AI pioneer Innoplexus and phytopharmaceutical company DrD are partnering toRead More
iPlexus is now powered by Google Cloud platform
Founded in 2011 and headquartered in Germany, with offices in US and India, Innoplexus AG offers Data as a Service (DaaS) and Continuous Analytics as a Service (CAaaS) products. Our products leverage Artificial Intelligence (AI) and advanced analytics to significantly reduce drug development time, from synthesis to approval. Crawling, aggregating, analysing and visualising millions of webpage every day is Innoplexus core business. The core product iPlexus has more than 300 terabytes of indexed scientific data across 25 million publications, 365k clinical trial databases, 200 biological databases, all major patent offices (20 million patents), regulatory agencies, patient forums, and so on. This is growing in numbers as we get additional terabytes of data is crawled each day. Soon, we will have a 360-degree access to the data, when we will enable searching through all five types of data sources viz. Published data, Unpublished data, Restricted data, Enterprise Data and Third party data.
“Key Google Cloud Platform services like BigQuery analytics-based data warehouse help our product in managing an enormous amount of data that the product generates on a daily basis. This expedited the training of information extraction models by 20x and scalability by 8x. Further, architectural enhancements led to increasing number of pages crawled per second from 1,000 to 20,000”. This resulted in cost savings by a whopping 80% and increased content capture and processing capability by 20x.”
iPlexusTM crawls, aggregates and analyses data from a range of formats and structures from multiple regions and providers. All ‘crawled’ data is passed through an information extraction pipeline that converts semi-structured and unstructured sources into a structured format. This is achieved through leveraging of various AI-based techniques like natural language programming, computer vision, machine learning and deep learning. All the information extraction models are implemented using TensorFlow and the Keras open source neural network library. These models are then trained using Google Cloud Machine Learning Engine before being deployed. Google Cloud Dataflow is used for batch processing and Google Kubernetes Engine API to run iPlexus applications in containers.
Innoplexus is really looking forward to Google Cloud to take iPlexus platform to the next level in terms of scalability, security and performance.
Featured Blogs
Machine learning as an indispensable tool for Biopharma
The cost of developing a new drug roughly doubles every nine years (inflation-adjusted) aka Eroom’s law. As the volume of data…
Find biological associations between ‘never thought before to be linked’
There was a time when science depended on manual efforts by scientists and researchers. Then, came an avalanche of data…
Find key opinion leaders and influencers to drive your therapy’s
Collaboration with key opinion leaders and influencers becomes crucial at various stages of the drug development chain. When a pharmaceutical…
Impact of AI and Digitalization on R&D in Biopharmaceutical Industry
Data are not the new gold – but the ability to put them together in a relevant and analyzable way…
Why AI Is a Practical Solution for Pharma
Artificial intelligence, or AI, is gaining more attention in the pharma space these days. At one time evoking images from…
How can AI help in Transforming the Drug Development Cycle?
Artificial intelligence (AI) is transforming the pharmaceutical industry with extraordinary innovations that are automating processes at every stage of drug…
How Will AI Disrupt the Pharma Industry?
There is a lot of buzz these days about how artificial intelligence (AI) is going to disrupt the pharmaceutical industry….
Revolutionizing Drug Discovery with AI-Powered Solutions
Drug discovery plays a key role in the pharma and biotech industries. Discovering unmet needs, pinpointing the target, identifying the…
Leveraging the Role of AI for More Successful Clinical Trials
The pharmaceutical industry spends billions on R&D each year. Clinical trials require tremendous amounts of effort, from identifying sites and…
Understanding the Language of Life Sciences
Training algorithms to identify and extract Life Sciences-specific data The English dictionary is full of words and definitions that can be…
Understanding the Computer Vision Technology
The early 1970s introduced the world to the idea of computer vision, a promising technology automating tasks that would otherwise…
AI Is All Hype If We Don’t Have Access to
Summary: AI could potentially speed drug discovery and save time in rejecting treatments that are unlikely to yield worthwhile resultsAI has…