Table 1.
Parameter estimates of the pharmacodynamic model for asciminib 80 mg q.d. versus 40 mg b.i.d. in the subset of patients without the T315I mutation
| Cmin (RSE) | Regimen (RSE) | |
|---|---|---|
| Population means | ||
| Q (t = 0) | 0.0260 (45.4%) | 0.0156 (46.4%) |
| P (t = 0) | 0.0246 (4.9%) | 0.0253 (4.0%) |
| R (t = 0) | 2.05 × 10–9 (75.4%) | 8.94 × 10–6 (48.4%) |
| kgr (1/y) | 28 (fixed) | 28 (fixed) |
| kqp (1/y) | 0.53 (fixed) | 0.53 (fixed) |
| kqr (1/y) | 6.5 (fixed) | 6.5 (fixed) |
| Effmag | 42.1 (3.4%) | 39.8 (3.18%) |
| Gamma | 0.0399 (7.2%) | |
| Standard deviation of random effects (IIV) | ||
| Q (t = 0) | 3.49 (7.6%) | 3.72 (8.3%) |
| P (t = 0) | 0.147 (20.5%) | 0.174 (17.2%) |
| R (t = 0) | 2.36 (27.4%) | 3.37 (11.7%) |
| Effmag | 0.265 (7.1%) | 0.277 (6.3%)† |
| Cov (Q [t = 0], Effmag) | − 0.647 (11.1%) | − 0.718 (7.1%) |
| Covariate effect magnitude†† | ||
| L10BA0 on Q (t = 0) | 2.53 (14.7%) | 1.97 (19.8%) |
| L10BA0 on P (t = 0) | 2.51 (1.7%) | 2.55 (1.5%) |
| Regimen on Effmag (80 mg q.d.) | − 0.0447 (148%) | |
| NUMTTRT (3,4,5) on Effmag | − 0.0725 (56.7%) | − 0.0692 (55.4%) |
| Residual error | ||
| a (additive) | 0.23 (2.7%) | 0.19 (2.6%) |
| b (proportional) | 0.0975 (7.1%) | 0.081 (6.3%) |
| Fit statistics | ||
| – 2 log-likelihood | 1316.21 | 998.68 |
| Corrected BIC | 1410.42 | 1090.72 |
BIC Bayesian information criteria, b.i.d. twice daily, Cmin minimum plasma concentration, Cov covariate, Effmag effect of drug, IIV inter-individual variability, kgr growth rate of resistant and proliferating cells, kqp and kqr transfer rate constants between proliferating, resistant and quiescent compartments, L10BA0 baseline log10-transformed BCR::ABL1IS, NUMTTRT number of prior TKI treatments, P proliferating leukemic bone marrow cells, Q quiescent stem cells, q.d. once daily, R proliferating resistant cells, RSE relative standard error, t time, TKI tyrosine kinase inhibitor, y year
†This value is for the 40-mg b.i.d. dosing regimen
††Covariate effect magnitude is reported as log. The linear effect is exp(value)