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.

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.

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.

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.

Poly(lactic-co-glycolic acid) (PLGA) hydrogels are highly utilized in biomedical research due to their biocompatibility, biodegradability, and other versatile properties. This review comprehensively explores their synthesis, properties, sustained release mechanisms, and applications in drug delivery. The introduction underscores the significance of PLGA hydrogels in addressing challenges like short half-lives and systemic toxicity in conventional drug formulations. Synthesis methods, including emulsion solvent evaporation, solvent casting, electrospinning, thermal gelation, and photopolymerization, are described in detail and their role in tailoring hydrogel properties for specific applications is highlighted. Sustained release mechanisms—such as diffusion-controlled, degradation-controlled, swelling-controlled, and combined systems—are analyzed alongside key kinetic models (zero-order, first-order, Higuchi, and Peppas models) for designing controlled drug delivery systems. Applications of PLGA hydrogels in drug delivery are discussed, highlighting their effectiveness in localized and sustained chemotherapy for cancer, as well as in the delivery of antibiotics and antimicrobials to combat infections. Challenges and future prospects in PLGA hydrogel research are discussed, with a focus on improving drug loading efficiency, improving release control mechanisms, and promoting clinical translation. In summary, PLGA hydrogels provide a promising platform for the sustained delivery of therapeutic agents and meet diverse biomedical requirements. Future advancements in materials science and biomedical engineering are anticipated to further optimize their efficacy and applicability in clinical settings. This review consolidates the current understanding and outlines future research directions for PLGA hydrogels, emphasizing their potential to revolutionize therapeutic delivery and improve patient outcomes.

In the current era of widespread antimicrobial resistance, the utilization of essential oils (EOs) derived from plants has emerged as a promising alternative in combating pathogens that have developed resistance to antibiotics. This review explores the therapeutic potential of essential oils as valuable tools in restoring the efficacy of antibiotics, highlighting their unique ability to affect bacteria in multiple ways and target various cellular systems. Despite the challenge of elucidating their precise mode of action, EOs have shown remarkable results in rigorous testing against a diverse range of bacteria. This review explores the multifaceted role of EOs in combating bacterial microorganisms, emphasizing their extraction methods, mechanisms of action, and comparative efficacy against synthetic antibiotics. Key findings underscore the unique strategies EOs deploy to counter bacteria, highlighting significant differences from conventional antibiotics. The review extends to advanced coating solutions for medical devices, exploring the integration of EO formulations into these coatings. Challenges in developing effective EO coatings are addressed, along with various innovative approaches for their implementation. An evaluation of these EO coatings reveals their potential as formidable alternatives to traditional antibacterial agents in medical device applications. This renaissance in exploring natural remedies emphasizes the need to combine traditional wisdom with modern scientific advancements to address the urgent need for effective antimicrobial solutions in the post-antibiotic era.