Why do we need virtual clinical trials? At a macro level, the failure rate in new drug development is high, leading to exorbitant costs. Over the past couple of years, due to the downturn in the biopharmaceutical industry and financial constraints, the number of clinical trials has decreased. Virtual clinical trials, by simulating trial and error in a virtual environment, significantly enhance the efficiency of clinical research and reduce costs.
At a micro level, simple animal models cannot fully replicate the complex human environment. Virtual clinical trials not only bridge the gap between ideal biological models and real human conditions but also explore early mechanisms of patient response, identify optimal indications, precisely select patient populations, and decrease the high costs associated with relying on large-scale patient cohorts for trial and error.
Furthermore, many marketed drugs undergo rigorous validation and regulatory scrutiny, yet they still prove ineffective for certain patients in real-world clinical settings. Understanding why these patients are not suitable for a particular drug and identifying their characteristics poses numerous scientific questions worth investigating. Virtual clinical research holds promise in helping us explore these answers and even driving innovation in the overall clinical research paradigm. In other words, it has the potential to break through the "ceiling" of the current clinical research paradigm.
The Future Trend of Clinical Trials
Looking at international developments, in 2015, the European Union released the "Computer Clinical Trial Roadmap - Avicenna Action," announcing a new route for the EU to support biomedical product innovation through "computer simulation." I believe this marks a significant milestone in global computational medicine. At the same time, the EU's "Horizon Plan" also utilizes computer modeling and simulation technology to develop patient-specific digital models, forming virtual patient groups for testing the safety and/or efficacy of new drugs and medical devices.
This trend indicates that future clinical trials may partially rely on information from virtual patients and use smaller sample sizes to validate drug efficacy.
An article titled "Current Status and Trends of Virtual Clinical Research" in China also mentioned that generating virtual patients is a key technology for conducting virtual clinical research. Virtual patients are digitally twinned through one-to-one mapping of patient data generated against the background of virtual patient queues based on population data and biological mechanisms. Although digital twinning technology is still immature, it has shown enormous potential. Therefore, interdisciplinary efforts are necessary to enhance our understanding of human diseases using digital twinning technology and to transform computational models into clinical practical tools.
In terms of implementation, virtual clinical trials can simulate the treatment effects of different drug regimens after disease progression and also simulate the dose-response relationships of Phase I and II drug trials. In terms of validation, virtual clinical trials can be used for retrospective validation, comparing with completed studies of marketed drugs, and for prospective validation, implementing parallel testing with new drug clinical trials and clinical treatment results. Once transformed into a tool, virtual clinical trials can not only optimize clinical trial design, including inclusion criteria, dose design, patient stratification, etc., but also guide the implementation of real-world precision and personalized treatment strategies.
A Groundbreaking Study
The Principal-001 study is a very bold clinical study. Prior to this, there was no precedent globally, so you could say we were the first ones to "try it out." It is a Phase II registered breast cancer study with a parallel control trial design, using a chemotherapy + targeted therapy regimen, targeting patients with triple-negative breast cancer. The project was initiated on February 7, 2023.
From the perspectives of targets, genomics, data, gene expression data, immune microenvironment, etc., the computational medicine team established six models, namely the ideal drug model, prognosis score prediction model, target expression prediction model, adverse prognosis score model for tumor-expressed targets, score model for specific responses, and tumor microenvironment model. Subsequently, electronic drugs were developed through model training. We also established corresponding digital twins for six patients who provided peripheral blood samples for model validation.
The latest results show that the responses of the six patients' digital twins to electronic drugs in virtual clinical trials are completely consistent with the results of parallel control trials. Next, in addition to completing model predictions, we hope to identify characteristics of the beneficiary population responding to this treatment regimen and outline a profile of this population.
This study shows us the future application direction of virtual clinical trials. Firstly, it can predict the individual efficacy of patients in advance, helping to evaluate the effectiveness and safety of treatments; secondly, it explores the relationship between the mechanism of tumor onset and the mechanism of anti-tumor drug action, guiding research and development strategies; thirdly, it screens indications and characteristic populations for target drugs, helping in patient recruitment and screening. Particularly for advanced cancer patients who may have poor physical condition after first- or second-line treatments, and with fewer trial-and-error costs, virtual clinical trials are a very valuable research direction.
The author is a professor at the Office of Clinical Trials at Peking University Cancer Hospital.
