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Innoplexus seeks to contribute to the effective fight against the coronavirus, with its AI-powered dashboard, freely available worldwide to Covid-19 / SARS-Cov-2 researchers, medical institutes, news portals, governments, and the public.
The dashboard will provide precise and comprehensive information on recent global developments concerning Covid-19, and will be continuously updated.
Innoplexus and Parexel have launched the COVID-19 Clearinghouse which is a comprehensive online resource for patients, researchers, and clinical trial sponsors to directly access publications, datasets, links to active global clinical trials, and current news related to COVID-19.
Innoplexus provides advanced artificial intelligence (AI) and blockchain solutions that support all stages of drug development from pipeline to market. Innoplexus identifies and extracts structured and unstructured life science data by scanning up to 95% of the world-wide-web and merges it with enterprise and third-party data in an ongoing, real-time process. This continually updated data repository is the foundation of our custom and off-the-shelf solutions that serve pharmaceutical companies, the biotech industry, and contract research organizations.
Ontosight® offers the largest searchable library of life sciences information to help companies develop accurate therapies much faster, saving them time and costs. The platform applies proprietary AI technologies along with our life sciences ontology to crawl, aggregate, analyze, and visualize life sciences data from multiple published, unpublished, third-party, and enterprise sources.
This one stop solution for life sciences comes with various modules and dashboards to help you optimize work potential with the most relevant knowledge, real-time intelligence, and discovery of new patterns across pre-clinical, clinical, regulatory and commercial phases of drug development.
An innovative and intuitive semantic discovery engine that understands biomedical concepts and allows users to see relevant results in context across multiple data sources
A life sciences–specific search engine that enables exploration, identification, and building of various direct and indirect connections between biological entities such as drugs, targets, pathways, and diseases
Real-time discovery, management, and network analysis of top and emerging key opinion leaders (KOLs) across the entire drug discovery and development value chain
A 100% automated, self-service engine that leverages internal and external data for real-time analysis of products/sales performance and status of budget and expenses
Our leading proprietary AI technology for life sciences generates real-time insights and relevant results for better decision-making
Our self-learning ontology understands the language of life sciences and enables context-based searches across multiple data sources
Our technology connects trillions of data points from structured, unstructured, public, third-party, corporate, and unpublished data
Testimonial by Global Medical Advisor Oncology @ Boehringer Ingelheim
Project-Title: Indication Prioritization using Artificial Intelligence (AI) and Machine Learning (ML).
“As Global Medical Advisor Oncology @ Boehringer Ingelheim – I have been assigned to lead a new project: “Indication Prioritization using Artificial Intelligence and Machine Learning”. The need for innovative technologies to accelerate pharmaceutical research and development has never been greater and Boehringer Ingelheim continues exploring technology approaches to complement our own expertise in research, development and translational medicine.
Innoplexus and its proprietary Knowledge Graph called Ontosight were seen as the right partner to look for solutions for the current project.
As expected, the Innoplexus’ Indication Prioritization approach with AI & ML was able to screen a far larger number of scientific publications, exclude potential “noise“ in a much shorter period versus traditional approach, delivering as well an unbiased and reliable result-set to support prioritize indications for a selected target.
We compared the results Innoplexus provided to our own traditional analysis and confirmed a substantial overlap in the results. It was indeed quite impressive to see that a machine-generated indication list matched well with our understanding. The advantage was to also have the result set ranked based on biological relevance, market potential as well as clinical feasibility, which is a limitation with our own analysis and the expert recommendations.
We also saw some positive surprises in Innoplexus' results. For example, some new tumor types were highlighted, and this is where innovation was generated, I would say.
Being highly satisfied with this new approach of drug discovery, I have recommended Innoplexus to my colleagues in other teams responsible for other assets at Boehringer Ingelheim.”
"Great technology and data"
Having sufficient data and analytical capability is critical to being able to identify potential baseline biomarkers. In working with Innoplexus our expectation was to leverage its technology to pool all of the publicly available patient level data that might help us in delivering on this objective. The Innoplexus team was very fast to develop its strategy to address our request.
Data analytics is becoming a core competency for Pharma. We do not want to outsource this anymore! I love the fact that you are focused on empowering our analytics teams with your solutions. This is a clear differentiation versus all the competitors. You seem to be working on a true partnership model.
‘’Efficiency and quality’’
Innoplexus using their AI technology delivered what we required on time with great quality. The resilience and expertise made us choose Innoplexus again
“Meet the finish line” effort of Innoplexus helped us make our decision easier for choosing a problem solver. We look forward to working with them more and more.
"Cutting edge tech!"
Innoplexus has cutting edge technology which could potentially revolutionize Pharmaceutical industry…. I am excited to be working with them.
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