Determining the ototoxic potential of COVID-19 therapeutics using machine learning and in vivo approaches
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 3R01DC020701-01A1S1
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Key facts
Disease
COVID-19Start & end year
20232028Known Financial Commitments (USD)
$39,973Funder
National Institutes of Health (NIH)Principal Investigator
ALLISON COFFINResearch Location
United States of AmericaLead Research Institution
WASHINGTON STATE UNIVERSITYResearch Priority Alignment
N/A
Research Category
Therapeutics research, development and implementation
Research Subcategory
Prophylactic use of treatments
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
Project Summary/Abstract There are over 900 drugs and drug combinations currently in clinical trials for COVID-19. While this pace of drug development is necessary, it also comes with increased risk of producing therapies with significant side- effects. One likely side-effect of some COVID-19 drugs is hearing loss. The potential of drugs to cause hearing loss is typically unassessed during drug development or clinical testing. Our research will rapidly assess COVID-19 drugs for ototoxic potential, as per NOT-DC-20-008 to determine the "Potential ototoxicity from therapeutics or vaccination related to COVID-19." Our goal is to promote the development of safe COVID-19 drugs with minimal side effects. Some drugs in clinical trials for COVID-19 are associated with hearing loss but the ototoxic potential for these drugs is based on individual case reports or in vitro experiments so the true ototoxic burden is largely unknown. We should not use patients as a testbed for a life-altering negative side- effect when there are rapid low-cost alternatives available. The objective of this proposal is to rapidly identify the ototoxic potential of COVID-19 therapeutics using both in silico and in vivo approaches. We will achieve this objective with three Specific Aims: 1) Predict ototoxic potential of COVID-19 therapies with Machine Learning (ML), 2) Determine the relative hair cell toxicity of COVID-19 therapies in the zebrafish lateral line, and 3) Determine the degree to which predicted ototoxins cause hearing loss in rats. Our innovative ML model correctly categorizes ototoxins vs. non-ototoxins with 87% accuracy. In this project we will employ our current model for immediate ototoxicity detection and further optimize the model for better predictive accuracy. In parallel with the ML model, we will screen COVID-19 therapeutics in the larval zebrafish lateral line, which is an excellent model for rapid ototoxicity screening. Prior work by our group and others demonstrates the validity of the lateral line as a platform for effective ototoxin discovery. Finally, we will validate predicted ototoxins from Aims 1 and 2 in rats using both physiological and morphological assays. Our research is significant because we will determine the ototoxic potential of new or repurposed therapeutics for COVID-19, which can inform efforts to 1) advance effective candidates that are not ototoxic, 2) modify successful yet ototoxic COVID-19 drugs and/or develop otoprotective co-therapies to preserve therapeutic efficacy while minimizing ototoxic side- effects, and 3) determine which patients require audiometric monitoring due to the drugs they receive. Our team includes experts in ototoxicity, medicinal chemistry, biostatistics, machine learning, and clinical expertise in large-scale human trials for COVID-19 therapies. Our research is highly likely to identify ototoxic COVID-19 drugs, facilitating development of safer pharmacotherapies to combat this deadly pandemic. Further, many drugs in clinical trials for COVID-19 are already approved for other indications. Our research will therefore provide important data about drugs in clinical use for non-COVID-related disease, adding additional value.