European Patent Office to Grant BioKey’s Patent Application for Foundational HYFT Technology - Seite 2

HYFT-based technologies have numerous applications in various fields beyond just data integration, organization, and analysis, such as drug immunogenicity testing, drug discovery, and natural language processing (NLP). These applications have the potential to accelerate the drug development process and improve patient outcomes.

In the field of immunogenicity, HYFTs can help predict parts of a molecule that may trigger an immune response. This information is crucial in therapeutic and vaccine development, as it helps identify potential safety concerns before they become problematic. Moreover, HYFTs can predict off-target effects, which occur when a drug or therapy affects unintended targets in the body. Early identification of potential off-target effects allows researchers to design safer and more effective treatments.

In drug discovery, HYFT-based technologies have multiple potential applications, including:

Toxicity Prediction: By linking genetic sequences to toxicological data, HYFTs can predict the toxicity of potential drug candidates, helping researchers identify compounds likely to cause adverse effects before entering clinical trials.

Drug Repurposing: HYFTs can identify existing drugs for repurposing by linking genetic sequences to known targets and functions, accelerating the drug discovery process by finding compounds already approved for other indications.

Clinical Trial Design: HYFTs can optimize clinical trial design by linking genetic sequences to patient data and clinical outcomes, identifying patient subgroups more likely to benefit from specific treatments, and enabling personalized and efficient clinical trials.

Biomarker Discovery: By linking genetic sequences to disease-specific phenotypes, HYFTs can identify biomarkers of disease, helping to identify at-risk patients and enable earlier diagnosis and treatment.

Another application of HYFT-based technologies is tied to NLP, which involves analyzing and extracting information from written or spoken language. HYFTs can link text-based information, such as scientific papers or medical records, to specific genetic sequences or structures, facilitating more efficient and accurate analysis. This is particularly valuable in genomics and personalized medicine, where vast amounts of textual data must be processed and analyzed to identify potential therapies or treatments.