Insights from SAHARA+ Conference: Harnessing Real-World Data and AI to Transform Healthcare

EVERSANA’s executive director and Middle East head, Prashant Pandarathil, recently presented at Saudi Arabia’s Healthcare Advancement for Resourceful Funding, Regulatory Excellence and Innovation (SAHARA+) Conference on the topic “Harnessing the Power of Real-World Data (RWD) and AI in Healthcare.”

Here are some key takeaways:

The integration of RWD into healthcare offers significant benefits, ranging from enhancing R&D to improving patient care through personalized medicine. There are broadly five areas where the prudent use of RWD and the application of AI can yield supernormal ROI.

1. Fast-track early R&D: It takes about 8 to 10 years on average and $2.5 billion to take a product from concept to market. And over the last five years, R&D costs have risen faster than sales growth for the industry as a whole. Also, R&D white space is disappearing as portfolios of big pharma are increasingly overlapping; i.e., 76% of the top 20 pharma companies have Phase 2 or 3 assets in the same 20 leading indications. RWD can:
   • Inform research decisions and optimize early-stage R&D to lower failure rates
   • Play a role in identifying and quantifying unmet needs and disease burden for target validation, compound screening and lead optimization
2. Enhance clinical development: Clinical trials globally are getting more complex and less efficient. In the last 10 years, inflation-adjusted pharma clinical trial spending has outpaced clinical trial starts, with no significant improvement in technical and regulatory success. Over the last 10 years, the average clinical trial timelines increased from 37 to 41 months for Phase 2 trials and from 41 to 44 months for Phase 3 trials. There are two areas where RWD and AI can change the game in clinical development:
   • Predictive enrichment: RWD and AI can be leveraged to select patient cohorts that are more likely to respond positively to treatment.
   • Patient recruitment: This comprises more than 30% of any trial’s costs; hence, AI’s ability to quickly process and analyze vast amounts of RWD can allow for rapid identification and prescreening of potential participants to lower cost and shorten timelines.
3. Support regulatory decisions: Regulatory decisions are getting more complex, and the importance of surveillance and long-term monitoring is rising, especially with newer treatments such as cell and gene therapies and CAR T-cell therapy. RWD and AI can support and improve the quality of regulatory decisions by:
   • Informing clinical guidelines: Integrating RWD into Health Technology Assessments can enhance understanding of treatment efficacy and resource utilization.
   • Monitoring the long-term safety and effectiveness of medications: The U.S. FDA released guidance on using RWD to support regulatory decisions, as well as its role in demonstrating the safety and effectiveness of drugs post-approval.
4. Better inform resource allocation: Healthcare systems globally are evolving from a utilization (volume-based) to an impact (value-based) marketplace, and RWD can play a key role in assessing this impact and enable better-informed decision-making. RWD can help inform both demand and supply side by:
   • Identifying high-need areas for intervention in a health system
   • Budgeting and financial planning informed by data-driven perspectives
5. Improve patient outcomes: Late diagnosis is a critical challenge faced by many health systems in emerging markets. For example, the economic impact of an avoidable delayed diagnosis of a rare disease to the health system is about $500,000. With the right application of AI and disease algorithms in RWD, significant improvement can be made in identifying patients at high risk of many chronic conditions. The two critical areas where a combination of RWD and AI can considerably improve patient outcomes are:
   • Early diagnosis: Identify patients on the path to a diagnosis, helping inform doctors about exact signs and symptoms, as well as connect patients to therapies sooner
   • Personalized interventions: Develop personalized treatment plans that account for patients’ unique characteristics