Drug developers are increasingly using cell and gene therapy approaches to develop treatments for rare diseases as well as personalized treatments for cancer patients. Natural history studies play a critical role in these programs by addressing knowledge gaps that would otherwise slow down or even derail the development.
Natural history studies are research studies that aim to understand the progression of a disease over time and without intervention, e.g. treatment. They follow a group of people who have a disease or are at risk of developing one to learn more about the symptoms and possible complications, identify potential risk factors, describe patient characteristics, usual care treatment patterns and the natural evolution of a disease.1 Natural history studies are especially important in cases where the gold-standard of clinical studies, the double-blinded randomized clinical trial, cannot be used.
Natural history studies are based on comprehensive patient data, both retrospective and prospective, and can include new data streams; e.g., genetic testing and biomarker data to better characterize and gain insight into patient populations and expand the use and value of these studies.
Natural history studies - a quick overview
Different types of natural history study designs exist: retrospective natural history studies use pre-existing data from patients with the disease, while prospective studies use new data collected during the study period by following the participants over a long period of time.
In cross-sectional studies, data from different groups (i.e. a cross section of the population) are collected at a specific point in time, while in longitudinal studies data from the same population is collected repeatedly over time. Either of these studies can be pro- or retrospective.2
Different study types are suited for different purposes, retrospective and cross-sectional studies can inform planning of future studies, prospective and longitudinal studies are generally richer in information and are used to support clinical trials.
Why are natural history studies critical for cell and gene therapy programs
Cell and gene therapies are developed primarily for patients suffering from rare diseases or cancer. Both disease fields face a common set of challenges:
- Life-threatening or very severe diseases make it unethical to use a placebo-controlled study where half of the patient population is not given the drug but serves as a control arm.
- Small patient populations make it impossible to generate statistically significant data in placebo-controlled trials, even if it were ethical. Lack of patients is not just a problem in rare disease, where patients, by definition, are rare, but also in precision oncology, where biomarkers are used to stratify patients into small subgroups that benefit from different treatment approaches.
- Lack of knowledge about a disease makes it difficult to develop a treatment. Cancers are caused by a large number of genetic and environmental factors and our understanding of how these factors work together to generate cancer is still evolving. In both rare diseases and precision oncology there is often little information available for researchers and clinicians to understand what is an appropriate outcome measure linked to efficacy.
These challenges have real world consequences for both patients and pharmaceutical companies. Clinical development can be significantly slowed down by lack of clear and meaningful endpoints and burdensome trial design. When every day means progression for these devastating diseases, any delay in getting potentially life-saving or -altering treatments to patients can be catastrophic.
Natural history studies can fill knowledge gaps in our understanding of a disease. They make it possible to design more effective cell and gene therapy trials, and provide a baseline against which the effectiveness of a potential treatment can be measured. In some cases, natural history studies can take the place of the control arm in a traditional study.
Data published by the FDA show the importance of natural history studies: between 2000 and 2019 the FDA approved 45 drugs that used external control data in their benefit/risk assessment. In 44% of these cases data from a retrospective natural history study were used.3
Using natural history studies can therefore de-risk clinical development of cell and gene therapies and shorten clinical development timelines.
Developing natural history studies for cell and gene therapy programs
Natural history studies need to be carefully planned and executed. The FDA’s Office of Tissue and Advanced Therapies suggest the following high-level process:4
- Start the study early to allow enough time to capture clinically meaningful outcomes, enroll enough subjects, and to fully capture the variability over the course of the disease.
- Review the data available in the literature to understand what is already known about the disease. In addition, speak with disease experts that you identify via your literature review. These experts are best qualified to fill you in on the existing research and can introduce you to patients who might agree to be part of your study.
- Develop a protocol for a retrospective cross-sectional or longitudinal natural history study using the information you have collected in your literature review and conversations with experts.
- Try and design a clinical trial or even a full clinical program based on the retrospective natural history study you performed. This will quickly highlight gaps in your knowledge that need to be filled before clinical development can begin.
- A prospective longitudinal natural history study is the best way to collect the missing data and fill these knowledge gaps.
Since all of these steps except literature review and expert interviews - which can be done concurrently - are sequential, the whole process is generally very time consuming.
Harnessing data capture for effective use of natural history studies
New data streams such as real-world data and biomarker information are now increasingly used to supplement natural history studies and are becoming an integral part of these studies.
Genetic biomarkers can predict disease severity and course as well as reaction to treatment. They can also be used to stratify patients into subpopulations with specific characteristics that might benefit from different, targeted treatments. Real-world data (RWD) can inform the development of cell or gene therapies. RWD can be collected retrospectively and prospectively from sources such as electronic health records, medical claims and billing data, data from product and disease registries, patient-generated data, and data from mobile devices.5
In order to leverage this data it’s essential to have proper data capture and management processes in place and eliminate data silos. Organized systems for collecting data about individuals who either suffer from the same disease or have a risk factor that predisposes them to a health-related event, allow for a data driven approach to cell and gene therapy development.
Cell and gene therapies provide a promising avenue for treating patients with cancer and those with rare diseases. Traditional clinical trials might not be possible when developing those therapies and in these cases natural history studies are a valuable alternative that can fill knowledge gaps and ensure that the clinical development can proceed and life-saving treatments become available to patients.