An in-depth understanding of the disease or condition for which a drug or biologic is being developed is an important component of drug development. However, in some situations, the detail about the disease or condition may be collected alongside the studies of the compound under development. This may be particularly true for rare diseases where patients and data are limited. The FDA in the 21st Century Cures Act1 has specifically noted the importance of natural history in understanding the full spectrum of the disease manifestations including “describing genotypic and phenotypic manifestations and identifying and defining distinct subpopulations affected by a rare disease or condition”. In the overall scheme of product development, gaining this knowledge ahead of or early in the development program is a small investment that can pay large dividends.
A natural history study provides the foundation for gaining this understanding. A natural history study is an observational, epidemiologic cohort study designed to collect information on patients who have been diagnosed with a specific condition or disease. Ideally, patients are identified at the time of diagnosis, and risk factors, treatments, and outcomes are documented over the course of their disease. A natural history study is a way to estimate disease incidence or prevalence (helpful in estimating market size), describe the demographic characteristics of the patients with the disease (helpful in recruiting a representative study population), document changes in severity over time, occurrence of concomitant conditions, and usual treatment patterns (all helpful in developing study protocols and case report forms), and to understand survival. Study design options for a natural history study are varied. Information can be compiled from a literature review or by conducting a study using a large automated database, a cross-sectional survey, a retrospective chart review, or an ad hoc prospective longitudinal cohort or registry. Some Sponsors have considered the placebo groups of randomized clinical trials as one source of natural history data.
Selection of the best design (or designs – in some instances, a portfolio of studies may provide the best insight) depends on several factors. Literature reviews are only feasible if historic cohorts exist. Often, however, if using the literature to estimate disease incidence or prevalence, estimates can vary widely depending on the methods used to collect the data, and the literature may lack sufficient detail to understand the reasons for the variation. If there are conflicting studies that show the frequency of a condition varying from 0.1% to 25% in the same population, then decisions on market size cannot reliably be made. Cross-sectional surveys can be used to estimate the prevalence of a condition. If the surveys are assembled to cover a heterogeneous, broad population, with patients at various levels of severity and at various time points in the spectrum of their disease, then some profile of disease characteristics and changes over time might be constructed. A carefully selected sample of medical charts may provide valuable insights into natural history, as long as the information required to understand the risk factors, historic and current treatments, and disease severity has been reliably documented in a similar fashion in medical charts across multiple practices in varied settings. Similar caveats apply to natural history studies conducted using electronic health records or medical claims databases. Prospective cohort studies or registries, while more costly than studies of existing data, can be the most efficient and effective design for capturing a sufficient level of detail to inform decision making.
Regardless of the design, the information to be documented on disease natural history serves many purposes during the drug development process and beyond. In the early stages of drug development, as indications for use are being evaluated for a new compound, an understanding of disease incidence or prevalence is important in estimating the potential market size for the product. This can assist in prioritizing the indications for development. Designation of an orphan condition depends on estimating the prevalence of a disease. Similarly, if it is determined from the study that available treatments are limited, characterization of an unmet medical need can also help direct the development process.
Understanding the disease for which a compound is being developed provides a great deal of important information that can be applied to effectively design the clinical development program. What safety risks are expected by virtue of the disease being treated? Does the disease itself put the patient at risk of liver toxicity? Or cardiac events? If so, then it is critical that such events be accurately captured during the clinical trials in a standardized way, for both the active therapy arm and the placebo group, so that the risk due to the disease (which should be evident in the placebo group) can be understood in the context of the new therapy under study. Something as fundamental as design of case report forms can benefit from this information. The FDA, in its Premarketing Risk Assessment Guidance,2 acknowledged that “certain kinds of adverse events are not likely to be detected or readily reported by patients without special attention. When a drug has a potential for such effects, additional testing may be appropriate, e.g., CNS effects.” A similar philosophy should be adopted early in drug development in regard to adverse effects of the disease itself. The background morbidity or mortality due to the underlying condition must be factored into sample size calculations for the clinical trial program. In order to evaluate a drug with an adverse event profile that may add to the background rate of specified adverse events, the clinical trial must be designed to have sufficient power to detect pre-specified increases over the background rates related to the disease itself. The importance of understanding the background risk due to the underlying disease is also an important concept in the European Risk Management Plan.3
Establishing and following a cohort of patient with the disease to be treated can also assist in the development and/or validation of biomarkers, companion diagnostics, and meaningful clinical outcome measures to be included in the pivotal trials required for product approval. This can lead to developing and selecting outcome measures that are more specific or sensitive to changes in the manifestations of the disease or more quickly demonstrate safety or efficacy than existing measures.
How do you know that your clinical trial population represents the general population of patients with the disease without having an understanding of the patient profile? Are there demographic subsets of the intended population who may be at greatest risk? If so, how should these patients be included in the clinical trial program? Relying on clinical research sites only can distort the profile, making the clinical trial results less than optimally generalizable to the population to be treated in clinical practice after product approval. An added benefit from structuring the clinical trial to be more representative of the presumed population who will be treated with the marketed product is that a more generalizable clinical trial population might allow the product to be labeled for broader use.
A careful evaluation of patient profiles, and current treatments for the disease, can anticipate interactions of concern. What are the likely concomitant conditions that occur in patients with the disease? How are these conditions treated? This can alert researchers of possible drugdrug interactions that should be proactively assessed, which is important not only for concomitant biopharmaceutical therapies, but also herbal products and dietary supplements. Understanding the progression of disease can identify critical milestones where the new therapy can have the most impact. Not only is this important from an efficacy standpoint, but also in relation to other outcome measures which may differentiate the new therapy, such as quality of life.
This philosophy is consistent with ICH E2E:4 pharmacovigilance planning, in effect, requires understanding of disease natural history. In order to understand important potential risks, limitations of the human safety database, and populations potentially at risk or that have not been studied in the clinical trial program, one must understand the patient profile, the effects of the disease, the likely concurrent conditions, and other epidemiologic considerations about the indication for drug use.
Understanding the variability of the patient population is important in directing the types of patients who should be recruited for the clinical development program. While the inclusion and exclusion criteria of patients in the clinical trials must be restricted in some ways for practicality and efficiency, it is important to understand which segments of the patient population are represented in the clinical program and which have been intentionally or inadvertently excluded. This information can be derived from the natural history study. The product’s effectiveness and safety in the unstudied segments is a deficiency that should be remedied after product approval with enrollment of a heterogeneous patient population into the natural history study.
An effective approach is to institute a disease registry during the drug development period to gather natural history data, and then to extend the registry after product approval to understand how the new product fits into the treatment armamentarium. Treatment switching patterns can be assessed, characteristics of patients initiated on therapy can be examined, and the safety profile of the new product under actual use conditions can be documented and compared with the data from patients with the same disease who have been treated with other therapies, or not treated at all. Developing an exposure cohort within the natural history study extends the value of the initial study throughout the product’s lifecycle.
FDA in its draft guidance for industry regarding rare diseases has indicated that, although natural history studies are not required, a welldesigned study may help in designing an efficient drug development program.5 For all the reasons cited above, natural history studies bring value to the drug development program from the planning phase through commercialization.
References
- 21st Century Cures Act, Pub. L. No. 114-255, 130 Stat. 1033 (2016).
- Food and Drug Administration. Guidance for Industry: Premarketing Risk Assessment. March 2005. http://www.fda.gov/downloads/RegulatoryInformation/Guidances/ ucm126958.pdf.
- GVP Module V- Risk Management Systems (Rev 2) of Good Pharmacovigilance Practice (GVP) (EMA/838713/2011 Rev 2). European Medicines Agency and Heads of Medicines Agencies. March 2017.
- International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. ICH Harmonised Tripartite Guideline: Pharmacovigilance Planning E2E. Current Step 4 version, 18 November 2004. http://www.ich.org/fileadmin/ Public_Web_Site/ICH_Products/Guidelines/Efficacy/E2E/Step4/E2E_Guideline.pdf.
- Food and Drug Administration. Guidance for Industry: Rare Diseases: Common Issues in Drug Development. August 2015 draft.