Publications, Pharmaceutical

Sustainable Propellants and Bioequivalence Innovation in OINDPs

In the evolving landscape of the pharmaceutical industry, sustainability has become a pivotal concern, particularly in the realm of propellants used in respiratory devices. The transition towards propellants with low global warming potential (GWP) is gaining momentum, with alternatives like HFA 152a and HFO 1234ze standing out as prime examples. This shift is not just about replacing one material with another; it involves a comprehensive understanding of the practical application and formulation approaches necessary to mitigate the differences between various propellant options. Such progress reflects a broader dialogue on sustainability, emphasizing a cradle-to-grave perspective within the circular economy, especially for respiratory devices. This conversation has been significantly advanced by the amendment to the Montreal Protocol in Kigali in 2016, aimed at phasing down hydrofluorocarbons (HFCs), ratified by 65 countries so far.

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Author(s): William Ganley
7 Mar 2024

Another crucial development in this realm is the exploration of novel characterization methods to demonstrate the bioequivalence of orally inhaled drug products (OINDPs). Traditional methods for establishing bioequivalence are complex and resource-intensive, requiring extensive clinical studies. Nanopharm, has integrated in vitro and in silico models within its SmartTrack™ platform, enabling a streamlined demonstration of bioequivalence with fewer endpoints. This approach not only facilitates early-stage drug development and regulatory approval but also fosters a multidisciplinary perspective among scientists. Such collaboration is crucial for embracing complex methodologies like physiologically based pharmacokinetic (PBPK) modelling techniques, enhancing patient outcomes through a holistic view of drug product lifecycles.

The integration of technology in mirroring real-world complexities presents its own set of challenges, particularly in clinical trials, where patient variability can significantly impact outcomes. Partnerships, like that with Fluidda, are pioneering the use of machine learning and computational fluid dynamics (CFD) simulations to address these challenges. By focusing on sensitivity analysis and stratifying sample populations based on critical factors rather than traditional biomarkers, a more accurate and efficient trial design is possible. This in-silico approach not only enhances trial efficiency but also contributes to a deeper understanding of bioequivalence, paving the way for innovations that promise better patient care and sustainability in pharmaceuticals.

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