The journey of developing and bringing a new drug to market is a long and complex one. In most countries, the process is almost entirely manual, and the path from initial research to regulatory approval and market authorization can take anywhere from several months to years. This challenge continues to worry stakeholders across research and development (R&D) who want to get medicines to patients more quickly.
To shorten this timeline, pharma companies and regulatory affairs subject matter experts (SMEs) are turning to artificial intelligence (AI) and gen AI solutions to enhance the discovery-to-market timeline.
Using AI to curate and disseminate regulatory insights
Traditionally, regulatory decision-making has relied on the experience and judgment of subject matter experts (SMEs). These individuals play a crucial role in guiding companies through diverse health authority (HA) requirements, but there may be instances of error. To improve regulatory processes and drive more predictive and proactive insights, pharma leaders can implement gen AI solutions in the process, allowing SMEs to make faster, more informed decisions.
3 actionable areas where companies can use AI-powered systems that combine both public and company-specific data to generate actionable insights:
Regulatory requirements: AI tools can automatically summarize legislation and health authority (HA) notifications and notify SMEs of any changes to regulatory submissions.
Internal precedence: Intelligent AI-enabled systems can scan historical data and generate insights, helping SMEs avoid repeating past mistakes.
External intelligence: AI can generate insights on competitor experience, market trends, and even real-world evidence to help pharma leaders understand the evolving regulatory landscape. This allows teams to act proactively in accelerating approvals and improving the quality of submissions.
For an AI solution to truly transform drug development and accelerate market access, it must improve in both speed and decision-making quality. An effective drug development consulting services can help:
- Anticipate and pre-empt HA queries before they arise.
- Improve regulatory strategies to increase the probability of technical and registration success.
- AI models equipped with advanced natural language processing (NLP) algorithms can help categorize and tag documents for quick searches
- Enable users to have access to the relevant regulatory information
While no end-to-end regulatory intelligence platform currently exists, many tools and technologies are already reshaping how regulatory teams operate. SMEs that work with gen AI capabilities and drug development consulting services stand to improve their therapies and accelerate patient access.
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