A computer model successfully simulated a clinical trial, testing two Alzheimer’s drugs head-to-head in a first-of-its kind study.
“We’re calling this a virtual clinical trial, because we used real, de-identified patient data to simulate health outcomes,” said lead author Dr Wenrui Hao, of Penn State University, in a statement. “What we found aligns almost exactly with findings in prior clinical trials, but because we were using a virtual simulation, we had the added benefit of directly comparing the efficacy of different drugs over longer trial periods.”
Alzheimer’s disease is a growing public health issue. In recent years, we have seen a slew of new theories about the potential causes of the disease, plus a few notable controversies. In 2021, the US Food and Drug Administration (FDA) approved the first new Alzheimer’s drug in 18 years, aducanumab.
This new study compared aducanumab with donanemab, another promising drug currently being evaluated. Both treatments aim to remove the plaques of beta-amyloid protein that build up in the brains of patients with the disease.
The researchers built a mathematical model to predict disease trajectory in patients, using clinical and biomarker data. The doses of each drug were set to the same dosages that are used in human trials for FDA approval. The virtual trial periods were set at 78 weeks for medium-term follow-up, and 10 years for long-term follow-up.
The model was also used to develop personalized treatment regimens for individual virtual patients. This meant that the doses of the drugs could be adjusted to combat potential side effects, such as brain swelling and vision problems.
“Our objective was to minimize cognitive decline while also minimizing the treatment dosage to limit the corresponding side effects,” said co-author Dr Suzanne Lenhart, of the University of Tennessee, Knoxville. “Our model will give the optimal treatment level over time of the drug, but maybe even more importantly, it provides the optimal personalized treatment plan for each patient.”
Personalized medicine is likely to play an important role in future Alzheimer’s treatment. As the researchers point out, continuing uncertainty about the best way to combat the disease is “rooted in an incomplete understanding of the complex mechanisms resulting in AD [Alzheimer's disease], and how disease trajectory and response to treatment may vary individual-to-individual.”
The results of the virtual trial showed that both drugs were highly successful at removing beta-amyloid plaques, corroborating findings from previous clinical studies.
Donanemab, the newer drug that does not yet have FDA approval, performed slightly better than aducanumab at slowing cognitive decline over 10 years, but neither drug had a large effect. The advantage of the virtual trial is that these results were obtained much more quickly than they could have been using traditional human trials.
“With over 10 anti-amyloid therapies in development, an important question is which one is better,” said co-author Dr Jeffrey Petrella, of Duke University. “It often takes tens of millions of dollars and many years to do a head-to-head comparison of drugs. Our study showed that the effect of these two anti-amyloid drugs on slowing cognitive decline is actually quite modest – and if given late in life, barely detectable.”
In the future, the researchers hope to further refine the model and apply it to different classes of Alzheimer’s drugs, as well as combination therapies. “We’ve shown that this type of model can work,” said Petrella. “I envision it being used as a precision tool to enhance actual clinical trials, optimizing dosages and combinations of drugs for individual patients.”
The study is published in PLOS Computational Biology.