An online survey on public awareness of drug clinical trials in inland cities of northern China

Objective

The aims of this survey were to investigate the public awareness of drug clinical trials (DCTs) and willingness to participate the DCTs, and provide references for propaganda and science popularization of DCTs.

Methods

A self-designed questionnaire named "an online survey questionnaire on public awareness of DCTs" was used to conduct an online survey from January to March 2022. The demographic characteristics and the response of participants to the awareness and willingness to participate the DCTs were collected. The factors affecting the public awareness of DCTs were analyzed by single factor and binary logistic regression analysis.

Results

One thousand three hundred eighty valid questionnaires were collected, and the respondents' awareness rate of DCTs was 61.1%. Thirteen demographic characteristics including age, gender, education, occupation, work fields, household type, marital status, city type, income, medical insurance, medical expenditure, pressure to seek medical care, financial pressure, both significantly affected the qualified rate of participants' awareness of DCTs (p < 0.001) by single factor analysis. Binary logistic regression analysis indicated that education level, work fields, city type, medical insurance, and medical expenditure affected independently the participants' awareness rate of DCTs (p < 0.001). 52.9% of the participants were willing to take part in DCTs. "to promote medical progress" (54.4%) or "believe doctors" (31.1%) were the most frequent reasons for subjects participating in DCTs.

Conclusion

The public awareness rate of DCTs and the willingness to participate in drug clinical were significantly affected by the demographic characteristics of subjects. Thus, targeting the needs of the public, propaganda, and science popularization of DCTs should be carried out and served public health.

Development of clinical trials for non-small cell lung cancer drugs in China from 2005 to 2023

Objective

Over the past few decades, the development of anti-cancer drugs in China has made outstanding achievements based on the support of national policies. To assess the progress of non-small cell lung cancer (NSCLC) drugs, we conducted a statistical analysis of clinical trials of drugs targeting NSCLC in China from 2005 to 2023.

Methods

We downloaded, screened and analysed the data from three official websites, the Centre for Drug Evaluation of China National Medical Products Administration website (NMPA), ClinicalTrials.gov and the Chinese Clinical Trial Registry (ChiCTR).

Results

From January 1, 2005 to April 15, 2023, a total of 1,357 drug clinical trials that met the standards were included, and the number of registered drug clinical trials has been increasing year by year, reaching the maximum of 199 in 2021. Among them, the maximum of 462 items (34.05%) in phase II clinical trials, followed by 333 (24.54%) in phase III clinical trials, and 139 (10.24%) in phase IV clinical trials. In all drug clinical trials, industry sponsored trials (ISTs) have 722 items (53.21%), which are higher than investigator-initiated trials (IITs). The clinical trials of chemical drugs have a maximum of 723 items (53.28%), while biopharmaceuticals have grown rapidly in the past 10 years, with a total of 374 (27.56%), and 48.19% of the drug clinical trials of combined medication. In addition, the geographical distribution of the leading units and participating units of Chinese drug clinical trials are uneven, and economic regions such as Beijing, Shanghai, Jiangsu are obviously ahead of other regions.

Conclusion

From 2005 to 2023, the clinical trials of registered drugs for the treatment of NSCLC increased rapidly. Among them, due to the development of immunotherapy, the clinical trials of biopharmaceuticals and drugs for combined medication are growing most rapidly, while the exploration of the original drugs is a little far from enough. Our research provides a direction for the future drug clinical trials of NSCLC, laying foundation for further extending the survival rate of patients with NSCLC.

Barriers to Screening: An Analysis of Factors Impacting Screening for Type 1 Diabetes Prevention Trials

Context

Participants with stage 1 or 2 type 1 diabetes (T1D) qualify for prevention trials, but factors involved in screening for such trials are largely unknown.

Objective

To identify factors associated with screening for T1D prevention trials.

Methods

This study included TrialNet Pathway to Prevention participants who were eligible for a prevention trial: oral insulin (TN-07, TN-20), teplizumab (TN-10), abatacept (TN-18), and oral hydroxychloroquine (TN-22). Univariate and multivariate logistic regression models were used to examine participant, site, and study factors at the time of prevention trial accrual.

Results

Screening rates for trials were: 50% for TN-07 (584 screened/1172 eligible), 9% for TN-10 (106/1249), 24% for TN-18 (313/1285), 17% for TN-20 (113/667), and 28% for TN-22 (371/1336). Younger age and male sex were associated with higher screening rates for prevention trials overall and for oral therapies. Participants with an offspring with T1D showed lower rates of screening for all trials and oral drug trials compared with participants with other first-degree relatives as probands. Site factors, including larger monitoring volume and US site vs international site, were associated with higher prevention trial screening rates.

Conclusions

Clear differences exist between participants who screen for prevention trials and those who do not screen and between the research sites involved in prevention trial screening. Participant age, sex, and relationship to proband are significantly associated with prevention trial screening in addition to key site factors. Identifying these factors can facilitate strategic recruitment planning to support rapid and successful enrollment into prevention trials.

Evolution of ischemic stroke drug clinical trials in mainland China from 2005 to 2021

Background

To assess the temporal changes in the characteristics of ischemic stroke drug clinical trials conducted in mainland China in 2005–2021.

Methods

A statistical analysis of registered clinical trials on ischemic stroke was performed using the platform of the Center for Drug Evaluation of China National Medical Products Administration, the Chinese Clinical Trial Registry, and ClinicalTrials.gov websites.

Results

From January 1, 2005 to August 1, 2021, a total of 384 registered drug clinical trials on ischemic stroke were identified in mainland China. Over time, the number of trials gradually increased each year, with a significant growth in 2014, from 16 in 2013 to 42 in 2014. Phase IV trials (31.8%) accounted for the majority, followed by phase II (16.4%), phase I (10.9%), and phase III (8.6%). In terms of sponsorship, the proportion of investigator‐initiated trials (IITs) (60.7%) was higher than industry‐sponsored trials (ISTs) (39.3%). Additionally, trials involving traditional Chinese medicines (TCMs) (36.2%) accounted for the largest proportion, followed by trials involving antithrombotic therapy (19.5%) and cerebral protection agents (16.7%). Furthermore, over the past 17 years, the number of leading drug clinical trial units for ischemic stroke in mainland China has continuously increased. The leading principal units from Beijing, Shanghai, Guangdong, Jiangsu, and Liaoning accounted for the majority of the trials (67.4%).

Conclusion

In the past 17 years, great progress has been made in the research and development (R&D) of drugs and clinical trials for ischemic stroke in mainland China. The most extensive progress was observed in TCMs, antithrombotic therapy, and cerebral protection agents. More clinical trials are needed to confirm whether the newly developed drugs can improve the clinical efficacy of ischemic stroke. Simultaneously, more pharmaceutical R&D efforts of innovative drugs are warranted.

MEDICASCY: A Machine Learning Approach for Predicting Small-Molecule Drug Side Effects, Indications, Efficacy, and Modes of Action

To improve the drug discovery yield, a method which is implemented at the beginning of drug discovery that accurately predicts drug side effects, indications, efficacy, and mode of action based solely on the input of the drug's chemical structure is needed. In contrast, extant predictive methods do not comprehensively address these aspects of drug discovery and rely on features derived from extensive, often unavailable experimental information for novel molecules. To address these issues, we developed MEDICASCY, a multilabel-based boosted random forest machine learning method that only requires the small molecule's chemical structure for the drug side effect, indication, efficacy, and probable mode of action target predictions; however, it has comparable or even significantly better performance than existing approaches requiring far more information. In retrospective benchmarking on high confidence predictions, MEDICASCY shows about 78% precision and recall for predicting at least one severe side effect and 72% precision drug efficacy. Experimental validation of MEDICASCY's efficacy predictions on novel molecules shows close to 80% precision for the inhibition of growth in ovarian, breast, and prostate cancer cell lines. Thus, MEDICASCY should improve the success rate for new drug approval. A web service for academic users is available at http://pwp.gatech.edu/cssb/MEDICASCY.