A new model can predict the best drug combinations for osteoporosis

The model, described today in eLife, may help improve outcomes for patients with post-menopausal osteoporosis and reduce the risk of side effects helping doctors develop more personalized treatment regimens.

Sudden loss of the hormone estrogen during menopause can interfere with the body’s natural processes to repair natural wear and tear on bones, leading to more weakened bones and possible fractures. Several medications are available to treat this type of postmenopausal bone loss. Although these treatments can be combined, there is little evidence to suggest which combinations might be most effective.

“We wanted to know if there were any combinations of treatments that would work considerably better than those tested and currently used in clinical practice,” says first author David Jörg, Senior Scientist in the Biomedical Modeling and Simulation Group, Fresenius Medical Treatment Germany, Poor Homburg, Germany. “If so, it could benefit the treatment of a large number of patients with osteoporosis by increasing the strength of their bones and reducing their risk of bone fracture more than standard therapies currently allow. ”

To investigate this issue further, Jörg and his colleagues constructed a mathematical model of bone turnover that predicts the effects of various osteoporosis drugs in postmenopausal women. They based the model on the latest evidence of how old bone breaks down and new bone is created, as well as how different osteoporosis medications work. They then verified the accuracy of the model by testing its predictions on clinical trial data.

Next, the team tested the effects of rearranging the order of different drugs for osteoporosis. Their model showed that certain combinations in a particular order would work significantly better than others. They also found that the combinations that cause the fastest increases in bone density don’t always build long-term bone strength and may instead cause accelerated bone loss to rebound after treatment is stopped. “These results show us why the order in which osteoporosis medications are taken matters for both short- and long-term treatment success in patients,” says co-author Doris Fürtinger, director of the modeling group. and biomedical simulation, Fresenius Professional medical Care Germany.

Although the model is specific to postmenopausal women, the authors state that it could be adapted to help design combinations of treatments for patients with bone loss caused by other medications or medical conditions. For example, it could be beneficial for those taking corticosteroids or suffering from hyperparathyroidism and gastrointestinal diseases.

“As our model could potentially predict the effects of a huge range of complex therapeutic drug combinations beyond those used in its development, it could be used for the design of future clinical trials,” says lead author Peter Kotanko, research director at the Renal Investigation Institute, New York , USA, and Assistant Professor of Medicine and Nephrology at the Icahn School of Drugs at Mount Sinai, New York.

Kotanko adds that the general limitations of the model should be considered when using it as a predictive tool, especially when applying the data to extreme dosing regimens, dosing frequencies, or age regions beyond those validated in the study. “However, we have shown that not only can the model be used as a starting point for predicting the success of osteoporosis treatment, but it also highlights the role of mathematical descriptions in helping us understand the biological principles of functioning. drugs”, he concludes.

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