Harnessing the power of data analytics in life sciences – Insights from the Digital Summit 2021

13 Jul 2022
Harnessing the power of data analytics in life sciences – Insights from the Digital Summit 2021

The Indegene Digital Summit in 2021 revealed that data analytics and artificial intelligence (AI) are top priorities for life sciences leaders. Experts from leading global organizations echoed the need for building strong analytical capabilities to accelerate drug discovery, development, time-to-market, and drive end-to-end personalization of healthcare professional (HCP) and patient experiences.

A series of panel discussions and case studies also reflected that a growing number of organizations are aggressively expanding their analytical investments and directing their efforts towards mining high volumes of unstructured data to extract valuable, hidden insights. What stood out to us from these conversations were three promising areas where leading life sciences organizations are leveraging advanced analytics and AI techniques to drive strategic decisions and better health outcomes.

1. Personalized CX

Customer engagement models are evolving. The life sciences industry is breaking away from the traditional, one-size-fits-all marketing approach and implementing an omnichannel style of engagement that is tailored to every HCP's needs and preferences. 

Advanced data analytics is at the core of this shift. The combination of AI and machine learning (ML) models for collecting and analyzing social, historical, and behavioural data is enabling organizations to gain a far more accurate understanding of HCPs to design personalized experiences for them.

Experts emphasized the need for organizations to leverage data from non-traditional sources (like social media) to better understand the attitudes and beliefs of their HCPs, understand what they actually think about a particular brand, and identify unmet needs.

However, data sources like these are highly unstructured – making them difficult to comprehend and extract insights from. The need of the hour is to build a modern data collection foundation powered by AI and ML analytical models that offer what traditional methods don't - conversion of unstructured data and integration of data collected from traditional and non-traditional channels.

Personalized CX

2. Accelerated Clinical Submission Approvals

Second on the list of top trends is the use of clinical analytics to speed up regulatory approval timelines. There is a high volume of data flowing in from various therapeutic areas and modalities, making it crucial to have automated AI-driven systems in place that can distill the data down to consumable chunks, which can be used for decision-making and strategy building.

Granular insights extracted from this technique can help life sciences organizations simplify patient characteristics, improve health outcomes, optimize research and development investments, and enhance regulatory affairs intelligence for early access and fast-track approvals.

Experts also discussed predicting a submission’s probability of success with additional realtime data. They also highlighted how AI can drive more global approaches to fit products to regulatory markets by applying insights from one submission process to another - encouraging thinking about the global picture earlier in the product’s development to do more for patients worldwide.

Accelerated Clinical Submission Approvals

3. Intelligent Patient Insights

HCPs have traditionally relied on a large number of drug efficacy data points when making decisions on how to treat their patients. Electronic Health Records, combined with a host of other data sources, help HCPs better understand the advantages of various treatment options. However, harnessing these data sources has always been a challenge.

Today, AI-driven analytics is playing a significant role in simplifying real-world data and generating a longitudinal view of the patient journey. This helps HCPs determine accurate patient and treatment outcomes, enabling them to make decisions with absolute certainty.

Experts also highlighted the shift from traditional probabilistic models to more modern counterfactual logic approaches that generate targeted patient insights with the help of novel AI and ML techniques – resulting in a significant rise in demand for medical possibilities.

Intelligent Patient Insights

Conclusion

Data and analytics have proven to be a powerful force in reshaping and disrupting the life sciences industry as it lays the foundation for an integrated and intuitive experience across the value chain. Experts at the Digital Summit shared how their companies are catalyzing focussed customer interactions, submission approvals, and data-driven patient insights. As more companies continue to raise the data and analytics literacy of their businesses, we see tremendous potential for them to further improve health outcomes and unearth medical possibilities. For more insights into how data and analytics are leading the way to a #FutureReadyHealthcare ecosystem, watch the on-demand sessions from the 2021 Digital Summit here. While you’re at it, don’t forget to sign up for the 2022 edition coming up this September!