CII Unveils Machine Learning-Powered Multi-Omics Platform to Accelerate Precision Diagnosis and Clinical Decision-Making

In 2012, Nicholas Schork, then director of the Scripps Center for Genomic Science, received a patient named Lily Grossman, a high school student.

Lily began experiencing muscle twitches in infancy, and by childhood, she even started to develop muscle atrophy. Her parents took her to seek medical help for many years, but they never found the cause of her condition. They all believed that this child would not live to be 18 years old.

After conducting whole-genome sequencing on the patient, the research center identified two gene mutations—ADCY5 and DOCK3. Dr. Schork inferred that these mutations were likely the underlying cause of the disease. Following the research center’s recommendation, Lily took acetazolamide (a carbonic anhydrase inhibitor) for a period of time, after which her symptoms began to alleviate. In 2015, Lily was admitted to a university in the United States.

Lily Grossman and Her Parents

This is just one of hundreds of case studies in the treatment of rare diseases. Undoubtedly, genomics plays a crucial role in disease management, particularly in the treatment of rare diseases. But is genomics the entire picture? Certainly not.

Schork told VCBeat, “Human anatomy is highly complex, and so are diseases; precision medicine should incorporate multi-omics data, including genomics, proteomics, biomarkers, and disease phenotypes.” He further noted to VCBeat that, with the emergence of new technologies, leveraging machine learning, statistical methods, and other approaches to integrate multi-omics data for assisting clinical diagnosis has become a major trend in the U.S. healthcare industry in recent years.

In January 2017, Schork co-founded CII with two long-time friends: Geoffrey Folkerth, founder of the U.S.-based Pathway Genomics, and Xiong Min, president of the U.S.-based Sunshine Consulting Group. The company aimed to establish a rapid, self-learning system capable of integrating multi-omics data for clinical applications, thereby serving as an accelerator for precision medicine in clinical practice.

Schork has over 15 years of research experience in the field of bioengineering, with extensive expertise in quantitative human genetics and genomics, particularly in designing and implementing methods to dissect the genetic basis of complex diseases. He serves on the advisory boards of five biotechnology companies and has previously held positions as Associate Professor of Biostatistics at Harvard University and Director of the Center for Human Genetics and Genomics at the University of California, San Diego. He has published more than 400 articles on the analysis of complex diseases and multifactorial traits.

During his tenure as Vice President of Statistical Genomics at the French biotechnology company Genset, Schork led the team in creating the world’s first high-density polymorphic human gene map, for which he obtained multiple patents related to genome-wide association studies (GWAS).

Folkerth is a serial entrepreneur with 16 years of experience in entrepreneurship and investment within the biomedical sector. The biotechnology company he co-founded, Pathway Genomics, secured a $40 million investment from IBM Watson in 2016.

Xiong Min, with a background in media, founded the Washington bureau of China’s 21st Century Business Herald in the United States. She graduated from the Department of Journalism at Fudan University and later earned an MBA from Georgetown University in the U.S. She previously served as the Asia-Pacific Business Director at CNS Global Consultants, bringing extensive experience and networks in Sino-U.S. bilateral commerce, along with a solid understanding of the Chinese market.

New technologies such as genetic testing, remote diagnosis, and intelligent imaging have brought significant transformations to clinical diagnosis and treatment, enabling physicians to collect increasingly extensive and comprehensive patient data. This trend is evident in the United States, Europe, and China alike. Such information helps physicians gain a more accurate understanding of patients’ conditions, while also supporting commercial insurance assessments and patient disease monitoring.

The U.S. healthcare market features numerous medical systems, yet their functionalities remain relatively limited—often confined to standalone electronic health records (EHR) or software solutions. Few systems are capable of both facilitating hospital information management and providing diagnostic support through machine learning-based analysis of comprehensive multi-omics data.

Folkerth argues that while new technologies are revolutionizing clinical practice, healthcare systems also require upgrading and optimization.

CII’s Rapid Learning System is a precision medicine diagnostic support software based on clinical cases. In addition to maintaining a database of historical case information, the system seamlessly integrates with emerging medical technologies. It can analyze genomic sequencing and other novel test results, while incorporating statistical methods to predict patients’ subsequent diagnosis and treatment pathways.

Once new diagnostic and treatment data are entered into the case information database, the system can automatically optimize its analytical subsystems through machine learning.

Schork stated, “With the assistance of the system, physicians can more readily grasp the associations between diseases and various omics layers, and more precisely characterize each patient’s individualized profile.” It is reported that Schork has also conducted extensive research on healthcare big data, with some findings already published.

Currently, the company’s primary markets are in the United States and Europe. It has established in-depth collaborations with 37 leading hospitals in the field of genetic diagnostics on the U.S. West Coast and in the Midwest, leveraging these institutions to promote its rapid learning system. These hospitals are offered a complimentary trial period of one to three years, during which case data within the database can be gradually accumulated.

For these hospitals, they can not only obtain diagnostic assistance through the system but also generate revenue from de-identified data, such as by licensing it to other hospitals or collaborating with insurance companies.

Commercial insurance in the United States exerts a pivotal influence on the healthcare industry. When patients seek medical care at hospitals, they are first required to complete three forms. In addition to their medical history, these forms collect other basic information, such as income level—a measure implemented by hospitals to ensure reimbursement from insurance companies. Digesting and analyzing this information not only enhances the quality of hospital services but also provides a basis for insurance companies to assess their loss ratios.

Xiong Min disclosed to VCBeat that the company currently collaborates primarily with private hospitals, which tend to be more receptive to adopting new technologies and have dedicated personnel for evaluating and selecting such innovations. In addition to serving hospitals, the company also provides services to pharmaceutical innovation enterprises.

For new drugs to enter the market, they must undergo animal testing and clinical trials, a process that generates substantial data on drug reactions and patients. Such a rapid-learning system can statistically compile, store, and analyze these data, including biomarkers.

Xiong Min also told VCBeat, “We are also closely following China’s policies on the internationalization of traditional Chinese medicine and the innovation of new drugs. I believe our system can be helpful to them.”

The system has already undergone small-scale application and validation in the United States, achieving favorable outcomes in terms of both product reliability and hospital feedback. Currently, the company is promoting the concept of the Rapid Learning System within the U.S. medical community and introducing it at major healthcare forums in Poland and the United States.

Folkerth revealed to VCBeat that they are very optimistic about the Chinese market and hope to bring such products to China to seek more market opportunities. However, he also emphasized that there are significant differences among the markets in China, the United States, and Europe, and that different markets should have different models and solutions.

He believes that in the US and European markets, clinical translation of new technologies is rapid, but funding challenges must be overcome. China, however, presents a different landscape: while its healthcare entrepreneurship ecosystem is highly favorable, the social environment and medical system are more complex, and the management of medical data differs markedly from practices in Europe and the United States.

“We warmly welcome Chinese enterprises to engage in exchanges and discussions with us, working together to identify solutions tailored to the Chinese market,” said Folkerth.