Eric Buckland of Translational Imaging Innovations and Ronald Schuchard, Medical Product Development Expert, explore the benefits of ophthalmic precision medicine to improve patient care across sectors

The term “precision medicine” has become very popular over recent years, driven by scientific and socio-political perspectives. The goal of precision medicine is to improve individual care through the stratification of patients according in order to a taxonomy derived from large-scale data, including clinical, lifestyle, genetic and further biomarker information, thus going beyond the classical “signs-and-symptoms” approach. Precision medication is a process that incorporates the comprehensive approach to understanding the specific needs of individuals with shared attributes, targeting more effective care with lower risks. Today’s medical records systems are not up to the task. The particular evolution associated with precision medicine requires a revolution in managing healthcare data, from clinical research, through clinical trials plus into medical practice.

Improvements in GTx and AI inherently target the holy grail of precision medication

As promising as Gene Therapy (GTx) and Artificial Intelligence (AI) are to the future associated with healthcare, the field of ophthalmology has seen one FDA-cleared gene therapy[1] and two FDA-cleared AI diagnostic products[2],[3]. While there are many reasons for the limited progress of precision medicine in ophthalmology, the lack of quality data sources and reproducible processes with regard to leveraging considerable image-rich data is a major contributing factor.

Degenerative ocular diseases, which includes glaucoma and dry age-related macular degeneration progress “gradually, then suddenly” [4]. This slow progression associated with disease presents a host of problems in both diagnosis and treatment. Even in cases with clear risk factors and suggestive clinical indications, deficiency of treatments mandates the wait-and-see scientific approach. Predictive biomarkers are usually needed that will accurately predict when a patient’s condition will progress to severe vision loss.

The absence of prognostic markers impacts the development of new drugs that might slow, halt, or reverse degeneration

How does one validate a drug that may slow disease progression over decades? How does one assess the particular risk-benefit trade-offs? In our aging society, progressive vision reduction will threaten the quality of life and increase the economic burden on the global economy. This is a real threat that requires new protocols for evaluating drugs plus prognostic biomarkers to identify at-risk patients as candidates for a given therapy. Current clinical health records, proprietary imaging devices, and image management systems designed around patient case management are not suited to discovering, validating, and deploying prognostic biomarkers or validating the new class of clinical endpoints required to get ahead of the problem of degenerative eye disease .

Drug molecules and biologics are necessary regarding a new drug, and clinical endpoints are the particular outcome measures for assessing safety plus effectiveness. Scientific endpoints form a battery of tests that measure structure, function, and impact on activities of daily living at each phase associated with clinical trials. The US Food and Drug Administration (FDA) provides guidance on selecting endpoints for medical trials[5]. The primary concern of the FDA is constraining Type I errors – minimizing the risk that an ineffective drug will be cleared through the process. The bar is usually high. The particular FDA mandates that the particular probability of clearing an ineffective drug be below one chance in 40. Statistical rigor requires the prospective selection of endpoints and prospective analysis methods that eliminate statistical inflation and data dredging. Tight control associated with Type I failures can increase the probability that good therapy candidates end up being rejected – the Type II failures. Developing robust scientific endpoints intended for slowly degenerative diseases and rare diseases that are applicants for gene therapy is the significant challenge and a major barrier to progress inside ophthalmology.

Clinical endpoints are certainly not born; they are made

It is critical to develop appropriate clinical endpoints in parallel with new medication development through the earliest phases. The FDA recognizes primary, secondary, and exploratory endpoints (or endpoint families). The main endpoint will be the main test that a treatment has worked. Secondary endpoints provide evidence of additional medical benefits or elucidate mechanisms of action; secondary endpoints are only considered following success against the major endpoint. On the other hand, explanatory endpoints are experimental and provide flexibility in order to test additional clinical hypotheses and evaluate new biomarkers that might evolve into future principal or extra endpoints.

New imaging plus testing modalities are increasingly moving from the laboratory to scientific trials. Innovative new techniques testing patient sensitivity to light[6] and micromotions of the particular retina[7] show promise as early markers of illness operating at the eye-brain connection. Such new endpoints do not need to be derived from clinical standards of care. Inclusion as exploratory endpoints in clinical tests maximizes the leverage associated with expensive medical trial processes to clear new remedies that benefit patients while advancing the particular development of future primary and secondary endpoints to get degenerative vision disease.

Improving patient treatment across all industries

Integrated image and data management across the entire lifecycle associated with pre-clinical plus clinical study, clinical studies, and scientific practice are necessary to advance ophthalmic accuracy medicine. The more finely grained we stratify patients and target therapies, the more likely we are to realize the value within emerging treatments, improve patient care throughout all areas of the population, and ultimately reduce health care costs. Finely grained medical solutions require large-data solutions with enough power to discover the needed biomarkers plus validate clinical endpoints.

Translational Imaging Innovations is leading the way with comprehensive systems that will simplify the capture, curation, and analysis of images and information, with transparency and traceability. Our architecture begins with the TII Data Genome, the scalable and extensible relational data structure supported by the ocuVaultTM database and application programming interface (API). ocuVaultTM simplifies data flows, automates data security, and simplifies database deployment across sites and programs. ocuLinkTM is the TII vendor-neutral, multimodal, information curation, visualization, and annotation application, optimized for large-scale image evaluation workflows. Mosaic is the particular TII computational platform designed for batch processing the multi-stage computational recipes required for biomarker discovery and trial data analysis. At TII, our goal is in order to enable translational researchers to develop better diagnostics plus better remedies, with even more predictable benefits – faster, at a lower cost, and with less frustration.

  1. LUXTURNA, Spark Therapeutics, Inc.
  2. IDx-DR, Digital Diagnostics Incorporation, DEN180001,
  3. EyeArt, Eyenuk, Inc, K200667,
  4. Ernest Hemingway, The Sun Also Rises
  5. Draft Guidance for Multiple Endpoints inside Clinical Trials, FDA- 2016-D-4460-0002,
  6. Aguilar MC, et al, Automated instrument designed in order to determine visual photosensitivity thresholds. Biomed Opt Express. 2018 Oct 18; 9(11): 5583-5596.
  7. Sheehy CK, et ing, Fixational microsaccades: A quantitative and objective measure of disability in multiple sclerosis. Mult Scler. 2020 Mar; 26(3): 343-353.

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