Latest Posts

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Mar 24

Partex NV announces collaboration with Althea DRF Lifesciences to provide comprehensive end-to-end services to accelerate drug discovery and development

Frankfurt, Germany; 28 March 2024 – Partex Group, a pioneer in AI-driven drug discovery, announces a collaboration with Althea DRF...
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18

Mar 24

Innovative AI technology in oncology: Partex Group presents results from a pilot project

During the German Cancer Congress 2024 in Berlin, the companies Innoplexus AG /Amrit AG, companies of Partex N.V., presented the...
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Innoplexus wins Horizon Interactive Gold Award for Curia App

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Life Sciences

Innoplexus’s Proprietary CAAV Framework for Intelligent Big Data Analysis

The amount of data currently being produced by the life sciences industry is exploding. Medical information alone is expected to double every 73 days by 2020,1 and much of this data is unstructured. If we want to put this extremely complex, vast ocean of data to use, we need to crawl, aggregate, analyze, and visualize …

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How Can AI Technologies Help Streamline Medical Affairs Processes?

For pharmaceutical companies, much of the success of a new drug depends on how well it is marketed. There are various stages a drug goes through before reaching the commercialization phase, and, by necessity, focus is placed more on drug development than on marketing. This puts a lot of pressure on commercial teams. They need …

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Better Drug Commercialization Strategies Powered by AI

The drug commercialization process is one of the most important and challenging steps in drug development. Creating a successful strategy rests on guidance provided by reliable data from multiple sources. In an increasingly competitive landscape, pharma companies need powerful solutions that make the commercialization process more efficient and increase the likelihood of success. Today, meeting …

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The importance of quality control in the vast data ocean of Life Sciences

Through the Internet, we have access to a vast ocean of life sciences data, and AI provides us with the tools to tame it. In data analytics, for example, it is important to collect the data most useful for generating relevant knowledge. AI enables this by specifying the context of interest to filter data by …

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Understanding ontology for better insight into the Life Sciences data ocean

The rapid advancement in the field of AI, and the necessity of extracting knowledge and generating insights from data to find sustainable solutions, demanded computers distinctly understand the language of the particular industries. Industry-specific terms used for research enables data analysis such that relevant insights are generated. With an ontology that consists of the relevant …

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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 applied to various contexts. The second edition of Oxford dictionary in 1989 recorded 228,132 words, including popularly used words, obsolete words, as well as derivatives. Words are used all over the world to discuss, …

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Why is Blockchain important to access unpublished data?

Today, blockchain technology applies to a variety of industries. The revolutionary technology that made virtual currency a possibility also enabled hyperledger and smart contracts. This offers an unprecedented opportunity to break down data silos in pharma and access unpublished data. Unpublished pharma data poses a limitation to successful drug development and increases the chance of …

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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 take humans years to do. In 45 years, computer vision would become an integral component in artificial intelligence (AI) applications across industries. After years of exponential growth, through breakthroughs in AI technology and an explosion …

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Advantages of Artificial Intelligence

AI or Artificial Intelligence works by effectively combining high volumes of data using intelligent and quick algorithms with iterative processing and thereby allowing itself to self-learn automatically from the characteristics of such data. The tasks can range from speech or natural language recognition and translation into different languages, to visual perception and even decision making. …

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