China healthcare innovation momentum is strengthening, with AI, licensing partnerships, and global execution as the main themes of the Chengdu field trip
AI summary card
China healthcare innovation momentum is strengthening, with AI, licensing partnerships, and global execution as the main themes of the Chengdu field trip
Following its Chengdu healthcare field trip on July 14-15, J.P. Morgan maintains a constructive view, believing that AI is improving R&D efficiency, but that the real moats still come from proprietary data, wet-lab capabilities, clinical differentiation, and global partnership execution.
- The two-day field trip covered nine companies, including Kelun Pharma, Kelun Biotech, Hinova, Haisco Pharma, Baili Pharma, Zenitar, Keymed, Hitgen, and HxMedbot.
- AI has already been used by multiple biotech companies for drug discovery, molecular design, target structure analysis, and lead compound optimization, but experimental validation, proprietary data, and integrated laboratory platforms remain critical barriers.
- Multinational pharmaceutical companies are still actively seeking differentiated innovative assets from China, and cases such as Kelun Biotech with MSD, Biokin with BMS, and Gilead's acquisition of Ouro support global demand for Chinese innovative assets.
- Anti-corruption measures and tighter pharmaceutical representative policies have caused limited near-term sales disruption for compliant innovative drug companies, but may accelerate industry differentiation, benefiting products with clear clinical value and compliant commercialization systems.
- Clinical catalysts and medical conferences in 2H26 may continue to support sentiment, with key focus areas including WCLC’26, ESMO’26, SABCS’26, and Phase III data related to Kelun Biotech and Baili.
Report interpretation
Overview
This report summarizes the key findings from J.P. Morgan's two-day Chengdu healthcare field trip in China. The trip covered biotechnology, pharmaceuticals, CROs, and medical technology, with the core conclusion that China's healthcare innovation trend continues to strengthen and that companies are converting stronger R&D platforms into clinical validation, out-licensing, and global development opportunities. The report explicitly states that it continues to favor the biotech and CXO sub-sectors most, with preferences for Kelun Biotech, Innovent, WuXi AppTec, WuXi Bio, and Medbot.
Core views
First, AI is improving R&D efficiency but cannot replace wet-lab work and clinical validation; companies with proprietary data, structural biology, DEL screening, automated DMTA, and experimental platforms are more likely to benefit. Second, demand for out-licensing Chinese innovative assets remains strong, with multinational pharmaceutical companies continuing to seek China-origin assets with differentiated clinical value. Third, tighter pharmaceutical representative and anti-corruption policies have limited impact on compliant innovative drug companies, but will squeeze companies that rely on high selling expenses or informal hospital channels. Fourth, investor sentiment has already improved, and if key clinical data in 2H26 remain strong, the China healthcare sector may present buying opportunities on pullbacks.
Analysis framework
The report uses a conference and company field trip note format, linking together management discussions from nine companies, investor feedback, observations on policy impact, out-licensing cases, and 2H26 clinical catalysts to form a judgment on the innovation capability, commercialization resilience, and globalization execution of China's healthcare industry.
Methodology notes
Summarizing industry trends through on-site discussions with multiple companies
The report is based on the Chengdu healthcare field trip conducted on July 14-15, covering nine companies, and distills investment views along four main themes: AI applications, licensing partnerships, policy impact, and clinical catalysts.
Licensing value is driven by unmet clinical needs and differentiated data
The report emphasizes that the value of overseas collaboration comes not only from lower development costs, but more importantly from whether an asset has strong clinical differentiation that addresses unmet clinical needs.
AI improves efficiency but does not replace experimental validation
The report believes AI can reduce the number of synthesized molecules and shorten discovery cycles, but the real barriers lie in high-quality private data, physical data, structural biology, and automated experimental validation capabilities.
Asset mapping & comparison
Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).
- Kelun Biotech 6990.HKOne of the core preferred biotech names, and used to illustrate out-licensing and AI data barriers
- Strengths
- Its partnership with MSD shows that its ADC and innovative assets are recognized by multinational pharmaceutical companies; the company emphasizes the importance of high-quality physical and private data for AIDD models.
- Weaknesses
- Subsequent valuation and sentiment still depend on delivery of clinical data and global development execution.
- Comparison
- Compared with earlier-stage platform companies, Kelun Biotech already has clearer external collaboration cases and clinical asset validation.
- Risks
- Clinical data missing expectations, slower licensing partnership progress, and policy or commercialization execution volatility.
- Innovent Biologics 1801.HKA biotech name explicitly preferred in the report
- Strengths
- It belongs to J.P. Morgan's preferred China biotech direction and benefits from improving sentiment toward innovative drugs and solid sector fundamentals.
- Weaknesses
- The report does not elaborate on standalone company fundamental details in the main text.
- Comparison
- Like Kelun Biotech, it belongs to the report's preferred biotech direction.
- Risks
- Investors are watching the impact of 2H26 data such as HARMONi-3 on sector sentiment.
- WuXi AppTec 2359.HKA CXO name explicitly preferred in the report
- Strengths
- As a leading CXO, it benefits from China's innovative drug R&D activity, global client demand, and the outsourcing trend in R&D.
- Weaknesses
- The report does not provide new company-level operating data.
- Comparison
- Together with WuXi Biologics, it forms the report's preferred CXO portfolio.
- Risks
- Changes in global pharmaceutical R&D budgets, geopolitics, client orders, and the regulatory environment.
- WuXi Biologics 2269.HKA CXO name explicitly preferred in the report
- Strengths
- It benefits from demand for biologics R&D and manufacturing outsourcing, as well as the globalization trend of China's innovative drugs.
- Weaknesses
- The report does not elaborate on standalone financial or order metrics.
- Comparison
- Like WuXi AppTec, it belongs to the report's most favored CXO direction.
- Risks
- Biologics project progress falling short of expectations, volatility in overseas client demand, and policy and geopolitical risks.
- MicroPort MedBot 2252.HKAn additionally preferred medical technology name in the report
- Strengths
- The report lists Medbot as a favored company beyond biotech and CXO, reflecting the allocation value of the medical technology innovation theme.
- Weaknesses
- The main text does not provide detailed data on orders, revenue, or product progress.
- Comparison
- Compared with innovative drugs and CXO, Medbot represents exposure to medical robotics/medical technology innovation.
- Risks
- Commercialization progress, hospital procurement pace, profitability path, and valuation volatility.
Key data
- Field trip period2026-07-14 to 2026-07-15J.P. Morgan China healthcare two-day Chengdu field trip.
- Number of companies covered9 companiesKelun Pharma, Kelun Biotech, Hinova, Haisco Pharma, Baili Pharma, Zenitar, Keymed, Hitgen, and HxMedbot.
- Preferred sub-sectorsBiotech and CXOThe report says it continues to favor the biotech and CXO sub-sectors most.
- Key preferred namesKelun Biotech, Innovent, WuXi AppTec, WuXi Bio, MedbotThe report explicitly lists preferred companies in the main text.
- Disclosed price date2026-07-15 closeThe stock prices disclosed in the report are all closing prices as of July 15, 2026, unless otherwise specified.
- Important 2H26 conferencesWCLC’26, ESMO’26, SABCS’26The report believes Chinese companies may disclose strong clinical data at these conferences.
Impact & implications
For investment, the report reinforces the structural opportunities in China's innovative drug and CXO sectors: companies with differentiated clinical assets, integrated R&D platforms, compliant commercialization systems, and global partnership capabilities are more likely to receive valuation support. By contrast, companies reliant on high selling expenses, auxiliary drug promotion, or informal channels may face pressure under tighter policies. The AI theme still helps improve R&D efficiency and capital market attention, but investment judgment should return to data quality, experimental validation capability, and real clinical value.
Risks
- If key clinical data in 2H26 are weaker than expected, this could hurt sentiment in the China healthcare sector.
- There is uncertainty over how long the current healthcare rebound can last, and some investors are already focused on pullback risk.
- Tighter pharmaceutical representative and anti-corruption policies may accelerate industry differentiation, pressuring companies that rely on high selling expenses or informal hospital channels.
- The value of out-licensing deals depends on clinical differentiation; if assets lack clear unmet need or data advantages, transaction attractiveness may decline.
- Geopolitics, global pharmaceutical R&D budgets, and changes in cross-border collaboration approvals may still affect licensing partnerships and CXO demand.
What to watch
- Kelun Biotech's Phase III data for sac-TMT.
- Baili's Phase III data for iza-Bren.
- The quality of clinical data disclosed by Chinese companies at WCLC’26, ESMO’26, and SABCS’26.
- Progress in licensing partnerships between multinational pharmaceutical companies and Chinese ADC, immunology, molecular glue, metabolism, and autoimmune assets.
- Selling expenses, sales progress, and industry differentiation of innovative drugs after tighter pharmaceutical representative policies.
- Whether AI drug R&D companies can convert model capabilities into verifiable experimental and clinical efficiency improvements.