Drug-related problems (DRPs) are common among surgical patients, especially older patients with polypharmacy and underlying diseases. DRPs can potentially lead to morbidity, mortality, and increased treatment costs. The enhanced recovery after surgery (ERAS) system has shown great advantages in managing surgical patients. Medication therapy management for surgical patients (established as “surgical pharmacy” by Guangdong Province Pharmaceutical Association (GDPA)) is an important part of the ERAS system. Improper medication therapy management can lead to serious consequences and even death. In order to reduce DRPs further, and promote the rapid recovery of surgical patients, the need for pharmacists in the ERAS program is even more pressing. However, the medication therapy management services of surgical pharmacy and how surgical pharmacists should participate in ERAS programs are still unclear worldwide. Therefore, this article reviews the main perioperative medical management strategies and precautions from several aspects, including antimicrobial agents, antithrombotic agents, pain medication, nutritional therapy, blood glucose monitoring, blood pressure treatment, fluid management, treatment of nausea and vomiting, and management of postoperative delirium. Additionally, the way surgical pharmacists participate in perioperative medication management, and the relevant medication pathways are explored for optimizing medication therapy management services within the ERAS programs. This study will greatly assist surgical pharmacists’ work, contributing to surgeons accepting that pharmacists have an important role in the multidisciplinary team, benefitting medical workers in treating, counseling, and advocating for their patients, and further improving the effectiveness, safety and economy of medication therapy for patients and promoting patient recovery.

Background: The orally disintegrating tablets (ODTs) are especially suitable for elders and children with dysphagia, who need to be customized dosages. Objectives: This study aimed to prepare orally disintegrating tablets (ODTs) which can be customized as drug content by using semi-solid 3D printing pressure extrusion technology, with water insoluble and thermally unstable drug loratadine. Methods: The influence of binder concentration, disintegrating agent dosage and ratio mannitol: cellulose on formability and disintegration time was investigated. The properties of orally disintegrating tablets were investigated by ATR-FTIR, XRPD, DSC and SEM. The correlation formula between tablet bottom area and drug content was established. Results: The formulation was optimized, and contained loratadine 3 g, cellulose 4 g, mannitol 2 g, carboxy methyl starch sodium 1g, 6% PVP K30 16 ml. The disintegration time was less than 60 s with a infilling percentage of 60%, and the disintegration time was less than 30 s with a infilling percentage of 40%. There was no detectable interaction between loratadine and the selected excipients by the analysis of ATR-FTIR, DSC and XRPD. The structure of the tablets was porous, and the drug was dissolved completely within 10 min. The drug content (x) of the tablet and the bottom area (y) of the tablet showed a linear fitting relationship, y = 3.8603x - 0.7176, r2 = 0.9993. Conclusion: Semi-solid extrusion of 3D printing technology was applied to prepare loratadine orally disintegrating tablets with customized drug content, which provides an alternative method for the research of customized preparation.

Background: Pathological complete response (pCR) after neoadjuvant immunotherapy is associated with improved prognosis in colon and rectal cancer. This study aimed to develop and validate a predictive nomogram for pCR in CRC patients receiving neoadjuvant immunotherapy. Methods: A total of 232 eligible CRC patients who received immune checkpoint inhibitors (ICIs) followed by surgical resection at the Sixth Affiliated Hospital of Sun Yat-sen University (January 2018–December 2024) were retrospectively included, with 162 in the training set and 70 in the validation set. Univariate and multivariate logistic regression analyses were performed to identify factors influencing pCR, and a nomogram was subsequently developed. The area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the nomogram. Results: The pCR rate in the entire cohort was 53.4%, with rates of 76.8% (73/95) and 37.2% (51/137) in the MSI-H/dMMR and MSS/pMMR subgroups, respectively. In multivariable analysis, MSI-H/dMMR status and pretreatment CEA level < 5 ng/mL were independent predictors of pCR and were used to construct the nomogram. The nomogram achieved AUCs of 0.741 in the training set and 0.730 in the validation set. Calibration curve analysis showed good agreement between predicted and actual pCR in both sets, and decision curve analysis demonstrated favorable net benefit. Conclusions: Our nomogram may predict pCR and help identify likely responders to neoadjuvant immunotherapy-based regimens in non-metastatic CRC patients. Prospective multi-center validation is warranted to confirm its clinical utility.