From adaptive licensing to adaptive pathways: delivering a flexible life-span approach to bring new drugs to patients

Abstract

The concept of adaptive licensing (AL) has met with considerable interest. Yet some remain skeptical about its feasibility. Others argue that the focus and name of AL should be broadened. Against this background of ongoing debate, we examine the environmental changes that will likely make adaptive pathways the preferred approach in the future. The key drivers include: growing patient demand for timely access to promising therapies, emerging science leading to fragmentation of treatment populations, rising payer influence on product accessibility, and pressure on pharma/investors to ensure sustainability of drug development. We also discuss a number of environmental changes that will enable an adaptive paradigm. A life-span approach to bringing innovation to patients is expected to help address the perceived access vs. evidence trade-off, help de-risk drug development, and lead to better outcomes for patients.

Figure 1

Treatment window of opportunity. The schematic illustrates why the time of access to a promising treatment is relevant to patients with any serious condition, independent of the time course of the disease. Treatment windows of opportunity are shown for a few exemplary serious conditions ranging from very short (metastatic melanoma) to extremely long disease courses (primary hypercholesterolemia and mixed dyslipidemia). Estimates of windows are symbolized by bold horizontal lines, the start‐ and endpoints are described for each condition; the lengths of the lines are for illustration purposes only, and are not based on epidemiological data. Note that the time of the endpoint of the treatment window of opportunity may not be known for many health states (e.g., hypercholesterolemia) and the window period may in reality end long before the time of the events shown in the figure (e.g., because irreversible vascular damage has occurred before the MACE occurs). Nonetheless, all patients will eventually reach the endpoint of their treatment windows of opportunity; this is illustrated by the right‐alignment of the horizontal lines. The thin lines underneath each bold line are intended to show that each year a new cohort of patients with the same condition emerges and will reach the endpoint of their window 1 year after the previous cohort. This is true for all conditions where the year‐on‐year incidences remain relatively stable and in the absence of other emerging treatment options. The dashed vertical lines illustrate that a difference in time to market access of, for example, 2 years (year –1 vs. year +1) will have the same effect on patients with metastatic melanoma as for patients with hypercholesterolemia, insofar as the two annual cohorts of patients who are at the end of their treatment window of opportunity will gain or lose an opportunity to benefit from promising treatment. It follows that the time course of a disease per se should not be a driver of the evidence vs. access debate. The obvious but rare exceptions to this rule will be conditions with highly variable incidence rates. This is illustrated by the last example, flu (or similar) pandemic, where urgency of access is primarily determined by the anticipated time to peak global spread. The two different treatment window of opportunity lines under the “hypercholesterolemia/dyslipidemia” heading are intended to show that subgroups of patients within the same broad condition may have very different windows. FH: familial hypercholesterolemia; MACE: major adverse cardiac events.

Figure 2

The transition from “big‐to‐small” towards “small‐to‐big” as proposed under an adaptive pathway. Under the blockbuster strategy, sponsors would initially aim to obtain a license and coverage population that is as broad as possible (symbolized by the large blue circle). Effects in identifiable patient subgroups that are nested within the broad population (symbolized by small colored circles) would be addressed subsequently, often for purposes of differentiation against incoming competitor products. By contrast, an adaptive approach would initially aim to show positive benefit–risk and added value in a defined subpopulation, followed by additional clinical trials and studies in other subpopulations. A potential beneficial effect of this staggered approach is use of more targeted extrapolation (where justified) and nontraditional (e.g., observational) studies which in turn may reduce the total number of patients required to enroll in interventional clinical trials. The total treatment‐eligible population will grow in sequential steps over time (symbolized by the light blue circles).