Artificial intelligence (AI) can transform drug discovery and early drug development by addressing inefficiencies in traditional methods, which often face high costs, long timelines, and low success rates. In this review we provide an overview of how to integrate AI to the current drug discovery and development process, as it can enhance activities like target identification, drug discovery, and early clinical development. Through multiomics data analysis and network-based approaches, AI can help to identify novel oncogenic vulnerabilities and key therapeutic targets. AI models, such as AlphaFold, predict protein structures with high accuracy, aiding druggability assessments and structure-based drug design. AI also facilitates virtual screening and de novo drug design, creating optimized molecular structures for specific biological properties. In early clinical development, AI supports patient recruitment by analyzing electronic health records and improves trial design through predictive modeling, protocol optimization, and adaptive strategies. Innovations like synthetic control arms and digital twins can reduce logistical and ethical challenges by simulating outcomes using real-world or virtual patient data. Despite these advancements, limitations remain. AI models may be biased if trained on unrepresentative datasets, and reliance on historical or synthetic data can lead to overfitting or lack generalizability. Ethical and regulatory issues, such as data privacy, also challenge the implementation of AI. In conclusion, in this review we provide a comprehensive overview about how to integrate AI into current processes. These efforts, although they will demand collaboration between professionals, and robust data quality, have a transformative potential to accelerate drug development.

Nanoparticles (NPs) are promising drug delivery systems (DDS) for identifying and treating cancer. Active targeting NPs can be generated by conjugation with ligands that bind overexpressed or mutant cell surface receptors on target cells that are poorly or not even expressed on normal cells. Receptor-mediated endocytosis of the NPs occurs and the drug is released inside the cell or in the surrounding tissue due to the bystander effect. Antibodies are the most frequently used ligands to actively target tumor cells. In this context, antibody-based therapies have been extensively used in HER2+ breast cancer. However, some patients inherently display resistance and in advanced stages, almost all eventually progress. Functionalized NPs through conjugation with antibodies appear to be a promising strategy to optimize targeted therapies due to properties related to biocompatibility, suitable delivery control and efficiency of functionalization. This review is focused on the different strategies to conjugate antibodies into polymeric NPs. Recent antibody conjugation approaches applied to the improvement of breast cancer therapy are highlighted in this review.

Breast cancer is the most common invasive tumor in women and the second leading cause of cancer-related death. Nanomedicine raises high expectations for millions of patients as it can provide better, more efficient, and affordable healthcare, and it has the potential to develop novel therapeutics for the treatment of solid tumors. In this regard, targeted therapies can be encapsulated into nanocarriers, and these nanovehicles are guided to the tumors through conjugation with antibodies—the so-called antibody-conjugated nanoparticles (ACNPs). ACNPs can preserve the chemical structure of drugs, deliver them in a controlled manner, and reduce toxicity. As certain breast cancer subtypes and indications have limited therapeutic options, this field provides hope for the future treatment of patients with difficult to treat breast cancers. In this review, we discuss the application of ACNPs for the treatment of this disease. Given the fact that ACNPs have shown clinical activity in this clinical setting, special emphasis on the role of the nanovehicles and their translation to the clinic is placed on the revision.

Bromo and extraterminal domain (BET) inhibitors-PROteolysis TArgeting Chimera (BETi-PROTAC) is a new family of compounds that induce proteasomal degradation through the ubiquitination of the tagged to BET inhibitors Bromodomain proteins, BRD2 and BRD. The encapsulation and controlled release of BET-PROTACs through their vectorization with antibodies, like trastuzumab, could facilitate their pharmacokinetic and efficacy profile. Antibody conjugated nanoparticles (ACNPs) using PROTACs have not been designed and evaluated. In this pioneer approach, the commercial MZ1 PROTAC was encapsulated into the FDA-approved polymeric nanoparticles. The nanoparticles were conjugated with trastuzumab to guide the delivery of MZ1 to breast tumoral cells that overexpress HER2. These ACNPs were characterized by means of size, polydispersity index, and Z-potential. Morphology of the nanoparticles, along with stability and release studies, completed the characterization. MZ1-loaded ACNPs showed a significant cytotoxic effect maintaining its mechanism of action and improving its therapeutic properties.