There has been a growing trend in the pharmaceutical industry to concentrate on the concept of Integrated Evidence (IE). The former approach of many compartmentalized and mainly sequentially applied approaches to evidence generation has led to conflicting priorities and unclear decision making that has ultimately not always been in the best interests of patients and other stakeholders. Integrated Evidence includes phase 1–4 clinical trials, PK/PD trials, and real-world evidence (RWE) studies as well as activities designed to investigate disease and clinical practice.

Integrated Evidence Plans (IEPs) are strategic tools to comprehensively plan evidence generating activities across various functions over a product’s lifecycle to meet the diverse needs of healthcare stakeholders. They serve many key purposes including a holistic approach to evidence, cross-functional collaboration, long-term planning, stakeholder alignment, resource optimization, and regulatory and market access support. The types of evidence considered are varied and meant to be all-encompassing. Examples would be clinical trials, modeling studies, RWE studies, literature reviews and evidence synthesis, and network meta analyses [1, 2].

Between 2011 and 2021, there was a ten-fold increase in the number of new Food and Drug Administration (FDA) approvals based, in part, on data and evidence gathered in clinical care, community and home-based settings (e.g., natural history studies; patient and electronic health records; claims data and registries) [3]. A separate study forecasts a nearly 15% annual growth rate in the real-world data (RWD) market between 2022 and 2026 [4].

There are many factors driving this promising trend in the use of IE for decision-making for pharmaceutical products. Among health care and clinical research stakeholders, for example, there has been increasing recognition of the need to efficiently translate scientific evidence on investigational treatments gathered in controlled clinical trial settings into optimal use within clinical care settings [5]. An extensive body of research in the literature consistently demonstrates a highly inefficient translational gap between clinical research and clinical care [6, 7]. The translational gap is also the subject of the growing field of implementation science that relies on evidence using qualitative methods, hybrid clinical trials, and RWD [8]. The use of RWD in IEPs in particular offers the advantage of including data on patients who are not typically included in RCTs.

Patient communities and advocacy groups, particularly in rare diseases, have echoed the important role that RWE can play in reducing translation delays with appropriate consent and privacy protection and therefore enable faster access to medicines [9]. Many believe that using all available evidence – scientific, observational and personal – will enhance public and patient trust and engagement and will more rapidly identify and provide the most clinically-meaningful and relevant outcomes as safely as possible [9]. Indeed, this leads to the concept of integrated evidence (IE) that combines evidence from all possible sources, including RCTs, into one integrated evidence plan (IEP) that seeks to optimize an evidence package that will satisfy the needs of all stakeholders simultaneously.

An IEP is used to identify evidence needs for the relevant stakeholders (internal and external). At early stages in the drug development process, the IEP focuses on shorter term goals like proof of concept, mechanism of action, the scientific story, epidemiology, unmet needs, and the performance of the competition (or standard of care) while also optimizing success in planning and execution of clinical trials. At later phases, IEP can be seen as an enabler of external decision-making. As drug development proceeds, the IEP is updated by incorporating new information and adapting to new challenges.

At the same time, in an ongoing effort to bring innovation to patients in an efficient way, pharmaceutical and biotechnology companies are looking to optimize clinical trial performance. A recent study, for example, reported a tripling in the number of procedures performed and a seven-fold increase in the volume of data collected per pivotal trial during the past 15 years. In that same period, clinical trial durations, participation drop-out rates, and the mean number of protocol amendments increased significantly [10]. The use of RWE holds promise in helping to optimize clinical trial planning, performance and cost through early identification of target populations and endpoints/outcomes; better investigative site selection and targeted recruitments [11].

The unprecedented growth in applications and technologies that capture and more easily access patient health information has improved the ability to integrate data across multiple clinical research and clinical care systems. Ultimately this cross-platform interoperability and integration will better inform and monitor more comprehensive and flexible patient care [12]. The Food and Drug Administration (FDA) and the European Medicines Agency (EMA) recognize the important role that these data management solutions can play and they have been encouraging the use of IE to gather more complete evidence demonstrating safety and efficacy, accelerate approvals and to enable a continuous learning health system [12].

Despite growing recognition and use of RWE, the adoption of integrated evidence in drug and biologic registration programs during the past decade has been muted. Pharmaceutical and biotechnology companies – organizations that fund the vast majority of clinical trials of new medical therapies – face several barriers [13]. It has been difficult, for example, to coordinate evidence generation activities as it is a shared responsibility among a fragmented collective of functional areas including research, clinical development, clinical operations, medical affairs, data management and health economics and outcomes [14]. Sponsor companies have expressed concerns about the level of investment required to fully support the generation of integrated evidence and the value proposition in doing so [15, 16].

To assist research sponsors in evaluating the return on investment, we developed a framework to assess the value of evidence, with the goal being to allow the comparison of different IEPs to enable data-driven decision making in terms of evidence needed to better meet patient needs.

This paper presents a novel value framework to develop a patient-relevant IEP along with relevant expected net present value (eNPV) calculations to quantify its value. An eNPV analysis is a commonly used, and widely accepted, risk-adjusted financial modeling technique for industrial investments. To our knowledge, the systematic use of a value framework combined with a quantitative component has not been performed previously. It is our hope that this analytical structure will inform decisions regarding commitment to and investment in the use of RWE and IE as they have the potential to have a significant impact on improving patient outcomes.