate technologies based on adoption speed, risk, and market interest.
©2015 IDC #254210 23
"Modernizing the clinical trial process requires a confluence of relevant technologies. With this study,
we provide our clients with a way to categorize those technologies and construct an optimal
investment strategy." — Alan Louie, research director, Clinical Development, Strategy and Technology
About IDC
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provide global, regional, and local expertise on technology and industry opportunities and trends in
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