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.
销售和营销团队面临的挑战是在做出治疗决策之前确定这些时刻。
营销任何药品都需要精心制作的活动，以教育医疗保健专业人员在正确的时间点为特定患者提供最佳治疗选择。必威手机APP在肿瘤学中，患者人群相对较小，并且对多种肿瘤类型进行了治疗，直到现在很难预期。
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.
肿瘤学市场
近年来，肿瘤学研究一直令人难以置信。免疫疗法和有针对性疗法的进展已改变了癌症治疗方法，有望提供更好的生活质量，更长的寿命，在某些情况下可以完全缓解。
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.
这些创新的疗法正在改变肿瘤学的景观，但是最常使用的药物和最佳作用非常昂贵。前38种癌症药物占总支出的80％，导致关键药物之间的竞争。