01 December 2021 | Wednesday | News
(From left) Jinhan Kim, CEO of Standigm and Youngmee Jee, CEO of Institut Pasteur Korea, exchanged a memorandum of understanding on the 29th.
The endeavor combines Standigm's AI drug discovery platform and IPK's research expertise in infectious disease. Under the MOU, the two parties will actively conduct joint research and academic exchanges to derive innovative drug candidates for infectious disease, setting the research priority on discovering novel anti-tubercular drug candidates.
Previously, the two parties conducted research collaboration on anti-tubercular drug discovery, applying Standigm's deep learning technology to the data generated through IPK's cell-based screening of one hundred thousand compounds against tuberculosis. As a result, hit compounds with several key scaffolds effective in multidrug-resistant and extensively drug-resistant tuberculosis (MDR/XDR-TB) were identified.
The follow-up research on these hits, 'Validation and optimization of an AI-driven platform for anti-tubercular drug discovery' has been selected for the Research Investment for Global Health Technology Fund's ("RIGHT Fund") "Technical Accelerator Award". The RIGHT Fund is a global health research funding foundation established in 2018 through the public-private partnership between the Ministry of Health and Welfare of South Korea, the Bill & Melinda Gates Foundation (BMGF), and Korean life science companies to address the medical and technological needs towards alleviating the burden of infectious diseases especially in developing countries. Standigm has been selected as a grantee for the RIGHT Fund's innovative infectious disease R&D project with IPK as its collaborating research partner.
Based on a list of key scaffolds identified in the previous research collaboration, Standigm will explore novel lead structures with improved anti-tubercular activity. For this, Standigm will utilize its proprietary AI platform for compound design (Standigm BESTTM). The scaffold-based generation module will generate novel anti-tubercular molecules based on predefined key scaffolds. After that, the activity prediction model which deep learned 3D molecular features will prioritize the most active anti-tubercular compounds and select the final candidates for synthesis.
IPK will synthesize the virtual candidates derived by Standigm into real chemical compounds and evaluate their efficacy, leveraging years of expertise in anti-tubercular drug discovery research. In particular, each compound will be tested and validated through cell culture experiments using IPK's image-based screening platform in the biosafety level-3.
"There are considerable difficulties in anti-tubercular drug discovery, such as resistance and interaction with other drugs. It is not easy to recover drug development costs because it occurs frequently among socially and economically vulnerable groups, making it one of disease that needs the most innovation in the drug development process," said Jinhan Kim, Co-founder and CEO of Standigm. "By pooling research expertise of IPK and Standigm's AI technology together, we expect to accelerate the discovery of innovative new tuberculosis drugs by reducing the time and cost compared to traditional methodologies," he added.
"Through this research collaboration with Standigm, we will establish and verify innovative strategies that can accelerate AI-based infectious disease research, and improve the efficiency of drug discovery," said Youngmee Jee, CEO of IPK. "Furthermore, we will continue multidimensional research and collaborations, including conducting follow-up research to commercialize the new anti-tubercular drug candidate developed by the IPK, TTCA, and contribute to the worldwide efforts to end the tuberculosis epidemic by 2030," she added.