Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery

Drug development is expensive, time-consuming, and has a high failure rate. In recent years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery, offering innovative solutions to complex challenges in the pharmaceutical industry. This manuscript covers the multifaceted role of AI in drug discovery, encompassing AI-assisted drug delivery design, the discovery of new drugs, and the development of novel AI techniques. We explore various AI methodologies, including machine learning and deep learning, and their applications in target identification, virtual screening, and drug design. This paper also discusses the historical development of AI in medicine, emphasizing its profound impact on healthcare. Furthermore, it addresses AI's role in the repositioning of existing drugs and the identification of drug combinations, underscoring its potential in revolutionizing drug delivery systems. The manuscript provides a comprehensive overview of the AI programs and platforms currently used in drug discovery, illustrating the technological advancements and future directions of this field. This study not only presents the current state of AI in drug discovery but also anticipates its future trajectory, highlighting the challenges and opportunities that lie ahead.

Polysaccharide-Based Coatings as Drug Delivery Systems

Therapeutic polysaccharide-based coatings have recently emerged as versatile strategies to transform a conventional medical implant into a drug delivery system. However, the translation of these polysaccharide-based coatings into the clinic as drug delivery systems still requires a deeper understanding of their drug degradation/release profiles. This claim is supported by little or no data. In this review paper, a comprehensive description of the benefits and challenges generated by the polysaccharide-based coatings is provided. Moreover, the latest advances made towards the application of the most important representative coatings based on polysaccharide types for drug delivery are debated. Furthermore, suggestions/recommendations for future research to speed up the transition of polysaccharide-based drug delivery systems from the laboratory testing to clinical applications are given.

Composite Drug Delivery System Based on Amorphous Calcium Phosphate-Chitosan: An Efficient Antimicrobial Platform for Extended Release of Tetracycline

One major warning emerging during the first worldwide combat against healthcare-associated infections concerns the key role of the surface in the storage and transfer of the virus. Our study is based on the laser coating of surfaces with an inorganic/organic composite mixture of amorphous calcium phosphate–chitosan–tetracycline that is able to fight against infectious agents, but also capable of preserving its activity for a prolonged time, up to several days. The extended release in simulated fluids of the composite mixture containing the drug (tetracycline) was demonstrated by mass loss and UV–VIS investigations. The drug release profile from our composite coatings proceeds via two stages: an initial burst release (during the first hours), followed by a slower evolution active for the next 72 h, and probably more. Optimized coatings strongly inhibit the growth of tested bacteria (Enterococcus faecalis and Escherichia coli), while the drug incorporation has no impact on the in vitro composite’s cytotoxicity, the coatings proving an excellent biocompatibility sustaining the normal development of MG63 bone-like cells. One may, therefore, consider that the proposed coatings’ composition can open the prospective of a new generation of antimicrobial coatings for implants, but also for nosocomial and other large area contamination prevention.

Degradation Behavior of Polymers Used as Coating Materials for Drug Delivery-A Basic Review

The purpose of the work was to emphasize the main differences and similarities in the degradation mechanisms in the case of polymeric coatings compared with the bulk ones. Combined with the current background, this work reviews the properties of commonly utilized degradable polymers in drug delivery, the factors affecting degradation mechanism, testing methods while offering a retrospective on the evolution of the controlled release of biodegradable polymeric coatings. A literature survey on stability and degradation of different polymeric coatings, which were thoroughly evaluated by different techniques, e.g., polymer mass loss measurements, surface, structural and chemical analysis, was completed. Moreover, we analyzed some shortcomings of the degradation behavior of biopolymers in form of coatings and briefly proposed some solving directions to the main existing problems (e.g., improving measuring techniques resolution, elucidation of complete mathematical analysis of the different degradation mechanisms). Deep studies are still necessary on the dynamic changes which occur to biodegradable polymeric coatings which can help to envisage the future performance of synthesized films designed to be used as medical devices with application in drug delivery.

Artificial Neural Network Algorithms for 3D Printing

Additive manufacturing with an emphasis on 3D printing has recently become popular due to its exceptional advantages over conventional manufacturing processes. However, 3D printing process parameters are challenging to optimize, as they influence the properties and usage time of printed parts. Therefore, it is a complex task to develop a correlation between process parameters and printed parts' properties via traditional optimization methods. A machine-learning technique was recently validated to carry out intricate pattern identification and develop a deterministic relationship, eliminating the need to develop and solve physical models. In machine learning, artificial neural network (ANN) is the most widely utilized model, owing to its capability to solve large datasets and strong computational supremacy. This study compiles the advancement of ANN in several aspects of 3D printing. Challenges while applying ANN in 3D printing and their potential solutions are indicated. Finally, upcoming trends for the application of ANN in 3D printing are projected.

Matrix-Assisted Pulsed laser Evaporation-deposited Rapamycin Thin Films Maintain Antiproliferative Activity

Matrix-assisted pulsed laser evaporation (MAPLE) has many benefits over conventional methods (e.g., dip-coating, spin coating, and Langmuir-Blodgett dip-coating) for manufacturing coatings containing pharmacologic agents on medical devices. In particular, the thickness of the coating that is applied to the surface of the medical device can be tightly controlled. In this study, MAPLE was used to deposit rapamycin-polyvinylpyrrolidone (rapamycin-PVP) thin films onto silicon and borosilicate optical glass substrates. Alamar Blue and PicoGreen studies were used to measure the metabolic health and DNA content of L929 mouse fibroblasts as measures of viability and proliferation, respectively. The cells on the MAPLE-deposited rapamycin-PVP surfaces exhibited 70.6% viability and 53.7% proliferation compared to a borosilicate glass control. These data indicate that the antiproliferative properties of rapamycin were maintained after MAPLE deposition.