Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology and machine learning present a transformative opportunity in the drug discovery, formulation, and testing of pharmaceutical dosage forms. By utilizing AI algorithms that analyze extensive biological data, including genomics and proteomics, researchers can identify disease-associated targets and predict their interactions with potential drug candidates. This enables a more efficient and targeted approach to drug discovery, thereby increasing the likelihood of successful drug approvals. Furthermore, AI can contribute to reducing development costs by optimizing research and development processes. Machine learning algorithms assist in experimental design and can predict the pharmacokinetics and toxicity of drug candidates. This capability enables the prioritization and optimization of lead compounds, reducing the need for extensive and costly animal testing. Personalized medicine approaches can be facilitated through AI algorithms that analyze real-world patient data, leading to more effective treatment outcomes and improved patient adherence. This comprehensive review explores the wide-ranging applications of AI in drug discovery, drug delivery dosage form designs, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies. This review provides an overview of various AI-based approaches utilized in pharmaceutical technology, highlighting their benefits and drawbacks. Nevertheless, the continued investment in and exploration of AI in the pharmaceutical industry offer exciting prospects for enhancing drug development processes and patient care.

Several developments and research methods are ongoing in drug technology and chemistry research to elicit effectiveness regarding the therapeutic activity of drugs along with photoprotection for their molecular integrity. The detrimental effect of UV light induces damaged cells and DNA, which leads to skin cancer and other phototoxic effects. The application of sunscreen shields to the skin is important, along with recommended UV filters. Avobenzone is widely used as a UVA filter for skin photoprotection in sunscreen formulations. However, keto-enol tautomerism propagates photodegradation into it, which further channelizes the phototoxic and photoirradiation effects, further limiting its use. Several approaches have been used to counter these issues, including encapsulation, antioxidants, photostabilizers, and quenchers. To seek the gold standard approach for photoprotection in photosensitive drugs, combinations of strategies have been implemented to identify effective and safe sunscreen agents. The stringent regulatory guidelines for sunscreen formulations, along with the availability of limited FDA-approved UV filters, have led many researchers to develop perfect photostabilization strategies for available photostable UV filters, such as avobenzone. From this perspective, the objective of the current review is to summarize the recent literature on drug delivery strategies implemented for the photostabilization of avobenzone that could be useful to frame industrially oriented potential strategies on a large scale to circumvent all possible photounstable issues of avobenzone.

Peptide–drug conjugates (PDCs) have emerged as a next-generation therapeutic platform, combining the target specificity of peptides with the pharmacological potency of small-molecule drugs. As an evolution beyond antibody–drug conjugates (ADCs), PDCs offer distinct advantages, including enhanced cellular permeability, improved drug selectivity, and versatile design flexibility. This review provides a comprehensive analysis of the fundamental components of PDCs, including homing peptide selection, linker engineering, and payload optimization, alongside strategies to address their inherent challenges, such as stability, bioactivity, and clinical translation barriers. Therapeutic applications of PDCs span oncology, infectious diseases, metabolic disorders, and emerging areas like COVID-19, with several conjugates advancing in clinical trials and achieving regulatory milestones. Innovations, including bicyclic peptides, supramolecular architectures, and novel linker technologies, are explored as promising avenues to enhance PDC design. Additionally, this review examines the clinical trajectory of PDCs, emphasizing their therapeutic potential and highlighting ongoing trials that exemplify their efficacy. By addressing limitations and leveraging emerging advancements, PDCs hold immense promise as targeted therapeutics capable of addressing complex disease states and driving progress in precision medicine.