COVID-19 revealed in stark terms the price to be paid for the lack of a comprehensive community-based research system that can generate evidence to answer a broad range of critical research questions, whether in the context of sponsor-driven product development trials, comparative effectiveness studies, or a fast-moving public health emergency. FasterCures aims to identify actions needed by key stakeholders to realize the potential of community-based research infrastructure and build a coordinated ecosystem of excellence to address future public health emergencies and prevalent health problems equitably.

The research and health ecosystem has entered an era where vast amounts of biological and clinical data are continuously generated. Integrating, analyzing, and understanding these data are only possible with computational tools such as artificial intelligence (AI) and machine learning. Incorporating such tools across the biomedical ecosystem has great promise to further the understanding of biological mechanisms, advance translational research, and enhance clinical care for better patient outcomes. 

The field of computational biology sits at the nexus of biology, big data, and computer science. The principles of AI intersect with the larger discipline of computational biology. Methods and approaches use mathematical modeling, simulations, analytics, statistical methods, and algorithm development to address biology-based questions.

The application of computational tools can revolutionize how to study, prevent, and treat human disease. However, the unique nature of the biomedical ecosystem brings specific challenges that must be overcome before the promise of these tools to help people live longer and healthier lives can be fully realized.

The Biswas Family Foundation partnered with the Milken Institute Science Philanthropy Accelerator for Research and Collaboration (SPARC) in 2023 to conduct a comprehensive review of the computational biology field and identify areas of opportunity for philanthropy to advance the integration of computational tools in biomedical research and clinical care. 

Using the findings and insights from this analysis, which are published in Transformative Computational Biology, a Giving Smarter Guide, the Biswas Family Foundation developed the Transformative Computational Biology Grant Program, which is focused on accelerating the use of computational approaches in translational research and clinical settings to improve the well-being and health of the global community.

Frontotemporal dementia is a family of neurodegenerative conditions that cause changes in behavior, mood, executive function, language, memory, and motor function. Based on brain pathology, FTD could account for as many as 10-20 percent of all dementia cases. The disease is underdiagnosed, and a true global prevalence estimate is hindered by a general lack of awareness and the complex nature of its detection. The hallmark trait of FTD is a progressive deterioration of the brain’s frontal and temporal lobes, but specific biomarkers or treatments for FTD have not been developed.

FTD tends to affect people earlier in life than other forms of dementia and is thought to be the most common form of dementia in people under the age of 60, with the average age of onset between ages 45 and 65. Although not fatal, FTD symptoms progress to the point where patients need full-time care. The average life expectancy is about 7.5 years after symptom onset. There are no definitive diagnostic tools, no disease modifying therapies, and most patients do not receive distinct care for FTD.

With these challenges top-of-mind, Milken Institute Science Philanthropy Accelerator for Research and Collaboration (SPARC) is working to bring more attention and strategic funding into the FTD field to change the experience and trajectory for people experiencing this disease.  As part of this initiative and in partnership with the Kissick Family Foundation, SPARC is leading a new effort to infuse research dollars into the ecosystem to drive accelerated discovery.