Artificial intelligence (AI) is transforming drug development from a race for speed to a competition for success rates. The technology has evolved to not only identify candidate substances more quickly but also to filter out toxic risks in advance and derive optimal drug candidates. South Korea's AI drug development company, Pharos AI Bio, is accelerating the development of treatments for rare and intractable diseases and expanding into next-generation modalities with its proprietary platform.
Nam Ki-yeob, CEO of Pharos AI Bio, explained at the 16th Global Healthcare Forum (2026 GHF) held on May 14 at the Korea Press Center in Seoul, that "AI drug development has entered the era of 'agent AI,' where it can now formulate hypotheses and make decisions after going through computer-based drug design, machine learning, and deep learning stages."
Major domestic bio companies are actively responding to this global change based on their own platforms in the AI era. Pharos AI Bio's core competitive advantage lies in its self-developed AI platform, Chemiverse.
Chemiverse is a platform that supports the entire drug development cycle by combining proteomics AI with generative model-based candidate substance design technology, based on multi-omics big data. It addresses the inefficiencies and high costs associated with drug development, covering everything from target discovery to candidate substance design, lead optimization, and the establishment of preclinical and clinical strategies.
Nam stated, "The success rate of our pipeline using the AI platform from Phase 1 to Phase 2 clinical trials reaches 87.5%." This reflects a reduction in the high failure rate, a fundamental challenge in drug development, through data and predictive technology. He added, "By combining a strategy focused on rare and intractable diseases with biomarker-based patient selection and open innovation, we are enhancing the likelihood of success in drug development."
A notable example of the company's AI application is the acute myeloid leukemia (AML) treatment, Rasmotinib (PHI-101). This candidate substance is a FLT3 inhibitor developed for patients who do not respond to or are resistant to existing treatments. Nam remarked, "Rasmotinib has achieved a 50% complete response rate in global Phase 1 clinical trials, emerging as a new hope for patients resistant to standard therapies." He added that they are pushing for early commercialization through entry into Phase 2 trials, conditional sales approval, and technology transfers.
Additionally, the company plans to expand into next-generation modalities such as antibody-drug conjugates (ADCs) and targeted protein degraders (TPDs) based on Chemiverse. They aim to broaden the scope of drug development by combining structure-based chemical design capabilities with specialized experience in rare and intractable targets and core structural big data.
Nam emphasized the importance of building competitiveness through in-house drug development, stating, "AI has evolved from a simple tool to an intelligent partner that supports decision-making throughout the entire drug development process." He further stressed that in the AI era, K-bio's success will depend not just on identifying good drug candidates but also on how well data is accumulated and interpreted to connect with the global value chain. A full value chain strategy that supports technology validation, capital acquisition, and global expansion is essential for the competitiveness of K-new drugs to become a reality.
Finally, Nam reiterated, "Pharos AI Bio will continue to strengthen its research and development competitiveness in innovative drugs for rare and intractable diseases and in various modality areas such as ADCs and TPDs based on Chemiverse."
Nam Ki-yeob, CEO of Pharos AI Bio, explained at the 16th Global Healthcare Forum (2026 GHF) held on May 14 at the Korea Press Center in Seoul, that "AI drug development has entered the era of 'agent AI,' where it can now formulate hypotheses and make decisions after going through computer-based drug design, machine learning, and deep learning stages."
Major domestic bio companies are actively responding to this global change based on their own platforms in the AI era. Pharos AI Bio's core competitive advantage lies in its self-developed AI platform, Chemiverse.
Chemiverse is a platform that supports the entire drug development cycle by combining proteomics AI with generative model-based candidate substance design technology, based on multi-omics big data. It addresses the inefficiencies and high costs associated with drug development, covering everything from target discovery to candidate substance design, lead optimization, and the establishment of preclinical and clinical strategies.
Nam stated, "The success rate of our pipeline using the AI platform from Phase 1 to Phase 2 clinical trials reaches 87.5%." This reflects a reduction in the high failure rate, a fundamental challenge in drug development, through data and predictive technology. He added, "By combining a strategy focused on rare and intractable diseases with biomarker-based patient selection and open innovation, we are enhancing the likelihood of success in drug development."
A notable example of the company's AI application is the acute myeloid leukemia (AML) treatment, Rasmotinib (PHI-101). This candidate substance is a FLT3 inhibitor developed for patients who do not respond to or are resistant to existing treatments. Nam remarked, "Rasmotinib has achieved a 50% complete response rate in global Phase 1 clinical trials, emerging as a new hope for patients resistant to standard therapies." He added that they are pushing for early commercialization through entry into Phase 2 trials, conditional sales approval, and technology transfers.
Additionally, the company plans to expand into next-generation modalities such as antibody-drug conjugates (ADCs) and targeted protein degraders (TPDs) based on Chemiverse. They aim to broaden the scope of drug development by combining structure-based chemical design capabilities with specialized experience in rare and intractable targets and core structural big data.
Nam emphasized the importance of building competitiveness through in-house drug development, stating, "AI has evolved from a simple tool to an intelligent partner that supports decision-making throughout the entire drug development process." He further stressed that in the AI era, K-bio's success will depend not just on identifying good drug candidates but also on how well data is accumulated and interpreted to connect with the global value chain. A full value chain strategy that supports technology validation, capital acquisition, and global expansion is essential for the competitiveness of K-new drugs to become a reality.
Finally, Nam reiterated, "Pharos AI Bio will continue to strengthen its research and development competitiveness in innovative drugs for rare and intractable diseases and in various modality areas such as ADCs and TPDs based on Chemiverse."
* This article has been translated by AI.
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