Oncology 2020: From Invention to Outcomes

Posted by Jon Roffman on Mar 12, 2020 8:03:05 AM

Pranav Srivastava co-wrote this blog post with Jon Roffman. 

In the last three years alone, the FDA has given the green light to nearly 50 new cancer drugs. Were excited to see what 2020 has in store for this sector, as biopharma companies continue to bring these novel therapies and diagnostics to market. The fast pace of innovation in the oncology market presents increasingly complex challenges to manufacturers seeking to maximize the benefit that they can deliver to patientsWe’re committed to helping our client partnerand their customers thrive and ultimately improve outcomes for cancer patientsWith that in mind, our oncology practice is focused on three core dimensions that will be central to oncology manufacturers in the year ahead: navigating clinical pathways that drive the majority of treatment decisions in oncology; leveraging AI to deliver more relevant and valuable information to customers at the point of care; and delivering solutions that help customers better support their patients.


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Using the ‘Goldilocks Principle’ to Develop Data-Driven Oncology Account Strategies

Posted by Anshul Agarwal on Jan 15, 2019 8:00:00 AM

Scott Sandford and Abhishek Singh co-wrote this blog post with Anshul Agarwal.

The “Goldilocks principle,” which borrows its concept from the famous children’s story to describe when something is “just right,” can be applied to many situations, and the oncology landscape is no exception. Given the evolution of pharmaceutical manufacturer strategies in approaching oncology accounts and the data needed to support these strategies, manufacturers need to know what’s “just right” when it comes determining the resources needed for each account—a lesson that they can learn from Ms. Goldilocks and her friends, the bears.


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Is Your Oncology Analytics Organization Best in Class Yet?

Posted by Arup Das on Oct 25, 2018 8:00:00 AM

Arun Jain co-wrote this blog post with Arup Das.

Imagine a world where oncology analytics transform the way that a pharma manufacturer engages with its customer: Sales reps have real-time insight into where patients are being diagnosed. Accurate predictions help them anticipate when to follow up with a customer with a relevant message about their soon-to-relapse patient. Customers give them unencumbered access because they trust that the manufacturer will engage with them through their preferred channels at the right cadence. Does this sound too good to be true? Some oncology companies are already exploring these possibilities today, but according to ZS’s recent benchmarking study of oncology analytics organizations, many are not there yet in their analytics maturity and are missing out on critical opportunities to engage their customers when it matters most.


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AI Is Driving Change in Oncology Practice and Commercialization. Are You Part of the Wave?

Posted by Shankar Viswanathan on Feb 15, 2018 9:15:07 AM

Arup Das co-wrote this blog post with Shankar Viswanathan.

Looking back at 2017, artificial intelligence and machine learning made impressive progress when it comes to improving cancer diagnosis and treatment. Using deep learning, computers are scouring images to detect signs of breast cancer in mammograms earlier than humans are currently capable of. Using AI “random forests,” a learning algorithm, investigators are more accurately predicting which drug combination will work better in BRAF mutant melanoma. The AI-facilitated discovery of Berg Health’s BPM 31510, a pancreatic cancer drug, has entered human development clinical trials. AI is not only powering oncology drug discovery, faster detection and personalized treatment but also helping to improve oncology commercialization effectiveness and agility through analytics. 


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