HanchorBio Partners with InSilicoTrials to Advance AI-Driven Clinical Development for HCB101

Collaboration will evaluate AI-enabled digital twins and external-control approaches that could reduce reliance on randomized control groups, accelerate clinical development, and improve capital efficiency

TAIPEI, SHANGHAI, and SAN FRANCISCO — September 16, 2026 — HanchorBio, Inc. (TWSE: 7827), a global clinical-stage biotechnology company developing next-generation immunotherapies for oncology and immune-mediated diseases, today announced that it has entered into a strategic memorandum of understanding (MOU) and an initial statement of work with InSilicoTrials Technologies S.p.A.

The collaboration with InSilicoTrials will evaluate whether advanced modeling, virtual patient populations—including digital twins—and external or hybrid control approaches can reduce the number of patients required in conventional randomized control groups in future HCB101 trials and, where scientifically justified and accepted by regulators, enable portions of conventional control-arm evidence to be generated through external or simulated approaches.

The potential impact is significant for both patients and HanchorBio. Fewer patients may need to be randomized to a control group, while more efficient trial designs could shorten enrollment timelines, reduce clinical-development costs and capital requirements, and accelerate the generation of evidence needed to advance HCB101 toward registration.

Under the initial statement of work, the companies will launch a regulatory and feasibility phase focused on HCB101 in second-line gastric/gastroesophageal junction (GC/GEJ) cancer. InSilicoTrials will integrate HanchorBio-generated clinical-trial data with relevant literature, real-world and standard-of-care data to model dose, exposure, safety, efficacy, and patient-variability scenarios.

The resulting simulations are intended to support dose selection, Phase 2/3 trial-design decisions, and the evaluation of external, hybrid, or augmented control approaches. Rather than automatically enrolling every comparator patient prospectively, these approaches may allow appropriately matched external or simulated patients to contribute part of the control evidence required for a clinical trial.

If successfully validated and accepted by health authorities, such approaches could potentially:

reduce the number of patients randomized to conventional control treatment;
shorten trial enrollment and development timelines;
reduce the size and cost of pivotal clinical trials;
improve probability-of-success assessment by evaluating multiple trial scenarios before large-scale investment decisions;
improve capital efficiency by testing trial scenarios before committing to large studies; and
increase the amount of clinically useful evidence generated from each enrolled patient.

“For us, the value of AI is very practical,” said Scott Liu, PhD, Founder and Chairman of HanchorBio. “If we can use scientifically rigorous modeling to reduce the number of patients who need to be randomized to a conventional control group, that has enormous potential value. For patients, it may mean fewer people needing to enter a trial knowing they may not receive the investigational treatment. For HanchorBio, it could mean faster enrollment, lower development costs, more efficient use of capital and ultimately a faster path toward bringing HCB101 to patients. That is the kind of AI application that matters to us.”

The companies will first evaluate the feasibility of such approaches and seek relevant regulatory feedback. No external or virtual control approach is presumed accepted in advance, and its eventual use would depend on data quality, methodological validity, the specific trial design, and feedback from regulatory authorities.

“We are excited to partner with HanchorBio to advance its promising HCB101 program through cutting-edge technology, AI, and rigorous modeling,” said Mario Torchia, Chief Executive Officer of InSilicoTrials. “This collaboration brings together clinical-trial simulation, virtual populations, real-world evidence, and regulatory planning around clearly defined development goals. Our ultimate goal is to bring safe and effective drugs to patients faster by applying innovation, AI, and rigorous modeling approaches to de-risk and accelerate drug development.”

Taking AI Beyond Drug Discovery

HanchorBio has already applied computational approaches across molecular design and development. The collaboration with InSilicoTrials extends those capabilities into an area that accounts for a substantial proportion of the time and capital required to develop new medicines: clinical trials themselves.

“AI in biotechnology is often discussed in terms of discovering molecules faster. We believe its impact can extend much further,” said Alvin Luk, PhD, MBA, CCRA, President and Chief Medical Officer (Group) and CEO (USA) of HanchorBio. “Clinical development is where enormous amounts of patient time and capital are committed. If modeling can help us select the right dose, test trial assumptions before enrollment begins, and ultimately reduce the number of patients required in conventional control groups, then AI can directly improve both the economics of drug development and the experience of patients participating in clinical trials.”

The collaboration is HanchorBio’s second publicly disclosed AI-enabled initiative, following the Company’s adoption of Bloomberg Intelligence to strengthen competitive, market and business-development analysis. The Company is also evaluating additional technologies in toxicology modeling, clinical-trial planning, patient selection, translational research and regulatory evidence generation.

The strategic MOU provides a framework to evaluate broader collaboration across additional HCB101 indications and, subject to future agreements, other HanchorBio pipeline programs, including HCB301 and HCB303.

HanchorBio management expects to discuss the collaboration and the Company’s broader AI-enabled drug-development initiatives during its previously announced participation in the inaugural Jefferies APAC Healthcare Conference in Shanghai on September 20–21, 2026.

About HanchorBio

HanchorBio (TWSE: 7827) is a global clinical-stage biotechnology company focused on inventing next-generation biologics for cancer and immune-mediated diseases using its proprietary FBDB™ platform. HanchorBio’s pipeline includes clinical-stage programs HCB101 and HCB301, next-generation trispecific program HCB303, and additional candidates across oncology and immunology. For more information, please visit http://hanchorBio.com

About InSilicoTrials

InSilicoTrials Technologies S.p.A. is a technology company applying artificial intelligence, modeling, and simulation to accelerate and de-risk drug development. Its AI Platform gives pharmaceutical and biotechnology teams access to validated computational models, virtual patient populations, synthetic-control methodologies, and clinical-trial simulation capabilities spanning discovery, preclinical development, clinical development, and CMC. By embedding advanced AI and computational evidence into development and regulatory decision-making, InSilicoTrials helps pharma partners bring safe and effective therapies to patients faster. For more information, please visit www.insilicotrials.com.

Selected Scientific and Regulatory References

S. Food and Drug Administration. Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products: Draft Guidance. January 2025. https://www.fda.gov/media/184830/download
International Council for Harmonisation. ICH M15: General Principles for Model-Informed Drug Development. Final Guideline, January 2026; FDA Guidance for Industry, June 2026. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/m15-general-principles-model-informed-drug-development
S. Food and Drug Administration. Considerations for the Design and Conduct of Externally Controlled Trials for Drug and Biological Products: Draft Guidance. February 2023. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-design-and-conduct-externally-controlled-trials-drug-and-biological-products
Jumper J, Evans R, Pritzel A, et al. Highly accurate protein structure prediction with AlphaFold. 2021; 596:583–589. doi:10.1038/s41586-021-03819-2. https://doi.org/10.1038/s41586-021-03819-2
HanchorBio Presents Two ASCO 2026 Abstracts Highlighting HCB101 Combination Activity and HCB301 First-in-Human Clinical Progress. June 1, 2026. https://www.hanchorbio.com/news/hanchorbio-presents-two-asco-2026-abstracts-highlighting-hcb101-combination-activity-and-hcb301-first-in-human-clinical-progress/

Note: These references provide general scientific, regulatory, and program context. They do not indicate that FDA or another health authority has reviewed, endorsed, or accepted any specific modeling, simulation, external-control, or hybrid-control methodology for HCB101.

Forward-Looking Statements

This press release contains forward-looking statements, including statements concerning the contemplated collaboration, potential uses of modeling and simulation, external or hybrid controls, real-world data, future regulatory interactions, potential co-development activities, and the development of HCB101 and other product candidates. These statements are based on current expectations and are subject to risks and uncertainties that could cause actual results to differ materially. The execution of the MOU does not guarantee that any subsequent workstream, regulatory submission, development strategy, co-development arrangement or transaction will be undertaken or completed. Except as required by applicable law, HanchorBio undertakes no obligation to update these statements.

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