The link between non-clinical and clinical testing ~ are non-clinical tests predictive of clinical effects? C Mike Perkins MD Pfizer Global Research & Development

Outline Based on standard agents with known effects on QT and arrhythmia Principal target - HERG/IKr Safety margins Are all HERG blockers the same? –repolarisation assays –in vivo evaluations –Proarrhythmia Pharmacokinetics and drug-drug interactions Integrated risk assessment

QTc in Man

QTc in Man (2)

E-4031 Cisapride Terfenadine Terodiline Verapamil Percentage Change Concentration (nM) Effects on HERG in HEK293 Cells

Dofetilide

Therapeutic Window and TdP Webster, Leishman & Walker (2002) Towards a drug concentration effect relationship for QT prolongation and torsades de pointes. Current Opinion in Drug Discovery & Development

H 1 Antagonists hERG IC50 (nM) IKr IC50 (nM) Unbound Plasma Conc (nM) Margin Terfenadine – 9.01 Astemizole (desmethyl astemizole) 0.9 – – Ebastine – Cetirizine , Fexofenadine13,100 – 23,000 >5, astemizole  terfenadine>>cetirizine  fexofenadine  ebastine Differences HERG/IKr potency, Plasma concentrations and PK interaction data taken into account

HERG – Predictive Value

Effect in Canine Purkinje Fibre

Anesthetized Dog - MAPD 150bpm Terfenadine Terodiline Verapamil Percentage Change Plasma Concentration (Unbound; nM)

AV Blocked Dog

Effect in Repolarization and Proarrhythmia Model

Correlation Between Models - Cisapride

Correlation Between Models - Terodiline

Correlation Between Models - Terfenadine

Weight of Evidence – Predictive Value

Relative HERG inhibitory potency Webster, Leishman & Walker (2002) Towards a drug concentration effect relationship for QT prolongation and torsades de pointes. Current Opinion in Drug Discovery & Development

Therapeutic Window and TdP Webster, Leishman & Walker (2002) Towards a drug concentration effect relationship for QT prolongation and torsades de pointes. Current Opinion in Drug Discovery & Development

ABPI Data set Literature search on 95 drugs –HERG/IKr data –Action potential data –In vivo QT data –Free plasma drug levels following therapeutic use

ABPI Data set Compounds were categorised as: 1 Class III antiarrhythmics 2Withdrawn from market for QT or Torsade de Pointes 3Strong evidence for Torsade de Pointes 4 Clinical evidence is weak or absent

HERG Selectivity of 5-fold Compounds in groups 1-3? Y Y N N Selectivity for human exposure vs HERG >5-fold 32%68% 95%5% attrition Missed opportunities

HERG Selectivity of 10-fold Compounds in groups 1-3? Y Y N N 20%80% 95% 5%

HERG Selectivity of 30-fold Compounds in groups 1-3? Y Y N N 12%88% 90% 10%

HERG Selectivity of 100-fold Compounds in groups 1-3? Y Y N N 8% 92% 60% 40%

HERG Selectivity of 1000-fold Compounds in groups 1-3? 96%4% 85% 15%

Conclusions HERG/IKr data alone is a remarkably good predictor of QT risk Smaller the TI the higher the risk Power of non-clinical studies are greatly increased with native tissue and in vivo data –Verapamil would be a true negative What is an appropriate TI? –Small TI (5-fold) identifies 68% ‘clinical actives’, but 32% false negatives and only 5% false positive –High TI (1000-fold) identifies 96% ‘clinical actives’, only 4% false negatives, but 85% false positive

Importance of PK on selectivity 1 o pharmacology 2nM Threshold for IKr (90 nM) Cmax vs.IKr selectivity 2 or 15-fold

Impact of drug interactions 1 o pharmacology Threshold for IKr Cyp 3A4 inhibitor increases t1/2 resulting in drug accumulation. Pharmacological selectivity is eroded further.

Summary & Conclusions (1) Drugs associated with arrhythmia can give large concentration dependent changes in QTc Correlation exists between HERG potency and plasma concentrations associated with QT prolongation and TdP Therapeutic ratio can be determined and appears to correlate with the prevalence of cardiac arrhythmias

Summary & Conclusions (2) Not all HERG blockers are the same –Other ion channel effects can be important –Additional effects may modulate risk of arrhythmia Plasma concentrations obviously are important –Need to appreciate the impact of variability in plasma concentrations –Drug-drug interactions can be very important as these influence safety margins

Summary & Conclusions (3) Non-clinical assays can guide clinical QT studies by predicting the concentrations and circumstances under which QT prolongation and arrhythmia might occur, thus highlighting particular questions to be addressed.

Acknowledgements Pfizer QT advisory council Derek Leishman Rob Wallis Reference: Redfern, Carlsson, Davis et al Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and Torsade de Pointes for a broad range of drugs: evidence for a provisional safety margin in drug development Cardiovascular research 58(2003) 32-45

ICH The Sixth International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use New Horizons and Future Challenges Osaka International Convention Center, Osaka, Japan November

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