Insilico Medicine's end-to-end AI-driven drug discovery platform, Pharma.AI, draws its strength from the quality and quantity of its data. As Insilico scientific advisory board member and Nobel Prize laureate in chemistry Dr. Michael Levitt has said, Insilico's platform capitalizes on the ability of artificial intelligence to take vast amounts of data from many different components and find patterns and make predictions that can point the way to new life-saving medications.
Insilico began building its platform, using a massive collection of data, beginning in 2014 when the company was founded. PandaOmics™, the target discovery portion of Pharma.AI, uses 1.9 trillion data points drawn from over 10 million samples (such as microarrays, RNA sequencing, and proteomes) and over 40 million documents (including patents, grants, publications, and clinical trial reports).
Insilico follows federal grant money from initial experiments to clinical trials, manually inputting when needed, comprising trillions in total. PandaOmics can now not only identify brand new targets for drugs, but it can also predict which targets are likely to be "hot" five years out.
Improving AI with CROs and pharma partners
One of the ways that Insilico improves its platform through data is by engaging over 80 contract research organizations who run redundant experiments and create reproducible data sets. The company has 30 internal therapeutic programs in various stages of development, and is turning out preclinical candidates at a record pace.
It named 8 preclinical candidates since 2021, including one for COVID-19 and two for cancer in recent months, and its lead candidate for idiopathic pulmonary fibrosis is currently in Phase 1 trials, the first AI-discovered and AI-designed drug to reach this milestone.
Insilico has also expanded its collaborations with pharma through co-development and software licensing deals. Since the launch of PandaOmics™ and Chemistry42™ in late 2020, nine out of the top 20 pharmaceutical companies, as measured by 2020 revenue, have licensed Insilico's AI platforms.
In 2022, Insilico signed multi-asset partnerships with Fosun Pharma and EQRX in January and March, respectively. Notably, Insilico achieved its first major milestone and nominated a preclinical candidate for the QPCTL program for cancer immunotherapy less than 40 days into the strategic collaboration with Fosun Pharma.
Next Step: robots
Now, Insilico aims to make its end-to-end AI platform even stronger by launching its own AI-run robotics lab. The lab has been in the design phase for the past two years and is expected to be fully operational this year.
It's a real world interconnected expansion of Insilico's drug discovery platform and will be run autonomously by its AI system with autonomous guided vehicles running experiments in place of human scientists. These robots will do cell culture, high throughput screening, next generation sequencing, cell imaging, and genomics analysis and prediction. As the robots generate data, that data will feed directly into the PandaOmics platform, improving the system's target hypotheses and ability to validate those hypotheses.
These robots are faster and more precise than humans. And as they perform experiments they feed the AI system with data, improving the system's target hypotheses and ability to validate those hypotheses."
Alex Zhavoronokov, PhD, Medicine founder and CEO, InSilico Medicine
It's all part of the company's focus on improving and validating its platform, bringing its lead candidate to Phase 2 trials, and further developing its numerous therapeutic programs. Recently, the company has received additional funding in a $60m Series D round from leading biotech investors, including BHR Partners, Warburg Pincus, B Capital Group, Qiming Venture Partners, BOLD Capital Partners, and Pavilion Capital.
Feng Ren, PhD, Insilico's Chief Scientific Officer and Head of Global Research and Development who has 15 years of experience working in large pharmaceutical companies and CROs says: "We plan to continue expanding the breadth of the pipeline and enhance our AI and robotics capabilities globally. Our rapidly growing team is composed of talented and experienced scientists in drug discovery with diverse backgrounds and relentless passion for novelty and innovation, and fully committed to developing novel drugs with a sense of urgency for the waiting patients.
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