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  6. GOSTAR Small Molecules

GOSTAR Small Molecules

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Excelra|GOSTAR

last updated:Jan 16, 2026

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Organized and standardized low molecular SAR data, in a usable format. GOSTAR Small Molecules reduces research preparation time.

●Unmatched Data Quality and Scale GOSTAR Small Molecules is one of the largest low molecular weight SAR databases in the world, containing over 11 million low molecular weight compounds and over 36.8 million SAR data points. Thanks to manual curation by specialized medicinal chemists and a three-tier quality control process certified by ISO 9001:2015, you can utilize organized and standardized reliable data directly in your research. 【Features】 ■ A centralized data source for one of the largest low molecular weight SAR information ■ Comprehensive understanding of low molecular weight SAR, including not only activity but also physicochemical properties and ADMET ■ Automatically adjusted for different types of ligands, making it easy to read ■ Sortable by any data column and color-coded based on values *For more details, please refer to the PDF document or feel free to contact us.

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GOSTAR Small Molecules

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basic information

GOSTAR Small Molecules is a large-scale SAR database for small molecules that contains quantitative biological activity data on compounds and targets obtained from in vitro and in vivo experiments (enzyme and cell-based systems). It provides high-quality data that can be readily analyzed, making it suitable as training data for AI/ML (machine learning) technologies. It enables the rapid construction of predictive models for specific target activities and ADMET properties, contributing to the acceleration of drug discovery. ■ Data Contents Chemical and Biological Data - Chemical structure information - Structure-activity relationship (SAR) data - Biological activity data related to compounds and targets Physical Properties and Development-related Data - Physico-chemical properties - ADME data - Toxicity data

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【Contract Model】 ◆ Online Access With GOSTAR's online service, you can search and analyze from a web browser. Depending on the contract, you can download search results, allowing integration into your internal database or use as training data for AI/ML predictive models. There are user-based licenses and unlimited user corporate licenses. ◆ File Delivery We provide all data or focus on specific categories. Data formats: Oracle, PostgreSQL, MySQL, text files, EXCEL, SDF, RDF, etc.

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Fifteen out of the top 20 pharmaceutical companies in the world are utilizing GOSTAR for their drug discovery programs. In today's data-driven drug discovery landscape, structured high-quality datasets that encompass structure-activity relationships (SAR), physicochemical properties, and ADMET have become essential for predictive modeling and AI/ML-driven drug discovery programs. ■ Main Uses ■ - As training data for AI (activity prediction, property prediction) - Drug design - Virtual screening - Lead optimization - Competitor research - Patentability research - Drug repositioning

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GOSTAR TPD | Protein Degradation Inducer Database

GOSTAR TPD | Protein Degradation Inducer Database

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GOSTAR | One of the world's largest manual curation structure-activity relationship (SAR) databases by EXCELRA.

GOSTAR | One of the world's largest manual curation structure-activity relationship (SAR) databases by EXCELRA.

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[Free Webinar] Manual Curation Techniques for Accelerating AI/ML Drug Discovery Using SAR and ADME Data | Held on June 11 (Thursday)

[Free Webinar] Manual Curation Techniques for Accelerating AI/ML Drug Discovery Using SAR and ADME Data | Held on June 11 (Thursday)

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In drug discovery research utilizing AI and machine learning, the biggest factor influencing the accuracy of predictive models is "data quality." Excelra and Patcore will co-host a free online webinar on the theme of GOSTAR(TM), which accelerates AI drug discovery, on June 11, 2026, at 13:30. Utilizing GOSTAR(TM), one of the world's largest manually curated SAR databases, the webinar will explain, with live demonstrations, the acceleration of predictive modeling using ML-ready data, improvements in molecular design accuracy in medicinal chemistry, and the establishment of a data foundation that supports go/no-go decisions from lead optimization. The speaker will be Dr. Nishanth Kandepedu from Excelra, who has over 10 years of experience in the drug discovery field. Researchers in drug discovery from pharmaceutical and biotech companies, AI/ML engineers, and R&D leaders are widely invited to participate. Participation is free, but prior registration is required. Registration will close once capacity is reached. ▼Details & Registration: https://patcore.com/news/webinar-gostar-2026

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Patocoa Inc. is a specialized company in drug discovery support systems. Additionally, we focus on improving and streamlining compliance-related operations concerning regulated substances, and we have provided various solutions to pharmaceutical companies, chemical companies, universities, and government agencies. We contribute to accelerating drug discovery and reducing costs with our cutting-edge chemoinformatics systems.

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