Biopharma companies should consider a new, integrated approach to evidence-generation strategies to better demonstrate the value of therapies to all stakeholders.
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Understanding and improving patient outcomes through the generation of evidence is one of the most critical activities of an innovative biopharmaceutical company. Evidence that a therapy is both effective and safe is the primary requirement. But that is just the start. Clinicians need evidence to support optimal treatment decision making. Payers need evidence to support patient access. And patients need evidence to understand how a therapy might meet their needs. Increasing volumes and types of available data raise the potential to generate this evidence, but if it is to be realized, biopharmaceutical companies may need to change their approach to evidence generation, working far more strategically and collaboratively than they do at present.
The status quo in most companies is one in which each function draws up its own evidence-generation plan. These may well be included in a master, asset-level plan. Yet they tend to be bolted together, not integrated, and so are a far cry from the integrated evidence-generation plans (IEPs) being developed by a handful of companies. From the outset, IEPs take into account the evidence needs of different functions and geographies across the life cycle of an asset, and then collaboratively determine how to meet them using a broad range of methods and data (Exhibit 1). The end result is a significantly more efficient and effective use of resources in pursuit of better patient outcomes.
The case for change
The role that evidence generation plays among key stakeholders is evolving and becoming increasingly important.
Regulators are beginning to consider evidence beyond randomized controlled trials (RCTs). They recognize that real-world evidence (RWE) can help to accelerate drug development or indication expansion, minimize exposure of patients to placebo control arms, and help to offset rising drug-development costs. As a result, regulators around the world are beginning to incorporate RWE into their approval processes.1 In a few instances, RWE has served as a primary source of evidence for the approval of therapies. The US Food and Drug Administration (FDA), for example, approved the expansion of indications for Pfizer’s Ibrance to include male breast cancer on the basis of data from electronic health records and insurance claims.2 More commonly, RWE has been used to augment evidence from RCTs, rather than accepting RWE on its own merit.3 The growing importance of RWE is nonetheless clear: roughly one in three new drug applications and biologic license applications in 2019 offered RWE as supportive evidence.4
Payers need to make increasingly complex decisions about coverage and reimbursement. Against a backdrop of rising healthcare spending, aging populations, and rising numbers of innovative, high-cost treatments, the strategic generation of evidence can help clarify the clinical, economic, and humanistic impact a new therapy might have versus the standard of care, bearing in mind that different payers will have different evidence needs. For instance, Spain and Italy prioritize evidence of budget impact, the United Kingdom stresses cost effectiveness, while Germany emphasizes using the right standard of care, as well as safety and efficacy in patient subpopulations, as the comparators.5
Providing the right evidence can prove powerful. In Japan, post-launch evidence showed that Boehringer Ingelheim and Eli Lilly’s Jardiance, a drug for treating type 2 diabetes, reduced the risk of cardiovascular events.6
Clinicians need more support.The more new therapies that launch, the more clinicians need to understand how they differ, how best to use them, the predictors of response, and whether to switch patients to alternative therapies. Understanding clinicians’ concerns and then generating the evidence to address them is therefore critical, and biopharmaceutical companies are increasingly turning to RWE for assistance. For example, a retrospective review of real-world data from the US VICTORY Consortium demonstrated a favorable safety profile for Takeda’s Entyvio in treating ulcerative colitis and Crohn’s diseases.7
Patient centricity is growing.Companies must consider patients’ needs, preferences, and concerns throughout the clinical development process and generate evidence to address them, hence the importance of patient engagement. At least ten EU member states have a mechanism for patient engagement in their health technology assessment process, mostly at the advice and decision-making stage.8
The results of patient engagement can be impressive. Amgen’s Aimovig for migraines, for instance, was approved by the FDA with the help of a new, patient-reported instrument to assess how migraines were affecting patients’ ability to function. The information that patients reported was successful in serving as secondary end points.9
Why integration matters
Together, these trends make a strong case for why an integrated approach to generating evidence is valuable. An IEP identifies evidence gaps across functions, geographies, and the asset life cycle to meet the needs of external and internal stakeholders. And it aligns priorities and resource allocation to fill those gaps. As a result, an IEP can hold down drug-development costs for an asset’s primary indications and the costs for indication expansions through the judicious use of RWE in lieu of costly RCTs. It can also avoid the duplication of evidence generation within the company or even, as sometimes occurs, the purchase of similar data sets. And the collaborative approach can more rapidly identify and fill critical evidence gaps. Increasing numbers of companies are using them to great effect:
- One company’s IEP for an oncology therapy identified no fewer than 18 critical evidence gaps that were not previously spotted by individual functions. Some gaps—such as those involving data to support payer needs in specific geographies, data to support patient adherence, and data on optimal treatment duration—needed to be addressed urgently. Others, such as supporting follow-on indications and improving patient outcomes with combination therapies, related to longer-term needs.Further, the IEP process helped focus and prioritize resources, such as by reducing the number of areas of interest for investigator-initiated research from more than 50 to 15. It also identified opportunities to generate data more effectively by means of collaboration—by medical supporting the design of health economics and outcomes research (HEOR) studies, and by HEOR and clinical working on post hoc analyses of clinical trial data for health technology assessment submissions and payer dossiers.
- A biopharma company initiating an IEP for a pipeline cell therapy uncovered high-priority evidence gaps on the importance of manufacturing turnaround time on patient outcomes. This resulted in prioritizing seven manufacturing studies, which ultimately led to reduced vein-to-vein time. Further, the process highlighted the need to demonstrate safety and efficacy versus competitors given the increasingly crowded landscape. The IEP team identified a specific disease registry as the optimal way to generate this data and was able to catalyze leadership to approve the registry approximately six months earlier than expected.
- An IEP identified a follow-on indication with high potential to be developed through RWE rather than sponsored trials as originally proposed—the result of insight sharing between medical, clinical, and commercial teams.
- In a McKinsey survey of four IEP teams across functions and geographies, all respondents said the IEP had improved strategic alignment on evidence needs across stakeholders and led to the development of an effective execution plan. Over 80 percent said the IEP had increased synergies in cross-functional evidence generation.
The challenges of an integrated evidence-generation strategy
Companies that choose to transition to a more integrated evidence-generation strategy face three initial obstacles. Functions and geographies are siloed, hampering communication and collaboration; there is a tendency to focus on generating evidence to win near-term regulatory approval in key markets, rather than evidence to support the asset throughout its life cycle; and data are fragmented, making it hard to know what evidence is available and what might be needed. Understanding these challenges can help companies devise a sound plan to overcome them.
Functional and geographic silos
Integrated evidence-generation strategies depend upon transparency and coordination, with functions sharing data and information on stakeholder needs to identify evidence gaps, align on priorities, and plan how to most effectively fill the gaps. But this can be challenging for functions accustomed to focusing on their own, specific deliverables, with minimal input from other functions. And care is required to ensure legal compliance in how data are shared between functions such as commercial and medical.
Geographic coordination is also needed, though not the norm. Companies headquartered in the United States, for example, tend to use US-focused evidence-generation strategies. The fact that most drugs are first launched there and most evidence is generated there—plus the commercial importance of the US market—helps explain this focus. So while there is often strong US participation in developing evidence-generation strategies, other major markets are not always adequately consulted. Different languages and time zones pose further challenges to collaboration. The end result is a so-called global evidence-generation plan that often fails to address many regional or local needs and sometimes the existence of regional or local plans that run counter to the global strategy.
A near-term focus
A tendency to focus on generating near-term evidence is another obstacle to an integrated approach. Across the industry, companies concentrate on generating evidence from RCTs to obtain regulatory approval, which is a critical near-term goal. Yet evidence is needed to inform therapy use along the entire patient journey, which means that other functions—medical, HEOR, and market access, for instance—need to provide input when clinical trials are designed to enable optimal patient use and access once therapies are approved. (Exhibit 2).
A near-term focus can also diminish support for investigator-initiated trials (IITs) for development-stage assets. The perceived or actual regulatory risk associated with conducting IITs prior to approval means biopharmaceutical companies often choose not to fund them until after launch, at which point clinical development priorities shift to different development-stage assets. Yet postapproval asset evidence plans can benefit tremendously from continued support and input from clinical development.
More broadly, a focus on the near term can prioritize the launch indication and launch geographies for a development-stage asset over longer-term needs. Hence, evidence-generation plans may not fully reflect the potential to use RWE for life-cycle management, or additional secondary end points or comparator arms in trial designs to allow approval or uptake in additional geographies.
Rarely is there a complete data catalog for an asset or disease, as different data sit with different functions and geographic units. In addition, each function typically uses its own system to track study execution, be that with the help of an ad hoc Excel spreadsheet, shared database, or sophisticated portfolio tools. And there is no guarantee that data are kept up to date—seldom is there a single accountable owner of the data even within a single function. As a result, obtaining a complete, cross-functional view of the data being generated for a specific asset or disease is hard, making it difficult to leverage all knowledge, know where evidence gaps might lie, or prevent the duplication of efforts to generate new evidence.
Making the shift
Companies that make the most progress implementing integrated evidence-generation strategies take account of these challenges. To that end, they do four things. They make sure the planning process is cross-functional and begins early in the asset life cycle. They foster change management to further encourage collaboration and break down functional and geographic silos. They establish governance processes that support a new way of working. And they invest not just in data platforms and advanced analytics capabilities but also in skills that facilitate cross-functional engagement.
Institute a cross-functional planning process two to three years before launch
Ideally, companies should begin building an IEP for an asset two to three years before launch. At that time, the strategic direction of the clinical development program will be clear but there remains an opportunity to expand evidence generation to support the asset along the entire patient journey and to support planned life cycle indications, not just the launch indication.
The work is typically led by global medical affairs, which is well placed to integrate the perspectives of all internal and external stakeholders. In some organizations, however, R&D plays a lead role prelaunch and then hands the task over to medical affairs postlaunch. Likewise, while in most organizations IEPs are distinct plans that synergistically build on clinical development plans (CDPs) to support an asset’s launch and full life cycle, in some organizations the CDP evolves into an IEP as the product progresses in development.
The typical IEP process generally entails the following steps (Exhibit 3):
- Convene a cross-functional IEP team and develop and agree on the work plan: The medical-affairs lead assembles the team and introduces the process and framework for the IEP.
- Develop strategic context:Clinical, medical, launch, and life-cycle management strategies need to inform the IEP.
- Assemble an evidence catalog:Develop a centralized catalog of current and planned evidence-generation efforts that can be shared across functions, with appropriate safeguards in place, such as those that will keep commercial and medical affairs legally compliant.
- Identify and prioritize evidence gaps: Identify, without imposing any initial constraints, potential evidence gaps across the patient journey and then prioritize those gaps that are both feasible to fill and that will have the most potential impact. Be sure to consider the evidence needs of both internal and external stakeholders across geographies.
- Develop plans to fill priority evidence gaps: Think beyond RCTs and consider and weigh the trade-offs between different types of data and approaches (for example, secondary analyses of existing data sets, Phase IV trials, investigator-initiated trials, HEOR studies, RWE, advanced analytics). Tactically, ensure that the right combinations of internal and external expertise are leveraged to design, plan, and execute studies for optimal value creation.
- Integrate input from additional stakeholders, then sign-off:Additional input can strengthen the plan. Stakeholders in different markets, as well as cross-functional partners that were not part of the IEP team, can provide insights, as can external stakeholders, often as part of an advisory board. A cross-functional governance body should give final approval to the plan (as discussed in “Establish effective governance,” below).
- Keep the plan updated: IEPs should be living documents that reflect changes in the asset strategy and study-execution updates. Strategic updates are made after major data readouts. Executional ones, such as updates on study status, occur every six to 12 months.
Foster a change-management program
To develop an IEP, people will need to change the way they work—hence the need for a change-management program to break down functional and geographic silos and any cultural resistance. A change-management program should include the following elements:
- Leadership role modeling:Executive sponsors, such as the CEO and head of global medical affairs, should be seen and heard supporting the new approach and driving change, as should the heads of each function.
- A compelling value story: A change story that makes clear the rationale for integrated evidence generation should be cascaded through the organization, potentially through town halls, asset-level workshops, and one-on-one meetings. Showcasing evidence of how the approach has benefited brand teams will also encourage adoption.
- Reinforcement mechanisms:Personal-development plans that encourage integrated evidence generation—key performance indicators (KPIs) for global disease teams that include the development and updating of IEPs, for instance—can accelerate adoption. Publicly celebrating the success of an IEP can also serve as an important reinforcement mechanism.
- Confidence and skill building:Formal training to understand the new processes and governance will build capabilities as well as confidence in the new approach.
Establish effective governance
Cultural resistance can be an issue if clarity on leadership and governance is lacking.
There is much to clarify. Who, for example, is best placed to lead cross-functional planning, and who has final authority to decide which projects to prioritize? Should a scientific, medical, commercial, or hybrid body be responsible for governance? How frequently should an IEP be renewed? And who has signing-off rights for new IEPs or updates? While in some companies the cross-functional asset team signs off on the IEP, the ideal is a cross-functional, executive-level governing body. Bear in mind, however, that the ideal functional leader and the makeup of the governance body may change depending on the stage of development of an asset and the input required.
Whatever the choices made, they need to be set out clearly in a governance framework that eases the transition to the new approach. Importantly, there should also be agile funding mechanisms in place to ensure that prioritized studies are adequately resourced.
IEPs represent a fundamental shift in the way evidence is generated across functions, geographies, and phases of the asset life cycle.
Build new skills and capabilities
Companies wishing to adopt an integrated approach to the generation of evidence across the entire portfolio will need to build new skills and capabilities.
Data and analytics. For a successful evidence-generation strategy, companies will need an integrated data solution that seamlessly links the data catalog of completed studies (translational data, clinical trial data, and RWE, for example) with ongoing or planned studies across functions (with role-based access control, traceability, and auditability). Such a solution not only facilitates the rapid development and updates of IEPs but also can be used to power an analytics engine to generate hypotheses.
Talent. Attracting, retaining, and building the right talent will also be key. Experts will be needed in areas such as non-registrational data generation. But to overcome cultural roadblocks, soft leadership skills that facilitate cross-functional buy-in and engagement are critical too. There may also be a shortage of strategic or creative thinkers who can look beyond their asset or function to disease or franchise-level needs and identify opportunities for innovative methods of evidence generation. Training and coaching may be required to build the skills that lead to high-quality, integrated evidence-generation strategies and their execution.
Agile delivery. A playbook for generating integrated evidence-generation plans helps to ensure a consistent approach and speeds development, with periodic updates allowing newly discovered best practices to be codified and shared. For maximum impact, this can be paired with an agile project-management function dedicated to coordinating and communicating integrated evidence planning across the organization.
IEPs represent a fundamental shift in the way evidence is generated across functions, geographies, and phases of the asset life cycle, and as such will entail considerable effort to implement. But growing numbers of companies are discovering it is an effort well worth making in the pursuit of improved patient outcomes.
ABOUT THE AUTHOR(S)
Palak Amin is a consultant in McKinsey’s Philadelphia office; Sarah Nam is an associate partner in the Washington, DC, office; and Lucy Pérez is a senior partner in the Boston office, where Jeff Smith is a partner.
The authors wish to thank David Champagne, Alex Davidson, Mattias Evers, Tomoko Nagatani, Brandon Parry, Lydia The, and Jan van Overbeeke for their contributions to this article.