AI pioneer Innoplexus and phytopharmaceutical company DrD are partnering toRead More
Partnering to unlock the true potential of cannabis in medical care
Innoplexus Assists in Biomarker Identification
In 2019, Innoplexus worked with Novartis on a pilot program that used Innoplexus’s proprietary artificial intelligence solutions and publicly available data to seek to identify baseline biomarkers of response. Innoplexus was talking to Eric Hughes – global development unit head for immunology, hepatology, and dermatology at Novartis: What is your role at Novartis, and what …
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 …
Innoplexus’s Proprietary CAAV Framework for Intelligent Big Data Analysis Read More »
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 …
The importance of quality control in the vast data ocean of Life Sciences Read More »
Standard or customizable or custom-made – how to decide?
Finding a Software Solution that aligns with your Business Data is the heart of a business, and software is its mind. Good software cannot only enhance productivity by offering better and simple solutions to complex problems, but it can also cut costs and decrease delivery time. However, figuring out the type of software – an …
Standard or customizable or custom-made – how to decide? Read More »
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 …
Understanding ontology for better insight into the Life Sciences data ocean Read More »
Why is Network Analysis important for Life Sciences?
Everything is connected! Genes to proteins, proteins to diseases, diseases to drugs, and drugs to proteins. All these connections are both simple and complex at the same time. Sometimes, not only understanding the complexity of the links is difficult, but even finding them is. How do we discover associations between two or three, or three …
Why is Network Analysis important for Life Sciences? Read More »
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, …
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 …
Why is Blockchain important to access unpublished data? Read More »
Why data monopoly in life sciences is not beneficial?
The pharma industry is one which is responsible for millions of lives. In 2018, the United States spent nearly 18% of GDP on healthcare. Moreover, the country spends more than U.S. $71 billion on Research & Development in pharma annually. According to statista, this figure is expected to increase to over 200 billion U.S. dollars …
Why data monopoly in life sciences is not beneficial? Read More »
