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Correlative Image-Based Release Prediction and 3D Microstructure Characterization for a Long Acting Parenteral Implant

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Abstract

Imaging-based characterization of polymeric drug-eluting implants can be challenging due to the microstructural complexity and scale of dispersed drug domains and polymer matrix. The typical evaluation via real-time (and accelerated in vitro experiments not only can be very labor intensive since implants are designed to last for 3 months or longer, but also fails to elucidate the impact of the internal microstructure on the implant release rate. A novel characterization technique, combining multi-scale high resolution three-dimensional imaging, was developed for a mechanistic understanding of the impact of formulation and manufacturing process on the implant microstructure. Artificial intelligence-based image segmentation and imaging analytics convert “visualized” structural properties into numerical models, which can be used to calculate key parameters governing drug transport in the polymer matrix, such as effective permeability. Simulations of drug transport in structures constructed on the basis of image analytics can be used to predict the release rates for the drug-eluting implant without running lengthy experiments. Multi-scale imaging approach and image-based characterization generate a large amount of quantitative structural information that are difficult to obtain experimentally. The direct-imaging based analytics and simulation is a powerful tool and has potential to advance fundamental understanding of drug release mechanism and the development of robust drug-eluting implants.

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Funding

The project was primarily funded by Merck, and partially by DigiM. Employees may own stocks of their respective companies.

Author information

Author notes

  1. Zhen Liu, Li Li and Shawn Zhang contributed equally to the manuscript.

Authors and Affiliations

  1. Preformulation Sciences, Preclinical Development, Merck & Co., Inc., Kenilworth, NJ, 07033, USA

    Zhen Liu & Wei Xu

  2. Analytical Sciences, Preclinical Development, Merck & Co., Inc., Kenilworth, NJ, 07033, USA

    Li Li

  3. DigiM Solution LLC, Burlington, MA, 01803, USA

    Shawn Zhang, Josh Lomeo, Aiden Zhu & Jacie Chen

  4. Biopharmaceutics & Specialty Dosage Forms Preclinical Development, Merck & Co., Inc., Kenilworth, NJ, 07033, USA

    Stephanie Barrett & Athanas Koynov

  5. Pharm Commercialization Technology, Merck & Co., Inc., Kenilworth, NJ, 07033, USA

    Seth Forster

  6. Discovery Pharmaceutical Sciences, Merck & Co., Inc., Kenilworth, NJ, 07033, USA

    Peter Wuelfing

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  1. Zhen Liu
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Correspondence to Shawn Zhang or Wei Xu.

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Liu, Z., Li, L., Zhang, S. et al. Correlative Image-Based Release Prediction and 3D Microstructure Characterization for a Long Acting Parenteral Implant. Pharm Res 38, 1915–1929 (2021). https://doi.org/10.1007/s11095-021-03145-2

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  • DOI: https://doi.org/10.1007/s11095-021-03145-2

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