Driving Digitalization in Biopharma R&D: Which direction ... · digital health technology, New...

Driving Digitalization in Biopharma R&D:

Which direction should you take?

Patient Inspired. Outcomes Driven.

2 | Driving Digitalization in Biopharma R&D

Which direction should you take? | 3

Across the biopharmaceutical industry, the convergence of science and technology into an era of New Science1 is helping create opportunities to develop more novel products, faster than ever before. Bringing together the best in science and digital health technology, New Science will help biopharmaceutical companies achieve better patient outcomes, improve patient engagement, and fuel new growth. A key component is technology—creating even more pressure to improve digitalization from discovery to commercialization.

The innovation-intensive biopharmaceutical industry has been on the cusp of a digital transformation for years. The innovative technologies that would enable the industry to make this change are readily available; however, few companies in the life sciences industry have successfully adopted new technologies at scale across research and development (R&D) functions. More recently, the rise of a global pandemic has highlighted the need for digitalization for business continuity and virtual data access— for employees, collaboration partners, and patients.

Certain segments of the life sciences industry are also attracting substantial investment from global tech giants, including Amazon, Apple, Google and Microsoft—who are leveraging artificial intelligence (AI), analytics2, and other technologies in efforts to reshape traditional product development and patient care models.


Technology is advancing at a such a rapid pace that today’s life sciences industry leaders are challenged to stay informed, let alone identify the right solutions and implement at scale. BenchSci, an AI-company that regularly tracks and updates a list of startups that are using AI and machine learning to research and develop drugs, started their list with 37 companies in November 2017, growing to more than 230 as of April 2020.3 This doesn’t include the companies that have been acquired by the tech giants, such as the Google-owned DeepMind.

Nature published a DeepMind study in January 2020 that demonstrates how AI-powered research can drive and accelerate new scientific discoveries. The DeepMind system, AlphaFold, is used to predict protein structures using large genomic datasets.4 The protein models it generates are reportedly much more accurate than what was previously possible, which will enable insights into the function of proteins and could lay the groundwork for a truly quantum jump in structural ideation and utility determination for new therapies.

On the clinical development side, Microsoft announced a new Clinical Trials Bot in 2019 that will make it easier for patients and their doctors to find clinical trials related to a specific illness. When the Bot is searched for studies5, it suggests links to trials that will match a patient’s needs. Biopharmaceutical companies can also use the Bot to find subjects to participate in their studies—a critical success factor for the advancement of any clinical trial.

When will life sciences companies make the turn to embrace digitalization as a fundamental driver of innovation and business growth in our new world?

Paving the way


In early 2020, Oxford-based Exscientia was the first company to put a drug molecule invented entirely by artificial intelligence into human clinical trials.6 The new compound, designed to help patients with obsessive-compulsive disorder, reached the human clinical trials milestone in just 12 months, compared with the typical four-and-a-half year path for drug development.

As technologies continue to mature and the industry shifts its focus to New Science, our research finds the biopharmaceutical industry at a crossroads. When will life sciences companies make the turn to embrace digitalization as a fundamental driver of innovation and business growth in our new world?


Checking the signposts

34%$11 billion – $25 billion



3%$751 million – $1 billion

5%$501 million – $750 million

5%Cannot disclose

6%>$25 billion

23%$250 million – $500 million

Company headquarters

Annual revenue

To better understand the current adoption and impact of digitalization on biopharmaceutical R&D, Accenture conducted a comprehensive study in 2019, collecting information from 250 life sciences industry respondents. Specifically, Accenture surveyed executives at various levels and functions throughout R&D, across a wide range of company sizes and geographic locations.

APAC6%

North America40%

Europe54%


Moving toward a clear destination The industry sees the value of digital

We found:

Staying in one lane While digital pockets exist, digitalization at scale is elusive

Tapping the brakes Risk-aversion is an impediment to progress

The survey focused on four areas related to the implementation and adoption of digital technologies in biopharma R&D: strategy, value, progress, and barriers to adoption. Some of the questions were mirrored from an Accenture 2016 research report titled, Industry at a Crossroads: The Rise of Digital in the Outcome Driven R&D Organization, to gauge progress and shifts in the way life sciences companies have been approaching digitalization within R&D.

At the outset, we believed biopharmaceutical companies would report seeing the value of digital but anticipated that industry adoption would be slow in gaining real momentum. We also expected to find evolving industry viewpoints around the value of digitalization and what is standing in the way of progress. In broad strokes, those expectations were validated by the data. However we were surprised by the difference between the expected value of digital in R&D and the degree to which organizations have moved to capture that value.

As we reviewed the results, four findings emerged from this survey that provide insight into the current state of digitalization in the biopharmaceutical industry.

Navigating the curves Companies can overcome operational and cultural impediments


In the 2016 Accenture Industry at a Crossroads study, one in four respondents felt digital capabilities would help drive patient outcomes and improve R&D productivity. Fast-forward to those responding to the survey in 2019, and we have seen a significant, nearly 200%, rise in the response to a similar question. Now, 72% believe digital will drive success in achieving key strategic R&D imperatives, while no respondents perceived digitalization as having a potential negative impact.

The three “strategic imperatives that could be impacted by digitalization that were selected most frequently by respondents”:• Be more focused on patient outcomes• Improve R&D productivity• Revitalize the pipeline by enabling breakthrough

science

In support of these imperatives, the respondents noted specific opportunities to create real, measurable value, such as enhancing decision making, collaboration with other companies, managing data across the enterprise, and improving the clinical patient experience.

The strong industry response goes beyond the theoretical. We found a number of significant responses to specific opportunities to create real, measurable value:

These results leave no doubt that the potential value of digitalization is apparent to R&D organizations. Despite this finding, the survey shows that digital has not been adopted at scale.

FINDING #1 Moving toward a clear destination: Digital is increasingly perceived as an enabler to achieve R&D imperatives

of respondents said using real world data (RWD) across R&D would enhance decision-making

reported that open collaboration with other companies would improve R&D outcomes

believed the ability to better manage data across the enterprise could deliver measurable business value

felt that improved digitalization would improve the patient experience in clinical trials


FINDING #2 Tapping the brakes: Risk-aversion is impacting digitalization While some areas within R&D perceive themselves as further along in the digital adoption journey, the fact remains that less than 50% of respondents across all R&D functions report having achieved their desired state of digitalization.

Why doesn’t adoption match the level of value expectation? One factor that stands out is an aversion to risk. A full two-thirds of respondents to our survey believe an aversion to risk in their organization is preventing them from fully embracing digitalization. Notably, in companies with market caps above $10B, that number jumps to 75%.

This is further supported by respondents’ status of adopting digital across R&D. Specifically:

The industry’s hesitation to take its “foot off the brakes” is slowing the adoption of digitalization and translating into activity that does not follow a clear vision or roadmap.

36%of companies are adopting digital as a key strategy in R&D

of the respondents are exploring how digital technologies can enable R&D

continue to take a “wait-and-see” attitude, observing how others are benefiting from digital before embarking on their own exploration

36%49%49%


FINDING #3 Staying in one lane: Digitalization is happening in silos Our experience has shown that all life sciences organizations have moved to adopt some form of digitalization, regardless of region or size. However, we find that companies are struggling with how to scale those digital capabilities. Far more often than not, we have observed that an R&D function (e.g., clinical, pharmacovigilance, regulatory) will focus on select digital use cases to meet a need at a point in time, all without an eye towards repeatability and extensibility.

Our industry observations were supported by the survey results. The majority of respondents (88% overall) note that digitalization is happening—but not broadly across the R&D functions. Results indicate it is instead being implemented in silos that exist inside their organizations; we see that bias toward silos reinforced by the proliferation of niche life sciences products and services from technology companies and service providers.

Specifically, our survey found that:• Less than half of respondents say that digitalization

is being driven enterprise-wide by the C-suite. Where it is occurring, it is instead being driven by individual R&D functions.

• Only 41% of respondents outside of North America report that digitalization is being driven by the C-suite. In North America, the response is higher at 60%, but still striking when we find in the same survey, digitalization is noted by nearly three quarters of respondents as a success factor in achieving key strategic imperatives for the business.

This cautious and incremental approach has resulted in widespread digital pilots, proofs-of-concept, and minimum viable products (MVP), but has generated few success stories of digitalization at scale. Collectively, R&D organizations have made sizeable investments in digital over the past several years, but without strategic alignment across the enterprise, they have yet to see the benefits from the repeatability and extensibility of those investments.

In a question exploring if digitalization is being driven across the enterprise by the C-suite

Digitalization is happening in silos

There is strong alignment on the importance of digitalization strategy across the R&D organization

41%41%

60%Agreed that digitalization is being driven across the enterprise in North America

Agreed with that statement outside of North America

60%


In addition to the impediment of risk aversion we noted in Finding #2, our research found several operational (that which is inherent to operating the business) and cultural (driven by the people of an organization and their shared assumptions, values and beliefs) opportunities to accelerate the adoption of digitalization.

The top three barriers to digitalization reported by survey respondents, in addition to risk aversion, are: • Ability to measure value: Nearly two-thirds (60%)

of respondents agreed that they struggle to measure the success of digitalization given its novelty in biopharma R&D. Without clear metrics to measure the impact of digital within R&D, executives are less likely to invest in emerging technologies—particularly if traditional methods have worked well for them in the past.

• Ability to invest: 60% of respondents state that they are insufficiently funded to undertake digitalization. For many, it is considered too financially risky to explore digitalization at scale without the ability to quickly demonstrate or quantify the value, while at the same time disrupting a functioning process.

• Access to talent: 46% cited lack of access to IT resources as preventing them from implementing change and 34% reported an inability to attract the right skills and talent. Without the right talent, innovative and new technologies won’t be implemented or activated to their full potential.

FINDING #4 Navigating the curves: Companies can overcome operational and cultural impediments

are struggling to measure the success of digitalization so far

do not have the budget available to fully realize plans for digitalization

say there is a lack of IT resources to implement digital technologies

are not able to attract the right skills and talent


Industry at a crossroads: stay on the current path or move from experimentation to scale?

Will these companies stay on their current path of experimentation, or will they find a path to accelerate to digitalization at scale?

It is clear from our survey results that the desire exists to further adopt digital technologies, a desire that we expect is greater even today given the desire to accelerate clinical development to solve global crises and better enable virtual solutions for both employees and patients. With courage and thoughtful execution, the industry could break free from the inertia that appears to be holding it back. Our observations and experience working with leaders in other industries prove that the change will happen. What we don’t know is the pace, who will set that tempo, and who will ultimately take the lead?

For those who want to set the pace, we see these steps as critical to the acceleration of R&D digitalization:

MAKE IT A STRATEGIC PRIORITY by creating an R&D digital “North Star”—a clear goal for digitalization that is tied to the organization’s R&D strategic objectives and aligned to an enterprise-wide digital strategy. Is it to create end-to-end data connectivity across the enterprise? Is it to improve access to the right data at the right place and time to enable R&D imperatives? Define success and gain agreement across key stakeholders to ensure the organization is chasing the same finish line.

ASSESS AND ADDRESS THE FULL SCOPE OF CHANGE by considering the organization’s business and organizational goals, current data and technology landscape, and the company’s appetite for investment and change to help determine the order and pace of transformation. If a cultural shift is needed, attempts to push forward without addressing that need first could doom the plans for full-scale digitalization.


This survey revealed that nearly three quarters of biopharma R&D organization’s executives see digitalization as a key enabler of success. While there are some challenges to overcome, they are not insurmountable if addressed with the support and direction from an actionable and visionary digital strategy for R&D.

Today, with product pipelines having pivoted from a primary focus on small-molecules to a more diverse set of modalities, and at a critical moment when technology could drive much-needed speed and access, it’s time for the industry to pivot toward digitalization to create new sources of value and better serve patients around the world.

MAKE IT A TEAM SPORT AND BREAK DOWN THE SILOS between the functional areas in the organization. Collaboration, cross functional data strategies, and data sharing platforms will be a critical enabler for the ability to move beyond digital pilots and experiments. Those companies that encourage digital collaborators find their way to success. In another study we did in 2019, AI: Built to Scale, we found that 92% of companies that treated the adoption of AI technologies as a ‘team sport’ were classified as ‘strategic scalers,’ or companies that are committed to truly scaling technological investments.

LEARN HOW TO FAIL FAST by establishing a robust digital use-case pipeline that allows for abandoning the losers and quickly picking winners to progress from rapid design sprints into prototyping. Do all of this with the upfront intent to create reusable and scalable digital solutions that can be embedded into relevant processes across the R&D enterprise.

PROVE THE VALUE OF YOUR INVESTMENTSby keeping your eye on the North Star. From the beginning, determine how you will measure success and use those metrics to build a case for sustainable digital investment. Highlight the examples where multiple functions are collaborating— and driving digitalization—in new ways. It’s about creating momentum, showing value, and keeping your eye on scaling your success.


PATIENT-OUTCOMES FOCUSED: We refer to a company as ‘patient-outcomes focused’ when its stated value proposition centers on delivering outcomes-based health and therapy management services, which are tailored to and improve the clinical outcomes and quality of life for each individual patient. This is usually realized through connected devices, sensors, services, social engagement and other ‘aware’ solutions.

DIGITALIZATION: Digitalization is leveraging technology to change a business model or process to invoke new value-producing capabilities. It is not, simply moving from analogue to digital.

VALUE: Value is the benefit gained from the change through digitalization, seen as one or a combination of increased return on investment, cost reduction, improved reputation in the marketplace, or increased agility.

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.

ARTIFICIAL INTELLIGENCE: Artificial intelligence, sometimes also known as machine learning, is the theory and development of computer systems being able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

ECOSYSTEM: The complex and interconnected network of internal resources (e.g., information technology, procurement, security) and external resources (e.g., independent software vendors, content providers, consultants, product and service providers) that contribute to achieving the goals of an organization.

CULTURAL BARRIERS: A cultural barrier is a rule or expectation within an organization (e.g., leadership bias, fear of retaliation) that prevents or impedes someone from achieving a task or goal.

OPERATIONAL BARRIERS: An operational barrier is the presence of a business reality (e.g., lack of available funds or a specific technology or tool) that prevents or impedes someone from achieving a task or goal.

Definitions

For Accenture’s survey of 250 industry leaders, we provided the following definitions to respondents. Each respondent was required to read the following definitions prior to starting the survey to put the terms in the context of the study.

About Accenture Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. We combine unmatched experience and specialized capabilities across more than 40 industries — powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. With 509,000 people serving clients in more than 120 countries, Accenture brings continuous innovation to help clients improve their performance and create lasting value across their enterprises. Visit us at www.accenture.com.

About Accenture Life Sciences Accenture’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.

References1 https://www.accenture.com/hk-en/insights/life-sciences/

new-science

2 https://healthcareweekly.com/how-the-big-4-tech-companies-are-leading-healthcare-innovation/

3 https://blog.benchsci.com/startups-using-artificial-intelligence-in-drug-discovery

4 https://www.nature.com/nature/volumes/577/issues/7792

5 https://www.bloomberg.com/news/articles/2019-03-01/microsoft-built-a-bot-to-match-patients-to-clinical-trials

6 https://www.ft.com/content/fe55190e-42bf-11ea-a43a-c4b328d9061c

Contact

TOM LEHMANNManaging DirectorAccenture Life [email protected]

KATIE MIINCHSenior ManagerAccenture Life [email protected]

PETRA JANTZERManaging DirectorAccenture Life [email protected]

Copyright © 2020 AccentureAll rights reserved.

/accenture_life_sciences

@AccentureLifeSci

This article 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.

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