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How Yaocheng uses AI automation to modernize the life sciences industry

2023-07-18

Resources from Microsoft for Startups Blog:

The power of AI to process and analyze vast amounts of data at unprecedented speeds holds immense potential for revolutionizing scientific research. AI algorithms can identify patterns, correlations, and anomalies in complex datasets, leading to new discoveries and insights. Yaocheng has positioned itself as a forerunner of this new frontier, developing SaaS products for the life sciences and healthcare industries. Their core product platform, Yaocheng, offers a suite of products for protocol design and trials data collection using cloud computing, AI, and big data. Yaocheng’s AI automation offerings are fully configurable to meet the needs of clinical trials and other health needs.


Yaocheng’s technology is powered by Microsoft Azure, which provides the startup with the infrastructure and tools they need to develop and deploy their products quickly and efficiently. As a member of the Microsoft for Startups Pegasus Program, Azure also gives AlphaLife access to Microsoft’s vast ecosystem of partners and resources, which helps them to stay ahead of the curve in the rapidly evolving clinical trials industry.


I sat down with co-founder and CEO Sharon Chen to better understand how Yaocheng is tackling these challenges, and what insight she has for other AI-focused startups to break into their respective markets.

Empowering better data and analysis with help from AI

One of the key features of Yaocheng’s technology is its AI-powered clinical logic engine. This engine helps to translate data from one part of the clinical trial process to another, ensuring that all the data is in a consistent format and can be easily analyzed. The clinical logic engine also helps automate many of the tasks involved in clinical trials, such as data entry and analysis. This frees up clinical trial staff to focus on other important tasks, such as patient recruitment and monitoring.


“Our vision is to empower better health through evidence-based innovation,” Sharon tells me. “When it comes to life sciences innovation or invention, you must conduct a clinical trial with human subjects to prove efficacy and safety. We use computer science technology like AI, big data, and cloud computing to support and empower scientists and let them focus on their innovations.”


Creating an efficient user experience

Through its comprehensive tech stack, Yaocheng harnesses the power of AI and cutting-edge technologies to deliver a secure and efficient experience for their users while maintaining seamless integration with other systems and data exchange capabilities.


“I feel extremely lucky that we use not only Microsoft Azure’s cloud capacity but also for the strong AI support that we get,” Sharon says. “We take advantage of an OpenAI ChatGPT empowered, large language model which helps with protocol design. You certainly still need human beings to bring expertise to the original synopsis and later the review, but it’s been a good start based on the historical experience we get from clinical trials.”


Yaocheng utilizes a robust tech stack that leverages AI capabilities to enhance its functionalities. The system allows AuroraLife tenant users to access their accounts through Azure AD SSO, offering options for password authentication or integration with other SAML/OAuth2 SSO providers. User interactions with the SaaS product occur via a compliant browser, with Microsoft Edge being a recommended choice.

Breaking into a market with new technology

Any startups aiming to penetrate a market that has yet to fully embrace AI can encounter significant challenges. The reluctance of an industry to adopt new technologies can pose hurdles in getting a fledgling business off the ground. For Yaocheng, Sharon told me that her goal to help make the life sciences industry run more efficiently and ultimately improve patients’ health wouldn’t be enough for success. She and her team would also need to convince potential customers about the benefits of AI and address concerns about its implementation.


“We saw a market demand with life sciences, which is an evergreen industry,” Sharon explains, “and the timing was right for them to easily use this advanced technology. But it’s a highly regulated, conservative industry, so we needed to figure out how to help them utilize the benefits of AI and putting data together to automate their processes.


“You have to play by their rules, but know how to help them,” she continues. “It requires patience and professionalism, because they might not be able to always embrace the new technology in a very agile way. But with our help to store and make sense of their data, and with the many new AI tools that can support this industry more efficiently, it became a perfect storm of timing, passion, and ability.”


A crucial decision leads to a productive partnership

On top of overcoming resistance to adopting new technologies, Yaocheng had other serious considerations for breaking into the life sciences industry. Security was a paramount concern when dealing with patients’ personal identifiable information (PII), as well as a company’s data, client list, and intellectual property. Sharon said the choice of cloud provider became crucial to address any potential security or regulatory challenges.


“We partnered with Microsoft almost from the start,” Sharon says. “Not only do they provide the technology support we need but have been really good at helping us on a global scale, working with local governments, regulators, and even tax advisors.”


Sharon also points to the affiliation of Azure business partners, including major pharmaceutical companies, that can help Yaocheng and other startups get a leg up in getting their solution more attention.  With the help of OpenAI, Yaocheng can engineer prompts that tailor data and context for any use case, helping such companies get the right answers right away.


“Even though our startup began with a few people, we had a very ambitious goal and grew very fast with professionals from both Computer Science and Life Science fields who shared the same vision,” Sharon says. “With Microsoft we can build the next generation of our platform to support this huge industry around the world.”



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

CONTACT US

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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