Bridging Precision Medicine and Informatics: A Vision by Mengchun Gong

In January 2015, U.S. President Barack Obama proposed the “Precision Medicine Initiative.” Precision medicine is a novel medical model that fully incorporates individual patient differences into disease prevention, diagnosis, and treatment systems, encompassing data from multiple dimensions such as clinical practice, genomics, environmental factors, and lifestyle habits. To date, “precision medicine” has become a prominent buzzword of the year. Achieving precision medicine, including the integration, aggregation, and transmission of information and the stratification of patients into subgroups, relies heavily on the support of precision medicine informatics.

A European research institution collected data from over 1,000 neonatal diabetes patients and conducted a follow-up study spanning nearly 14 years. This included the collection of detailed clinical data and genetic testing, ultimately establishing a network map illustrating the relationship between gene mutations and clinical manifestations. This development greatly facilitates diagnosis and pharmacological treatment by clinicians, saving significant time and resources. For clinicians, this provides a reference for diagnosing all future neonatal diabetes cases: based on the newborn’s clinical symptoms, preliminary judgments regarding gene mutation sites can be made using this network map alone; conversely, for patients with known mutation sites, their likely clinical manifestations can be predicted with considerable accuracy. In a sense, such a knowledge network represents an application of precision medicine informatics.

However, given the current state of medical informatics, it is impossible to establish a mapping network linking the clinical manifestations of every disease to its corresponding genetic mutations, and it is even more unrealistic to expect physicians to memorize all such technical details. Healthcare providers on the front lines are currently facing a crisis driven by information overload, making the need to construct such relational networks increasingly urgent, particularly in resource-constrained specialties such as endocrinology and pediatrics. It is critically important for physicians to access information promptly, understand potential clinical presentations, and enable the real-time transmission of patient records through electronic medical records (EMRs). The field of medical informatics does not directly engage in clinical practice or EMR system redesign; rather, it focuses on solving the problem of integrating whole-scale bioinformatics analytical data into clinical systems.

Gong Mengchun shared a research article published in late 2015 on the treatment of metastatic prostate cancer refractory to conventional therapies. Researchers conducted the most comprehensive genomic analysis to date on hundreds of patients, including DNA sequencing and RNA transcriptome sequencing. The study yielded encouraging results: nearly 90% of patients who were refractory to conventional treatments had identifiable molecular targets amenable to clinical intervention.

For patients who have failed conventional therapies and exhibit poor postoperative recovery, options are essentially exhausted. However, DNA and RNA sequencing analysis reveals that 90% of these patients still have an opportunity for pharmacological intervention. Among them, 25% harbor mutations in genes associated with DNA repair pathways. Targeted therapies for this pathway are already commercially available, well-established, and demonstrate significant clinical efficacy. With the advancement of precision medicine, such patients can now identify effective therapeutic agents, extending survival by at least six months.

“We began to consider what benefits the era of precision medicine could truly bring to patients. What we value is the underlying rationale reflected in the research,” said Gong Mengchun.

Medical informatics constitutes a critical framework. The entire workflow—from sample collection on day one, initiation of pathological analysis on day two, sample preparation and sequencing between days three and nine, data analysis between days nineteen and twenty-two, subsequent multidisciplinary discussions, to final therapeutic decision-making—is underpinned by informatics principles. The ability to implement systematic process monitoring determines whether key information is available in a timely manner and whether subsequent steps can proceed smoothly. From an IT perspective, this merely involves process management software or integrated information platforms, which are technologically feasible to develop. However, post-development, how such software integrates with precision medicine and is implemented in clinical practice remains a subject that warrants discussion from an informatics standpoint.

In the future, precision medicine will advance in four key directions: first, the discovery of novel molecular biomarkers; second, the development of innovative clinical trial designs; third, the re-establishment of constitutional assessment frameworks to analyze why certain patients exhibit longer survival outcomes with conventional chemotherapy, thereby enabling the reformulation of treatment protocols. Some patients gradually develop chemoresistance during treatment, as tumor cells acquire new mutations; thus, therapeutic regimens must be adjusted to further eradicate these mutated tumor cells.

Research and development in each of these areas require the support of in-depth informatics research. For instance, basket trials based on genomic technologies were initially designed for ovarian cancer, but it was later discovered that prostate cancer, as mentioned earlier, could also be treated with the same drugs. This reveals a shift away from focusing solely on the tissue origin of the tumor toward a molecular-level perspective. As long as patients share the same DNA mutations, they can be included in the clinical trial and treated with the same medication, allowing for observation of therapeutic outcomes. This represents a new paradigm in the era of precision medicine. In this process, integrating and summarizing information to classify and enroll patients, as well as providing such information to clinicians, constitutes the critical work of precision medicine informatics.

Similarly, the value of precision medical informatics is also evident in certain rare genetic disorders, such as those managed in the Neonatal Intensive Care Unit (NICU). Clinical manifestations include markedly reduced facial expressiveness in newborns, with some patients exhibiting declining limb function as they age. Leveraging medical informatics facilitates a relatively easier diagnosis of such conditions. By extracting relevant clinical information from electronic health records (EHRs) based on prior experience and conducting bioinformatics analyses, the entire diagnostic process can be shortened from one month to just one day. Time is of critical significance for the treatment and prognostic assessment of neonates.

The profiles generated by genetic analysis are composed equally of clinical manifestations and genetic expressions. Therefore, after testing is completed, how to apply this knowledge at the clinical level has become a challenge for physicians: the diagnosis of each disease generates massive amounts of data, far exceeding the information processing capacity of clinicians in their daily practice. It is nearly impossible for clinicians to master all such data.

In the future, precision medicine will gradually transition from research to clinical practice. The integration of healthcare, IT, and biomedicine, coupled with cliniciansMultidisciplinary collaboration across multiple departments will maximize the collection of precision medicine informatics data. Hospitals primarily collect clinical data, including patients’ medical history and family history. Meanwhile, post-discharge patient data—such as geographic location, air quality, and allergen information—can also be captured through modern informatics technologies.

Medical informatics has passed its inflection point, with information and data across all domains experiencing exponential growth. The subsequent integration of this data to elucidate individual variations within patient populations constitutes the next major challenge facing medical informatics. The field has transitioned from administrative medicine to an evidence-generating system, or what may be termed a self-learning system.

What does it mean to generate evidence? It refers to the process whereby, supported by information systems, data is transformed into knowledge, which in turn informs clinical actions applied to patients; these interventions then generate further patient data. In other words, the integration of data, information, knowledge, and action represents the future direction of development.

Gong Mengchun believes that the development of precision medicine informatics must first address the machine readability of informed consent forms and biobanks. Biobanks are essential systems for biological research, and real-time tracking of samples along with real-time aggregation of testing data are crucial for biobank management and the timely updating of informed consent forms. Currently, in addition to ongoing international research, this year’s Precision Medicine Project 3.1.1 also involves the construction of multi-omics biobanks.

Second is the standardization and operability of data. The structuring of future clinical data, how to integrate these data with genomics or other omics, and how to support the development of precision medicine are issues currently being focused on and discussed in medical informatics. For example, regarding type 2 diabetes, modern medicine believes that the analysis of this disease is already very thorough, but through medical informatics methods, it has been found that it can be further divided into several subtypes. This new subtype analysis of diseases is mainly based on traditional molecular typing, detailed clinical patient data, and topological research. Based on these studies, combined with genotype analysis, new molecular pathways can be identified, thereby addressing individual differences among patients. However, this is not achieved overnight; the integration of more than a dozen centers in the United States is supported by extensive genetic data behind it. Domestic research designs basically follow this approach, and progress in this area will also be seen in the future.

Moreover, the construction of knowledge bases represents a key direction for the future development of precision medicine informatics. The development of knowledge bases is indispensable to the advancement of precision medicine informatics; they deliver real-time updated knowledge to clinicians, which must undergo manual verification and may even incorporate data not yet publicly available in China. Currently, some companies have achieved notable progress, primarily through specialty-specific knowledge bases. At the core of precision medicine, particularly in clinical practice, lies the accumulation of clinical knowledge. The current stage of medical informatics in China essentially involves integrating pharmacogenomics knowledge into electronic health records (EHRs) to provide medication guidance for clinicians.

Finally, there is the Rare Disease Registry System, established under the National Key R&D Program, which has built a biobank and a comprehensive collaborative network and will be promoted for use in hospitals across China in the future. Hospitals with relevant clinical experience and an interest in participating in scientific research can apply to join the National Rare Disease Registry System.

Gong Mengchun, who previously worked in clinical practice, is now primarily focused on medical informatics research. He stated, “Currently, rare disease registries in China are highly underdeveloped and require exploratory efforts from various institutions. Through multi-party collaboration and exchange, a mature medical informatics system can be gradually established.”

M.D., graduated from Peking Union Medical College in 2011 (eight-year clinical medicine program). Completed internal medicine residency training at the Department of Internal Medicine, Peking Union Medical College Hospital. Conducted research in pediatric nephrology and served as a visiting scholar at the University of California, San Francisco (UCSF). Joined InterSystems in early 2015 as Executive Physician, responsible for market expansion, product design and planning, clinical support, and user training, fostering positive interaction and efficient collaboration between InterSystems and healthcare professionals.