- January 23, 2019
- Posted in AI
This post was last updated on January 7, 2020 at 2:20 pm
By Theresa Greco, Chief Commercial Officer
The PMSA Winter Symposium, “Innovation in Analytics via Machine Learning & AI” brought together industry leaders in data science and analytics to share experience and knowledge on real world applications of ML/AI within Life Sciences. Expert speakers and panelists shared deep insights with a focus on three areas: innovation, application, and collaboration.
- Innovation: The Industry investment in data science is alive and well as organizations continue to invest in strategies that deliver data-driven insights. Data acquisition strategies continue to expand the data fabric that informs model development and feature engineering. The expanding variety of data sources, when combined, help to identify new relationships that exist between variables and close missing data gaps. This allows identification of relationships that simply are not accessible when the sources are kept separate or are missing. Innovative applications of data science are applied to yield better insights faster.
- Application: There is a strong appetite for applications of ML/AI across the commercial lifecycle with key areas identified as segmentation, targeting, field and non-personal promotion, patient journeys, and forecasting, among others. Identification of the optimal patient for treatment in the world of personalized medicine is a real focus where AI applications can add significant value to help patients get the proper treatment at the right time in their journey.
- Collaboration: There is a strong desire for collaboration between data science and business stakeholders and a common perspective that both parties need to embrace the expertise and value being offered by the other in order to solve some of the most challenging business questions facing the industry today. The external partner landscape provides an additional layer of value and collaboration where domain experts complement the talents that exist within.
A recent WSJ article highlighting the value of startups in healthcare AI, featured Prognos as an innovative startup that applies best-in-class AI to clinical data to drive the right decisions earlier and improve health. The vast diagnostic data housed in the Prognos Registry is exactly the type of data that helps inform treatment and outcomes. The innovation of Prognos data scientists in applying AI to diagnostic and clinical data has real predictive power that is helping to identify ideal patients earlier in their disease progression in many broad, oncological and rare conditions so that patients can be matched with the optimal treatment at the optimal time. Prognos will continue to innovate and partner with the industry to improve health outcomes.