In our work with life sciences organizations, we see a number of trends coming together that create tremendous opportunity.
Thanks to the burgeoning power of digitization over the last several years, the latent potential of AI and machine learning is now being realized. At the same time, we’re seeing the long-promised potential of ground-breaking therapeutics like cell and gene therapy come to market. To leverage this timely convergence of discovery and digitalization, life sciences organizations are merging, acquiring, starting up, and moving into new areas of interest. We’re even starting to see some large, traditional pharmaceuticals expand into cell and gene therapy.
Market demand is creating a powerful pull. Recent events have underscored the need for new life-saving drugs and therapies, generating public and private interest in accelerating the pipeline. In 2020, years of innovation behind mRNA enabled the rapid development of highly effective vaccines. The hope is this platform will accelerate development of other vaccines and targeted immunotherapies for cancer. These advances coincide with the federal government’s aim to “reignite the Cancer Moonshot,” which was first proposed in 2016. The initiative is anticipated to drive a surge of investment and innovation in its goal to reduce cancer deaths by at least 50 percent within the next 25 years.
The discoveries and digitization that make such breakthroughs possible also call for new ways of organizing, thinking, working, and communicating. The areas of product planning, commercialization, and supply chain will change. Government programs will change the way reimbursement happens. The regulatory landscape will be in flux, too.
Across the industry, organizations are realizing that traditional operating models don’t allow for the levels of integration, innovation, efficiency, and speed needed to address the change and leverage the opportunities ahead. In our work with leading life sciences organizations, we see them focusing on five areas for success in these transformational times.
Moving boldly from silos to synchronization.
Whether life sciences organizations are looking to expand their product portfolio or reach out to new markets, business operations must mature their operating model in order to optimize how their people, processes, and technology work together. Companies are looking for more holistic, integrated approaches to operating their business —whether working with healthcare professionals, insurance companies, and patients; contracting with manufacturers; ensuring quality and regulatory compliance; or optimizing every step of clinical development to accelerate speed to market. And, as in every industry that has been impacted by the pandemic, life sciences organizations are keeping an intense focus on their supply chains. Resiliency, including integrated business planning, will be paramount to navigate disruptions in life science’s complex supply chain.
It takes synchronized operations to remain competitive today. Every part of business operations needs to be in tune with the others. The thorniest challenges are in maintaining this synchronization across international borders, ever-changing regulatory structures, and fast-evolving technologies. When companies get their business operations in sync, they free up precious time, talent, and money to focus on bringing breakthrough products to market in less time.
Therapeutic advances will require new commercialization roadmaps.
Advanced medicines such as cell and gene therapies require complex integration and alignment across the organization to maintain patient safety and the chain of identity as the products move through the arm-to-arm manufacturing process. Investing in enterprise planning roadmaps that can support the commercialization journey and scale to meet future demand will make the difference between successful commercial launches or over-extension of critical resources. These new commercialization approaches demand that organizations avoid operational silos, which are common in larger pharmaceutical companies. When synchronized across functions, the likelihood of commercial success for these complex therapies increases.
At the same time, organizations that are launching their first therapy or entering a new class of therapy are challenged with building operating models at just the right level of investment. An operation model that’s too lean will stymie the launch and prevent healthy scaling. A model that’s too “fat” will lead to a launch that’s expensive and inefficient. Commercial readiness requires finding the “just right” operating model that balances growth and maturity of people, process, and technology as the organization scales. This means looking for ways to simplify complex therapeutic operational models and introducing new, supportive elements when new demands arise. It requires starting with the end in mind to anticipate and avoid roadblocks on the path to commercialization.
Better insight leads to more informed product valuations and timelier decisions.
Product planning has never been more conscious of the clock and the calendar. Manufacturers are implementing methodologies and integrating disparate data sets as well as analytic tools in order to decrease the time it takes to conduct clinical trials, advance the product through each development phase, and communicate with regulatory agencies. They’re looking to accelerate all these moving parts, even as they must continuously assess the product’s market viability in a changing landscape: “Does it fit within the portfolio of the type of products we’re best at producing?”, “Is this a market-viable product?”
At the same time, product planning faces new challenges. Recruiting, data management, site logistics and emerging decentralized trials create new complexities. Small changes have always had the ability to create a butterfly effect, adjusting the value of therapies. Now those insights are trackable, traceable, and sometimes foreseeable to make those “go” or “no-go” decisions. The workflows across patients, investigators, specific sites, and clinical operations are intricate webs that are easily tangled. But this web of information is crucial to the continuous market-access analyses that drive key business decisions.
In this environment, it pays to be standardized and intentional about how you measure the value proposition of potential products throughout new product planning—whether it’s done for internal market analysis or regulatory requirements. Astute product planning includes “how to measure,” which is just as critical as “what to measure.” A consistent and accurate data flow enables product valuation that allows people to make crucial decisions as early as possible.
Data and Analytics
Powering up to advance product development and commercialization.
For decades, companies developed applications for specific business units and geographies in silos, with little focus on integrated operations across the organization. The result was disparate data sets, data repositories, and applications that don’t support the needs of the organization from end to end. Life sciences organizations are naturally data-rich, yet they’re often unable to tap into the value of their data or even define what data needs to be extracted.
IT and business sponsor teams understand that having access to data in a common format and context provides the backbone for implementing applications and creating analytic insights across business units and regions. As a result, life sciences companies are focusing on efforts to harmonize master data, introduce data governance discipline, and use AI/ML advances to maximize the value of data and applications across the organization. Results from these initiatives are not always recognized in the short term but become evident when common data formats and context are required to share data across applications, enterprise platforms, or data lakes that will be used for analytics and reporting. Life sciences organizations need to implement data architecture, management, and governance with a deep understanding of the multiple requirements they face as they develop and commercialize their products.
Getting it right means establishing a data hierarchy in a way it can be integrated into platforms or applications both up and downstream of various business processes, building a data structure to access the right data, at the right time, in the right format. Like all of the challenges we’ve mentioned, data and analytics needs to be viewed and supported as a strategic imperative.
Creating an integrated digital infrastructure is key to speed.
Life sciences companies recognize the advantages of communicating and sharing data across user communities utilizing the myriad of platforms available. As technology capabilities have increased, the ability to provide access to data, conduct analyses, and interact with information across channels has resulted in the ability to “streamline” operations with regulatory agencies, supply chain partners, patient participants, and more. To enable this transformation, organizations are moving to the cloud, investing in customer relationship management platforms and infrastructure, and centralizing all their digital assets to realize a fast, seamless data stream.
Done right, this transformation will meet the growing demand by patients, providers, investigators, and regulatory bodies to access accurate data and information quickly and easily. These investments will decrease time for product reviews and approvals, increase efficiencies, and eliminate communication barriers. It will support the decentralization of clinical trials, making participation easier and more diverse. It will reduce the time it takes to process regulatory paperwork, from improving communications to expediting approvals. Inside and out, it paves the way for a much more rapid and accurate information flow.
But smart, streamlined communication is difficult to achieve without the infrastructure to collect, organize, and disseminate information in a customized manner. Ultimately, an organization’s ability to communicate faster and more effectively with all stakeholder groups can only be as robust as its integrated digital business ecosystem. Building this ecosystem requires a holistic approach with attention to content management and digitization, digital asset management tools, customer data platforms, and meaningful CRM tools.
Organizing for Transformational Times
Rallying around collaboration, communication and common purpose.
In order to leverage the opportunities ahead, life science organizations are transforming the way they work. It takes leadership to pilot the journey, together with a company of talented people who join forces across the organization to achieve a business that supports life-saving therapeutics for humankind. Point B puts people at the center of transformation. We bring industry expertise, empathy, and fresh perspective to power up life sciences organizations for sustainable success that’s faster and efficient.