Insilico Medicine announces the publication of a new research paper titled "Molecular Generation for Desired Transcriptome Changes With Adversarial Autoencoders" in Frontiers in Pharmacology. This is the first study of this kind where novel molecular structures are created for a desired transcriptional response.
In this study, Insilico Medicine researchers developed a new model, the Bidirectional Adversarial Autoencoder, that learns a joint distribution of molecular structures and induced transcriptional response. The model can generate molecular structures for a given transcriptional response and vise versa.
As a result, Insilico Medicine provided a model that combines both generative biology and generative chemistry. Using this model, researchers can run virtual screening, discover novel molecular structures, and predict transcriptional responses--one model to solve many problems.
"This paper shows that it is possible to generate novel molecular structures that induce the desired transcriptional response. At Insilico, we have been working on this project since 2016 and have created critical intellectual property covering the original ideas in generative biology proposed and patented by Alex Zhavoronkov and Alex Aliper.
I hope that the generative chemistry and biology developed at Insilico will become household tools for big pharmaceutical companies. Many of these tools are available in our upcoming AI platform soon to be available for deployment at customer premises."
Daniil Polykovskiy, Study Senior Author and Group Leader, Insilico Medicine
ShayaKhmetov, R., et al (2020) Molecular Generation for Desired Transcriptome Changes With Adversarial Autoencoders. Frontiers in Pharmacology. doi.org/10.3389/fphar.2020.00269.