Clinical Trial Simulation to Inform Phase 2: Comparison of Concentrated Versus Distributed First-in-Patient Study Designs in Psoriasis
M. G. Dodds,1 D. H. Salinger,1 J. Mandema,2 J. P. Gibbs,1 M.A. Gibbs1* 1Department of Pharmacokinetics & Drug Metabolism, Amgen, Inc., Seattle, WA; 2Quantitative Solutions, Menlo Park, CA
Table S-1 Test Case Potency Parameters and Desired Trial Outcome Simulation Parameters in log domain Group Marketed Examples No-Go Examples Go Examples
Compound
Emax
ED50
E0
adalimumab
-2.4
2.834
-0.1
golimumab
-2.4
3.82
-0.1
ustekinumab
-2.4
2.63
-0.1
discontinumab
-0.288
2.47
-0.1
mehmimab
-0.598
3.47
-0.1
cuspmimab
-1.05
3.47
-0.1
lowpomab
-2.4
5.20
-0.1
nopomab
-2.4
6.59
-0.1
Phase 1 FIP CTS
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Model Control file. Eight designs (DESNO) were considered, and the control file did not vary between designs and was produced using a script. The data file contains the dose (DOSE), design (DSN) and drug (DRUG) logic as columns to control the simulation and back-estimation process. ;Model Desc: PsO simulator, using mean change in PASI; DATE; Design DESNO ;Project Name: p1 trial design ;Project ID: NO PROJECT DESCRIPTION $PROB RUN# RUNNO $INPUT C ID DOSE DSN DRUG TE0 TEMAX TED50 TEDRUG DV $DATA ../SimData_DATE_DESNO.csv IGNORE=C $PRED ; control stream set to handle a single design for multiple drugs ; as the design information really resides in the data file ; load the typical population values, depending on which drug we're talking about IF( DRUG.EQ.1 ) THEN E0=THETA(1) EMAX=THETA(2) ED50=THETA(3) ENDIF IF( DRUG.EQ.2 ) THEN E0=THETA(4) EMAX=THETA(5) ED50=THETA(6) ENDIF IF( DRUG.EQ.3 ) THEN E0=THETA(7) EMAX=THETA(8) ED50=THETA(9) ENDIF IF( DRUG.EQ.4 ) THEN E0=THETA(10) EMAX=THETA(11) ED50=THETA(12) ENDIF IF( DRUG.EQ.5 ) THEN E0=THETA(13) EMAX=THETA(14) ED50=THETA(15) ENDIF IF( DRUG.EQ.6 ) THEN
Phase 1 FIP CTS
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E0=THETA(16) EMAX=THETA(17) ED50=THETA(18) ENDIF IF( DRUG.EQ.7 ) THEN E0=THETA(19) EMAX=THETA(20) ED50=THETA(21) ENDIF IF( DRUG.EQ.8 ) THEN E0=THETA(22) EMAX=THETA(23) ED50=THETA(24) ENDIF SERR = THETA(25) IERR = THETA(26) E0=E0+ETA(1) ; $OMEGA[1,1] is set to zero, so this does not play a role in the simulation or estimation ; step (see "$OMEGA" below) ; BEGIN ESTIMATION MODEL DEFINITIONS ; prediction for % change in PASI ; DSN
