A digital future for the life sciences industry

Sunil Rao, global managing director of technology for Accenture’s Life Sciences’ practice, explores the role of digital in the future of the life science industry.

In today’s digital age, the pharmaceutical industry is adapting to the ‘new normal’ after the peak of the patent cliff. Life sciences companies as well as governments and private payers are trying to control costs, while scientific advances create opportunities to improve patient outcomes. The future high-performing companies in this industry (including pharmaceutical, biotech, medical technology, consumer health and generics companies and their regulators) are facing up to this challenging environment by extending business models to provide evidence of outcomes, developing specialised treatments to better target specific patients and the most challenging diseases and conditions and gradually changing mind-sets from products to services. To achieve these changes, they are increasingly collaborating seamlessly with partners and extending availability of treatments to consumers in new markets. Such changes will be accelerated through developments in digital technologies. It is time for every C-suite executive to develop a digital mind-set by considering the seven key technology trends outlined below.

1. Relationships at scale

The life sciences industry needs to rethink how it can deliver more personalised services to move beyond the traditional rep-based selling model, and provide a customer experience that is integrated, compelling and individualised across all interactions. Patients are already using online and digital media to learn about and discuss their conditions, as can be seen in online communities like PatientsLikeMe.com.

Life sciences companies now have the opportunity to use digital technologies such as analytics and social media to build trust, understand health care practitioners and patients better and create compelling experiences based on increasingly digital interactions. GSK, for example, used social listening to understand parents’ fears on vaccine usage, which informed their campaigns to dispel myths and fears around vaccinating children.1 The multichannel approach is already being used in developing markets – for example, a biotech pioneer in India uses a text messaging service as an educational tool for diagnosis and treatment of diabetic patients.

2. Design for analytics

Life sciences companies have vast quantities of research and patient data, but often not the ‘right data’ or a way to access it to make key strategic decisions. It’s not the volume of data that is important, but the ability to derive insights from it that can lead to better products and services. Implementing data standards and curating data to enable it to allow different analytics to be run, is key to their ability to analyse information.

“GSK, for example, used social listening to understand parents’ fears on vaccine usage”

Designing for analytics is more than simply adding data requirements to a software or process. It is blurring the lines between the Life sciences business processes and Information Technology functions. For example, the concept of value management – understanding the value of a new product on trial through design and data collection early in its development – has cross-functional impacts.

3. Data velocity

As important as collecting the right data is the ability to match the speed of decision to speed of action, and to quickly absorb and act on data. This can help improve competitiveness and even increase revenue. Sales reps can have access to accurate data compiled across internal and external sources on their mobile devices. Marketing executives can see the impact of campaigns engaging healthcare providers across multiple channels.

In Research & Development, as clinical trials focus more on specialty therapies and personalised medicines, closer monitoring and a more rapid response to results helps improve outcomes and speeds up regulatory approval. Data velocity strategies are likely to take two approaches. The first is to build new capabilities to rapidly absorb and digest data, matching real-time insight to real-time opportunities. The second approach is to capitalise on hybrid models which blend in real-time data with existing data on an ongoing basis to enhance real-time insight with historic insight.

4. Seamless collaboration

Fostering the right environments between colleagues and partners to allow creativity, productivity and networking across geographical and company boundaries supports innovation and operational excellence. Within the life sciences industry in particular, research scientists must work even more closely with those in commercial functions to identify patient populations and design trials that will garner the support of payers and providers, and deliver distinct value to patients. To ensure availability of products across global markets, companies must also work closely with their network of supply chain partners. Scientists and knowledge workers, often working in different locations and organisations, must be able to collaborate seamlessly.

Enterprise collaboration tools (including web conferencing, messaging and social networking) and knowledge management tools (including document databases, and shared intranet / extranet repositories) foster environments that enable innovation and problem-solving. As an example, one major global life sciences company began using an enterprise-wide social network tool as a mechanism for communicating with its sales force, replacing weekly bulletins and an intranet landing page.

“Scientists and knowledge workers, often working in different locations and organisations, must be able to collaborate seamlessly.”


Increasingly, industry consortia are developing cross-industry platforms to help seamless collaboration between industry partners and cloud based technology providers are delivering technology which help integrate global supply chains and provide companies with visibility needed to maintain secure supply.

5. Beyond the cloud

Cloud computing has gone from an intriguing idea to a core capability in just a few years. Already well-established in commercial areas of the business, leading Life Sciences companies are approaching new system architectures with a “cloud first” mentality and vendors are responding with vertical cloud services, specifically targeted to Life Sciences’ needs.

Current adoption by pharmaceutical companies in R&D has been limited to pilot and niche projects. Regulatory restrictions as well as a strong desire to protect intellectual property have limited its use. But requirements for large data sets and associated computing capacity, as well as collaboration across entities make R&D a prime candidate for cloud technologies. We see the adoption of cloud technology as a key trend in the coming decade. In areas such as bioinformatics2-5, next-generation gene sequencing4-6, and molecular imaging and modelling, cloud offers a scalable, cost- effective and high-performance computing environment.

6. Software defined networking

Software Defined Networking (SDN) will become an essential enabler for the industry as companies strive to become digital businesses. The technology decouples the network functions from the intricacies of the underlying hardware and enables true technology virtualisation, something that companies have been seeking for a number of years. Just as with the virtualisation of hardware before it, the virtualisation of the network promises to make IT far more cost-effective, agile and dynamic for life sciences companies, enabling collaboration across different stakeholders, enabling expansion through mergers & acquisitions and globalisation, and improving regulatory compliance throughout the enterprise.


“…it’s no longer possible to separate “the technology” from “the business”; the two are inextricably intertwined.”


7. Active Defence

Securing intellectual property and maintaining control of critical regulated components is a battle as hackers target life science companies. Taking an active defence approach moves a company from reactively monitoring to proactively understanding patterns and adapting responses. It is incumbent upon the executive leadership team to be stewards of this new approach. They must recognise that it’s no longer possible to separate “the technology” from “the business”; the two are inextricably intertwined.

In conclusion, the next few years is a crucial phase for the life sciences industry with companies buffeted by market pressures on one side and regulatory demands on the other. Business leaders must now set out strategic initiatives to drive changes in the context of a digitally enabled world. In every company, IT will have to become a strategic competency woven through the enterprise – in particular, it will need to ensure the company can absorb technological advancements so that it can continue to grow, innovate, and derive insights from an increasingly quantified world.


1. http://blogs.wsj.com/cio/2013/05/01/glaxo-mined-online-parent-discussion-boards-for-vaccine-worries/

2. http://research.microsoft.com/pubs/140453/mtags.pdf

3. http://www.biomedcentral.com/1471-2105/13/315

4. http://aws.amazon.com/lifesciences/

5. http://aws.amazon.com/publicdatasets/


About the author:

Sunil Rao is Global Managing Director, Accenture Life Sciences, Technology Lead and Life Sciences APAC lead. Rao has been with Accenture for 10 years and is responsible for complex global system integration programs and large global application outsourcing engagements.

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