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Life Science
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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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 lead, and optimizing the drug development process present significant challenges. Initially, the drug discovery process was more serendipitous rather than a planned process. Today, drug discovery involves a streamlined progression from identification to optimization. It …
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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 enrolling patients to overseeing research functions and coordinating trial logistics. Trials often run over budget or are delayed because of a number of factors, such as an inadequate number of patients available for the study, …
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How a self-learning Ontology benefits Pharma and Life Sciences
Every domain has its own language. The same word used in different domains can have totally different meanings. In fact, the same word can mean two separate things for different subdomains, eg. in science, hedgehog is both animal and protein. Moreover, domain language is dominated by abbreviations and terminology used by researchers and experts. A …
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What is unstructured data?
Did you write a mail today? Or did you use facebook, twitter, or Instagram? Regardless, chances are high that you produced some so-called unstructured data. But, what exactly is unstructured data? Unstructured data is digitized information that is available in a non-formalized structure. It is not relational and is not organized in a uniform, pre-defined …
Extracting Medical Data with Computer Vision Technology
Computer vision is one such AI technology that has seen exponential breakthrough over the last few years. Today, the technology is being realized in many forms and to solve various problems across different industries. Besides its very popular application in facial recognition and driverless cars, one of the attractive uses of computer vision is data …
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Leveraging AI for Drug Discovery in early stage Biotech Companies
Many biotech firms lack the basic data infrastructure to properly exploit digital tools and AI-technologies like machine learning, computer vision, entity normalization, network analysis, etc, and they don’t employ their own data scientists. However, some investors are specifically looking at biotech companies combining the DNA of both pharmaceutical and digital technology groups. Funding is only …
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Five Reasons to Embrace Data-Driven Drug Development
The growth of the pharmaceutical and biotechnology industry depends on successful clinical trials. The cost of developing a new drug that gets approval is estimated at around $2-3 billion. The longer the trial lasts and the more patients it has involved, the larger the loss. The researchers at Johns Hopkins Bloomberg School of Public Health …
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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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