Standigm is a global workflow AI-driven drug discovery company with offices in Cambridge, UK; Cambridge, MA, US; and Seoul, South Korea. The company has a goal of shortening the drug discovery process and reducing costs by combining the Standigm AI platform with disease-specific data from its strategic partners. And the company believes that combining artificial intelligence with drug discovery will result in major advances in how researchers understand diseases and create solutions.
Hanjo Kim’s Background
Hanjo is an organic chemist by training and education and he worked for different organizations, including a non-profit research organization, biotechs, and a pharmaceutical company, in molecular modeling and cheminformatics fields. Since joining Standigm in 2019, Hanjo has led the development of Standigm BEST, which is novel compound design technology. As an SVP of Strategic Planning, Kim manages the company’s global offices (one in Cambridge, USA, and the other in Cambridge, UK), PR team, and business development team under the supervision of the chief business officer Carl Foster.
Standigm’s Core Products
The most simplified definition of drug discovery is the combination of novel biology and novel chemistry:
“Novel biology” is a new hypothesis about the connection between target proteins and disease, for which the company has developed Standigm ASK, a multi-modal approach (knowledge-level, omics-data drive, etc.) for target identification.
“Novel chemistry” is a new capability for designing synthesizable and patentable small molecules targeting proteins identified by Standigm ASK.
When the company used both technologies to create first-in-class drug discovery programs, it took an average of 7 months to decide whether we could secure novel scaffold(s) to optimize. Using this process (a “Magic Project”), the company created a list of early assets in different disease areas, including cancer, fibrotic, metabolic, and rare diseases.
Evolution Of The Company’s Technology
How has the company’s technology evolved over time?
“The database for the Standigm ASK system was initially developed for several drug repurposing programs, one of which is DR004, a mitochondrial disease program. We quickly realized this database system could work well for target identification purposes,” said Kim. “We added several proprietary technologies like mathematical representations of knowledge graphs, efficient management of network databases, simulation algorithms, and deep learning models, to evolve it to a fully functional system for target identification. Besides this knowledge-level approach, we have added several distinct methods to add more specific contexts of the biological systems we are dealing with. Now, Standigm ASK is a multi-modal approach where knowledge-level and unbiased data-level approaches are combined with multiple filters to manage the sophisticated requirements of clients and collaborators.”
The Standigm BEST technology started from a variation of early generative chemistry models and went through rigorous validations in several in-house drug discovery projects. And along with the advancement of those projects, different generative models were added according to their requirements.
Standigm AI scientists had added several proprietary algorithms for chemical representation, few-shot learning algorithms, machine learning-based rescoring methods, etc. And one notable characteristic of Standigm BEST is its various optimized and automated workflows, which are carefully ordered tasks for different project stages of early-drug discovery; hit identification, hit-to-lead, and lead optimization.
Biggest Milestones
When I asked Kim about some of the company’s biggest milestones, he cited DR004.
“DR004 is one of our drug repurposing programs where we identified a marketed drug for mitochondrial disease, including Leigh Syndrome, a rare pediatric disease. Regardless of its economic value, we are trying to do clinical trials of this drug and seeking partners with the needed expertise,” Kim explained. “As our AI technologies generally apply to any disease, we actively use them for rare or neglected diseases. We recently finished our collaborative research program on tuberculosis titled “Validation and optimization of an AI-driven platform for anti-tubercular drug discovery” with the Institute Pasteur Korea (IPK) funded by Right Foundation.”
Kim also pointed out that one of the company’s collaboration projects with a pharmaceutical company is in the final stage of preclinical candidate nomination. And they are proud of winning a gold Stevie Award in the pharmaceutical category, a bronze Stevie Award in the computer software category, and the finalist in Fast Company’s 2022 World Changing Ideas Awards.
Differentiation From The Competition
When I asked Kim about the company’s differentiation from the competition, he noted:
“‘The devil is in the details,’ and there should be tons of differences between all AI drug discovery companies and most of them are hidden know-how from different experiences and contexts. Our technologies provide a certain level of explainability, enabling human experts to have testable hypotheses and actionable validation plans, one of the key differences we deliver. As for the company itself, the balance between different expertise, AI and drug discovery, is arguably the most critical requirement of AI drug discovery companies. Standigm has maintained this balance to understand the difficulty of harmonizing distinct expertise. Conflicts between wet-lab scientists and dry-lab scientists happen when drug discovery companies work with AI technology companies, which is inevitable. Standigm already experienced them and found several effective ways to reduce or remove them.”
Future Company Goals
In terms of future company goals, Standigm has solid capabilities but cannot solve many problems without excellent partners – which is why they are actively seeking strategic partners with unique abilities to create readily available solutions for drug discovery projects with particular contexts.
“In other words, we want to be an essential member of a vibrant ecosystem in this field to transform drug discovery to an engineering level. As Arthur C. Clarke, said, ‘Any sufficiently advanced technology is indistinguishable from magic,” and it is our goal to make the drug discovery process magic,” Kim concluded.
