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White Paper
Predictive Analytics in Oncology
How Artificial Intelligence Drives Greater Precision for Pharma Brands
Nov 27, 2019
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  • Predictive Analytics in Oncology
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In the world of innovative oncology drug sales and marketing, the ability to foresee when an oncology patient is ready to start initial treatment or switch to next line therapy represent fleeting moments of opportunity. These are the brief windows of time to link the right patients to the right treatments for the best possible outcomes.

The challenge that sales and marketing teams face is identifying those moments before treatment decisions are made.

Marketing any pharmaceutical product requires carefully crafted campaigns that educate healthcare professionals about the best treatment options for a specific patient at the right point in time. In oncology, where patient populations are relatively small, and treatments are indicated for multiple tumor types, that timing has been difficult to anticipate – until now.

Advances in big data analytics and artificial intelligence (AI) make it possible to predict when patients may need to start initial treatment, or may be moving to the next line of treatment, as well as which physicians are treating them. These predictive analytics can eliminate the trial-and-error approach to marketing oncology products and empower sales and marketing teams to deliver more precise physician engagement. The result? Personalized treatment for the right patient at the right time, providing better patient outcomes.

But while there is power in predictive analytics, not all models are created equal. Pharmaceutical companies need partners with access to diverse global healthcare data and the expertise to develop advanced machine learning models that can leverage human data science to accurately identify these patients. The right combination of science and data has been proven to deliver impressive results.


THE ONCOLOGY MARKETPLACE

Oncology research has hit incredible highs in recent years. Advances in immunotherapies and targeted therapies have transformed cancer treatment, promising to provide better quality of life, greater longevity, and in some cases, full remission.

These advances are drawing significant attention and investments as the number of approved cancer therapies continues to rise. From 2014 -2018, 57 oncology drugs were launched, gaining 89 indications across 23 different cancer types. In 2018, a record 15 new oncology therapeutics were launched – more than half of them are delivered as an oral formulation, have an orphan indication, or include a predictive biomarker on their label.The rapid pace of investment is likely to continue. There are currently 711 companies active in late-stage oncology R&D, working on a total of 849 products, including 29 academic institutions, 626 emerging biopharma (EBP) companies, and 28 large companies with global revenues over $5 billion.

These innovative therapies are changing the oncology landscape, but the drugs used most often and that work the best are very expensive. The top 38 cancer drugs account for 80 percent of total spendingiv leading to competition amongst the key drugs.


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Focus oncology development on the patient, manage trial complexity, and increase predictability and speed.

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