Application of Deep Learning in Pharmaceutical Manufacturing

Dear Colleagues,

Artificial intelligence (AI) and machine learning (ML) are attracting tremendous attention in the pharmaceutical industry as valuable tools for product and process development. Although the lack of large, standardized datasets can make their application challenging, there are many recent examples of successful applications wherein these approaches helped to improve drug manufacturing efficiency. Moreover, it is ever more clear how computer-generated data, by means of numerical simulations, can rapidly close the gap of data availability for the training of very sophisticated deep learning architectures. Thus, their applications include product design, process optimization, process monitoring and control, and many others. All these may involve both classical deep learning techniques (fully connected neural networks) and more recent architectures (convolutional and graph-convolutional neural networks).

This Special Issue on “Application of Deep Learning in Pharmaceutical Manufacturing” seeks high-quality papers focusing on the most recent advances in deep learning and their applications in drug product manufacturing. Topics include, but are not limited to:

• Design of pharmaceutical formulation;
• Prediction of physicochemical properties of drug products;
• Design of innovative nanomedicine technologies and drug delivery systems;
• Product quality control;
• Process development and design of new manufacturing technologies;
• Process monitoring and control;
• Continuous manufacturing;
• Use of innovative deep learning architectures for product design or process investigation.

 We hope you consider participating in this Special Issue.

Prof. Dr. Roberto Pisano
Dr. Gianluca Boccardo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• machine learning
• artificial intelligence
• pharmaceutical manufacturing
• formulation
• optimization
• process control
• process monitoring