Pharma eyes AI deals to stem lost revenues from patent expirations

Core Insights - The pharmaceutical industry is increasingly leveraging artificial intelligence (AI) to enhance drug development efficiency and reduce costs, with companies like In Silico demonstrating significant advancements in this area [1][2][8] - A notable trend is the shift from traditional acquisition strategies to targeted deals that focus on acquiring specific assets, particularly in response to impending patent expirations [4][10][14] AI in Drug Development - In Silico has showcased the potential of AI in drug development, reporting an average of 13 months from project initiation to candidate selection for its drug rentosertib, which has shown positive signals in increasing lung function in a Phase IIa study [1] - AI-driven tools are sought by pharmaceutical companies to enhance internal R&D productivity and streamline the drug development process [2][3] Patent Expirations and Industry Response - The upcoming patent cliff between 2024 and 2030 is projected to reduce the global share of drugs protected under patents from 6% to 4%, resulting in an estimated loss of $236 billion in US revenues [6][7] - The industry is witnessing a surge in deal-making as companies seek to replenish their drug pipelines in light of patent expirations, with AI partnerships becoming increasingly common [7][9] Changing Acquisition Strategies - Pharmaceutical companies are moving away from large-scale mergers and acquisitions (M&A) towards smaller, asset-specific acquisitions to mitigate revenue losses from patent expirations [10][14] - Companies like Eli Lilly and AstraZeneca are actively pursuing AI capabilities through strategic partnerships, indicating a shift in mindset towards more targeted investments [4][11] Market Dynamics and Future Trends - The hierarchy of top-selling drugs is shifting, with a growing focus on metabolic disorders and peptide-based drugs, while oncology remains a significant area of interest [16][17][18] - Companies are also exploring secondary patents and trademarks as strategies to extend the lifecycle of branded drugs and maintain revenue streams despite patent expirations [20][22] Conclusion - AI is positioned as a transformative force in the pharmaceutical industry, with the potential to reshape drug development timelines and strategies for managing patent cliffs, although its impact may vary [23]