AI pioneer Innoplexus and phytopharmaceutical company DrD are partnering toRead More
You Can’t Find the Needle If You Don’t Know It Exists
This blog is adapted from my book titled “Inside the Cockpit: Navigating the Complexity of Drug Development with AI and Blockchain”. Full copies are available here. In December 2014, a twenty-nine-year-old investor named Vivek Ramaswamy bought a patent from GlaxoSmithKline (GSK) for $5 million. The patent covered an Alzheimer’s drug candidate that had failed GSK’s …
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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 development. Pharma companies are investing in AI-driven applications for transforming healthcare, reducing R&D spends, and expanding the scope of drug discovery. By expediting research efforts, AI is turning hype into use cases and increasing ROI …
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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 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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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 …
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