Using R For Flexible Modelling Of Pre-Clinical Combination Studies

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Interaction Indices • Wish to calculate these: • With standard errors / confidence intervals • Statements of confidence – significance tests • Use more flexibly and powerfully • Combining combination doses together • Overall assessments of synergy • Covering a wide variety of situations • Inactive agent • Partial Response Agent • Multiple Plates / Experiments AstraZeneca Discovery Statistics 10 Chris Harbron, Using R For Flexible Modelling Of Pre-Clinical Combination Studies, USE-R 2009
Unified Tau ⎧ d ⎪ D ⎪ 1 = ⎨d A ⎪ τ ( i ⎪ ⎩ DA A A ) + + d D d B B B τ D B ( i) d d A A and • Where τ (i) is either: • a constant – response surface • (with discontinuities at the axes) • a separate value for each point • Berenbaum’s interaction index • a separate value for each ray (segment) • a separate value for each dose level of a compound • could fit tau as a continuous function of dose or ray or d B d B = > 0 0 Monotherapies Combinations AstraZeneca Discovery Statistics 11 Chris Harbron, Using R For Flexible Modelling Of Pre-Clinical Combination Studies, USE-R 2009
Page 1 and 2: Using R For Flexible Modelling Of P
Page 3 and 4: Why Drug Combinations? • Making b
Page 5 and 6: Combination Studies [B] Benefit? :
Page 7 and 8: Interaction Index - Berenbaum Combi
Page 9: Interaction Index - Berenbaum Combi
Page 13 and 14: EDA Suggests Synergy At Higher Dose
Page 15 and 16: Estimates Of Synergy With 95% CIs O
Page 17 and 18: Flexibly Building Formula Varying n
Page 19 and 20: mynls() : A less temperamental nls(
Page 21 and 22: mynls() : A less temperamental nls(
Page 23: Summary • Early identification of

Using R For Flexible Modelling Of Pre-Clinical Combination Studies

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