Each week we highlight five things affecting the life sciences industry. Here’s the latest.
Biopharma research productivity increases
- Recent advancements in artificial intelligence are significantly enhancing research and development productivity by streamlining drug discovery processes, leading to more efficient development of new treatments.
- Per CHEManager, global biopharma research and development saw improved success rates and increased funding in 2023, driven by innovative trial designs and regulatory acceptance of data-driven methodologies.
Implications of Chevron’s demise for medtech
- The potential Supreme Court ruling on Chevron deference, a principle that compels courts to defer to a federal agency’s interpretation of ambiguous laws, could profoundly impact medtech regulation, with agency decisions subject to increased legal challenges.
- Per AdvaMed, eliminating Chevron deference may offer opportunities to contest overreaching regulations but also risk reduced regulatory certainty, impacting innovation and patient access.
BIOSECURE Act and its impact on U.S. biopharma
- The BIOSECURE Act aims to prevent U.S. federal funding from supporting biopharmaceutical collaborations with certain Chinese companies, potentially affecting over 120 drugs in development.
- Per Pharmaceutical Technology, this legislation could lead to increased costs and regulatory challenges for U.S. companies, especially those in clinical-stage trials as they seek alternative partnerships and suppliers.
Economic pressures prolong drug shortages, says U.S. Pharmacopeia report
- Drug shortages in the U.S. are lasting longer due to economic pressures such as low prices, manufacturing complexities and geographic concentration, according to a report by U.S. Pharmacopeia.
- Fierce Pharma reports that the profitability issues, particularly affecting generic drugs, and quality concerns leading to facility shutdowns, have exacerbated supply chain vulnerabilities, with shortages now averaging over three years in duration.
AI model predicts immunotherapy responses
- Researchers at the National Institutes of Health and Memorial Sloan Kettering have developed an AI model named LORIS to predict patient responses to immunotherapy using routine clinical data.
- Per Fierce Biotech, this model, incorporating data from over 3,700 patients, aims to enhance the precision of immunotherapy treatments by identifying likely responders and forecasting survival outcomes.
For more insights in life sciences, check out RSM’s industry outlook.
