Silexon AI and Excelra Partner to Enhance AI-Powered Drug Discovery Platform

Hyderabad, India and Nanjing, China, December 2, 2021 /PRNewswire/ -- Excelra, a global leader in data and analytics, today announced a collaboration with Silexon AI Technology, a next-generation biotechnology company with a scalable artificial intelligence and machine learning (AI/ML) drug discovery and biopharmaceutical research platform.

According to the cooperation agreement, Excelra will provide Silexon with ADMET and binding assay datasets from its GOSTAR database. GOSTAR offers summarized information covering more than 8 million compounds and contains over 28 million SAR-related data points. The well-structured relational database can be used for various applications across different stages of drug discovery and development, assisting in target validation, hit identification, early lead identification, and optimization.

Silexon's AI/ML platform combines high-quality real-world biological data with advanced machine learning capabilities, utilizing its disruptive predictive tools to drive new drug design, drug discovery, and biopharmaceutical research. These tools help streamline the drug discovery and design process, reducing the time it takes for new life-saving drugs to reach the market. Silexon focuses on developing innovative biologics with unique target product profiles for undruggable, hard-to-drug, and novel targets across multiple therapeutic areas.

Excelra CEO Anandbir Singh Brar stated: "We are thrilled that GOSTAR has become the gold-standard dataset for biopharmaceutical and AI/ML companies. Our collaboration with Silexon highlights GOSTAR's ability to provide large-scale, standardized, quality-controlled datasets that support various predictive models. We are excited to partner with Silexon and jointly develop the AI4D drug discovery platform."

Silexon CEO Hai-Nian Zeng stated: "We look forward to combining the well-annotated GOSTAR data with the data accumulated and generated by Silexon's proprietary AI/ML models and wet lab experiments. By leveraging our artificial intelligence and machine learning platforms, we aim to address bottlenecks in drug discovery and biopharmaceutical research, ultimately delivering innovative therapeutic candidates with higher overall success rates. Our preliminary evaluation results give us confidence that GOSTAR's database will be an important addition to our current efforts in building next-generation modeling training datasets."