Much of the historical progress has been led by AI-native drug discovery companies that offer software or service to pharma players. And facilitating such services by one-of-a-kind organic chemists having expertise in molecular modeling combined with the knowledge of AI can only bring about disruption. So is this inspiring interview with Hanjo Kim, SVP of Global Strategy, Head of Medicinal Chemistry at Standigm. 

He believes that AI has the potential to propagate to other intersections of different expertise and improve the overall productivity in drug discovery. To learn more kindly go through the interview highlights below:

Please brief our audience about yourself and your role as the SVP of Global Strategy, Head of Medicinal Chemistry at Standigm.

I’m an organic chemist by training and education. I have worked for various organizations, a non-profit research organization, a biotech, and a pharmaceutical company, before joining Standigm in 2019. I led the development of Standigm BEST, its chemistry technology, until 2021. From 2022, my role has changed to half research, head of medicinal chemistry, and the other half business development.

Please share your source of inspiration for exploring various facets of technology.

As an organic chemist with molecular modeling expertise, I have spent my entire professional career living on the edge of two totally different disciplines; wet lab and dry lab. As these two have different philosophies, customs, and ways of thinking, my primary job has been as a translator or a facilitator in most cases. Therefore, it was natural for me to join Standigm and deal with combining AI and drug discovery, two different technologies. The questions from experts with diverse backgrounds are a trustworthy source of inspiration.

Kindly brief our audience about Standigm and give us an overview of its standout solutions.

Standigm, which comes from the ‘standard paradigm,’ is a start-up founded in 2015 by three co-founders who are former SAIT (Samsung Advanced Institute of Technology) colleagues. It has over fifty employees, most of whom are R&D scientists with different expertise, such as AI algorithms, software engineering, chemistry, and biology, in its three offices, headquartered in Seoul, South Korea, Standigm UK in Cambridge, UK, and Standigm US in Boston, USA. Standigm focuses on early drug discovery, which can be defined as the combination of novel biology and novel chemistry.

Standigm ASK is a set of processes to identify promising and novel target proteins for a given disease. It uses multi-modal methods, a general knowledge-level approach using knowledge graphs and AI algorithms, various ways to use experimental data (mostly multi-omics data from patient samples) for the specific contexts of biological systems, and many filters. Standigm BEST is a collection of different workflows for hit identification, hit-to-lead, and lead optimization, and their components, generative models, prediction models, and automated learning systems. By combining these two techniques, Standigm could shorten the time to get confirmed lead compounds to an average of seven months.

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