Alan Nafiiev

CEO & Founder at Receptor.AI        


I am a founder of RECEPTOR.AI, an innovative biotech company specialized in Artificial Intelligence drug discovery. The company mission is to create superior drugs, which are safe, efficient and successful in clinical trials by developing a next-generation drug discovery platform based on the synergy of AI, computational chemistry and biomimetic technologies, such as organs-on-a-chip.

I successfully ran two AI startups for B2B and have vast experience in automation and optimisation of business processes in big companies. I have proven to successfully build up and coach highly efficient teams, as well as to set and realise strategic plans of prospective expansive growth. Now, I am applying my expertise to implement the synergy of sophisticated AI technologies for breakthrough progress in biotech.

Contributing Author   in
AI & Digital  

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Articles from Alan

Receptor.AI Tests an Innovative Technique of Chemical Data Augmentation for Discovering Anti-cancer Drugs

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Receptor.AI Tests an Innovative Technique of Chemical Data Augmentation for Discovering Anti-cancer Drugs

The BRD4 (Bromodomain-containing protein 4) protein is a transcriptional factor that plays an important role in cancer development. It has attracted a lot of attention in recent years as a promising drug target because its inhibition stops the proliferation of cancer cells.

BRD4 is a member of a family which contains several related proteins sharing the same structural motif called Bromo- and Extra-Terminal domain (BET). Although dozens of drugs that target bromodomains are proposed, the search for better inhibitors of BRD proteins in general and selective inhibitors of BRD4 in particular is still of great demand for cancer therapy.

This Startup Proposes New Lightweight and Informative Molecular Descriptors for Drug Discovery

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This Startup Proposes New Lightweight and Informative Molecular Descriptors for Drug Discovery

Over the last five or so years, the drug discovery industry has started adopting artificial intelligence (AI) at unprecedented scale, with pretty much every big and small pharma company doing some kind of pilots or more substantial projects having some AI component in it from machine learning algorithms and deep learning networks to natural language processing models. Technology proved to have such a fundamental impact on performance of drug discovery work, that we now see a wave of young companies  – sometimes referred to as "digital biotech" which have a whole new business model revolving around the platform-based process of innovation. Some companies have "end-to-end" drug design platforms capable of automatically doing not only concept creation and target discovery, but also hit discovery, part of lead optimization work, and even predicting clinical trial outputs and identifying clinically-relevant biomarkers.