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Product Launch: With Intelligent Content Recommendations, Prime Create 2.0 Clinical Research Document Generation System Is Online

2022-08-17

On August 17, 2022 - Yaocheng Health Science&Technology (hereinafter referred to as "Yaocheng") confirmed that the independent and innovative clinical research document generation system, AuroraPrime Create (referred to as "Prime Create"), will undergo important updates with the release of version 2.0. As a unique professional writing system for the life science industry's information technology field, Prime Create 2.0 provides leading features such as intelligent content recommendations, a rich template library, and full-process collaborative management, ushering in a new era for clinical research document writing such as the trial protocol.


Prime Create 

Prime Create is the document writing system on the AuroraPrime clinical research platform, supporting the standardization, structuring, and dataization of key documents from the start of clinical research. Prime Create aims to assist experts in various departments such as medical, biostatistics, and clinical operations to efficiently write documents like research protocol, facilitate cross-team and cross-department collaboration and editing, review, approval, and submission work, fully utilize protocol knowledge content, achieve dataization and structuring of knowledge retention, assist in the generation of execution documents, plans, and guidance files related to clinical operations, and highly automate the docking of trial construction work, achieving "protocol writing and construction," accelerating the process from protocol writing to clinical research launch.


Selected Features of Prime Create 2.0

1.Rich Template Library

Prime Create provides a variety of preset template options, allowing for one-click construction of a protocol's initial "skeleton," including main chapters, sub-chapters under main chapters, and the main topics to be written in each sub-chapter. This structured approach helps authors clearly understand and create the main structure of the protocol.


2. Intelligent Content Recommendations

Based on Yaocheng's proprietary Clinical Logic Engine, Prime Create offers intelligent content association and recommendations during the protocol writing process. The system includes a large amount of reference content (based on public documents and customer-owned knowledge bases). When writing a specific topic (such as inclusion and exclusion criteria, ethics, etc.) based on the selected protocol template, the system will automatically provide matching recommended content based on the study period, treatment area, randomization, and other attributes. Users can directly select and modify the reference content for reuse. This significantly optimizes the thinking process during writing and the repetitive work of copying and pasting across different protocols.


3. Full-Process Protocol Management

Prime Create achieves the complete process and life cycle of research protocol operations and application management, including the standardization and dataization of protocol content, revision and approval, eCRF generation and construction, knowledge accumulation, and reuse after archiving. This is a true accomplishment in the collaborative operation and application management of protocol design.


Mr. Zhu Bogong, Chief Business Architect of Yaocheng, said, "Prime Create 1.0 achieved cross-team, cross-department, and cross-organization collaborative editing of research protocols, as well as the overall structuring and standardization of protocols. In Prime Create 2.0, based on the customer's protocol knowledge base and public data library, intelligent identification and processing can provide rich and fitting protocol templates and recommend appropriate reference content during the writing process, further enhancing writing efficiency. On the other hand, finished protocol content can be directly identified and utilized by the Prime Construct construction system, automatically generating editable visit schedule, eCRFs, and other database content, supporting and utilizing trial protocols throughout the clinical research life cycle."


About Yaocheng Health Science&Technology

Yaocheng focuses on the field of life sciences and consumer health, and is committed to creating a new generation of clinical research SaaS platform. It empowers innovative clinical trials and real-world research with world-leading technologies such as Cloud Services and AI .  Yaocheng is realizing process automation and intelligent decision-making driven by research doc and data ensures data consistency, improves operational efficiency, and accelerates innovative research and development in global life sciences and consumer health.


Improve the efficiency of clinical research and development and
bring innovative products to market faster.

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AI Specialist

Shanghai|Engineering|Published 2023-06-02

Responsibilities

1. Engage in AI research and development in the field of clinical and biomedical informatics, including data collection, algorithm research, and model building.

2. Explore innovative applications of AI and be responsible for the application development of NLP technology in specific business scenarios.

3. Build machine learning platforms and frameworks, including algorithm implementation and system development.

4. Keep up with the latest developments in cutting-edge technologies in the industry and integrate them into the existing technical system to continuously enhance the platform's capabilities and meet business needs.

5. Provide insights and take the lead in implementing AI initiatives based on practical application products and scenarios within the company.

Job Requirements

1. Bachelor's degree or above in computer science or a related field, with at least five years of experience in AI research and development. In-depth research in natural language processing or computer vision, solid theoretical foundation, good mathematical and statistical knowledge, and programming skills are required.

2. Practical experience in implementing AI applications, preferably with experience in building from scratch and continuous optimization.

3. Familiarity with cutting-edge research in natural language processing, extensive research experience, and preferred experience in training and applying large-scale language models.

4. Proficiency in various machine learning and deep learning algorithms and their application scenarios.

5. Familiarity with at least one machine learning framework such as TensorFlow, PyTorch, scikit-learn, etc.

6. Strong innovation spirit and scientific research capabilities, good information search, literature reading, and algorithm implementation skills.

7. Strong documentation skills and the ability to communicate effectively with technical teams and management.

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