dose & sample-size selection for dose- response studies
TRANSCRIPT
Efficient solution• Practically realistic• Incorporate prior information• Robust to model uncertainty• Discrimination
Dosing options• Fixed: PLAC & 75 mg• Select 3 doses: 1, 2, 3, 5, 10, 15, 20, 25 & 50 mg
(120 dosing permutations)
Iterative approach• Create all possible dosing options• For each design option:
–Add prior P2a data–Pass through PFIM1.2 algorithm[1]
–Save criterion• Enables discrimination[1] Retout & Mentré (2003). Optimisation of individual and population designs using Splus. J. Pharmacokinet. Pharmacodyn., 30(6): 417-443.
DiscriminationFIX 1 D1 D2 D3 FIX 2 Criterion
0 1 30 50 75 5.510 1 25 50 75 5.490 1 20 50 75 5.470 1 2 50 75 5.460 1 25 30 75 5.45
….0 25 30 50 75 1.83
Include model uncertainty• Sample new set parameters (NPBS)
–For each design option:•Add prior P2a data•Pass through PFIM1.2 algorithm•Save criterion
–Calculate efficiency (crit/max(crit))• Repeat n times
Solution now robustFIX1 D1 D2 D3 FIX2 Efficiency
>5% >50% >95%0 1 30 50 75 0.82 0.98 1.000 1 25 50 75 0.82 0.98 1.000 1 20 50 75 0.85 0.97 1.000 1 2 50 75 0.96 0.99 1.000 1 25 30 75 0.82 0.97 1.00…0 25 30 50 75 0.03 0.36 0.57
Sample size
ED
50 p
reci
sion
(SE
)
0 20 40 60 80 100
05
1015
ED50 precision
Plac, 25, 30, 50 & 75 mg
Sample size
ED
50 p
reci
sion
(SE
)
0 20 40 60 80 100
05
1015
ED50 precision
Plac, 25, 30, 50 & 75 mg
Plac, 1, 2, 50 & 75 mg
Recommendations• Doses: PLAC, 1, 2, 50 & 75 mg
–1 mg essential (ED50 ≈ 0.7 mg)–2 mg for robustness
• Sample size n = 55, good precision– If appropriate doses selected