Vitreo‐retinal disorders constitute a significant portion of treatable ocular diseases. These pathologies often require vitreo‐retinal surgery and, as a consequence, the use of vitreous substitutes. Nowadays, the vitreous substitutes that are used in clinical practice are mainly divided into gases (air, SF₆, C₂F₆, C₃F₈) and liquids (perfluorocarbon liquids, silicone oils, and heavy silicone oils). There are specific advantages and drawbacks to each of these, which determine their clinical indications. However, developing the ideal biomaterial for vitreous substitution continues to be one of the most important challenges in ophthalmology, and a multidisciplinary approach is required. In this sense, recent research has focused on the development of biocompatible, biodegradable, and injectable hydrogels (natural, synthetic, and smart), which also act as medium and long‐term internal tamponade agents. This comprehensive review aims to cover the main characteristics and indications for use of the extensive range of vitreous substitutes that are currently used in clinical practice, before going on to describe the hydrogels that have been developed recently and which have emerged as promising biomaterials for vitreous substitution.

Age-related macular degeneration (AMD) is a common ocular disease characterized by degeneration of the central area of the retina in the elderly population. Progression and response to treatment are influenced by genetic and non-genetic factors. Proteomics is a powerful tool to study, at the molecular level, the mechanisms underlying the progression of the disease, to identify new therapeutic targets and to establish biomarkers to monitor progression and treatment effectiveness. In this work, we systematically review the use of proteomics-based approaches for the study of the molecular mechanisms underlying the development of AMD, as well as the progression of the disease and on-treatment patient monitoring. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reporting guidelines were followed. Proteomic approaches have identified key players in the onset of the disease, such as complement components and proteins involved in lipid metabolism and oxidative stress, but also in the progression to advanced stages, including factors related to extracellular matrix integrity and angiogenesis. Although anti-vascular endothelial growth factor (anti-VEGF)-based therapy has been crucial in the treatment of neovascular AMD, it is necessary to deepen our understanding of the underlying disease mechanisms to move forward to next-generation therapies for later-stage forms of this multifactorial disease.

Over the last two decades, pharmacogenetics and pharmacokinetics have been increasingly used in clinical practice in Psychiatry due to the high variability regarding response and side effects of antipsychotic drugs. Specifically, long-acting injectable (LAI) antipsychotics have different pharmacokinetic profile than oral formulations due to their sustained release characteristics. In addition, most of these drugs are metabolized by CYP2D6, whose interindividual genetic variability results in different metabolizer status and, consequently, into different plasma concentrations of the drugs. In this context, there is consistent evidence which supports the use of therapeutic drug monitoring (TDM) along with pharmacogenetic tests to improve safety and efficacy of antipsychotic pharmacotherapy. This comprehensive review aims to compile all the available pharmacokinetic and pharmacogenetic data regarding the three major LAI atypical antipsychotics: risperidone, paliperidone and aripiprazole. On the one hand, CYP2D6 metabolizer status influences the pharmacokinetics of LAI aripiprazole, but this relation remains a matter of debate for LAI risperidone and LAI paliperidone. On the other hand, developed population pharmacokinetic (popPK) models showed the influence of body weight or administration site on the pharmacokinetics of these LAI antipsychotics. The combination of pharmacogenetics and pharmacokinetics (including popPK models) leads to a personalized antipsychotic therapy. In this sense, the optimization of these treatments improves the benefit–risk balance and, consequently, patients’ quality of life.

Background and Objectives: The use of artificial intelligence (AI) and, in particular, machine learning (ML) techniques is growing rapidly in the healthcare field. Their application in pharmacokinetics is of potential interest due to the need to relate enormous amounts of data and to the more efficient development of new predictive dose models. The development of pharmacokinetic models based on these techniques simplifies the process, reduces time, and allows more factors to be considered than with classical methods, and is therefore of special interest in the pharmacokinetic monitoring of antibiotics. This review aims to describe the studies that use AI, mainly oriented to ML techniques, for dose prediction and analyze their results in comparison with the results obtained by classical methods. Furthermore, in the review, the techniques employed and the metrics to evaluate the precision are described to improve the compression of the results. Methods: A systematic search was carried out in the EMBASE, OVID, and PubMed databases and the results obtained were analyzed in detail. Results: Of the 13 articles selected, 10 were published in the last three years. Vancomycin was monitored in seven and none of the studies were performed on new antibiotics. The most used techniques were XGBoost and neural networks. Comparisons were conducted in most cases against population pharmacokinetic models. Conclusions: AI techniques offer promising results. However, the diversity in terms of the statistical metrics used and the low power of some of the articles make the overall assessment difficult. For now, AI-based ML techniques should be used in addition to classical population pharmacokinetic models in clinical practice.

Inhaled administration of ethanol in the early stages of COVID-19 would favor its location on the initial replication sites, being able to reduce the progression of the disease and improving its prognosis. Before evaluating the efficacy and safety of this novel therapeutic strategy in humans, its characterization is required. The developed 65° ethanol formulation is stable at room temperature and protected from light for 15 days, maintaining its physicochemical and microbiological properties. Two oxygen flows have been tested for its administration (2 and 3 L/min) using an automated headspace gas chromatographic analysis technique (HS-GC-MS), with that of 2 L/min being the most appropriate one, ensuring the inhalation of an ethanol daily dose of 33.6 ± 3.6 mg/min and achieving more stable concentrations during the entire treatment (45 min). Under these conditions of administration, the formulation has proven to be safe, based on histological studies of the respiratory tracts and lungs of rats. On the other hand, these results are accompanied by the first preclinical molecular imaging study with radiolabeled ethanol administered by this route. The current ethanol formulation has received approval from the Spanish Agency of Medicines and Medical Devices for a phase II clinical trial for early-stage COVID-19 patients, which is currently in the recruitment phase (ALCOVID-19; EudraCT number: 2020-001760-29).