Syntekabio (KOSDAQ: 226330), an artificial intelligence (AI) drug discovery and development company headquartered in South Korea, announced today the launch of its cost-effective AI-based total solution service for finding new drug candidates. STB CLOUD works as a comprehensive one-stop solution built on Syntekabio's own proprietary AI platform DeepMatcher®, powered by supercomputing technology. The total solution supports auto-hit-discovery, auto-lead-generation, auto-ADMET/PK (at task), and PGx biomarker for drug labeling.
Using deep-learning analysis and automatic molecular dynamics (MD) simulation technology for target proteins, the solution generates pre-stage, pre-clinical candidates within two years, including the completion of animal testing. This process drastically shortens the period before pre-clinical trials to two years from what averages to be up to seven years in traditional drug development.
Generally, it takes three to four years for candidate discovery and screening, one to three years for optimization, and the same length for non-clinical and toxicity tests. Adding five to six years for clinical trials and a couple more years for commercialization, the time it takes for full drug development from discovery can last many years causing the development price tag to go up while losing potential return on investment. Furthermore, Traditional new drug development can cost more than 10 million dollars until pre-clinical trials. Syntekabio’s STB CLOUD not only saves time but achieves substantial cost savings as it is set at only two million dollars for the entire cycle of drug development.
“Using our AI-based STB CLOUD and supercomputing technology, we have created an optimal environment for servicing the global biopharma industry,” CEO of Syntekabio, Jongsun Jung, said. “The fully automated technology covers toxicity, metabolism and pharmacokinetics prediction and will provide in the near future an automated total service for each individual model. It’s only a matter of time to automatically produce drugs with high unmet needs, including rare disease treatments.”
Currently, Syntekabio is conducting two studies in the area of auto-ADMET/PK (at task). The first is about toxicity and metabolism caused by protein binding, which is modeled based on the 3D convolutional neural network (3D-CNN). The second study is on passive delivery and permeability due to the physical and chemical properties of the compound itself, which will be implemented with pre-trained generative transformers models, such as GPT-2, using large-scale compound databases.
Syntekabio’s new drug discovery solutions will be unveiled at the 2023 BIO International Convention in Boston, June 5-8 at booth #2785. Contact Ellie Woo at email@example.com or +1 (917) 257-4533 to request one-on-one meeting.
Syntekabio is a global artificial intelligence (AI) and big data-based drug discovery and development company, headquartered in South Korea since 2009, with U.S. operations bringing innovative technologies and science to create transformative medicines worldwide that are compliant with international standards to cure diseases and improve people's lives. Find out more about DeepMatcher®, NEO-ARS™, NGS-ARS™ and PGM-ARS™ at STB CLOUD (syntekabio.com)
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