In the intricate landscape of healthcare, patients with rare diseases often face a unique set of challenges. With approximately 11,000 rare diseases affecting almost 400 million people worldwide, the rarity and complexity of these conditions can lead to isolation and difficulties in accessing specialized care. However, the advent of artificial intelligence and remote accessibility technologies is beginning to transform the patient experience, offering new avenues for participation and empowerment.
The Struggle for Rare Disease Patients
The World Health Organization defines a rare disease (RD), sometimes called an orphan disease, as a disease that affects fewer than 65 per 100,000 people. Although a single RD may be rare, RDs collectively are not. Despite the name and diverse disease phenotypes, an estimated 10,800 RDs collectively impact more than 400 million individuals worldwide, constituting approximately 5% of the global population. Diagnosis and treatment of RDs frequently lag behind common conditions due to healthcare providers’ unfamiliarity with these diseases, often resulting in delayed or incorrect treatments. Consequently, patients often endure prolonged diagnostic journeys, with an average time to diagnosis of 6 years, and even longer for marginalized individuals. This journey termed the diagnostic odyssey, entails navigating numerous specialist visits, tests, and hospitalizations, leaving patients feeling isolated and unsupported.
Even after receiving a diagnosis, patients with RDs often encounter limited or non-existent treatment options, with available treatments frequently being prohibitively expensive. The approval process for drugs targeting RDs has been significantly expedited, particularly following the enactment of the US Orphan Drug Act in 1983. As of 2022, the US Food and Drug Administration (FDA) approved 882 orphan drug designations resulting in at least one FDA approval for use in 392 RDs. Nonetheless, this constitutes less than 5% of known RDs, leaving many RD patients without viable treatment options.
For the orphan drugs used in treating RDs, the median cost exceeds USD 200,000 at market entry, resulting in substantial out-of-pocket expenses for patients and their caregivers. The exorbitant cost of these drugs presents significant financial barriers to patient access, emphasizing the urgent need for a more sustainable and equitable pricing framework to ensure affordable treatment access. Some argue that pharmaceutical companies establish monopolistic prices, protected by patent rights, to maximize profits, and others assert that these high prices are necessary to recoup research and development (R&D) and production costs from a limited patient pool.
Moreover, the dispersed nature of the RD patient population poses challenges in enrolling, engaging, and retaining patients for research and clinical trials that are essential for developing new therapies. Many RDs still need to be better understood due to insufficient scientific studies on disease processes, natural history data, and clinically meaningful endpoints. Without quality patient data, designing and evaluating clinical trials become risky to invest in. Consequently, these challenges further diminish the success rate of drug discovery for RDs.
Global Collaboration: Key to success
To overcome the challenges in diagnosing and providing affordable treatment for all RD patients, sharing information and knowledge among multiple stakeholders, and coordinating joint activities, is the key. Access to data from diverse patient populations and multiple countries could significantly enhance interpretation capabilities, aiding in diagnosis and accelerating the identification of accurate biomarkers, defining disease phenotypes, increasing knowledge of disease natural history, and promoting patient engagement and research collaboration.
Multiple private-public partnerships across nations, such as Rare Diseases International (RDI), the International Rare Disease Research Consortium (IRDiRC), the Global Commission, and the Undiagnosed Diseases Network International (UDNI), are dedicated to these objectives. A recent example is the Rare Disease Cures Accelerator Data Analytics Platform (RDCA-DAP), an FDA-funded initiative providing centralized and standardized infrastructure to expedite RD characterization, effectively accelerating therapy development across RDs.
Expanding awareness, advocacy, and outreach is crucial to ensure inclusivity, especially for those with lower socio-economic status, limited literacy, minority ethnic backgrounds, indigenous populations, and individuals residing in underserved and marginalized locations.
Artificial Intelligence (AI): Promising Tool
With its ability to process vast amounts of data and recognize patterns, AI is already aiding as a co-pilot to physicians in accurately diagnosing RDs. Machine learning algorithms can analyze genetic information, medical images, and patient records to identify markers that human experts might overlook. This helps accelerate the diagnostic process and enhances the precision of treatment plans.
Furthermore, AI-driven platforms facilitate the aggregation of high-quality patient data globally. This data convergence is invaluable for researchers and pharmaceutical companies, enabling them to understand the natural history of RDs and aid in developing targeted therapies. AI also plays a pivotal role in patient monitoring, using wearable devices and sensors to track health metrics and alert medical professionals to any concerning changes.
Decentralized Clinical Trials: Bridging the Gap
Digital technology has become integral to the daily lives of billions worldwide, facilitating remote accessibility and bridging geographical gaps between patients and disease experts through telemedicine platforms. This not only saves time and resources but also ensures patients receive expert advice without the need for travel, which can be particularly burdensome for those with debilitating RDs.
This remote accessibility, combined with the integration of human-centric AI, is revolutionizing how clinical trials are conducted. The next generation of clinical trial management platforms is enabling a patient-centric approach that utilizes new technologies and innovative procedures for interaction with participants in the comfort of their homes, thereby increasing participation rates and ensuring a more diverse and representative patient population. Using digital tools such as electronic health records (EHR), digitized consent, and smartphones, patients can be recruited, enrolled, and followed up with in a completely digitized, site-less manner. Wearable technologies facilitate both passive (e.g., triggered by device) and active (e.g., patient-triggered) remote data collection, streamlining trial operations and accelerating data analysis, ultimately expediting the development of RD drugs and improving outcomes for individuals with RDs6.
Deepti Dubey, Ph.D.
Deepti Dubey, Ph.D., is an accomplished researcher with expertise in Molecular Genetics, Neurological Disorders, and Rare Diseases from esteemed institutions. With a Clinical Trials Specialization, Deepti is a scientific writer at IndoUSrare (https://indousrare.org).
Harsha K Rajasimha, Ph.D.
Harsha K Rajasimha, Ph.D., is the Founder and CEO of Jeeva Clinical Trials (https://jeevatrials.com), a venture-backed startup on a mission to modernize clinical research with Human-Centric software and CRO solutions for biopharmaceutical and medical device sponsors. Harsha is a fierce advocate for patient-focused drug development for rare and common diseases including oncology. He chairs the annual Indo-US bridging RARE Summit (https://summit.indousrare.org to bring the stakeholders together to address grand challenges.
