Receptor.AI Aims to Develop a Fully Automated End-to-End Drug Discovery Platform

Artificial Intelligence is currently ubiquitous in drug discovery and is expected to revolutionize the field and open up new opportunities of creating new drugs faster, cheaper, and with a much higher success rate.

Receptor.AI, a new ambitious player in the field, is developing an innovative drug discovery platform based on the synergy of AI, computational chemistry and biology to design new drugs, assess their safety and efficiency and predict the success rate of experimental validation and clinical trials.

Since founded in the beginning of 2021 in Delaware (USA), Receptor.AI employs a Kyiv located R&D team of 25 experts in machine learning, data science, bioinformatics, medicinal chemistry, biophysics and molecular modeling. Over six months AI has developed an in-house AI platform for generating molecules, assessing drug-target interactions, high-throughput virtual screening, predicting ADME-Tox and repurposing drugs. Their solution is on par or even superior to market leaders' products as far as synthetic benchmarks are involved and is suitable for big pharma, medium biotech and academic scientists.

The company's mission is to develop a fully automated end-to-end drug discovery platform driven by an advanced AI combining computational discovery of new drug candidates and their subsequent experimental validation. As a result, a human factor will be minimized at all stages of the drug discovery process: starting from clinical trials on people and ending with regulatory approval of novel drugs.

The company CEO, Alan Nafiiev, has successfully run two AI startups for B2B, including Panzor Cybersecurity Inc, whose product (Panzor Cloud Antivirus) was rewarded by Virus Bulletin 100 as the best AI-based cyber security solution of 2018. "Imagine the world in which new safe and effective drugs would be developed so fast new diseases would have no chances to spread. This could be accomplished with the help of advanced artificial intelligence techniques, which minimize the need for experimental validation of drug candidates and clinical trials", — says Alan. Besides, he believes that AI will make our world safer and humanity healthier.

Sergii Starolyla, a CTO with 10+ years of experience in drug discovery, is confident that with the help of combining 40+ proprietary AI methodologies the company will build up a flexible and scalable drug discovery pipeline. "We are particularly proud of our molecular generators based on transformer architecture and reinforcement learning as well as the drug-target interaction technology, which encodes protein structure and large-scale dynamics into graph neural networks. Our AI platform has already been validated experimentally in several successful pilot projects".

Chief scientific officer, Semen Yesylevskyy, a biophysicist with 15+ years of experience in molecular modeling, emphasizes the importance of the company being currently engaged in more than 10 scientific collaborations with research institutions worldwide. He believes that drug discovery is initiated by the basic scientific research of а particular disease and its molecular mechanisms. "Such a scientific collaboration has already yielded positive results. We have obtained promising hit compounds for several challenging proteins and successfully modelled novel targets associated with obesity".

Receptor.AI has successful partnerships with world leaders in chemical synthesis and experimental drug validation and offers turnkey solutions for drug discovery projects of any complexity. At present, they are fundraising to create an integrated system based on the company's AI drug discovery platform and modern organ-on-a-chip technologies aimed at reducing clinical trials on humans and animal experiments.


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