Draper's Airway-on-a-Chip Accurately Predicts COVID-19 Drug Efficacy
核心洞察
Draper (搜索)'s PREDICT96-ALI, an airway-on-a-chip model, accurately predicted the failure of two COVID-19 (搜索) therapies that had shown promise in preclinical studies.
The model correctly identified three FDA-approved antiviral drugs (搜索) as effective against SARS-CoV-2 (搜索), aligning with observed clinical outcomes.
This microphysiological system (MPS) offers a more predictive preclinical screening tool for emerging respiratory infections, addressing a critical unmet need.
Draper (搜索), a nonprofit engineering innovation company, has developed an airway-on-a-chip model called PREDICT96-ALI that accurately predicts the efficacy of COVID-19 (搜索) therapies. The model, a microphysiological system (MPS), mimics the human airway and has demonstrated the ability to distinguish between effective and ineffective treatments for SARS-CoV-2 (搜索), potentially accelerating drug development and reducing the failure rate of clinical trials.
Validating Therapeutic Candidates
The researchers cultured human primary bronchial epithelial cells under air-liquid interface (ALI) conditions within the PREDICT96-ALI system. When exposed to various therapies, the model accurately reflected clinical outcomes. Specifically, two therapies that failed in human clinical trials, despite promising preclinical results, also failed to control viral infection in the airway-on-a-chip. Conversely, three FDA-approved antiviral drugs (搜索) that have proven effective in clinical settings successfully suppressed the infection within the model.
Christine Fisher, Group Leader of Microbiology and Immunology at Draper (搜索), emphasized the significance of these findings, stating, "This is the first report of comprehensive and accurate screening of therapeutic candidates for COVID-19 (搜索) in an organ-on-chip. PREDICT96-ALI can increase clinical success, and that represents a new and major milestone in the effort to use human primary cell-based preclinical models to expedite countermeasure development for emerging infectious disease threats and, more broadly, in the drug development pipeline."
Addressing Unmet Needs in Preclinical Modeling
Ashley Gard, Group Leader of Cellular and Tissue Engineering and Principal Biomedical Engineer at Draper (搜索), highlighted a major limitation in current preclinical models: their inability to reliably predict human clinical responses. The PREDICT96-ALI system addresses this gap by providing a more accurate and predictive platform for evaluating drug candidates before they enter clinical trials. According to the researchers, "There still exists a tremendous unmet need for predictive MPS airway models to fill a critical gap in preclinical therapeutic screening for COVID-19 (搜索) and other emerging respiratory infections."
Technical Details of the PREDICT96-ALI System
The airway tissue models within PREDICT96-ALI are maintained in a culture media with dynamic fluid flow, ensuring adequate nutrient and oxygen supply. Testing is conducted in a biosafety level 3 (BSL-3) high-containment laboratory, allowing for comprehensive evaluation of the SARS-CoV-2 (搜索) viral life cycle. The system's throughput enables the testing of multiple compounds at various concentrations on a single plate.
The research, published in Advanced Biology, builds upon previous work published in the journal Cells in 2023. The authors conclude that PREDICT96-ALI is a valuable tool for drug discovery, capable of assessing the efficacy of SARS-CoV-2 (搜索) therapeutics with sufficient throughput to test multiple compounds at multiple concentrations in a single plate.
Implications for Drug Discovery and National Security
PREDICT96-ALI is part of Draper (搜索)'s broader portfolio of technologies supporting drug discovery and national security missions. These capabilities include biothreat detection technologies developed for programs such as IARPA's FELIX, DARPA's DIGET, and BARDA's Project NextGen.