Additive Manufacturing in Pharmaceuticals

See the new book, edited by Dr. Subham Banerjee, Ph.D., Associate Professor in the Department of Pharmaceutics, National Institute of Pharmaceutical Education & Research (NIPER), Guwahati, Assam, India.

Description: This book presents the different 3D/4D printing technological applications of Additive Manufacturing (AM) in Pharmaceutical Sciences. The initial chapter provides the historical perspective and current scenario of AM in pharmaceuticals. The book further discusses about different 3D printing platform technologies such as FDM, SLA, SLS, SSE, Ink-jet & binder jet principles & applications in developing advanced drug delivery systems. It also covers the methodology, materials for AM and important parameters associated with these platform technologies. The book highlights the progress and practical applications of 4D-printing technology in healthcare & pharmaceuticals fraternity as well including the essence of bioprinting in pharmaceuticals. Finally, the book reviews the regulatory guidelines, perspectives, and integration of Artificial Intelligence (AI)/Machine learning (ML) in pharmaceutical AM. This book is indeed a valuable resource for students, researchers/scholars, young start-ups/entrepreneurs, and pharmaceutical professionals by providing thorough detailing about AM in Pharmaceuticals.

Chapter 8

4D Printing in Pharmaceuticals

The term four-dimensional (4D) printing refers to the fabrication via additive manufacturing (AM) of structures with the capability to shape transform over time under a predefined stimulus (e.g., temperature, pH, electric field, humidity). Since its introduction in 2013, 4D printing has been in rapid expansion in several fields, including smart textiles, autonomous and soft robotics, biomedical devices, electronics, and tissue engineering. Shape-changing, self-repairing, and self-assembly are some of the characteristics usually associated with 4D printing, highlighting that 4D printed structures are no longer static objects but programmable active structures that accomplish their function through a change in their physical and/or chemical properties over time when exposed to a predetermined stimulus. Here, AM acts as an enabling technology by allowing a precise arrangement of an exact amount of one or more stimulus-responsive materials in predefined positions, without any constraints on the geometric complexity.

In the last few years, 4D printing has been exploited to develop increasingly sophisticated pharmaceutical and drug delivery systems, providing several advantages when compared with conventional fabrication approaches, such as (i) obtaining a highly controllable kinetic thanks to the smart properties and patterning of the involved stimulus-responsive material(s), (ii) achieving a time- and/or site-dependent drug release according to the shape-shifting of the structure after the sensing of a defined stimulus (e.g., change in pH or temperature, near-infrared lighting), and (iii) increasing the freedom to design systems able to settle, adapt, or remain and then release the conveyed drug in the target districts or move away from them.

In this chapter, we aim to provide the reader with an overview of 4D printing, as an emerging and breakthrough fabrication technology. Then, relevant examples from the recent literature regarding the use of 4D printing for the development of pharmaceutical and drug delivery systems are presented and deeply discussed.

See the chapter

Chiesa, I., Bonatti, A.F., De Acutis, A., Fortunato, G.M., Vozzi, G., De Maria, C. (2023). 4D Printing in Pharmaceuticals. In: Banerjee, S. (eds) Additive Manufacturing in Pharmaceuticals. Springer, Singapore. https://doi.org/10.1007/978-981-99-2404-2_8

Chapter 10

Regulatory Perspective of Additive Manufacturing in the Field of Pharmaceuticals

Spritam^® is the first 3D printed drug product approved by the FDA for clinical use. 3D printed drug product has to meet the standards of identity, strength, quality, and purity. Generally, the regulatory pathway to be followed in obtaining marketing authorization does not change with a manufacturing method employed in preparing a drug product or a device. New drug application can be submitted via 505(b)(1) or 505(b)(2) regulatory pathway, while abbreviated new drug application (generics) through 505j regulatory pathway. Generic versions of a branded product can be prepared by using a different manufacturing process than the one used by the branded product. For example, the generic version of Spritam^® does not need to be manufactured by any additive manufacturing method. As per the regulation, the sponsor of generic product has to demonstrate pharmaceutical equivalence and bioequivalence with Spritam^®. To encourage the adoption of novel technology in drug product manufacturing, including 3D printing, the FDA/CDER has established “Emerging Technology Program” to guide sponsors in identifying and resolving potential technical and regulatory challenges. This chapter reviews primarily the regulatory aspects of 3D printed drug products.

See the chapter

Rahman, Z., Charoo, N.A., Mohamed, E.M., Kuttolamadom, M., Khan, M.A. (2023). Regulatory Perspective of Additive Manufacturing in the Field of Pharmaceuticals . In: Banerjee, S. (eds) Additive Manufacturing in Pharmaceuticals. Springer, Singapore. https://doi.org/10.1007/978-981-99-2404-2_10

Chapter 11

Machine Learning in Additive Manufacturing of Pharmaceuticals

The application of machine learning and deep learning in additive manufacturing, also called 3D printing, is expected in industrial fields to be an effective method to optimize the manufacturing process, to control the quality of 3D printed objects, to detect defects in the objects, and to predict material properties. In the pharmaceutical field, 3D printed medicine has been approved by the United States Food and Drug Administration, and since then, 3D printing technology has been attracting attention, even creating a new model of tailored medicine. The 3D printing of pharmaceutical products needs a trial-and-error process due to the complex printing parameters as well as the physical properties of the printer ink, which is the drug formulation in this case. Machine learning may hold promise in solving the complex problems of drug manufacturing using 3D printers. This review introduces recent articles about 3D printed medicine and the application of machine learning. We also include recent articles about 3D printed medicine that use statistical approaches in the experimental methods. Finally, we discuss a possible future where “artificial intelligence pharmacists” will regularly use 3D printers in a clinical setting.

See the chapter

Tagami, T., Ogawa, K., Ozeki, T. (2023). Machine Learning in Additive Manufacturing of Pharmaceuticals. In: Banerjee, S. (eds) Additive Manufacturing in Pharmaceuticals. Springer, Singapore. https://doi.org/10.1007/978-981-99-2404-2_11

See the full book here

Dr. Subham Banerjee, Ph.D., Additive Manufacturing in Pharmaceuticals, Hardcover ISBN 978-981-99-2403-5, Published: 14 September 2023, eBook ISBN 978-981-99-2404-2, Published: 13 September 2023, DOI https://doi.org/10.1007/978-981-99-2404-2

There will be to additional articles here soon with the remaining book chapter contents: