Achieving more with less in pharma R&D: Takeda’s open innovation programs
Japan’s oldest and largest pharmaceutical company chose open innovation as a tool to compete in the race to increase R&D productivity
Submissions
The Promise and Perils of Machine Learning in Pharmaceutical Drug Development
A look at GlaxoSmithKline's efforts to incorporate machine learning into their drug development processes.
Progressive Insurance: Are you a good driver? Let Machine Learning tell you
The insurance sector is not traditionally ahead of the curve when it comes to new technologies. But for this particular time, Machine Learning is tailor-made for the insurance industry.
Optum: Machine Learning at the center of Health Care
A brief analysis of Optum and its capabilities and challenges towards developing and implementing machine learning in the Health Care industry.
Under Armour: Can it Continue to Customize and Expand its Line of 3D-Printed Midsole Performance Footwear?
Under Armour has created 3D-printed midsoles for peak athlete performance, and continues to innovate to differentiate itself within the extremely competitive apparel industry.
Open innovation in the Public Sector: The Argentinean case
While governments have to deal with many of the most pressing issues of our era, their organizations are often not prepared to nurture innovation and implement disruptive solutions. To make things worse, most governments are not able to pay competitive salaries. In this article we will explore how the Argentinean government leverages open innovation processes to improve policy making
Paypal vs. Fraud – Have no fear, machine learning is here !
As globalization and online shopping increase the risk of fraud, consumers are looking to protect their data. Some companies, like PayPal, promise end-users to keep their information safe. But how can they deliver on this promise? Machine learning is certainly playing an increasing role.
Airbnb: Machine Learning to optimize the future of Gig Economy and the power of economy-sharing
Airbnb has focused in delivering a product that boosts the actual volatility, uncertainty, complexity and ambiguity of the market scenario by addressing the value in “experiences” for millennial generation
How L’Oréal is using AI and Machine Learning to disrupt the beauty industry
Personalization is the future of the beauty industry
Can data buy you value in the capital-intensive oil and gas industry?
“Data is just like crude. It’s valuable, but if unrefined it cannot really be used.” [1]