NIH Promotes Big Data to Enhance Eye Disease Research

1Aug - by aiuniverse - 0 - In Big Data


July 31, 2019 – Improving collaboration between specialists and integrating multiple datasets to leverage big data will be key for advancing research for dry age-related macular degeneration (AMD), according to a new report from a National Institute of Health (NIH) working group.

Over 11 million people in the United States are diagnosed with AMD, an eye disease that ultimately results in blindness. It is the leading cause of blindness among individuals 65 years of age and older.

The disease can manifest in one of two forms: neovascular (wet) or non-neovascular (dry). While the neovascular form progresses more rapidly, there are several known and proven treatments for the disease. There are no preventive measures for dry AMD nor treatment options.

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“The working group thoroughly assessed what is known about dry AMD pathobiology, and the recommendations will be informative for considering future NEI research priorities to align with promising pathways for discovering therapeutic targets,” said Director of National Eye Institute (NEI), Paul Sieving, MD, PhD, in an earlier news release.

The working group recommended a systems biology approach to disease treatment, an integration of genomic, preclinical, medical, pharmacological, and clinical data to inform modeling of the disease progression. Synthesizing big data from all these areas including tissue samples from clinical trials will help inform predictive modeling which can then be used to inform individual patient care.

A personalized approach to disease management may also be helpful, the working group recommended. Such an approach should consider the disease stage, progression, and individual risk factors to provide preventive and treatment strategies specific to the patient, the report said. Collaborating will all points of care will allow a multidisciplinary team to use a patient’s unique clinical, imaging, and genomic data to treat the disease.

“We propose that researchers utilize a systems biology approach, integrating the big data available from clinical registries and various fields of biology known as ‘omics’ to develop better models and ultimately treatments for patients with this blinding disease,” stated report co-author Joan W. Miller, MD.

Due to a lack of preventive strategies and treatment options for dry AMD, the working group noted the need for improved understanding of the disease pathology and promoted clinical trial investigations to do so. Previous research has shown a genetic link to the disease as well as several lifestyle factors including smoking, but there is no work examining the effects these factors have on dry AMD.

A better understanding of how these factors impact the disease will help providers be better informed to watch for risk factors and promote inventive preventive strategies. Such understanding only comes from examining data and promoting the use of big, integrated data sources to help investigators use multiple sources to answer their questions.

Effective disease management will need multiple targets that differ based on the disease stage progression, the report notes. A strategy overhaul needs to take place that focuses on large-scale, collaborative, systems biology in order to effectively treat the disease.

“This approach would integrate basic, genomic, pre-clinical, medical, pharmacological, and clinical data into mathematical models of pathological processes at different stages of dry AMD in order to ask how relevant individual components act together within the living system,” Miller said.

The working group was appointed by the National Advisory Eye Council, a 12-member panel that establishes guidelines for the NEI under the NIH. The group was charged with a multilayered goal: to raise public health awareness about the impact of dry AMD, review the current state of research about the disease for a better understanding of its pathology, propose future research directions, encourage scientists to focus on AMD, and promote collaboration among a network of specialized providers.

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