AI & Clinical Trials: Poised for Disruption

Posted by Arun Shastri on Wed, Sep 11, 2019

This blog post is the third in a series on the impact that AI will have on different business aspects of pharma.

We always tell our clients to start small with AI. As Pratap Khedkar shared in my first interview, it’s important to start with clear, specific use cases. For some aspects of the business, it may take some time to carefully consider what these specific use cases are and what opportunities AI can create. Clinical trials present no such difficulties. The opportunities to improve efficiencies are numerous and clear, and AI has begun to make an impact. The industry is aware of the inefficiencies that abound in clinical trial design and execution and is eager to solve them.


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AI & Product Launch: Meeting the Need for Speed

Posted by Arun Shastri on Wed, Aug 07, 2019

This blog post is the second in a series on the impact that AI will have on different business aspects of pharma.

AI is changing the way we do business. In my last post, I sat down with Pratap Khedkar to discuss AI’s role across the industry. Now that we’ve been introduced to AI and pharma, we can get more specific.

All aspects of the pharmaceutical organization are striving for increased efficiency and effectiveness by leveraging AI. As we pointed out in our previous post, there’s been more excitement in R&D because of how much data is available from clinical trials and consumer activity. But because of the focus on R&D, many commercial uses of AI have been underserved. One of those areas is product launch.


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AI & Pharma: Start Small But Think Big

Posted by Arun Shastri on Wed, Jul 24, 2019

This blog post is the first in a series on the impact that AI will have on different business aspects of pharma.

AI has been here for many decades, but the buzz around this latest wave of AI is louder than any I can remember. You can find articles about AI in every publication and medium. These articles deal mostly with broad themes, rarely delving into how AI might be applied in our work lives. There are plenty of stories about self-driving cars and the latest human expert to be outwitted by an algorithm. But what about the unsexy business that most of us find ourselves in? How can we apply AI to improve customer interactions, maximize product launches, optimize clinical trial operations, or find patient insights?


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Veeva Summit 2019: How AI and Customer-First Strategies Help Sales and Marketing Teams Stay Ahead of the Curve

Posted by Omer Hancer on Wed, May 22, 2019

Today, successful pharma outreach requires a customer-first mindset. This includes personalizing both content and channels, sending content at the right time and in the right channel to match customers’ levels of interest, adapting to physician reactions and humanizing AI sales and marketing suggestions for the rep so they understand why a suggested next best action is made. According to ZS research, personalization has resulted in a 20% increase in open rates for both marketing and rep-triggered emails and up to a 30% uplift in impactable sales.


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Intelligent Process Automation: Starting Is Easy, Scaling Is a Different Ball Game

Posted by Vishal Kabra on Thu, May 09, 2019

Satish Jha co-wrote this blog post with Vishal Kabra 

Today, there is no denying that when it comes to increasing efficiency, reducing cost and offering a better customer experience, intelligent process automation (IPA) is a go-to strategy for businesses, and pharma is no exception. IPA promises that it can free up people to do more value-added work and play more strategic roles within their organizations. At a fundamental level, IPA is an emerging set of new technologies that include robotic process automation (RPA), conversational AI and machine learning to mimic activities carried out by humans. With the evolution in IPA technologies and the broad applicability of such automation, IPA continues to be a buzzword in every industry. Given the many benefits and possibilities, it’s understandable why organizations are jumping onto the IPA bandwagon.

However, most organizations aren’t succeeding at scaling intelligent process automation.


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