The landscape of medical treatments is undergoing a transformative shift. Precision medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and treatments according to each patient’s uniquely evolving health status. This groundbreaking method of tailoring disease prevention and treatment considers individual variations in genes, environments, and lifestyles. The goal of precision medicine is to target the “five rights”: the right patient, the right drug, the right time, the right dose, and the right route. In this pursuit, in silico techniques have emerged as an anchor, driving precision medicine forward and making this a realistic and promising avenue for personalized therapies. With the advancements in high-throughput DNA sequencing technologies, genomic data, including genetic variants and their interactions with each other and the environment, can be incorporated into clinical decision-making. Pharmacometrics, gathering pharmacokinetic (PK) and pharmacodynamic (PD) data, and mathematical models further contribute to drug optimization, drug behavior prediction, and drug–drug interaction identification. Digital health, wearables, and computational tools offer continuous monitoring and real-time data collection, enabling treatment adjustments. Furthermore, the incorporation of extensive datasets in computational tools, such as electronic health records (EHRs) and omics data, is also another pathway to acquire meaningful information in this field. Although they are fairly new, machine learning (ML) algorithms and artificial intelligence (AI) techniques are also resources researchers use to analyze big data and develop predictive models. This review explores the interplay of these multiple in silico approaches in advancing precision medicine and fostering individual healthcare. Despite intrinsic challenges, such as ethical considerations, data protection, and the need for more comprehensive research, this marks a new era of patient-centered healthcare. Innovative in silico techniques hold the potential to reshape the future of medicine for generations to come.

Asthma is a common inflammatory disease of the lungs. The prevalence of asthma is increasing worldwide, and the tendency indicates that the number of asthma sufferers will soar in the coming years for several reasons, in particular, the lifestyles we have adopted that expose us to risk factors. Salbutamol is the first selective short-acting β₂-agonist (SABA) used as an alternative reliever in the treatment of asthma. Its therapeutic effect is based on its potent smooth muscle relaxant properties, which allow the inhibition of bronchial smooth muscle contraction and subsequent bronchodilation. Salbutamol can be administered orally, intravenously (IV), intramuscularly (IM), subcutaneously, or by inhalation. For this reason, the pharmacokinetic (PK) parameters—absorption, distribution, metabolism, and elimination—are highly diverse and, consequently, the efficacy and adverse effects also differ between each formulation. Here, we review the pharmacological profile of different salbutamol formulations, focusing on their efficacy and adverse effects for its original application, asthma.

The healing process is a dynamic process accompanied by some classical symptoms of inflammation such as redness, swelling, pain, and loss of function. Chitosan is a natural polymer with properties that contribute to tissue healing, with properties that could be applied in periodontal therapy, such as the wound healing of oral mucosa. This experimental split-mouth study aims to assess the possibilities of chitosan influencing the healing process of oral mucosa in eight patients, where the studied group was subjected to two oral surgeries: one with chitosan hydrogel into the socket and other without the biomaterial. A semi-quantitative analysis of the data was performed. Some classic signs of inflammation in a short period of time were observed where chitosan acted, compared to the control. An absence of bleeding was observed in the chitosan cases. According to the literature, chitosan recruits and activates neutrophils and macrophages and stimulates angiogenesis. Hemostatic and antimicrobial activity of chitosan also play an important role in wound healing. Chitosan seems to improve the postoperative quality of patients, allowing rapid wound healing with less complications.

Sexually transmitted infections (STIs), such as Chlamydia trachomatis (Ct) infection, have serious consequences for sexual and reproductive health worldwide. Ct is one of the most common sexually transmitted bacterial infections in the world, with approximately 129 million new cases per year. C. trachomatis is an obligate intracellular Gram-negative bacterium. The infection is usually asymptomatic, notwithstanding, it could also be associated with severe sequels and complications, such as chronic pain, infertility, and gynecologic cancers, and thus there is an urgent need to adequately treat these cases in a timely manner. Consequently, beyond its individual effects, the infection also impacts the economy of the countries where it is prevalent, generating a need to consider the hypothesis of implementing Chlamydia Screening Programs, a decision that, although it is expensive to execute, is a necessary investment that unequivocally will bring financial and social long-term advantages worldwide. To detect Ct infection, there are different methodologies available. Nucleic acid amplification tests, with their high sensitivity and specificity, are currently the first-line tests for the detection of Ct. When replaced by other detection methods, there are more false negative tests, leading to underreported cases and a subsequent underestimation of Ct infection’s prevalence. Ct treatment is based on antibiotic prescription, which is highly associated with drug resistance. Therefore, currently, there have been efforts in line with the development of alternative strategies to effectively treat this infection, using a drug repurposing method, as well as a natural treatment approach. In addition, researchers have also made some progress in the Ct vaccine development over the years, despite the fact that it also necessitates more studies in order to finally establish a vaccination plan. In this review, we have focused on the therapeutic options for treating Ct infection, expert recommendations, and major difficulties, while also exploring the possible avenues through which to face this issue, with novel approaches beyond those proposed by the guidelines of Health Organizations.

Drug–drug interactions (DDIs) represent a significant concern in healthcare, particularly for patients undergoing polytherapy. DDIs can lead to a range of outcomes, from decreased therapeutic effectiveness to adverse effects. Salbutamol, a bronchodilator recommended for the treatment of respiratory diseases, is metabolized by cytochrome P450 (CYP) enzymes, which can be inhibited or induced by co-administered drugs. Studying DDIs involving salbutamol is crucial for optimizing drug therapy and preventing adverse outcomes. Here, we aimed to investigate CYP-mediated DDIs between salbutamol and fluvoxamine through in silico approaches. The physiologically based pharmacokinetic (PBPK) model of salbutamol was developed and validated using available clinical PK data, whereas the PBPK model of fluvoxamine was previously verified by GastroPlus. Salbutamol–fluvoxamine interaction was simulated according to different regimens and patient’s characteristics (age and physiological status). The results demonstrated that co-administering salbutamol with fluvoxamine enhanced salbutamol exposure in certain situations, especially when fluvoxamine dosage increased. To sum up, this study demonstrated the utility of PBPK modeling in predicting CYP-mediated DDIs, making it a pioneer in PK DDI research. Furthermore, this study provided insights into the relevance of regular monitoring of patients taking multiple medications, regardless of their characteristics, to prevent adverse outcomes and for the optimization of the therapeutic regimen, in cases where the therapeutic benefit is no longer experienced.

Chemotherapy is the main treatment for most early-stage cancers; nevertheless, its efficacy is usually limited by drug resistance, toxicity, and tumor heterogeneity. Cell-penetrating peptides (CPPs) are small peptide sequences that can be used to increase the delivery rate of chemotherapeutic drugs to the tumor site, therefore contributing to overcoming these problems and enhancing the efficacy of chemotherapy. The drug combination is another promising strategy to overcome the aforementioned problems since the combined drugs can synergize through interconnected biological processes and target different pathways simultaneously. Here, we hypothesized that different peptides (P1–P4) could be used to enhance the delivery of chemotherapeutic agents into three different cancer cells (HT-29, MCF-7, and PC-3). In silico studies were performed to simulate the pharmacokinetic (PK) parameters of each peptide and antineoplastic agent to help predict synergistic interactions in vitro. These simulations predicted peptides P2–P4 to have higher bioavailability and lower T_max, as well as the chemotherapeutic agent 5-fluorouracil (5-FU) to have enhanced permeability properties over other antineoplastic agents, with P3 having prominent accumulation in the colon. In vitro studies were then performed to evaluate the combination of each peptide with the chemotherapeutic agents as well as to assess the nature of drug interactions through the quantification of the Combination Index (CI). Our findings in MCF-7 and PC-3 cancer cells demonstrated that the combination of these peptides with paclitaxel (PTX) and doxorubicin (DOXO), respectively, is not advantageous over a single treatment with the chemotherapeutic agent. In the case of HT-29 colorectal cancer cells, the combination of P2–P4 with 5-FU resulted in synergistic cytotoxic effects, as predicted by the in silico simulations. Taken together, these findings demonstrate that these CPP6-conjugates can be used as adjuvant agents to increase the delivery of 5-FU into HT-29 colorectal cancer cells. Moreover, these results support the use of in silico approaches for the prediction of the interaction between drugs in combination therapy for cancer.