GlamorousAI

GlamorousAI, founded in London in 2020 by CEO Noor Shaker, developed an artificial intelligence-based drug discovery platform to tackle challenges in preclinical research. The company secured $451K in funding from investors, including MassChallenge and P4, to advance its core technology. In October 2021, GlamorousAI was acquired by X-Chem, a US-based leader in DNA-encoded library (DEL) technology, to create a combined powerhouse in AI-driven drug discovery.

Noor Shaker, with extensive experience in AI and machine learning, founded the company with the vision of making drug discovery faster and more cost-effective, particularly for diseases with limited available data. The goal was to address the high failure rate and expense of bringing new drugs to market by leveraging AI to navigate the vast chemical space for potential drug candidates. This mission led to the creation of RosalindAI, a platform designed to empower researchers in the biopharma sector.

The company's primary offering is RosalindAI, an AI-first SaaS platform designed for the biopharmaceutical industry. This end-to-end, cloud-based platform enables drug hunters, even those without a background in coding or machine learning, to design and optimize novel chemical entities. A key differentiator of RosalindAI is its ability to operate effectively on sparse, noisy, and small datasets, which are common challenges for difficult-to-treat disease targets. The platform can start from a single known data point, such as a small molecule that interacts with a target, and then generate and computationally validate billions of potential compounds, rapidly narrowing them down to a few promising candidates for lab testing. This capability was validated experimentally in the lab on challenging targets like Keap1, an oncology target with no existing drugs on the market.

Following its acquisition, GlamorousAI's technology is being integrated with X-Chem's vast DEL-generated datasets. This synergy allows X-Chem's partners to unlock the full potential of their data, accelerating the identification of high-quality starting points for drug discovery programs. The business model centers on providing this fully integrated service to the biopharma industry, aiming to reduce risks and increase the probability of success in moving from initial screening to a clinical candidate.

Keywords: drug discovery, artificial intelligence, preclinical studies, RosalindAI, computational chemistry, small molecule discovery, AI platform, biopharma, DNA-encoded library, machine learning, Noor Shaker, X-Chem, low-data drug discovery, chemical scaffolds, target validation, computational drug design, lead optimization, generative AI in pharma, SaaS for drug discovery, high-value therapeutic targets