AegiDR™（a Platform for Drug Research and Repurposing）基于安吉知识图谱（AegiKG™）集成的知识，开展遗传疾病药物靶点筛选。对于单基因疾病，根据疾病流行率与突变频谱数据，结合转录组与蛋白组验证结果，设计核酸药物并开展细胞和动物实验。对于多基因疾病，根据公开GWAS与内部NGS数据，结合eQTL、空间可及性等多组学数据，采用网络分析方法进行药物靶点筛选。对于候选靶点，采用基于结构或基于人工智能的网络分析方法，开展药物重定位，寻找潜在药物。 AegiDR™ is a novel, knowledge-driven platform that's aimed to revolutionize the process for drug discovery and repurposing. It uncovers the associations between molecular changes and clinical phenotypes, identifies genomic drug targets, and performs in silico screening of drug candidates, therefore substantially improves the efficiency and success rate of pre-clinical drug development.
全球已知的罕见病约有7,000多种，仅有不到10%的疾病有已批准的治疗药物或方案。将罕见病纳入公共治理范畴，建立罕见病医疗保障体系，不仅能保障患者获益，还有利于 激励产业创新，增强市场活力。根据IQVIA全球药品终端销售数据显示，在美国，罕见病药物市场规模在过去的二十年间发展迅速，其中非罕见病适应症的销售贡献远超罕见病适应症。罕见病药物身份认定及适应症的获批，带动了药物在常见病适应症的扩展。 There are over 7,000 genetic diseases known to exist today, but only 10% of them have an approved treatment. Biopharmaceutical industry researchers have been making great progress in the fight against genetic diseases and more than 770 medicines have been approved by the U.S. Food and Drug Administration (FDA) since enactment of the Orphan Drug Act in 1983.
根据制药公司公开财务报告，2018年全球市场销售金额排名前10的药物中，有8个已在美国获得“孤儿药”身份认定，其中有4个药物是以“孤儿药”身份上市并逐渐扩展多个罕见病或非罕见病适应症，而全球销售排名第二的来那度胺（商品名：瑞复美）在美国获批的所有适应症都是罕见病且获得了“孤儿药”身份认定。 According to public financial reports, out of the 10 top-selling drugs in 2018, 8 are FDA-approved "orphan drugs", and 4 of them were initially aprroved as orphan drugs and later have expanded to treat other rare or non-rare conditions.
安吉康尔通过大数据构建-分析预测-功能实验验证的研究路径，可以提供候选疾病和靶点筛选、先导化合物预测与优化，以及临床试验人群招募等服务。 However, there is still much more work to be done.
The complicated molecular mechanism underlying many dieases pose great challenges to the drug development process, while AegiDR™ platform is designed to ease this process. The AegiDR™ is integrated with our in-house database AegiKG™ which contains WES and WGS data and associated clinical information from over 10,000 patients, and with the latest deep learning algorithm, the AegiDR™ can dig through massive amount of biomedical data to identify molecular alterations that's of interest. It also supports functional study using cell culture or model organisms.
1. Deep learning-based target identification
The whole exome and whole genome sequencing enable the decipher of genomes with unprecedented resolution, and allow scientists to discover disease-causing mutations in a high throuhput fashion. However, they generate a vast amount of data, and therefore require a lot of computing power and advanced data analysis algorithm.
Equiped with the latest deep-learning algorithm, the AegiDR™ platform is able to dig through the immense sequencing data and predict genomic variants that are suitable as drug targets.
2. Data-driven drug design and screening
Genomic variants can disrupt fundamental cellular processes such as transcription, splicing and translation, therefore alter gene function and cause diseases. Understanding the pathogenesis mechanism is essential for drug design.
The AegiDR™ is integrated with an AI-based in silico drug screening system as well as a cell-culture or aninal model based functional study pipeline, and can facilitate the new drug design and drug repurposing process.
创新药厂· Innovative pharmaceutical companies
1、ASO设计：组织特异性转录组分析，可变性剪切预测和计算，isoform分析，搜寻最合适ASO1. Gene Therapy Design
2、药物重定向2. Drug Repurposing
3、自然语言处理3. Natural Language Processing