Artificial intelligence meets massive repositories of multi-omics data linked to chemical compounds to streamline drug discovery R&D
Insilico Medicine, one of the leaders in advanced signaling pathway activation analysis and deep learning for aging and cancer research is proud to announce the formation of the Pharmaceutical Artificial Intelligence division focused on applying latest advances in artificial intelligence to streamline drug discovery and drug repurposing processes and significantly cutting time to market.
"Since its inception Insilico Medicine is taking the umbrella view on aging research developing biomarkers and drug candidates in a broad number of fields. We collaborate with some of the largest pharmaceutical companies, cosmetics companies and academic institutions on a number of disease- or drug-specific projects. However, our focus on aging and "we do everything" approach is confusing for many of our customers and partners and with the launch of Pharma.AI as a division, we will highlight a core part of our business and explore the possibility of spinning it off as a separate company in the future", said Alex Zhavoronkov, PhD, CEO of Insilico Medicine, Inc.
With the exception of cancer immunology, most of the pharmaceutical companies are facing declining returns on their R&D investments and are not open to external innovation in early stage development. Pharma.AI aims to bridge this gap by providing cutting-edge machine learning services delivered by an experienced team of bioinformatics and deep learning experts working with millions of drugs, annotated gene expression samples and blood biochemistry data sets that can be used to augment customer's data.
With 11 highly-expert machine learning experts worldwide, Pharma.AI team is developing deep learned transcriptomics-, proteomics-, blood biochemistry-based biomarkers of multiple diseases, predictors of alternative therapeutic uses of multiple drugs and analytical tools for high-throughput screening. Pharmaceutical companies utilizing Broad Institute's Connectivity Map or LINCS projects of pipelines will find powerful analytical drug discovery tools readily available.
"I am happy to join Pharma.AI division as a research scientist focusing on interpreting the results of our AI analytical systems in skin care applications. I am already supporting this team as a geneticist, but with a full-time appointment I have a chance to help transform the pharmaceutical industry forever. I am also happy with Insilico Medicine's mission to empower women in emerging geographies and giving us visibility and skills that will be in high demand over the next two decades when many other jobs will be lost to automation", said Polina Mamoshina, senior research scientist at Insilico Medicine.