近日公開 Coming Soon

薬物臨床試験データセット

♪ The real world research data ♪

臨床試験
中心次元
I-IV/BE/RWE
カバレッジ阶段
CDE/RWE
ソース
近日公開
状态

データセット概要

薬物臨床試験データセットChangsha Langhui Information Technology Co., Ltd.The compilation of structured clinical trial data from the National Drug Review Authority (DNE) drug clinical trial registration and information dissemination platform, as well as from the Real World Study (RWE), adaptive disorders, application, core dimensions of entry, main endpoint, test state, etc., are being cleaned and standardized, supporting competitive drug research and development intelligence, intelligent analysis of clinical trials and line assessment.

データセット名薬物臨床試験データセット
データ種別CDE Register Clinical Trial + BE Experiment + Real World Research RWE Data + Structured JSON
核心内容Test registration number, trial phase (I/II/III/IV/BE), adaptation (ICD code), applicant/contract research organization (CRO), pilot programme number, main/minor endpoints, number of entry cases, test status (in progress/complete/termination), first entry/test completion date
ソースデータCED-Dictal Clinical Trial Registration and Information Dissemination Platform, China Clinical Trial Registration Centre (CHCTR), Clinical Trials.gov, book publication RWE research
活用シーンDrug development competition intelligence, pipeline analysis and target tracking, intelligent search for clinical trials, synthesis of RWE evidence, assessment of drug registration strategies
フォーマット 出力Structured JSON + CSV 导出 + API 接口
状态近日公開

核心データ次元

The data set is organized according to the ICH clinical trial guide and the CDE registration specifications, covering the entire chain from the pilot design to the results.

サイズ:大类フィールド数代表的なフィールド价值层级
试验标识8CED registration number (CTR), ChicTR registration number, Clinical Trials.gov NCT number, test program number, common/scientific name of the test, date of registration, date of first release of data, date of latest update基础标识
试验设计14Test phases (I/II/III/IV/BE/Other), test design types (parallel/cross/one arm/dialysis), randomization (Yes/No), blindness (open/single/blind), control types (placebot/positive drugs/empties), scope of testing (national/international multicentres), experimental purpose (treatment/preventive/diagnosis)中心次元
药品信息12Test drug generic/code, drug type (chemical/biological products/Chinese/vaccinum), target/role mechanism, ATC code, drug registration classification (Impressed/Impressed/Impressed/Class/Classes/Venc), route of delivery, formulation, laboratory drug production unit中心次元
适应症8Adaptive Chinese/English description, According ICD-11 code, treatment area (oncology/cardiovascular/infection/ metabolism/neurological/self-immunisation, etc.), target population (adult/child/old age), disease stratification, biomarker layer (e.g. PD-L1/HER2/EGFR/ALK/BRAF, etc.), rare disease mark, paediatric drug mark中心次元
申办方8Name of applicant (enterprise/scientific institution), type of applicant (domestic/transnational/CRO/academic institution), Organisation for Contract Research (CRO), partner, province/country of applicant, main researcher (PI), pilot person, ethics committee高级分析
入组与终点10Planned cluster numbers (domestic/international), actual entry cluster numbers, entry criteria/standard exclusion criteria key conditions, main endpoint indicators, secondary endpoint indicators, time of major endpoint evaluation, data monitoring committee (DMC) markers, intermediate analysis markers, adaptive design markers高级分析
试验状态8Test status (ongoing - recruitment not yet ongoing/completed/completed/active suspension/termination), first entry date (FPI), final entry date (LPI), completion date of test, date of change of status, termination/suspension reason, results mark, NDA/BLA submission mark高级分析
RWEデータ10Type of study (forward looking/retroactive/registration study), data sources (electronic patient records/health-care database/patient registration/documentation), sample volume, exposure definition, endpoint indicator, Methodologies for control of mixed factors (PSM/IPTUW/multifactor regression), EFF (HR/OR/RD) and 95% CI, bias risk assessmentRWEの特徴
メタデータ6Date of data entry, source system, data quality rating, completeness rating, standardized version, update of batch log品質管理

AI活用シーン

Competition intelligence on drug research and development

Based on progress in CDE registration data and testing, training in competition intelligence AI models, implementation of tube panorama analysis, target heat tracking and dynamic monitoring of competitor development.

Clinical trial intelligent retrieval

Multi-dimensional search matching syntax, such as ADD+D+STP+According criteria, supports researchers in fast-tracking related tests and assessing the feasibility of entry.

RWE Evidence Synthesis and Evaluation

The Real World Research Training Evidence Integrated AI Model supports systematic evaluation, analytical and pharmaceutical clinical integrated evaluation, supporting registration decision-making and health-care negotiations.

Test success projection

Historical test data + drug properties + adaptation + business information training predictor models to assist in assessing the probability of success of clinical trials and optimizing R & D decisions.

よくあるご質問

When will the dataset go live?
The drug clinical trial data set is currently in the data collection and standardization processing phase and is expected to be formally available in the near future. The data set will be extracted and structured from multiple sources such as the CDE drug clinical trial registration platform, ChicTR and ClinicalTrials.gov.
Do the data contain test results?
The data set focuses mainly on test registration and process information (conforming to the CDE registration specifications), including test design, grouping information and status tracking. A summary of key results from completed trials will be gradually incorporated, and the RWE module will consolidate published evidence of real world studies. For clinical trials where the results of published experiments are available, the data set will provide structured result fields (main endpoint results, safety data aggregation, etc.).

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Changsha Langhui Information Technology Co., Ltd. The DataAssetsAPI platform is dedicated to providing AI enterprises and scientific institutions with high-quality, compliant data assets.

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