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Pharma news on AI's role in drug development, new FDA/EMA guidance, clinical advances, MFN pricing agreements, and ongoing quality control challenges.
In this PharmTech video feature, we highlight the week’s industry news in an easy-to-consume, fun format. New roundups will drop every Friday, so be sure to come back each week. And be sure to check the links below for more in-depth coverage.
Collectively, the week’s coverage discusses the pharmaceutical industry’s recent developments and current regulatory landscape. Read on for recaps of each story we’ve covered.
Pfizer is the first pharmaceutical company to agree to the White House's most-favored-nation mandate, committing to lower its United States drug prices to match the lowest price among other developed nations.
FDA has released draft guidance on its regenerative medicine advanced therapy designation, an expedited program for cell and gene therapies. The guidance allows for flexibility in clinical development but maintains stringent chemistry, manufacturing, and controls standards.
The European Medicines Agency has proposed using patient experience data to complement scientific data in regulatory decision-making. A draft reflection paper encourages developers to collect this real-world evidence throughout a drug's lifecycle.
FDA's approval of Novartis' remibrutinib for chronic spontaneous urticaria expands the Bruton's tyrosine kinase inhibitor drug class beyond oncology. This provides an oral alternative to injectable biologics for the immune-mediated condition.
In the latest “Behind the Headlines,” recent industry developments include clinical trial progress for multiple myeloma and breast cancer, Merck's FDA approval for a subcutaneous formulation of Keytruda, and Pfizer's acquisition of Metsera to enter the weight-loss drug market.
Since 2018, the discovery of nitrosamine impurities in widely used drugs has prompted significant regulatory action. Global regulators now require pharmaceutical companies to conduct rigorous risk assessments to mitigate these risks throughout the supply chain.
Radiopharmaceuticals offer a precise, image-guided "theranostic" approach to cancer treatment, but development faces challenges including isotope supply and strict regulations. A new collaboration aims to create an integrated preclinical workflow to accelerate development.
Artificial intelligence (AI) and machine learning are being integrated into pharmaceutical workflows to screen compounds, predict drug properties in silico, and implement predictive controls in manufacturing. High-quality data and evolving regulatory frameworks are crucial for realizing AI's full potential.
In part two of a three-part series, there is an exploration of how agentic AI, which involves the autonomous coordination of goal-driven AI agents, can accelerate discovery by synthesizing information to generate novel hypotheses and has practical applications in pharmacovigilance and regulatory compliance.
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