Pharmaceuticals & Biotechnology


AI In Health Care: The Top Ways AI Is Affecting The Health Care Industry

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Artificial intelligence (AI) is having a major impact on the health care industry. In fact, AI in health care is redefining the medical care field and all its functions. It is playing a big role in health care data. When health care data uses AI, it provides new and improved analytics. AI analytics are of use in the detection, diagnosis and treatment of many diseases.


What is Quantum Computing and How is it Useful for Artificial Intelligence?

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After decades of a heavy slog with no promise of success, quantum computing is suddenly buzzing! Nearly two years ago, IBM made a quantum computer available to the world. The 5-quantum-bit (qubit) resource they now call the IBM Q experience. It was more like a toy for researchers than a way of getting any serious number crunching done. But 70,000 users worldwide have registered for it, and the qubit count in this resource has now quadrupled.


AI in Biopharma Slowed by Challenges Involving Data, Corporate Culture

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Biopharmas are warming up to artificial intelligence (AI), but a series of challenges will need to be addressed before it becomes widely used by drug developers, a panel of industry executives agreed. Speaking at the 2019 Annual Meeting of NewYorkBIO in New York City yesterday, panelists identified those challenges as finding more and better data, integrating data from multiple sources, and creating partnerships to gather and analyze that data. The panel also cited challenges that go beyond data, such as attracting a new generation of professionals capable of applying AI and related technologies such as machine learning--and adapting biopharmas to the new technologies. Those observations are in line with a study released today by The Pistoia Alliance, a global not-for-profit organization of more than 150 members established by executives from AstraZeneca, GlaxoSmithKline (GSK), Novartis, and Pfizer. The Alliance surveyed 190 life sciences professionals in the US and Europe, with 52% citing access to data, and 44% a lack of skills, as the two key barriers of adoption of AI and machine learning.


Breakthrough research demonstrates AI can predict a psychotic break

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A trio of researchers have developed an experimental machine learning method that allows AI to listen for the early whispers of psychotic break that humans can't hear. The team, consisting of Neguine Rezaii of Harvard Medical School and Emory School of Medicine, and Elaine Walker and Philipp Wolff from Emory University's Department of Psychology, set out to see if there was any way to use language as an indicator of impending latent onset psychosis. They developed a machine learning method that looks for specific indicators long thought associated with psychosis, especially schizophrenia. The team then spent two years observing study volunteers, a significant portion of whom ended up demonstrating psychotic break (the first experience of a fully psychotic episode). The results of the study were incredible.


Faster Customer Service with AI Bots and Humans Together SAP News

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It's one thing to bring conversational bots and robotic process automation (RPA) into business applications. But the strongest opportunity for innovative companies is in combining these capabilities. I discovered how some market leaders have already found this exponential power during one session at the recent SAPPHIRE NOW and ASUG Annual Conference. "It's the convergence of these technologies that provide the opportunity for a better experience, as well as the ability to apply machine learning technologies to create an ever-learning enterprise, applying knowledge and skills acquired from that machine learning technology to create the Intelligent Enterprise," said Shawn Brodersen, global vice president and SAP CTO at HCL Technologies Ltd. One pharmaceutical company improved workforce engagement with intelligent RPA and conversational artificial intelligence (AI).


AI Trends To Watch In 2019 - CB Insights Research

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Our analysts looked across industries to identify 25 of the biggest AI trends to watch in 2019, from next-gen prosthetics to crop monitoring. Artificial intelligence is spreading across every industry.


Artificial Intelligence for Pharma: Time for Internal Investment

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Artificial intelligence (AI) has achieved human-level capabilities and continues to rapidly improve. For the pharmaceutical industry, AI can improve decision-making and transform the quest for better medicines. The keys are investing in data management and in internal AI talent who can create value by leveraging corporate data to tackle crucial business problems.


AI-Friendly CEOs and Board Members AI in Drug Discovery

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The goal of this report is to identify the leaders who are driving AI development in pharma and tech industries. This serves as an indicator for the companies, who are committed to using AI in their innovations processes and thus have a potential to improve their market position, comparing to their peers. To this extent, the presence of AI-friendly CEOs and Board members also indicates that the corporation is focused on increasing its R&D efficiency and thus is more likely to succeed in the drug discovery sector. This benchmarking shows the level of commitment of corporations to applying of AI methods and tools in their businesses. We assume that in the future we will be able to observe a correlation between such benchmarking and market and investment prospects of pharma and tech corporations.


World's Top 20 AI Drug Development Companies

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As Margaretta Colangelo, Partner at Deep Knowledge Ventures, mentions in her recent article'Although pharmaceutical companies spend over $172 billion on research and development annually, over 90% of molecules discovered using traditional techniques fail in human clinical trials. Moreover, 75% of newly approved drugs are unable to cover the cost of development and some analysts predict that ROI in pharmaceutical R&D may hit zero by 2020.' If we accept that this prediction has some good chances to become reality, then we should see the AI as the Deus ex Machina in the field of pharmaceutical R&D to keep a business alive, but also give the invaluable hope of choice to some patients. In this race for life, some firms set the pace trying to test their limits in uncharted waters. Deep Knowledge Analytics, a subsidiary of Deep Knowledge Ventures, an investment fund focused on DeepTech, separates the companies that are solely dedicated to core scientific R&D out of a total of 1000 AI Healthcare companies globally.


World's Top 20 AI Drug Development Companies

#artificialintelligence

As Margaretta Colangelo, Partner at Deep Knowledge Ventures, mentions in her recent article'Although pharmaceutical companies spend over $172 billion on research and development annually, over 90% of molecules discovered using traditional techniques fail in human clinical trials. Moreover, 75% of newly approved drugs are unable to cover the cost of development and some analysts predict that ROI in pharmaceutical R&D may hit zero by 2020.' If we accept that this prediction has some good chances to become reality, then we should see the AI as the Deus ex Machina in the field of pharmaceutical R&D to keep a business alive, but also give the invaluable hope of choice to some patients. In this race for life, some firms set the pace trying to test their limits in uncharted waters. Deep Knowledge Analytics, a subsidiary of Deep Knowledge Ventures, an investment fund focused on DeepTech, separates the companies that are solely dedicated to core scientific R&D out of a total of 1000 AI Healthcare companies globally.