DEVELOPMENTAL PK/PD: WHAT HAVE WE LEARNT? Geoff Tucker - PowerPoint PPT Presentation

DEVELOPMENTAL PK/PD: WHAT HAVE WE LEARNT? Geoff Tucker

UNDERSTANDING AND PREDICTING PK/PD IN JUVENILES

PHARMACOKINETICS Can we scale from juvenile animals? Can we scale from allometry? Can we scale from in vitro ?

ORAL BIOAVAILABILITY From Grass & Sinko ( Adv Drug Deliv Rev,2002 ) from Sietsema ( Int J Clin Pharmacol Ther Toxicol,1989)

% Adult 100 HUMAN CYP3A4 (Johnson et al ,2006) ♂ RAT CYP3A1 (Johnson et al , 2000) 80 60 DOG CYP3A12 (Taneka, 1998) 40 ♀ RAT CYP3A1 (Johnson et al , 2000) 20 0 neonate infant child adolescent adult

ONTOGENY OF TRANSPORTERS (ANIMALS) weaning Liver Intestine Kidney PgP – MOUSE (Mahmood et al , 2001) Bile salt/OATs – RAT LIVER PgP – RAT BRAIN (Gao et al , 2004) (Matsouka et al , 1999) OATs – RAT KIDNEY (Buist et al , 2002)

PHARMACOKINETICS Can we scale from juvenile animals? Can we scale from allometry? Can we scale from in vitro ?

“THE 3/4 (Klieber’s) LAW” From allometric principles: Metabolic Rate ∝ BW 0.75 Clearance ∝ BW 0.75 Holford – “A size standard for pharmacokinetics” Clin Pharmacokin 30: 392-32, 1996

“THE 3/4 (Klieber’s) LAW” From measurements in 5036 N.Europeans, N.Americans and Japanese: Liver Volume = 0.722 x BSA 1.176 BSA ∝ BW 0.67 Liver Volume ∝ BW 0.78 Clearance ∝ BW 0.78 Johnson et al – “Changes in liver volume from birth to adulthood: a meta-analysis” Liver Transpl 11: 1481-93, 2005

: 1.6 1.4 Liver Size (L) 1.2 1 0.8 0.6 Johnson et al : LV=0.722 x BSA 1.176 0.4 Allometric: LV child =LV adult x (BW/70kg) 0.75 0.2 0 0 20 40 60 80 Body weight (kg)

Liver Volume (L) 1.6 LV = 0.722 x BSA 1.176 (n = 162 patients) LV = 1.46 x (BW/70kg) 0.75 1.2 0.8 Fanta et al – “Developmental pharmacokinetics of ciclosporin: A population pharmacokinetic study in paediatric transplant 0.4 patients Br J Clin Pharmacol 64:772, 2007 0 10 20 30 40 50 60 70 Body Weight (kg)

The ‘3/4 Rule’ holds for predicting the clearance of several drugs (e.g.CYP3A substrates– ciclosporine, midazolam, alfentanil etc) But it does not account for the ontogeny of drug metabolising enzymes in neonates and infants. Use ‘3/4 Rule’ to normalise clearance only > 2 years .

PHARMACOKINETICS Can we scale from juvenile animals? Can we scale from allometry? Can we scale from in vitro ?

AGE-RELATED CHANGES IN CYP EXPRESSION/ACTIVITY 1A2 2B6 2C8 2C9 2D6 2C19 Johnson et al (2006) 2E1 3A

EFFECT OF DIET ON CAFFEINE ELIMINATION RATE CONSTANT (CYP1A2) Blake et al (2006)

GLUCURONIDATION Time to maturity? UGT1A1 < 6 months ( e.g. ethinylestradiol UGT1A4 < 2 years ( e.g. imipramine) UGT1A9 > 2 years ( e.g. propofol) UGT2B4 > 2 years UGT2B7 < 6 months (e.g. morphine) Strassburg et al , 2002; Miyagi & Collier, 2007

Predicting Paediatric 2.5 2.5 7 7 Midazolam (Oral) Midazolam (IV) Midazolam (IV) 6 6 2 2 5 5 Clearance 1.5 1.5 4 4 3 3 1 1 2 2 0.5 0.5 1 1 0 0 0 0 0 0 20 20 40 40 60 60 80 80 100 100 0 0 20 20 40 40 60 60 80 80 100 100 0.60 0.60 1.4 1.4 Caffeine (Oral) Caffeine (Oral) Diclofenac (IV) 1.2 1.2 0.50 0.50 1 1 0.40 0.40 0.8 0.8 0.30 0.30 0.6 0.6 0.20 0.20 0.4 0.4 0.10 0.10 0.2 0.2 0 0 0.00 0.00 0 0 20 20 40 40 60 60 80 80 100 100 0 0 20 20 40 40 60 60 80 80 100 100 4.5 4.5 Omeprazole (Oral) 1.5 1.5 Cisapride (Oral) 4 4 CL (L.kg.h) 3.5 3.5 3 3 1 1 2.5 2.5 2 2 1.5 1.5 0.5 0.5 1 1 0.5 0.5 0 0 0 0 0 0 20 20 40 40 60 60 80 80 100 100 0 0 20 20 40 40 60 60 80 80 100 100 0.35 Theophylline (Oral) Carbamazepine 0.25 0.25 0.3 (Oral) 0.2 0.2 0.25 0.2 0.15 0.15 Johnson et al. 0.15 0.1 0.1 0.1 0.05 0.05 0.05 Clin Pharmacokin 2006 0 0 0 0 20 40 60 80 100 0 0 20 20 40 40 60 60 80 80 100 100 0.4 0.4 0.016 0.016 Phenytoin (Oral) S-Warfarin (Oral) 0.35 0.35 0.014 0.014 0.3 0.3 0.012 0.012 0.25 0.25 0.01 0.01 0.2 0.2 0.008 0.008 0.15 0.15 0.006 0.006 0.1 0.1 0.004 0.004 0.05 0.05 0.002 0.002 0 0 0 0 0 0 20 20 40 40 60 60 80 80 100 100 0 0 20 20 40 40 60 60 80 80 100 100 Weight (kg)

Below ~ 2years – prediction of clearance is drug specific due to differential development of its determinants.

Full Paediatric PBPK Model Lung Lung Lung Lung Adipose Adipose Adipose Adipose Bone Bone Bone Bone Brain Brain Brain Brain Heart Heart Heart Heart Venous Blood Venous Blood Arterial Blood Arterial Blood Kidney Kidney Kidney Kidney Muscle Muscle Muscle Muscle Skin Skin Skin Skin Liver Liver Liver Liver Spleen Spleen Spleen Spleen Portal Portal Portal Portal Vein Vein Vein Vein Gut Gut Gut Gut IV IV PO PO • Incorporating information on organ size, tissue composition and blood flow • Allows for prediction of full PK profile ( V, MRT, C max , C min )

ORGAN SIZE RENAL FUNCTION GFR (ml/min/1.73m 1800 1600 ORGAN BLOOD FLOWS Brain Weight (g) 300 1400 Female Male 1200 PLASMA PROTEINS BBF (L.h) RBF (L.h) 250 Renal Brain Liver 1000 Ogiu et al Qh (L.h) ) 80 60 2 120 70 50 800 100 ICRP 60 40 200 80 0.887 Age 0.38 TISSUE COMPOSITION - 50 WATER × 600 30 40 60 AAG = D Alb = 1.1287Ln(t) + 33.746 30 20 400 40 g/L 20 GASTROINTESTINAL FUNCTION 8.89 0.38 Age 0.38 150 + 10 20 10 200 D 0 0 0 70 90 0 2 4 6 8 10 12 14 90 0 2 4 6 8 10 12 14 0 5 10 15 20 0 80 80 Age (y) Age 60 Age (y) 100 % Adult Adipose BF (L.h) Adipose 70 70 Muscle BF (L.h) Muscle 50 60 60 0 5 10 15 TISSUE COMPOSITION - FAT 40 50 50 Skin Skin BF (L.h) 40 1.4 40 30 60 HCl production 30 50 30 20 Age (y) 20 200 20 Skin Muscle 10 Adipose 25 10 10 20 Albumin (g/L) 60 1.2 0 0 0 90 4.5 50 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 50 20 90 90 16 100 Bile acid secretion 80 4 0 AAG (g/L) Muscle 70 3.5 90 80 80 Skin fixed 3.95% 40 1 % Water 60 3 80 70 70 15 Adipose 12 0 4 8 12 50 2.5 Kidney 70 60 60 40 30 40 2 60 50 50 Intestinal length Liver 10 8 30 1.5 50 Heart 40 0.8 40 20 20 1 40 Age (year) 30 30 10 0.5 4 5 30 20 10 20 30 0 0 20 0 5 10 15 20 0 5 10 10 10 15 20 10 6 0 7 0.6 8 0 0 0 0 0 150 Kidney Heart 7 0 5 Liver 10 15 20 0 0 5 4 10 8 15 12 20 16 0 4 6 8 12 16 0 4 8 12 16 5 0 5 10 15 20 100 90 % fat 6 70 Age (y) 20 5 90 4 80 Age (y) Age (y) 5 60 0.4 80 4 70 4 3 70 50 3 60 Brain Lung 3 60 2 2 50 40 2 50 10 1 40 0.2 1 Bone 1 40 30 30 0 0 30 0 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 20 20 10 10 10 0 14 4 8 0 Brain 0 0 0 12 3.5 7 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 3 6 90 90 10 100 0.1 1 10 100 100010000 100000 0.1 1 10 100 100010000 100000 Bone Lung 2.5 100 80 90 5 8 80 70 80 2 4 70 Spleen 6 Plasma Age (days) 70 1.5 3 60 60 4 Age (days) 60 1 2 50 50 2 50 0.5 1 40 40 GI tract 40 0 0 0 30 30 30 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 20 20 2 10 0.8 7 10 10 0 0.7 6 0 0 1.5 0 5 10 15 20 0.6 0 5 10 15 20 0 5 10 15 20 5 Plasma 0.5 Spleen 4 Age (y) 1 0.4 GI tract 50 3 0.3 2 0.5 0.2 1 0.1 0 0 0 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 Age (y) 0 Birth1wk 2wk 3wk 1mo 3mo 1-3y 4-6y5-10yAdult

PK MODELLING “TOP DOWN” Plasma Data POPPK Confirming Demography, PBPK/IVIVE Learning Physiology, Genetics, In Vitro Data “BOTTOM UP”

PHARMACODYNAMICS Age-Related Changes in Concentration-Reponse Drug Age Range n Observation Reference Increased CR Marshall & Kearns (1999) 3mo – 39y 56 Cyclosporin effect in <1-4y group Warfarin 1 – 76y 134 Increased CR Takahashi et al (2000) effect (INR/dose) in 1-11y group Midazolam Preterm – 29w 31 Decreased CR De Wildt et al (2001) (sedation)

MIDAZOLAM (10mg/kg S/C – Rats) Latency to right (secs) Koch et al (2008) 25 Baseline 20 After midazolam 15 10 5 0 3 10 21 Postnatal Age (days) “Dynamic mapping of human cortical development during childhood through early adulthood” Gogtay et al – PNAS 101: 8174, 2004

PK-PD MODELLING “Contribution of midazolam and its 1-hydroxy metabolite to preoperative sedation in children: a pharmacokinetic- pharmacodynamic analysis” Johnson et al : Br J Anaesth 89:428, 2002 “A 50% increase in dose would increase odds ratio from 4 to 275 in favour of sedation score 2 (drowsy/asleep) at start of surgery”

Br J Clin Pharmacol 54:140,2002 Methionine - Homocysteinuria (3 in 1 million) N,N. N,N. Dimethyl glycine - Betaine S- Adenosyl homocysteine (orphan drug) Betaine Homocysteine - Limited population of Cystationine beta-synthase patients to study dH = k in – k out S(t) H(t) - No Pharma funding for dt large studies ( ) E C t Solution: + Max Betaine 1 S(t) = + Clinical Trial Simulation ( ) EC C t 50 Betaine