Digitizing the Life Sciences Value Chain
The healthcare and life sciences industry is undergoing a wholesale transformation. In every corner of the world, healthcare and life sciences companies — which include pharmaceutical, biotech and medical device manufacturers —face similar challenges. While each region has different expectations about how medical products and therapies should be developed and delivered, companies are seeing growing healthcare demand, medical technology advances and a fundamental shift in who pays for their products.
The question for CIOs is how to lead their organizations beyond their focus on providing treatments for diseases and toward becoming a valued part of a healthcare ecosystem – one that is focused on population health and well-being.
A key part of this effort is digital technologies, such as software-defined networks, hyperconverged cloud, big data and mobility – and most importantly, digital patient engagement. Digitization is making a vast impact at every point along the pharmaceutical value chain, from the R&D lab, through distribution channels to the pharmacy shelf. And digitization will play a crucial role in medicine itself with low-cost genomic scanning, machine learning and analytics.
The new role of the CIO is to lead their organization’s digital journey all along the value chain.
The Digital Shift
Organizations have long used information technology to more efficiently execute business processes through sales force automation, enterprise resource planning (ERP) software, financial systems and the like. Now, technologies like advanced analytics, intelligent software, cloud computing and the Internet of Things are driving the next wave of advanced business process automation.
See Also: Life Sciences Review
Meeting regulatory requirements is a long, complex process that influences every aspect of operation, from R&D all the way to the sales team
Today, IT has evolved far past its former role in back-office support and has become a core element of the process to provide holistic care.
Sensors that collect, analyze and monitor patients for responsiveness and compliance to a prescribed treatment plan are creating new models of personalized medicine. Similarly, digitally empowered patients have a wealth of information available to them through websites, health applications and wearables that enhances their confidence in evaluating therapies and health benefits. Analytics is turning that information into insights that provide personalized care for patients and a much clearer picture of health outcomes for providers.
The wealth of online information and the prevalence of social media also mean companies no longer have full control over information about their products and services. Accurate and inaccurate information abounds. Experiences with products are being shared. And while that sounds like trouble, on the whole this is (or can be) a positive development.
On one hand, it can be a challenge for companies to make sure patients are getting the right information about products from credible sources. On the other hand, patients sharing vast troves of information about devices, medicines and therapies can provide a rich source of intelligence for gathering safety information.
Many life sciences companies and healthcare providers are embracing these new ideas and models with gusto. But one major obstacle stands in the way — an aging, outdated value chain.
New Care Models Require New IT Models
The practices and processes that companies use to govern the development of medicines and devices is the medical value chain. While these practices have worked for many years, they have not evolved in decades – and they lack the transparency, connectivity and efficiency to adequately support an industry transformation that relies on a much freer flow of data. Creating a value chain that supports these characteristics is essential if life sciences companies plan to maintain a competitive pace of innovation.
Things have to change in an environment where personalized medical devices and precision medicine are supplanting standardized “blockbuster” products.
Applying digital technologies to the life sciences value chain represents a transformative strategy that achieves several urgent goals: 1) it enables capital-efficient, agile innovation; 2) it improves industry business model and process agility; and 3) it capitalizes on an increasingly integrated digital healthcare ecosystem.
Consider the impact of such a change on the regulatory process. Meeting regulatory requirements is a long, complex process that influences every aspect of operation, from R&D all the way to the sales team. Digitizing mission-critical regulatory content and automating the regulatory process is a clear way to improve efficiency and reduce risk today while setting the stage for greater gains to come.
Supply-chain management is another important area that can and should be digitally transformed, using advances in the Internet of Things and mobile technologies to closely track products from manufacturing to the end of the distribution channel. This move leads to improved transparency and responsiveness to demand and risks. It offers a way to optimize time-to-clinical-site in clinical trials, time-to-patients across the globe, and is an important method for reducing the risk of counterfeit products.
These are just a couple of examples of a modern, digital value chain — a cloud-based, hybrid platform that both provides new digital health functionality and surrounds and enhances legacy systems. It is a platform designed to provide reliable systems support, from business development to mission-critical processes. It is one that expands elastically, tolerates failure, and builds in cybersecurity that continuously evaluates the environment’s risk, compliance and regulatory obligations.
An Essential Step to Secure the Future
Considering the speed and scope of change brought by digital health, it’s hardly surprising that many organizations are struggling to adapt. Some trends, such as the evolution of patient-centric care and population health enablement, are challenging norms that have existed throughout the life of organized care systems. Treatment plans are shifting from episodic care supported by medicines and devices to lifelong care pathways supported by an ecosystem that includes life sciences companies and healthcare providers.
Driven by changes like these, business models that were built on high patient volumes and frequency of treatment are now shifting to payments based on health outcomes. Inevitably, these trends will have an impact on demand for devices, therapies and medicines that may differ significantly from what’s offered today.
The good news is that demand is growing. The challenges are that it’s growing in new directions – managing wellness, not treating illness.
As a result, life sciences companies should gladly embrace the opportunity they have to become more deeply embedded in the care continuum. Patients will benefit from access to the best products available, while life sciences companies gain greater access to health outcomes and patient feedback — a valuable repository of information that can drive the next cycle of product development.
Making this happen requires flexible and interoperable computing resources, a task for which the current IT status quo is not well suited. Digitizing the life sciences value chain is a critical step forward that’s needed in order to realize the promise of all the breakthroughs and innovations that are sure to follow.
And it requires CIOs to think beyond running the business, and start changing the business – all the way along the value chain.
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