In this forward-looking whitepaper, Blue Mountain explores how agentic AI —autonomous, context-aware AI agents—could ...
Mechanistic models and hypothesis-driven strategies generate optimized efficient solutions for drug development, says Catalent’s Nathan Bennette at AAPS PharmSci ...
In the quest to develop safe and effective medicines, pharmaceutical companies rely on the precise combination of active pharmaceutical ingredients (APIs) and excipients. These crucial components play ...
Formulation scientists are behind the conversion of active pharmaceutical ingredients (API) into stable, bioavailable, and commercially viable dosage forms, rarely a simple process. Image Credit: ...
To optimize the final formulation for a drug, it must meet many criteria beyond producing a safe and effective product. For example, it must be stable and amenable to various manufacturing steps, such ...
Early on, the drug substance (DS) manufacturer will provide a wealth of preliminary characterization data. And if the drug is active in early nonclinical and preclinical testing, a larger quantity of ...
Scientists at the University of Toronto have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine learning ...
The funding round was led by Spero Ventures with participation from MBX Capital, Shimadzu Future Innovation Fund managed by Global Brain Corporation, Eli Lilly & Company, SignalFire, Ford Street ...
Lipid nanoparticle formulation has increased over the past two decades. LNPs have proven to be effective nano-based delivery vehicles for cytotoxic chemotherapeutic drugs, nucleic acid therapies and ...
The media have been replete with reports of ways in which the pharmaceutical industry has been able to increase revenue from medications that have been available for decades. 1 We report a new ...
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