AI driven solutions enable sales and marketing team to identify KOLs based on research, doctor profiles; improve demand forecasts based on patient group activity and accelerate AER
Multiple inputs such as disease prevalence in a region, likelihood of prescription etc. would have to be considered to forecast drug demand in a region. Getting this right is important as it has multiple downstream implications on manufacturing and distribution supply chains
AI based models that use patient groups activity on social media, Electronic Health Records (EHR) data in a particular region, medical practitioners’ inputs help in estimation of demand for a particular drug or therapeutic treatment by region
Key Opinion Leaders (KOL) play a significant role in adoption of a drug. They could belong to patient health groups or medical practitioners who actively research in the subject therapeutic area.
AI models can help sales team sift through social media activity of patient health groups and literature to identify potential KOLs for upcoming drugs and therapies.
Adverse event case reporting involves high costs and labor intensity.
AI based tools can be used to detect adverse events through social listening and detect safety signals in clinical trial data and scientific literature. Models can be trained to specifically extract case critical information from source documents to identify valid adverse events and reduce false positives.