Goal 1: Advance Development of and Access to More Treatments, Particularly for Diseases With Unmet Needs
Thousands of diseases, many of which are rare, affect millions of people, and very few treatments exist. In fact, of the approximately 10,000 rare diseases, only 5% have treatments. Health care expenses for Americans with rare diseases are three to five times greater than for those without rare diseases, resulting in a total economic burden approaching $1 trillion annually. By advancing the development of more treatments, NCATS is on a mission to change the direction of research, particularly for rare diseases and diseases with unmet needs.
We’re committed to expanding capacity to develop faster and more accurate diagnoses, along with new treatments to help offset this public health challenge. We aim to revolutionize research, treatment, and diagnostic tools for diseases with unmet needs, especially rare and intractable conditions. We use a variety of approaches, including enhancing preclinical screening, refining clinical research methods, finding new indications for existing medications, and advancing personalized medicine. We are tackling common research challenges with innovative standardized platform approaches that streamline research and development processes and can be applied to multiple diseases. A platform approach or platform technology is intentionally built to be used in multiple ways. NCATS-enabled platforms include human cell–based models to better predict drug response (e.g., tissue chips and organoids), gene-targeted therapies using delivery approaches that can address many rare diseases at a time, and high-throughput screening to find new uses for existing drugs.
Our goal is clear: Increase the number of treatable diseases by increasing knowledge about their underlying causes, supporting the development of new treatments, and improving the reach, accessibility, and uptake of existing treatments. Imperative in this work is pursuing effective dissemination and implementation strategies that aim to bridge the gap between research and clinical practice.
Objective 1-1: Prioritize efforts to advance diagnosis and targeted interventions for multiple diseases, particularly rare diseases and others with unmet needs.
Developing one drug for one disease is inefficient, particularly with the extremely small number of approved treatments reaching patients per year.
We can address this challenge by investing in efforts to develop scientific platforms and tools that can address multiple diseases simultaneously. By creating diagnostic or research tools or interventions for one disease that can be easily adapted for others, we aim to make the research process more efficient and broadly applicable. Strategies to accomplish this objective include finding new or additional uses for existing compounds and approved drugs, also called repurposing. We will also advance methods that connect different types of data in meaningful ways, resulting in identifying more treatment options. We will also explore novel treatment approaches, such as gene- and cell-targeted therapies, that can be used as a platform to study multiple diseases.
Objective 1-2: Advance biological and chemical discovery to identify new molecules and targets for potential treatments.
An Emory University scientist is conducting experiments using a multipipettor. (Daniel Soñé Photography)
The development of potential medications is a long and difficult process that often results in only a few treatments for the many diseases that need them. Many diseases and conditions are currently untreatable because they involve complex issues, like proteins that don’t work correctly, or because the places to treat in the body where they are treated are difficult to reach, such as certain cell components like RNA and small molecules. NCATS will create novel approaches for these challenging conditions, opening the door to new possibilities beyond traditional drug discovery methods.
In the NCATS laboratories, we aim to make processes in drug discovery more rigorous, reproducible, data driven, and semiautonomous. Doing so allows effective chemical compound discovery, testing, and development for more diseases more quickly. As part of this objective, we will combine multidisciplinary expertise, automation, and artificial intelligence (AI)/machine learning (ML) to advance biological and chemical discoveries and translate them for therapeutic impact, leveraging both NCATS labs and support of external research organizations. Also, through our NCATS labs and other research programs and activities we support, we will explore quantum methods in AI-based drug discovery, aiding in the rapid and accurate design of new therapeutic compounds from start to finish.
Objective 1-3: Support and leverage existing national clinical and translational networks to conduct high-impact clinical research, clinical trials, and translational science and disseminate and implement successful interventions and treatments into the clinic and the community.
Clinical research and trials are a critical step to getting more treatments to those who need them. However, the barriers to success can be high. Barriers include the time to develop a trial, get approval to conduct it, and identify, recruit, and retain participants.
Translating a discovery into a therapy efficiently and working to ensure it reaches the people who need it benefits from a national ecosystem of clinical and translational research networks ready and able to innovate in study design and recruitment strategies. We will support, coordinate, and bolster our flagship CTSA Program and the Rare Diseases Clinical Research Network (RDCRN). Both networks enable data sharing, collaboration, patient and community engagement, and training, which are all critical to turning promising research observations into health interventions.
The CTSA Program includes a collaborative and efficient network of over 60 institutions and their partners working at the local, regional, and national levels. The CTSA Program is built upon CTSA institutions’ relationships at the community level, which allows them to rapidly address public health priorities and conduct impactful clinical research. A recent example is the public-private partnership to test drugs to reduce the immune response from COVID-19. This CTSA infrastructure also includes developing and using innovative trial designs, real-world data, and analytics, such as electronic health records research; prioritizing research to address rural health and women’s health; and developing ways to apply what is learned across the CTSA network and in primary care settings. Importantly, the CTSAs train the next generation of clinical and translational scientists to meet the research needs ahead.
Led by NCATS and with support from multiple NIH institutes and centers and the Office of the Director, RDCRN researchers and patient advocacy groups (PAGs) enhance clinical trial readiness in the rare diseases research community. They support data sharing and leverage the regulatory flexibility to conduct research, such as biomarker development and natural history studies. These efforts will be leveraged for future clinical trials and contribute to new drug approvals for rare diseases.
Objective 1-4: Support tools and technologies for preclinical testing and drug development.
Nearly 90% of promising treatment candidates that enter clinical trials fail. To improve success rates, we need more robust and predictive preclinical approaches, ensuring potential therapies that are likely to fail do so earlier, while those with real promise have a better chance of succeeding in late-stage clinical trials.
We strive to improve preclinical research models by developing more human cell–based, physiologically relevant tissue and other non-animal models. This approach will increase the potential of those models to better predict the safety and efficacy of potential treatments in humans. In addition, an early step in drug development is creating assays, or test systems, where researchers can study the effects of compounds of interest or identify underlying molecular causes of disease. For example, using induced pluripotent stem cells either from patients with rare diseases or normal cells CRISPR-edited with rare disease mutations, we can create models that help improve our understanding of the causes of diseases, identify new targets and biomarkers, and test potential therapeutics to find possible new treatments. Another example is the use of AI/ML for predicting novel molecular structures as drug candidates, assessing safety early by analyzing chemical structures and biological data, and identifying adverse effects early in the process. These AI tools can serve as reliable indicators in preclinical data and aid further development stages.