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Yaocheng Completes RMB 100 Million A Round Financing

2021-07-22

On July 22, 2021 - Yaocheng, a leading provider of next-generation clinical research SaaS platforms, announced the completion of its RMB 100 million A round financing with participation from Lightspeed China, Hankang Capital, Lenovo Ventures, Primavera Venture, & etc..


Yaocheng, founded in August 2020, focuses on the informatization and intelligence of clinical research in the life sciences field. Its team members come from leading global companies in related fields such as Google, Verily, Splunk, Medidata, and Veeva. In May 2021, the company launched the AuroraPrime clinical research platform, which has been favored by many well-known life science innovation companies. Unlike other clinical research systems, the AuroraPrime platform has a powerful Clinical Logic Engine as its unified underlying infrastructure, enabling natural and efficient interconnection of multiple functional modules, information crossing different dimensions, and enhancing trial design and execution efficiency, real-time status control, collaborative optimization, and cost reduction.


Mr. Pengcheng Xu, Chairman and CTO of Yaocheng, said, "Although Yaocheng is a newly established enterprise, our team is very professional and complete in terms of computer technology and life science clinical research. From the perspective of product and technology planning, we have been focusing on building a solid, flexible, and intelligent underlying technology architecture from the beginning to support our future-oriented product design and technology applications. After this round of financing, based on our current market planning and personnel configuration, Yaocheng will continue to focus on technology empowerment, continuously implement cutting-edge technologies in the clinical trial field, and build a comprehensive, multifunctional, highly intelligent, and global SaaS platform to support CROs and sponsors in the exploration and practice of life science innovation under the premise of compliance."


Mr. James Mi, Founding Partner of Lightspeed China, said, "As the earliest investor in the company, we are pleased to see the company achieving remarkable results in just one year since its establishment. Yaocheng's team has accumulated deep industry experience in the fields of life sciences and computer software, possessing cross-border and cross-disciplinary capabilities in clinical research informatization. The intelligent, integrated, and interconnected clinical research platform officially launched by the company has played an effective role in promoting research and development efficiency and industry upgrading. We look forward to the company continuing to explore more industry solutions in user scenarios and accelerating the upgrading of the global life science industry."


Mr. Gang Lu, Partner of Legend Star, said, "With the rapid development of innovative drugs and new policy implementations, clinical research will quickly move from the informatization stage to the digital popularization stage and then accelerate into the intelligent stage. In this upgrading process, technology-driven clinical research digital enterprises will be able to provide better, more internationally-aligned empowering services for innovative drug enterprises. Yaocheng's product is not just a user-friendly trial design and process management tool. Its product design concept and architecture are rare in that it starts from the bottom of the data and has both enough foresight and systematicness. It can be very well combined with the research and development pain points of Chinese innovative drug enterprises at the application layer, promoting the digitization of the entire clinical process for customers. The accumulated data also has the potential to provide continuous value-added services to customers in the intelligent stage."


Mr. Johnny Zou, Co-head of Primavera Venture, said, "China's clinical trial digitalization process is still in its early stages, but the prospects are very promising. We highly value AlphaLife's team's cross-border service experience, as well as its underlying technological strength, commercialization capabilities, and profound insight into the pain points of the pharmaceutical industry. Primavera Venture looks forward to working with Yaocheng to build a first-class clinical research SaaS platform."


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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