OBJECTIVE To systematically sort out the drugs causing drug-induced liver injury （DILI） and their relevant information， and to develop the Expert consensus on the medication catalog for drug-induced liver injury and rational drug use （hereinafter referred to as the Consensus）， so as to provide a reference for rational clinical use. METHODS Systematic searches were conducted across various literature databases， guideline retrieval websites and professional liver injury websites. Drugs identified as causing DILI from the included literature and online resources were extracted and assigned scores based on source credibility： three points for LiverTox A-class drugs and two points for B-class drugs； two points for drugs from Hepatox and guidelines； and one point for drugs from consensus and related literature sources. Drugs classified as LiverTox category A/B or with total scores ≥4 were included in the preliminary list of DILI-causing drugs. Opinions were collected and integrated from a multidisciplinary expert panel comprising 45 medical and pharmaceutical experts from 27 provinces across China through three rounds of the Delphi method （including questionnaires and discussion sessions）， and after revision， the final version of Consensus was formed. RESULTS & CONCLUSIONS This Consensus included 12 traditional Chinese medicines （TCMs） such as Polygoni Multiflori Radix and Ephedrae Herba， 151 Western medicines including amiodarone and atorvastatin， along with rational use information. For TCM， eight rational use information were included： evidence-based score， liver injury classification based on pathogenesis， liver injury classification based on biochemical abnormality pattern， clinical phenotype， laboratory examination manifestations， latency period， recovery time， and management strategies. For Western medicines， six additional items were included based on the TCM， namely liver function monitoring， discontinuation， contraindications， cautions， dose adjustments， and risk factors， totaling 14 items. This Consensus systematically compiles DILI drugs and their rational use information， which will support clinicians in enhancing the prevention， identification， and management of DILI， reducing the incidence of liver injury， and ensuring patient medication safety and efficacy.

OBJECTIVE To provide standardized guidance for the rational clinical use of antibody-based drugs for the treatment of myasthenia gravis， and to enhance the evidence-based system of guidelines and consensus in this field. METHODS The consensus expert team consisted of 71 multidisciplinary experts from 28 provinces/autonomous regions/municipalities directly under the Central Government. Evidence was systematically retrieved through multiple databases， drug package inserts， and official websites of international and national health administrative authorities， drug regulatory agencies， healthcare security departments， and related industry associations， up to April 30， 2025. Evidence was graded according to the 2014 version of JBI pre-grading system for evidence from intervention studies. Based on full consideration of the current best evidence and multidisciplinary expert experience， the expert consensus recommendations were formulated using a modified Delphi method. RESULTS The Evidence-based expert consensus on the clinical application and pharmaceutical management of antibody-based drugs for the treatment of myasthenia gravis standardized the key points of whole-process pharmaceutical management for four antibody-based drugs approved for marketing in the mainland of China for the treatment of myasthenia gravis （efgartigimod alfa， efgartigimod alfa/hyaluronidase， eculizumab， and rozanolixizumab）. It formulated 37 expert consensus recommendations covering nine pharmaceutical management aspects： drug suitability selection， medication in special populations， administration methods， drug storage， therapeutic drug monitoring and pharmacogenetic testing， immunization management， drug interactions， pharmaceutical care， and off-label drug use. CONCLUSIONS Based on the current best evidence and multidisciplinary expert experience， this consensus establishes a whole-process management framework for antibody-based drugs for the treatment of myasthenia gravis， from clinical application to pharmaceutical management. It provides a scientific basis for the rational and precise use of these drugs in clinical practice， effectively promotes the enhancement of pharmaceutical management efficiency， and helps improve the overall therapeutic benefits for patients.

The liver is the primary target organ for hematogenous metastasis of colorectal cancer, and colorectal cancer liver metastasis is one of the key and challenging aspects in its treatment. In order to improve the diagnosis and comprehensive treatment of colorectal cancer liver metastasis in China, the guideline development group has summarized advanced experiences and the latest achievements from both domestic and international sources, and has once again revised and updated the Guideline for the diagnosis and comprehensive treatment of colorectal cancer liver metastases (2025 edition) to continuously provide guidance and reference for clinical practice in this field in China.

The importance of consensus research in medical decision-making has become increasinglyprominent. However, this field has long lacked unified terminology definitions and reporting standards, leading to significant heterogeneity in study design, implementation, and result presentation that affects the credibility and reproducibility of outcomes. The ACCurate COnsensus Reporting Document (ACCORD) in the field of biomedical research provides a structured writing framework for various consensus methods such as the Delphi method and nominal group technique, aiming to enhance the completeness and transparency of study reports. Combined with specific cases, this article interprets the core items of ACCORD, offering references for the design, implementation, and reporting of high-quality consensus research in China.

OBJECTIVE To further standardize the technical operations and management processes throughout therapeutic drug monitoring （TDM）， clarify the clinical value of TDM implementation， improve the scientific validity and reliability of monitoring results， and provide a solid reference basis for the formulation and optimization of clinical individualized precision dosing regimens. METHODS The Guidelines for the Management of Therapeutic Drug Monitoring were formulated in accordance with the latest definition of guidelines by the Institute of Medicine of the National Academies and the standard guideline development methodology of the World Health Organization， and in compliance with the requirements of the appraisal of guidelines for research and evaluation. A modified Delphi method was adopted to establish the research question system； evidence-based medicine research methods were applied to systematically search multiple databases to screen the latest and most comprehensive evidence. Evidence was graded and evaluated based on the evidence grading system of the Chinese Evidence-Based Medicine Center， and the grading criteria for recommendation strength from the Oxford Centre for Evidence-Based Medicine were used to determine the recommendation strength. The recommendation opinions were formed through multidisciplinary expert consensus. RESULTS The Guidelines for the Management of Therapeutic Drug Monitoring cover four core modules， including TDM application indications， technical procedures， result interpretation and clinical application， and quality control， involving 18 primary research questions， 34 secondary research questions， and yield 82 recommendations. CONCLUSIONS The guidelines systematically standardize the key technical links and management requirements of the whole TDM process， provide scientific and operable standardized tools， help improve the standardization level of TDM work， promote the translation of monitoring results into clinical decision-making， and provide strong support for precision personalized medicine and ensuring the safety and rationality of medication use.

OBJECTIVE To clarify the current development status of clinical pharmacist training bases and the pharmacist workforce in China， and to provide evidence for standardizing base construction and promoting the high-quality development of hospital pharmacy. METHODS Questionnaires were distributed to all clinical pharmacist training bases for urgently-needed health professionals and clinical pharmacist training bases under the Chinese Hospital Association that had been approved by the end of 2023 to collect data including base profiles and pharmacist staffing conditions. Expert teams carried out field investigations to verify the collected data. Descriptive statistical analyses were conducted on the quantity， type and regional distribution of training bases， and the influencing factors of pharmacist staffing in the bases were analyzed. RESULTS Field surveys were completed covering 297 training bases across 31 provincial-level administrative regions. Among the base hospitals， 87.88% were Grade A tertiary general hospitals， and 65.32% were located in provincial capitals. The eastern region had the largest number of bases （136， accounting for 45.79%）， followed by the western region （79， 26.60%）. Great disparities existed among provinces in terms of base quantity and hospital scale. The median proportion of pharmaceutical technical personnel in base hospitals was 4.05%， and the median number of clinical pharmacists per 100 hospital beds was 0.53. Both indicators reached the highest in the eastern region （0.57， 4.43%） and the lowest in the northeastern region （0.45， 3.01%）. A total of 3 627 full-time clinical pharmacists were employed in all surveyed bases， among whom 83.68% held clinical pharmacist training certificates， 35.43% possessed senior professional titles， and 78.19% had postgraduate or higher educational background. The total annual training capacity of the surveyed bases was 4 291 trainees， with obvious differences in annual training capacity across regions and provinces. Training specialties covered 19 specialized disciplines plus one general discipline， and no province could deliver training for all 20 specialties simultaneously. Multivariate Logistic regression analysis showed that geographic region exerte d a significant impact on the proportion of pharmaceutical technical personnel （≥4%） （ P ＜0.05）， while the approval time of training bases and hospital scale had significant effects on the number of clinical pharmacists per 100 beds （≥0.6） （ P ＜0.05）. CONCLUSIONS China’s clinical pharmacist training system has basically matured and taken initial shape. The distribution of clinical pharmacist training resources is generally consistent with regional population and economic development levels. However， the allocation of pharmaceutical staff and clinical pharmacists has not yet met national standards and clinical service demands.

OBJECTIVE To clarify the current development status of clinical pharmacist training bases and the pharmacist workforce in China， and to provide evidence for standardizing base construction and promoting the high-quality development of hospital pharmacy. METHODS Questionnaires were distributed to all clinical pharmacist training bases for urgently-needed health professionals and clinical pharmacist training bases under the Chinese Hospital Association that had been approved by the end of 2023 to collect data including base profiles and pharmacist staffing conditions. Expert teams carried out field investigations to verify the collected data. Descriptive statistical analyses were conducted on the quantity， type and regional distribution of training bases， and the influencing factors of pharmacist staffing in the bases were analyzed. RESULTS Field surveys were completed covering 297 training bases across 31 provincial-level administrative regions. Among the base hospitals， 87.88% were Grade A tertiary general hospitals， and 65.32% were located in provincial capitals. The eastern region had the largest number of bases （136， accounting for 45.79%）， followed by the western region （79， 26.60%）. Great disparities existed among provinces in terms of base quantity and hospital scale. The median proportion of pharmaceutical technical personnel in base hospitals was 4.05%， and the median number of clinical pharmacists per 100 hospital beds was 0.53. Both indicators reached the highest in the eastern region （0.57， 4.43%） and the lowest in the northeastern region （0.45， 3.01%）. A total of 3 627 full-time clinical pharmacists were employed in all surveyed bases， among whom 83.68% held clinical pharmacist training certificates， 35.43% possessed senior professional titles， and 78.19% had postgraduate or higher educational background. The total annual training capacity of the surveyed bases was 4 291 trainees， with obvious differences in annual training capacity across regions and provinces. Training specialties covered 19 specialized disciplines plus one general discipline， and no province could deliver training for all 20 specialties simultaneously. Multivariate Logistic regression analysis showed that geographic region exerte d a significant impact on the proportion of pharmaceutical technical personnel （≥4%） （ P ＜0.05）， while the approval time of training bases and hospital scale had significant effects on the number of clinical pharmacists per 100 beds （≥0.6） （ P ＜0.05）. CONCLUSIONS China’s clinical pharmacist training system has basically matured and taken initial shape. The distribution of clinical pharmacist training resources is generally consistent with regional population and economic development levels. However， the allocation of pharmaceutical staff and clinical pharmacists has not yet met national standards and clinical service demands.

OBJECTIVE To provide guidance on the scientific and standardized application of artificial intelligence （AI） and multimodal fusion techniques in constructing predictive models for adverse drug reactions （ADR） of antineoplastics， thereby enhancing the safety of antineoplastic therapy. METHODS Jointly initiated by the Clinical Pharmacy and Translational Pharmacy Society of the Liaoning Provincial Life Sciences Association and other professional societies， and organized by the Fourth Affiliated Hospital of China Medical University， the writing group conducted a comprehensive search of domestic and international databases using keywords such as “multimodal data” “artificial intelligence” “adverse drug reactions”“antineoplastics” and “models” to collect guidelines， expert consensuses， and relevant guidance literature. Based on this search， and combined with China’s practical experience in applying AI to oncology pharmaceutical care， a consensus framework and preliminary recommendations were drafted. Following evaluation and discussion by an external expert panel， the writing group incorporated the assessment results and formulated recommendations based on those endorsed by 90% or more of the experts. RESULTS &CONCLUSIONS After multiple rounds of review， discussion and revision， this consensus outlines the process for constructing an ADR prediction model of antineoplastics， encompassing “defining research objectives-data preparation-selection of algorithmic frameworks-design of multimodal data fusion strategies-model training and validation-interpretability analysis-clinical deployment-publication of results”. It also formulates 18 recommendations regarding core aspects such as data preparation， algorithm framwork selection， multimodal data fusion strategy design， model validation and interpretability analysis， and clinical deployment. These recommendations are intended for use by physicians in the field of oncology， clinical pharmacists， researchers， and AI technology developers to assist in making optimal clinical treatment decisions.

OBJECTIVE To investigate the current status of quality management in clinical pharmacist training bases in China， and to provide references for the standardized development and improvement of these bases. METHODS A combined approach of questionnaire survey and on-site investigation was adopted， targeting the healthcare highly sought-after talent （clinical pharmacist） training bases in 31 provinces of China as well as the clinical pharmacist training bases affiliated with the Chinese Hospital Association. A training quality management evaluation index system consisting of 25 tertiary indicators was established. Investigations were conducted from two dimensions： structural quality of training and quality management of training processes. Data were statistically analyzed using descriptive statistical methods. RESULTS On-site investigations were completed for 297 clinical pharmacist training bases across the 31 provinces， among which 284 were affiliated with the Chinese Hospital Association and 271 were healthcare highly sought-after talent （clinical pharmacist） training bases. In terms of structural quality， the core indicator compliance rate for hospital-level training systems exceeded 80%， the rate of special fund utilization for designated purposes reached 80.13%， and the overall compliance rate for software and hardware facilities surpassed 88%. A total of 1 348 preceptors were employed across the training bases， among whom those with senior professional titles and full-time specialist clinical pharmacists as lead preceptors accounted for 62.91% and 94.36%， respectively. Regarding process quality， the compliance rate for “establishment of clinical practice teaching groups in accordance with regulations during clinical department rotations” was 85.19%， and 79.80% and 76.09% of the bases were found to implement strict confidentiality in theoretical examinations and meet the required scale of assessment cases， respectively. However， formal documents of corresponding training management regulations were formulated in only 57.91% of the bases， and the completeness and standardization rate of training manual completion was merely 47.47%. In addition， considerable disparities in quality management levels were observed among provinces， with issues in training process quality being particularly prominent. CONCLUSIONS The management system， hardware facilities， and preceptor staffing of clinical pharmacist training bases in China are relatively well-established， yet notable variations in quality management exist among training bases across different provinces.