A new platform that optimises drug combinations for the treatment of multiple myeloma has been created.
The developers hope that the computational quadratic phenotypic optimisation platform (QPOP) could help improve clinical outcomes in people who have become resistant to standard therapies.
The condition is frequently treated with combination therapies that include bortezomib, a first-line drug with promising response rates.
However, most patients end up relapsing due to the development of resistance against bortezomib, which has highlighted a need to identify secondary combination treatments that can overcome or forestall therapeutic resistance.
Masturah Rashid, from the National University of Singapore, and colleagues developed QPOP, which approximates biological responses to therapies using advanced mathematical equations.
Unlike conventional models, QPOP does not require predetermined information about the mechanisms or composition of a drug to optimise treatments.
The research team tested the platform with 128 different combinations of 14 FDA-approved anti-cancer drugs, and found QPOP successfully identified effective combinations and dosages against bortezomib-resistant disease.
In addition, the team demonstrated combination of the approved drugs mitomycin C and decitabine decreased tumour size and prolonged survival in a mouse model of bortezomib-resistant disease, which suggests that QPOP could be a useful tool to identify promising drug combinations for patients.
Source: Rashid, M.B.M.A., Toh, T.B., Hooi, L., Silva, A., Zhang, Y., Tan, P.F., Teh, A.L., Karnani, N., Jha, S., Ho, C.M. and Chng, W.J., 2018. Optimizing drug combinations against multiple myeloma using a quadratic phenotypic optimization platform (QPOP). Science translational medicine, 10(453), p.eaan0941.
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