Model-informed drug development in pediatric, pregnancy and geriatric drug development: States of the art and future.

The challenges of drug development in pediatric, pregnant and geriatric populations are a worldwide concern shared by regulatory authorities, pharmaceutical companies, and healthcare professionals. Model-informed drug development (MIDD) can integrate and quantify real-world data of physiology, pharmacology, and disease processes by using modeling and simulation techniques to facilitate decision-making in drug development. In this article, we reviewed current MIDD policy updates, reflected on the integrity of physiological data used for MIDD and the effects of physiological changes on the drug PK, as well as summarized current MIDD strategies and applications, so as to present the state of the art of MIDD in pediatric, pregnant and geriatric populations. Some considerations are put forth for the future improvements of MIDD including refining regulatory considerations, improving the integrity of physiological data, applying the emerging technologies, and exploring the application of MIDD in new therapies like gene therapies for special populations.

Optimal use of ß-lactams in neonates: machine learning-based clinical decision support system.

BACKGROUND: Accurate prediction of the optimal dose for ß-lactam antibiotics in neonatal sepsis is challenging. We aimed to evaluate whether a reliable clinical decision support system (CDSS) based on machine learning (ML) can assist clinicians in making optimal dose selections. METHODS: Five ß-lactam antibiotics (amoxicillin, ceftazidime, cefotaxime, meropenem and latamoxef), commonly used to treat neonatal sepsis, were selected. The CDSS was constructed by incorporating the drug, patient, dosage, pharmacodynamic, and microbiological factors. The CatBoost ML algorithm was used to build the CDSS. Real-world studies were used to evaluate the CDSS performance. Virtual trials were used to compare the CDSS-optimized doses with guideline-recommended doses. FINDINGS: For a specific drug, by entering the patient characteristics and pharmacodynamic (PD) target (50%/70%/100% fraction of time that the free drug concentration is above the minimal inhibitory concentration [fT > MIC]), the CDSS can determine whether the planned dosing regimen will achieve the PD target and suggest an optimal dose. The prediction accuracy of all five drugs was >80.0% in the real-world validation. Compared with the PopPK model, the overall accuracy, precision, recall, and F1-Score improved by 10.7%, 22.1%, 64.2%, and 43.1%, respectively. Using the CDSS-optimized doses, the average probability of target concentration attainment increased by 58.2% compared to the guideline-recommended doses. INTERPRETATION: An ML-based CDSS was successfully constructed to assist clinicians in selecting optimal ß-lactam antibiotic doses. FUNDING: This work was supported by the National Natural Science Foundation of China; Distinguished Young and Middle-aged Scholar of Shandong University; National Key Research and Development Program of China.

Machine Learning: A Potential Therapeutic Tool to Facilitate Neonatal Therapeutic Decision Making.

Bacterial infection is one of the major causes of neonatal morbidity and mortality worldwide. Finding rapid and reliable methods for early recognition and diagnosis of bacterial infections and early individualization of antibacterial drug administration are essential to eradicate these infections and prevent serious complications. However, this is often difficult to perform due to non-specific clinical presentations, low accuracy of current diagnostic methods, and limited knowledge of neonatal pharmacokinetics. Although neonatal medicine has been relatively late to embrace the benefits of machine learning (ML), there have been some initial applications of ML for the early prediction of neonatal sepsis and individualization of antibiotics. This article provides a brief introduction to ML and discusses the current state of the art in diagnosing and treating neonatal bacterial infections, gaps, potential uses of ML, and future directions to address the limitations of current studies. Neonatal bacterial infections involve a combination of physiologic development, disease expression, and treatment response outcomes. To address this complex relationship, future models could consider appropriate ML algorithms to capture time series features while integrating influences from the host, microbes, and drugs to optimize antimicrobial drug use in neonates. All models require prospective clinical trials to validate their clinical utility before clinical use.

Factors Influencing Early Diagnosis and Poor Prognosis of Dysphagia After Senile Ischemic Stroke.

Dysphagia is often a long-term problem after ischemic stroke, which are often accompanied by complications and results in poor outcome. This study aimed to investigate the influencing factors associated with the prognosis of dysphagia after senile ischemic stroke and evaluate the diagnostic performance of crucial factors. A total of 192 elderly ischemic stroke patients (96 patients without dysphagia with average age of 69.81 ± 4.61 years and 96 patients with dysphagia with average of 70.00 ± 6.66 years) were enrolled in the retrospective study. The clinical factors of the patients were collected and recorded for chi-square analysis and logistic analysis. The receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance of international normalized ratio (INR) and homocysteine (Hcy) in senile ischemic stroke patients. The age, cough reflex, history of stroke, mechanical ventilation, eating posture, insufficient elevation of the larynx, standard swallowing assessment (SSA) score, Hcy value, and INR were closely related to endpoint events of patients with dysphagia. The joint model (combined INR and Hcy value) can increase the area under the curve (AUC) value (0.948) with higher sensitivity and specificity for predicting patients with dysphagia occurred endpoint events. The influencing factors for older ischemic stroke patients with dysphagia include age, cough reflex, history of stroke, mechanical ventilation, eating posture, insufficient elevation of the larynx, SSA score, Hcy value, and INR. INR and Hcy were independent risk factors for prognosis and diagnostic markers for patients with dysphagia after senile ischemic stroke.

Population pharmacokinetics and dose optimization of levofloxacin in elderly patients with pneumonia.

AIMS: Levofloxacin is a quinolone antibiotic with a broad antibacterial spectrum. It is frequently used in elderly patients with pneumonia. The pharmacokinetic profile of elderly patients changes with age, but data on the pharmacokinetics of levofloxacin in these patients are limited. The aim of this study was to establish a population pharmacokinetic model of levofloxacin in elderly patients with pneumonia and to optimize individualized dosing regimens based on this newly developed model. METHODS: This is a prospective, open-label pharmacokinetic study in elderly patients with pneumonia. Blood samples were collected using an opportunistic approach. The plasma concentrations of levofloxacin were determined by high-performance liquid chromatography. A population pharmacokinetic model was established using nonlinear mixed-effect model software. Monte Carlo simulations were used for dose simulation and dose optimization. RESULTS: Data from 51 elderly patients with pneumonia were used for the population pharmacokinetic analysis. A one-compartment model with first-order elimination was most suitable for describing the data, and the estimated glomerular filtration rate was the only covariate that had a significant impact on the model. The final model estimated that the mean clearance of levofloxacin in elderly patients with pneumonia was 5.26 L/h. Monte Carlo simulation results showed that the optimal dosing regimen for levofloxacin was 750 mg once a day in elderly patients with pneumonia, with a minimum inhibitory concentration of 2 mg/L. CONCLUSIONS: The population pharmacokinetic model of levofloxacin in elderly patients with pneumonia was established, and the dose optimization of levofloxacin was completed through Monte Carlo simulation.

Machine Learning: A New Approach for Dose Individualization.

The application of machine learning (ML) has shown promising results in precision medicine due to its exceptional performance in dealing with complex multidimensional data. However, using ML for individualized dosing of medicines is still in its early stage, meriting further exploration. A systematic review of study designs and modeling details of using ML for individualized dosing of different drugs was performed. We have summarized the status of the study populations, predictive targets, and data sources for ML modeling, the selection of ML algorithms and features, and the evaluation and validation of their predictive performance. We also used the Prediction model Risk of Bias Assessment Tool (PROBAST) to assess the risk of bias of included studies. Currently, ML can be used for both a priori and a posteriori dose selection and optimization, and it can also assist the implementation of therapeutic drug monitoring. However, studies are mainly focused on drugs with narrow therapeutic windows, predominantly immunosuppressants (N = 23, 35.9%) and anti-infectives (N = 21, 32.8%), and there is currently only very limited attention for special populations, such as children (N = 22, 34.4%). Most studies showed poor methodological quality and a high risk of bias. The lack of external validation and clinical utility evaluation currently limits the further clinical implementation of ML for dose individualization. We therefore have proposed several ways to improve the clinical relevance of the studies and facilitate the translation of ML models into clinical practice.

Accuracy of antibiotic concentrations in drug dispensing in neonates: a laboratory-based study.

BACKGROUND: Antibacterial therapy plays a crucial role in neonatal infections. The efficacy of antibacterial agents is closely related to the actual dose given to neonates. So we evaluated factors potentially affecting the actual dose of intravenous antibiotics during dispensing process in neonates. METHODS: Meropenem, cefoperazone/sulbactam and piperacillin/tazobactam with two strengths were used to evaluate three methods. Method A (MA) was diluted once and the volumes of 5% glucose for MA were meropenem 4.00 mL, cefoperazone/sulbactam 3.00 mL, piperacillin/tazobactam 9.00 mL. Method B (MB) differed by doubling the volume of 5% glucose. The difference in method C (MC) involved diluting with 5% glucose twice. The concentrations were measured by high-performance liquid chromatography. Relative error (RE) was used to evaluate the preparation accuracy. RESULTS: The RE values using MA/MB/MC were: (1) meropenem 0.5 g: 15.1%, 8.0%, 10.4%; 0.25 g: 7.8%, 3.1%, 6.0%; (2) cefoperazone/sulbactam 1.5 g: 13.6%, 4.2%, 3.4%; 0.75 g: 8.8%, 3.5%, 4.0%; (3) piperacillin/tazobactam 4.5 g: 18.2%, 8.7%, 6.3%; 562.5 mg: 8.1%, 2.8%, 6.1%. MB was better than MA in all three drugs. No difference in RE values was found between single and double dilution, except meropenem with 0.25 g. Using MB, meropenem and piperacillin/tazobactam with small drug strength had higher accuracy in preparation. CONCLUSIONS: MB was suitable for neonatal drug dispensing because of its high accuracy and simple operation. Drugs with small strength were promoted due to the high accuracy.

Recombinant Klotho alleviates vancomycin-induced acute kidney injury by upregulating anti-oxidative capacity via JAK2/STAT3/GPx3 axis.

Emerging studies support that Klotho protects against different kidney diseases. However, the role of Klotho in vancomycin induced acute kidney injury (Van-AKI) is largely unclear. Hence this study aimed to explore the regulatory mechanism of Klotho in Van-AKI. The mRNA expression of Klotho and the JAK2/STAT3/GPx3 in renal tissue were assessed by RNA sequence analysis after 600 mg/kg Van daily for seven days; Small interfering RNA and recombinant protein are applied to examine the mechanism action of Klotho in vitro and in vivo respectively. Flow cytometry and spectrophotometry detected the expression of reactive oxygen species and antioxidant enzymes. Transmission electron microscopy scanned the structural damage of mitochondria. Western blotting, qPCR, and immunofluorescence were employed to explore the JAK2/STAT3/GPx3 expression. RNA sequence analysis found that Van challenging reduced Klotho and GPx3 expression but increased JAK2/STAT3 in renal tissue. In HK-2 cells, Klotho were decreased by Van in a dose-dependent manner. Klotho siRNA enhanced the production of reactive oxygen species and the cell apoptosis ratio by regulating the JAK2/STAT3, and JAK2/STAT3 inhibitors prevented the decrease of GPx3. Meanwhile, 1 µg/ml recombinant human Klotho showed the opposite function to 120 pmol Klotho siRNA. In Van-AKI BALB/c mice, 20 µg/kg recombinant mouse Klotho once every two days improved the anti-oxidative enzyme expression, mitochondria structure, renal dysfunction, and histological damage. In conclusion, Klotho enhances antioxidant capacity through the JAK2/STAT3/GPx3 axis, which in turn improves Van-AKI.

Genome-Wide Association Mapping of Processing Quality Traits in Common Wheat (Triticum aestivum L.).

Processing quality is an important economic wheat trait. The marker-assisted selection (MAS) method plays a vital role in accelerating genetic improvement of processing quality. In the present study, processing quality in a panel of 165 cultivars grown in four environments was evaluated by mixograph. An association mapping analysis using 90 K and 660 K single nucleotide polymorphism (SNP) arrays identified 24 loci in chromosomes 1A, 1B (4), 1D, 2A, 2B (2), 3A, 3B, 3D (2), 4A (3), 4B, 5D (2), 6A, 7B (2) and 7D (2), explaining 10.2-42.5% of the phenotypic variances. Totally, 15 loci were stably detected in two or more environments. Nine loci coincided with known genes or QTL, whereas the other fifteen were novel loci. Seven candidate genes encoded 3-ketoacyl-CoA synthase, lipoxygenase, pyridoxal phosphate-dependent decarboxylase, sucrose synthase 3 and a plant lipid transfer protein/Par allergen. SNPs significantly associated with processing quality and accessions with more favorable alleles can be used for marker-assisted selection.

Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates.

BACKGROUND AND OBJECTIVE: High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C0) and steady-state area-under-curve (AUC0-24) targets is important to optimize treatment. The objective was to evaluate whether machine learning (ML) can be used to predict these treatment targets to calculate optimal individual dosing regimens under intermittent administration conditions. METHODS: C0 were retrieved from a large neonatal vancomycin dataset. Individual estimates of AUC0-24 were obtained from Bayesian post hoc estimation. Various ML algorithms were used for model building to C0 and AUC0-24. An external dataset was used for predictive performance evaluation. RESULTS: Before starting treatment, C0 can be predicted a priori using the Catboost-based C0-ML model combined with dosing regimen and nine covariates. External validation results showed a 42.5% improvement in prediction accuracy by using the ML model compared with the population pharmacokinetic model. The virtual trial showed that using the ML optimized dose; 80.3% of the virtual neonates achieved the pharmacodynamic target (C0 in the range of 10-20 mg/L), much higher than the international standard dose (37.7-61.5%). Once therapeutic drug monitoring (TDM) measurements (C0) in patients have been obtained, AUC0-24 can be further predicted using the Catboost-based AUC-ML model combined with C0 and nine covariates. External validation results showed that the AUC-ML model can achieve an prediction accuracy of 80.3%. CONCLUSION: C0-based and AUC0-24-based ML models were developed accurately and precisely. These can be used for individual dose recommendations of vancomycin in neonates before treatment and dose revision after the first TDM result is obtained, respectively.

Regulatory considerations for paediatric drug evaluation in China.

The regulatory guidelines for the research and development of paediatric drugs are still evolving in China. The formulation of the guidelines started from learning and borrowing existing experience, and gradually changed to the exploration and improvement of local guidelines, which was not only in line with international standards but also had breakthroughs, innovations and Chinese characteristics. In this paper, the current setting of paediatric drug research and development in China and corresponding technical guidelines have been introduced from regulatory perspectives, and the accessibility of further improvement in regulatory strategies has also been discussed.

Optimizing ganciclovir and valganciclovir dosing regimens in pediatric patients with cytomegalovirus infection: a spotlight on therapeutic drug monitoring.

INTRODUCTION: Infants and immunocompromised children with cytomegalovirus (CMV) infection have significant morbidity and mortality. Ganciclovir (GCV) and its oral prodrug valganciclovir (VGCV) are the major antiviral options of choice for the prophylaxis and treatment of CMV infection. However, with the currently recommended dosing regimens used in pediatric patients, large intra- and inter-individual variability of pharmacokinetic (PK) parameters and exposure are observed. AREAS COVERED: This review describes the PK and pharmacodynamic (PD) characteristics of GCV and VGCV in pediatrics. Moreover, the role of therapeutic drug monitoring (TDM) and current clinical practice for GCV and VGCV dosing regimens optimization in pediatrics are discussed. EXPERT OPINION: GCV/VGCV TDM has shown the potential value to improve the benefit/risk ratio in pediatrics when using the therapeutic ranges derived from adults. However, well-designed studies are required to evaluate the relationship of TDM with clinical outcomes. Furthermore, studies to explore the children-specific dose-response-effect relationships will be helpful to facilitate the TDM practice. In the clinical setting, optimal sampling methods such as limited sampling strategies for pediatrics can be used in TDM and intracellular ganciclovir triphosphate may be used as an alternative TDM marker.

Impact of social reward on the evolution of cooperation in voluntary prisoner's dilemma.

The existence and sustainability of cooperation is a critical issue in nature and social systems. Reward is an essential mechanism to enhance cooperation. Meanwhile, some individuals loathe competition and then choose to escape and become a loner in competition. In this scenario, we propose a four-strategy networked evolutionary game model involving rewarders, loners, cooperators, and defectors. The classical square lattice and the Erdös-Rényi random network are adopted to describe the interaction between individuals. The four-strategy model is an extension of the classic prisoner's dilemma game model. The simulation results show that the introduction of new strategic choices can significantly improve cooperation in the population. The promotion level of cooperation is directly correlated with reward intensity and negatively correlated with reward cost. With regard to the evolution of altruistic behaviors, the fixed income from interactions with loners has an impact that is connected to the temptation to defect. Furthermore, by analyzing characteristic snapshots of four strategies, we further dissect the essence of the evolution of cooperation. As the temptation value increases, cooperators and rewarders first form compact clusters, then more and more loners join to resist the intrusion of defectors. Eventually, the three strategies coexist stably in a spatially structured population. Our research may shed some light on exploring the nature of cooperation and solving social dilemmas in the future.

Epithelial lining fluid concentrations of ceftriaxone in children with community-acquired pneumonia.

Ceftriaxone is widely used in children with community-acquired pneumonia. Currently, there are no available data regarding epithelial lining fluid (ELF) concentrations of ceftriaxone in children. Thus, blood and bronchoalveolar lavage fluids samples were collected by using an opportunistic sampling design, then we determined plasma and ELF concentrations in 22 children (0.5-11.7 years), with a total of 36 plasma and 22 ELF samples available for analysis. Ceftriaxone plasma and ELF concentrations ranged from 1.07 to 138.71 mg/L and from 0.61 to 26.69 mg/L, respectively. Ceftriaxone concentration in ELF was 12.18 ± 5.15 (mean ± standard deviation) times higher than that in plasma, ranging from 1.29 to 20.44.

A liquid chromatography-tandem mass spectrometry method for simultaneous quantification of thirty-nine tyrosine kinase inhibitors in human plasma.

Currently, the use of targeted drugs such as tyrosine kinase inhibitors (TKIs) plays an important role in clinical therapy. As the number of approved TKIs continues to increase, existing analysis methods will not be able to meet the growing needs, and will hamper the development of therapeutic drug monitoring (TDM) of TKIs. Based on LC-MS/MS technology, this study tends to develop and validate a multi-component analysis method for simultaneous determination of the concentrations of 39 TKIs in plasma. Spiked plasma was blended with isotope labelled internal standards, and injected into the LC-MS/MS system after protein precipitation by acetonitrile. Chromatographic separation was achieved using an ODS-4 column with gradient elution of formic acid/water (1:1000; v/v) and acetonitrile. Analytes detection was conducted in positive ionisation mode using MRM. The total run time was 8 min. The method validation was conducted by assessing the following parameters: selectivity, linearity and the lower limit of qualification, accuracy and precision, stability, matrix effect and recovery. The concentrations of 39 TKIs showed good linearity within the range of their respective standard curves in plasma, the accuracy of all quality control samples ranged from 85.9% to 114.1%, and the precision was lower than 13.3%. The extraction recovery ranged from 92.6% to 114.7%, and the matrix effect of plasma was lower than 11.3%. This new method was successfully developed, can be used for the determination of drug concentrations in multiple patients with different kinds of TKIs, and will therefore be suitable for TDM of 39 TKIs.

Meropenem for children with severe pneumonia: Protocol for a randomized controlled trial.

Background: Pneumonia, caused by infection or other factors, seriously endangers the health of children. Meropenem is an effective broad-spectrum antibiotic using in the treatment of infectious diseases. In the therapy of pneumonia, meropenem is mostly employed for the treatment of moderate to severe pneumonia. Previously, we established a population pharmacokinetics (PPK) model for meropenem in pediatric severe infection and simulated the control rate of the time during which the free plasma concentration of meropenem exceeds the minimum inhibitory concentration (MIC) is 70% of the dosing interval (70% fT > MIC). Therefore, we plan to conduct a multicenter randomized controlled trial (RCT) to compare the efficacy and safety between conventional regimen and model regimen for meropenem in pediatric severe pneumonia. Methods: One hundred patients (aged 3 months to 15 years) will be recruited in this RCT. They will be assigned randomly (at a 1:1 ratio) to a conventional treatment group (20 mg/kg, q8h, with 0.5-1 h infusion) and a model treatment group (20 mg/kg, q8 h, with 4 h infusion). The primary outcome will be 70% fT > MIC. Secondary outcomes will be the prevalence of meropenem therapy failure, duration of antibiotic therapy, changes in levels of inflammatory indicators, changes in imaging examination results, and prevalence of adverse events. Ethical approval of our clinical trial has been granted by the ethics committee of Beijing Children's Hospital ([2022]-E-133-Y). This trial has been registered in the Chinese Clinical Trial Registry (ChiCTR2200061207). Discussion: Based on our previous PPK data, we have designed this RCT. It is hoped that it will promote rational use of antibacterial drugs in children suffering from severe pneumonia. Clinical Trial Registration: http://www.chictr.org.cn identifier, ChiCTR2200061207.

Systematic review of efficacy, safety and pharmacokinetics of intravenous and intraventricular vancomycin for central nervous system infections.

Objective: The decision of vancomycin dosage for central nervous system (CNS) infections is still a challenge because its bactericidal nature in cerebrospinal fluid (CSF) has not been confirmed by human studies. This study systematically reviewed the literatures on vancomycin in patients with meningitis, ventriculitis, and CNS device-associated infections, to assess efficacy, safety, and pharmacokinetics to better serve as a practical reference. Methods: Medline, Embase, and Cochrane Library were searched using terms vancomycin, Glycopeptides, meningitis, and central nervous system infections. Data were extracted including characteristics of participants, causative organism(s), administration, dosage, etc., The clinical response, microbiological response, adverse events and pharmacokinetic parameters were analyzed. Results: Nineteen articles were included. Indications for vancomycin included meningitis, ventriculitis, and intracranial device infections. No serious adverse effects of intravenous (IV) and intraventricular (IVT) vancomycin have been reported. Dosages of IV and IVT vancomycin ranged from 1000-3000 mg/day and 2-20 mg/day. Duration of IV and IVT vancomycin therapy most commonly ranged from 3-27 days and 2-21 days. Therapeutic drug monitoring was conducted in 14 studies. Vancomycin levels in CSF in patients using IV and IVT vancomycin were varied widely from 0.06 to 22.3 mg/L and 2.5-292.9 mg/L. No clear relationships were found between vancomycin CSF levels and efficacy or toxicity. Conclusion: Using vancomycin to treat CNS infections appears effective and safe based on current evidence. However, the optimal regimens are still unclear. Higher quality clinical trials are required to explore the vancomycin disposition within CNS.

Developmental Population Pharmacokinetics-Pharmacodynamics of Meropenem in Chinese Neonates and Young Infants: Dosing Recommendations for Late-Onset Sepsis.

The pharmacokinetic (PK) studies of meropenem in Chinese newborns with late-onset sepsis (LOS) are still lacking. Causative pathogens of LOS and their susceptibility patterns in China differ from the data abroad. We, therefore, conducted a developmental population pharmacokinetic−pharmacodynamic analysis in Chinese newborns with the goal to optimize meropenem dosing regimens for LOS therapy. An opportunistic sampling strategy was used to collect meropenem samples, followed by model building and validation. A Monte Carlo simulation was performed to show the probability of target attainment (PTA) for various dosages. The information from 78 newborns (postmenstrual age: 27.4−46.1 weeks) was compiled and had a good fit to a 1-compartment model that had first order elimination. The median (range) values of estimated weight−normalized volume of distribution (V)and clearance (CL) were 0.60 (0.51−0.69) L/kg and 0.16 (0.04−0.51) L/h/kg, respectively. Covariate analysis revealed that postnatal age (PNA), gestational age (GA) and current weight (CW) were the most important factors in describing meropenem PK. Simulation results showed for LOS with a minimal inhibitory concentration (MIC) of 8 mg/L, the doses of 30 mg/kg 3 times daily (TID) as a 1-h infusion for newborns with GA ≤ 37 weeks and 40 mg/kg TID as a 3-h infusion for those with GA > 37 weeks were optimal, with PTA of 71.71% and 75.08%, respectively. In conclusion, we proposed an evidence-based dosing regimen of meropenem for LOS in Chinese newborns by using the population pharmacokinetic−pharmacodynamic analysis, based on domestic common pathogens and their susceptibility patterns.

Treatment of endometriosis with dienogest in combination with traditional Chinese medicine: A systematic review and meta-analysis.

Background: Endometriosis is now considered to be a systemic disease rather than a disease that primarily affects the pelvis. Dienogest (DNG) has unique advantages in the treatment of endometriosis, but it also has side effects. Alternatively, Traditional Chinese Medicine (TCM) has been used for over 2000 years in the treatment and prevention of disease and growing numbers of Chinese scholars are experimenting with the combined use of Dienogest and TCM for endometriosis treatment. Objectives: This review evaluated the efficacy and safety of TCM in combination with Dienogest in the treatment of endometriosis through meta-analysis. Methods: MEDLINE, Embase, the Cochrane Library, PubMed, Web of Science, China National Knowledge Infrastructure, Journal Integration Platform, and Wanfang were used in literature searches, with a deadline of May 31, 2022. Literature quality was assessed using the Cochrane Collaboration "risk of bias" (ROB2) tool, and the "meta" package of R software v.4.1 was used for meta-analysis. Dichotomous variables and continuous variables were assessed using the relative risk (RR) and 95% confidence intervals (95% CI); standard mean differences (MD) and 95% CI, respectively. Results: Twelve human randomized controlled trials (RCTs) and one retrospective study, all 13 written in the Chinese language, were included in the meta-analysis (720 experiments and 719 controls). The result indicated that TCM plus Dienogest was superior to Dienogest/TCM alone in increasing the cure rates (RR = 1.3780; 95% CI, 1.1058, 1.7172; P = 0.0043), remarkable effect rate (RR = 1.3389; 95% CI, 1.1829, 1.5154; P < 0.0001), invalid rate (RR = 0.2299; 95% CI, 0.1591, 0.3322; P < 0.0001), and rate of adverse effects (RR = 0.6177; 95% CI, 0.4288, 0.8899; P = 0.0097). The same conclusion was drawn from the subgroup analysis. Conclusion: Results suggest that TCM combined with Dienogest is superior to Dienogest or TCM alone and can be used as a complementary treatment for endometriosis. TCMs have potential to improve clinical efficacy and reduce the side effects of Dienogest. This study was financially supported by Annual Science and Technology Steering Plan Project of Zhuzhou. PROSPERO has registered our meta-analysis as CRD42022339518 (https://www.crd.york.ac.uk/prospero/record_email.php).