Iris Zhu
Beigene

ancer has been sometimes viewed as more of an ecosystem (in which patients, healthcare professionals, researchers, industry, regulatory authorities, and payers transfer demands and values to and from each other) than a malignant disease. Due to the vast and increasing disease burden attributable to cancer in China, prevention and treatment of cancer has been listed as one of the fifteen goals in the Health China Action Plan released by the Chinese State Council in July 2019.

One year later, at DIA China 2020, experts from different areas shared intelligence and insights from their own perspectives, igniting the spark of discussion about the cancer patient’s journey in China’s emerging healthcare ecosystem. The cancer ecosystem in China has been inspired to progress from what might be called Step 1.0, which is more focused on equal access to cancer therapy, to Step 2.0, with expectations for providing healthcare to patients with quality and efficiency. Biomarker-based early cancer detection and big data analyses have been highlighted among the new forces driving China’s cancer ecosystem in a more patient-centric direction.

• Biomarker-based early cancer detection, from routine tumor tissue baseline testing to the use of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) and circulating free DNA (cfDNA) as liquid biopsies, and related new technologies, empowers and enables the potential to diagnose cancer in its early stage and to support prognosis in real-time.
• Patient needs uncovered by big data through analyses of the full patient journey data can reveal undiscovered and diverse patient preferences which further guide clinical development of cancer therapies and promote the evolution of this ecosystem.

Liquid biopsy, a kind of non-invasive molecular pathology technique, continues to attract the public’s attention to its mechanism for detecting tumor-derived cells or even DNA in blood or other body fluids, relieving some of the patient’s pain and inconvenience associated with collecting tissue samples during their cancer journey. Although aspects of this technique have been challenged, including its reliability in early detection and its possibility to replace routine clinical diagnostic testing, its original patient-centric intention still unleashes tremendous expertise and enthusiasm in exploring and improving it.

In 2016, liquid biopsy demonstrated its capability as a companion diagnostic when one developer’s test was approved by FDA. Now that high-throughput sequencing (or next generation sequencing [NGS]) has been brought into public use through clinical practice, synergy between these two techniques is strongly expected to support early stage cancer screening and then guide treatment decisions with one test. One product was granted access to the EU market in March 2019 and another was approved by FDA in August 2020, offering more choices to clinical practice.

Big data is defined as “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” Compared to diagnostic companies, big data companies are really new and novel participants in this cancer ecosystem. We all know that various data including those generated by physical examinations, clinical diagnoses (including biomarkers), treatment regimens, disease prognoses and survival, are generated in every patient’s journey through cancer. But how to “let these data talk” and provide patients with what they are looking for remains an important unanswered question. Governments worldwide are realizing the strategic value of setting up interactive digital medical platforms to share data and then structure those data for analysis to help establish their public health strategies. Utilization of medical big data was acknowledged as a national strategy by the Chinese State Council in June 2016. Remaining challenges, such as data privacy protection, electronic data exchange between medical records systems, lack of medical data standards, and linguistic differences between Chinese and English medical terminology systems limit big data’s capability to drive the evolution of the cancer ecosystem. It is encouraging that several medical data-focused start-up companies in China, such as Happy Life Technology, whose founder was invited to speak in these sessions, have already committed to utilizing data to provide patient-centric solutions to patients, the pharmaceutical and insurance industry, payers, and eventually the whole ecosystem.

Voices from the commercial perspective agree that access to the right therapy to the right patient at the right price at the right time is critical for everyone inside this community, even researchers hunting for a drug candidate and pharmaceutical companies designing their clinical development strategy. One interesting but not unexpected emerging topic is commercial insurance as a supplement to national insurance; this was mentioned many times by almost all speakers. National insurance, as the essential public health security system to mitigate disease burden in the entire population of China, has proved its fundamental position and value in ecosystem 1.0. Diverse demands from cancer patients, sometimes for more than their basic needs, are gradually emerging in this ecosystem. Commercial health insurance that provides diversified access to different therapies at affordable prices to address different needs from cancer patients must be developed and integrated into the ecosystem.

China’s cancer ecosystem 2.0 is evolving from a supply-driven to a patient-driven era. Patients in this system deserve recognition for their role as the primary source of data in clinical trials and clinical practice that drive science forward. In return, each participant in this ecosystem must always commit to addressing the needs of cancer patients, including timely access to breakthrough therapies and convenient and affordable access to satisfactory healthcare. The cancer ecosystem, as a coordinated unit, must always be a patient-oriented system.