Opportunities to Pursue a Cost and Differentiation Strategy in Life Sciences Organizations

Executive summary

Over the past few years, Life Sciences companies have committed to cost and differentiation strategy to improving operational efficiencies and automation focusing on Digital Innovation. The goal is to work smarter through advanced automation and data-driven decision making throughout all organization’s business functions.

Achieving this commitment is a challenge because commercially available AI based intelligent solutions are still in their infancy as compared to other industries such as finance and consumer goods.

By implementing the following sample strategies, a company can support their cost and differentiation/optimization objectives in the following business areas:

1. Pharmacovigilance

Automate the entire PV Case Intake process to reduce human interaction and move towards a touch-less case submission environment. The reduced manual hours directly result in cost savings. This includes NLP to read an Adverse Event either within a form or an unstructured email, and intelligently submit the Adverse Event to the Safety Database in a specific structured format. The NLP engine also translates the text from 5 languages into a PV Case in English.

2. Medical affairs

Implement a KOL (Key Opinion Leader) platform which includes an AI engine to help users search for and engage with these leaders in a targeted scientific and advocacy capacity. The AI based tool can utilize big data from various unstructured data sources, and apply AI to support selecting the fit-for purpose individual based on therapeutic area, disease, location, number of research articles, publications etc. By selecting the right KOL based on data, the firm can reduce long-term costs and improve efficiencies through targeted engagement strategies.

AI capabilities of the KOL platform can be used to process social media data to infer positive and negative sentiment on a relevant therapeutic area or disease. This will help identify leading and current influencers based on reach, relevance, and resonance criteria.

3. Commercial

Due to the COVID pandemic, the Commercial team has an opportunity to adopt technology to fill the gaps in activities that were traditionally always conducted in-person. Running Advisory Boards can now be conducted via a virtual platform. The data collected can be processed through an intelligent AI based tool to conduct intelligent focused surveys. This will save on travel and hotel costs which add up significantly over an annual period.
Conclusion

Conclusion

The above examples address a combined strategy of cost and differentiation. Differentiation is not from an end-product standpoint but a combination of how AI can help differentiate the collective organization from the competition and attract the best of breed talent. These are just a few examples of how a data-driven and digital innovation-focused leadership strategy is being fulfilled and where opportunities for improvement exist.