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Today Pharmaceutical Executive DailyReuters reports that Eli Lilly and Novo Nordisk’s low-cost oral GLP-1 tablets are keeping patients away from compound weight-loss drugs, reports Gilead Sciences renews five-year collaboration with WHO, Johnson & Johnson renews collaboration with Abu Dhabi Ministry of Health, and finally Parta Anvil argues that true industrialization of machine learning and AI in life sciences requires systems that are scientifically sound, clinically defensible, regulatory traceable, and operationally sustained.
This is reported by doctors interviewed by Reuters. meaningful shift Lower entry prices for Eli Lilly’s Foundayo and Novo Nordisk’s oral Wegovy are changing patient behavior as patients gravitate away from compounded GLP-1 drugs and towards branded tablets. Both Foundayo and the lowest-dose oral Wigoby start at $149 per month, which is the same price or less than many pharmacies currently charge for custom versions of semaglutide and tirzepatide. Doctors note that patients choosing between the two options are primarily drawn to the pills rather than switching to more effective injectables due to the combination of comparable price, oral convenience, and familiarity of a once-a-week pill. injection.
Two international health partnerships made news today. Gilead Sciences has renewed its five-year partnership with the World Health Organization, pledging funding, strategic support and donations to accelerate progress toward eliminating visceral leishmaniasis, the second most deadly parasitic disease after malaria, with the expansion of the agreement further strengthening its focus on high-infection countries in East Africa. Separately, Johnson & Johnson announced that it will collaborate with the Abu Dhabi Ministry of Health to launch a global intelligent operating room network and deploy J&J’s polyphonic open digital ecosystem across Abu Dhabi’s hospital systems, including Cleveland Clinic Abu Dhabi, PureHealth, Mediclinic Group and NMC Healthcare.
Finally, Partha Anbil addresses what it means. Machine learning actually takes time to work. AI is being leveraged in a variety of areas, from proof-of-concept pilots to industrial-scale deployments in life sciences organizations. Anvil argues that most pharmaceutical and biotech companies have amassed disconnected AI experiments that demonstrate capabilities but fail to scale, and that the organizations positioned to lead in the next decade will be those that build AI infrastructure that simultaneously meets four criteria: scientifically sound, clinically defensible, regulatory traceable, and operationally sustainable. His argument is that the industrialization of AI in life sciences is not primarily a technology issue, but a governance and system design challenge.
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