Modeling osteoporosis to design and optimize pharmacological therapies comprising multiple drug types.
David J JörgDoris H FuertingerAlhaji CherifDavid A BushinskyAriella MermelsteinJochen G RaimannPeter KotankoPublished in: eLife (2022)
For the treatment of postmenopausal osteoporosis, several drug classes with different mechanisms of action are available. Since only a limited set of dosing regimens and drug combinations can be tested in clinical trials, it is currently unclear whether common medication strategies achieve optimal bone mineral density gains or are outperformed by alternative dosing schemes and combination therapies that have not been explored so far. Here, we develop a mathematical framework of drug interventions for postmenopausal osteoporosis that unifies fundamental mechanisms of bone remodeling and the mechanisms of action of four drug classes: bisphosphonates, parathyroid hormone analogs, sclerostin inhibitors, and receptor activator of NF-κB ligand inhibitors. Using data from several clinical trials, we calibrate and validate the model, demonstrating its predictive capacity for complex medication scenarios, including sequential and parallel drug combinations. Via simulations, we reveal that there is a large potential to improve gains in bone mineral density by exploiting synergistic interactions between different drug classes, without increasing the total amount of drug administered.
Keyphrases
- bone mineral density
- postmenopausal women
- body composition
- clinical trial
- adverse drug
- emergency department
- drug induced
- randomized controlled trial
- healthcare
- electronic health record
- inflammatory response
- risk assessment
- nuclear factor
- big data
- toll like receptor
- cancer therapy
- breast cancer risk
- genome wide
- artificial intelligence
- data analysis