How natural history studies support data-driven precision medicine

Natural history studies play a pivotal role in deepening our understanding of diseases by observing them in their unmodified state. These studies offer invaluable insights by serving as "natural" comparisons for assessing the impact of treatments, thus playing a crucial role during the drug development process and in comprehending how diseases evolve without medical intervention. They act as fundamental benchmarks to gauge the effectiveness of new therapies.

By meticulously collecting data throughout an individual's life—including diagnoses, clinical observations, and patient-reported experiences on quality of life—natural history studies provide a detailed narrative of disease progression and its implications for patients. This wealth of information, gathered over the lifetime of a person, is instrumental in shedding light on the varied responses individuals may have to a disease, paving the way for the creation of more tailored treatment approaches. This article aims to provide a comprehensive overview of natural history studies and explore their significant contribution to the advancement of precision medicine.

What are natural history studies?

Ideally, to purely understand a disease's natural history, researchers would observe a group without any medical intervention. However, from an ethical standpoint, leaving participants without treatment could significantly harm their well-being, making such an approach virtually nonexistent. Typically, these studies monitor individuals who have no further treatment options or compare existing or traditional treatments against new ones and alternative approaches.

The objectives of natural history studies are multifaceted, focusing on:

Understanding disease progression: Particularly for rare diseases, where existing research can be sparse, these studies offer valuable insights into a disease's natural course, aiding in the development of effective treatments and management strategies.

Identifying variability and subtypes: Given the broad spectrum of symptoms and progression rates across individuals, natural history studies are instrumental in identifying disease subtypes and variations, facilitating tailored and more efficacious treatment plans.

Designing clinical trials: The small population sizes typical of rare diseases pose significant challenges to traditional clinical trial designs. Natural history studies inform these designs by defining appropriate outcome measures, criteria for participant selection, and other crucial trial components.

Improving patient care: By gaining a deeper understanding of a disease's progression and impact, healthcare providers can better anticipate and manage symptoms, thereby enhancing patient quality of life.

Both regulatory agencies and investors increasingly recognise the importance of real-world evidence, endorsing natural history studies as a significant element of drug development. These studies can provide baseline data that, when used alongside clinical research, demonstrate the efficacy of new therapies.

Natural history studies are categorised into two primary types:

Retrospective and prospective (longitudinal) studies

• Retrospective studies analyse data from patient records, literature reviews, and other pre-existing disease-specific sources.
• Prospective or longitudinal studies collect data over time, making them ideal for serving as external control groups.

Cross-Sectional Studies

• These studies offer a snapshot of a disease at a particular moment by gathering data at a specific point in time. While cost-effective, they are limited in their ability to establish cause-and-effect relationships.

A hybrid or mixed-design approach can blend elements of both study types, offering a comprehensive understanding of disease progression and impact.

How natural history studies support precision medicine

Natural history studies are a cornerstone for advancing precision medicine, providing the foundational knowledge necessary to tailor healthcare to individual patients with specificity. These insights enable researchers and clinicians to identify biomarkers and disease mechanisms that can predict how different patients will respond to specific treatments. This precision approach moves beyond the traditional one-size-fits-all treatment model, offering the promise of personalised therapies that are optimised for the unique genetic makeup and lifestyle of each patient.

In the realm of rare genetic diseases, where patient populations are small and heterogeneity in disease presentation is high, natural history studies are particularly valuable. Presently, the number of identified rare diseases exceeds 7,000, collectively impacting over 250 million individuals worldwide. Natural history studies can assist in identifying subtypes and patient segments that may respond differently to treatments. This segmentation is crucial for the development of precision medicine strategies, as it allows for the design of targeted therapies that address the specific pathophysiology present in different subgroups. 

Additional benefits of natural history studies in precision medicine include: 

• By understanding the natural course of a disease, researchers can better design clinical trials, selecting endpoints and outcome measures that are most relevant to the specific patient populations, thereby increasing the likelihood of successful intervention and bringing more effective treatments to those in need. The Food and Drug Administration (FDA) has recently published guidance for integrating natural history summaries into drug development, including how they can be used to develop biomarkers. 
• Natural history studies facilitate the evolution of precision medicine by contributing to the development of predictive models. These models can forecast disease progression and treatment outcomes based on a combination of genetic, environmental, and clinical factors. This predictive capability is essential for preventive strategies in precision medicine, allowing for interventions that can delay or even prevent the onset of disease in individuals at high risk. 
• By providing a benchmark for untreated disease progression, natural history studies enable the assessment of treatment efficacy in a real-world context, ensuring that new therapies show statistical significance in clinical trials while delivering meaningful benefits to patients in their everyday lives. 

Natural history studies not only inform the development of precision therapies but also play a pivotal role in ensuring these interventions are genuinely effective and beneficial for patients.

Technological advancements in data collection and analysis

The integration of artificial intelligence (AI) into natural history studies is transforming the way data is collected and analysed, offering improvements in both efficiency and accuracy. These studies, traditionally reliant on extensive data gathered over prolonged periods, are now benefiting from AI-driven methodologies for more streamlined operations.

Enhanced data collection: AI technologies, particularly through wearable devices and mobile applications, facilitate the continuous, real-time monitoring of an array of health metrics. This includes not only physiological measurements—such as heart rate, blood pressure, and glucose levels—but also behavioural data encompassing physical activity, sleep patterns, and adherence to medication regimes. Such a comprehensive and uninterrupted flow of information offers a far more detailed and accurate overview of a patient's health status than what intermittent assessments can provide.

Advanced data analysis: AI's ability to manage and interpret vast datasets is unmatched, enabling the identification of patterns and correlations that may elude human researchers. Through machine learning algorithms, AI can analyse complex, multi-layered data to extract critical insights on disease progression, identify potential biomarkers, and understand varied responses to treatments. This capability fosters a deeper, more nuanced comprehension of diseases' natural trajectories.

Beyond data collection and analysis, AI's application in natural history studies provides several advantages:

• Predictive modelling: AI's predictive models can anticipate disease progression, foresee potential complications, or predict outcomes of treatments. Such foresight aids in pinpointing patients at higher risk, customising interventions accordingly, and designing clinical trials that target the most responsive patient demographics.
• Facilitated patient recruitment: By analysing vast electronic health records (EHRs), AI algorithms can efficiently identify prospective study participants who match specific criteria, accelerating recruitment while ensuring a representative and diverse participant base.
• Enhanced patient engagement and compliance: AI-driven tools, including chatbots and apps, offer personalised interactions to reinforce medication schedules, appointments, and data submission, alongside providing support and information to boost adherence to study protocols.
• Data standardisation and integration: AI aids in harmonising data from varied sources, making it uniform and analyzable across multiple study sites, an essential factor for the success of multicentric studies.

AI is transforming natural history studies, significantly elevating the scope and quality of medical research through superior data collection, analysis, and a host of other benefits, marking a pivotal shift towards more effective and impactful healthcare solutions.

Natural history studies in action

Natural history studies have been instrumental in shedding light on a range of rare diseases, including Duchenne Muscular Dystrophy (DMD), Spinal Muscular Atrophy, and Huntington's disease. These research efforts have been crucial in uncovering the origins and mechanisms underlying these conditions, significantly enhancing our knowledge base and fueling advancements in treatment development. 

A prime example of such pioneering work is the Duchenne Natural History Study conducted by the Cooperative International Neuromuscular Research Group (CINRG). Recognised as the most comprehensive prospective natural history study on DMD thus far, it spanned over ten years and involved 440 participants aged 2 to 28 years, drawn from 20 centres across nine countries. This extensive study, along with other key research efforts like the Treat-NMD's global DMD database, Universitair Ziekenhuis Leuven, CureDuchenne, iMDEX, and ImagingDMD, has significantly contributed to our understanding of DMD. These initiatives, among others, have been pivotal in advancing our comprehension of these complex diseases, paving the way for the development of more targeted and effective treatments in the future.

Conclusion

Natural history studies play a crucial role in the progression towards precision medicine, offering detailed insights into diseases by observing their natural development over time. By utilising advanced technologies like AI for more efficient data collection and analysis, these studies significantly improve our understanding of how diseases evolve and affect individuals differently. This knowledge is instrumental in developing personalised treatment strategies and enhancing patient care, particularly for those with rare diseases. As we move forward, the contributions of natural history studies to medical research are invaluable, providing a solid foundation for more targeted and effective treatments that are tailored to meet the specific needs of patients.