human pharmacology for biologicals – first into man studies daren austin phd clinical pharmacology...
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Human pharmacology for biologicals – First into man studies
Daren Austin PhDClinical Pharmacology Discovery Medicine
GlaxoSmithKline
27/04/2007 AGAH/Club Phase I Annual Mtg 2
London - March 13, 2006
27/04/2007 AGAH/Club Phase I Annual Mtg 3
London - March 13, 2006
27/04/2007 AGAH/Club Phase I Annual Mtg 4
Some perspective Developing new medicines is a collaborative effort
– industry, academia and regulatory bodies
FTIH studies are generally very safe
– protocols represent a high standard of science and medicine
TGN1412 underscores the importance of translational science, clinical pharmacology and study design for safe drug development
Most antibodies are very safe
– At least one marketed antibody has the same cytokine profile as TGN1412
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A few successes…
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Applications of therapeutic antibodies
AbciximabBasiliximabDaclizumabEfalizumab
NatalizumabPalivizumab
AdalimumabBavacizumab
EtanerceptInfliximab
Omalizumab
GemtuzumabozogamacinIbritumomab
tiuxetanTositumomab
AlefaceptCetuximabMuronomabMuronomab
Trastuzumab
DESTROYDESTROYTARGET CELLSTARGET CELLS
ALTER CELLALTER CELLFUNCTIONFUNCTION
TARGETED DRUGTARGETED DRUGDELIEVRYDELIEVRY
NEUTRALIZE “TOXINS”NEUTRALIZE “TOXINS”IMMUNOTOXICOTHERAPYIMMUNOTOXICOTHERAPY
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The wrong way …We’ve got a new wonder
drug! … we give it to you and wonder what it will do
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The right way…Outline Understand the mechanism
Understand the pharmacology
Design the right study (theory)
Define the right dose
Understand the population
Design the right study (practice)
Conduct the study right
www.prairierivers.org
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Understand the mechanism
Soluble or cell-associated target Pleiotropy Redundancy Potential for biological amplification Downstream signalling Tissue expression and homeostasis Translation plan for human systems
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Understand the pharmacologyBig molecules – small differences?
Characteristic Small Molecule Antibody
Molecular weight < 700 150,000 (300x higher)
Potency pM – nM (agonist/antagonist)
pM – nM(typically antagonists)
Clearance Linear at low doses, Non-linear at high doses
Non-linear at low doses, linear at high doses
Volume Wide range, < 1000 L/kg 70 ml/kg, 2x plasma
Bioavailability 0 – 100%, predictable from Phys Chem properties
0% via oral, 30 – 90% via sub-cut
PK/PD timeframe PD slower than PK PK slower than PD
Preclincal NOAEL Dose limiting, non-specific, off-target binding
Exaggerated pharmacology
FTIH design Multi-cohort, cross-over design
Multi-cohort, parallel group design
27/04/2007 AGAH/Club Phase I Annual Mtg 11
Understand the pharmacology Antagonists
– possess affinity without activity acts by blocking a receptor, occupying or
inhibiting messenger
Agonists– possess affinity with efficacy,
binds and activates a response via downstream signalling
Hence, an agonist activates a receptor, an antagonist binds but doesn’t activate it (i.e., it blocks access of agonist)
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Design the right study (theory)What dose range? What starting dose?
www.pbase.com
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Dose ranges: are they adequate?Data from 100 GSK FTIH studies
Median of 6 dose levels (8 periods)
Cumulative escalation is 60x (2–20000x)
Distribution is different to industry benchmark#
# Buoen et al. (2005) J. Clin Pharm 45: 1123-1136
0
5
10
15
20
25
30
2 4 8 16 32 64 128 256 512 1,024 2,048 4,096 8,192 16,384 32,768
Log2 (Dose range)
Per
cen
t Data
BPCEDD
Industry
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Design the right studyTypical GSK FTIH designs
For small molecules typically five period (incl. placebo) with repeated dose across cohorts and 2-3 fold escalations:– P, X, 2X, 4X, 8X then P, 8X, 16X, 32X, 64X– 23 x 23 = 64-fold– 3 x 3 x 2 x 2 x 1.5 x 1.33 = 72-fold
For large molecules typically six period parallel group with log/semi-log decreases– X, 10X, 10X, 3X, 3X, 3X– 102 x 33 = 2700-fold
Overall dose range defined by number of cohorts Define starting dose to give top dose
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Exposure ranges for responses Agonists are very
efficient at signalling (80/20)
Antagonists must block most receptors before signal is turned off
0%
20%
40%
60%
80%
100%
120%
0.001 0.01 0.1 1 10 100 1000
Relative Dose
Rel
ativ
e R
esp
on
se
Shallow
Antagonist
Agonist
Switch
Desired response
Exposure Ratio Shallow
Anta-gonist Agonist "Switch"
90% ED90/ED10 4 2 1 <1
95% ED95/ED5 5 3 1 <1
99% ED99/ED1 8 4 2 1
Orders of magnitude for exposure rangeGOOD (<100x)POSSIBLE (100 – 1000x)IMPOSSIBLE (>1000x)
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Exposure ranges for responses Agonists are very
efficient at signalling (80/20)
Antagonists must block most receptors before signal is turned off
0%
20%
40%
60%
80%
100%
120%
0.001 0.01 0.1 1 10 100 1000
Relative Dose
Rel
ativ
e R
esp
on
se
Shallow
Antagonist
Agonist
Switch
Desired response
Exposure Ratio Shallow
Anta-gonist Agonist "Switch"
90% ED90/ED10 4 2 1 <1
95% ED95/ED5 5 3 1 <1
99% ED99/ED1 8 4 2 1
Orders of magnitude for exposure rangeGOOD (<100x)POSSIBLE (100 – 1000x)IMPOSSIBLE (>1000x)
27/04/2007 AGAH/Club Phase I Annual Mtg 17
Exposure ranges for responses Agonists are very
efficient at signalling (80/20)
Antagonists must block most receptors before signal is turned off
0%
20%
40%
60%
80%
100%
120%
0.001 0.01 0.1 1 10 100 1000
Relative Dose
Rel
ativ
e R
esp
on
se
Shallow
Antagonist
Agonist
Switch
Desired response
Exposure Ratio Shallow
Anta-gonist Agonist "Switch"
90% ED90/ED10 4 2 1 <1
95% ED95/ED5 5 3 1 <1
99% ED99/ED1 8 4 2 1
Orders of magnitude for exposure rangeGOOD (<100x)POSSIBLE (100 – 1000x)IMPOSSIBLE (>1000x)
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Define the right dose
http://pixelsoap.com/photos/album32/roulette
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Define the right dose What starting dose?
Define No Observable Adverse Effect Level
Safety cover for top dose (1 – 5x)
Low dose basedon enhanced cover
(100 – 500x)
Low dose basedon expected
pharmacology
For NMEs, low dose will be typically 100x lower based on design arguments
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Define lowest level of biological activity preclinically Equivalent to “Minimally effective” Phase IIB dose Will require downward preclinical dose titration for antibodies
Define NOAEL
Safety cover fortop dose (1 – 5x)
Safety cover forlow dose
(100 – 500x)
Low dose based on pharmacology
Define MABEL
Low dose = Min(MABEL, NOAEL/cover, Binding)
Minimally Active Biological Effect Level
Define the right dose What starting dose?
27/04/2007 AGAH/Club Phase I Annual Mtg 21
MABEL based on PD/PD of orthologues
Raptiva™ targets CD11a did not bind to preclinical species muM17 is an anti-mouse CD11a Mab developed as a surrogate
molecule to assess reproductive toxicity in mouse Mechanistic PK/PD model used to determine dose equivalence to
humans
Wu (2006) J Pharm Sci 96 (6) 1258
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PK/PD and orthologues
Wu (2006) J Pharm Sci 96 (6) 1258
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PK/PD and orthologues model validation
Wu (2006) J Pharm Sci 96 (6) 1258
27/04/2007 AGAH/Club Phase I Annual Mtg 24
Allometric scaling of proteins
Established for small and larger molecules Assumes conservation of clearance pathway across species For monoclonal antibodies this assumption is frequently violated
– Human target may only be shared by primate species– Single species allometry– Consider target expression and target mediated clearance
http://www.elephants.com/sharma_photos.htm
Mordenti et al (1991), Pharm Res 8, 1351
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Scaling capacity-limited binding to humans
MUC-18 cell surface adhesion (melanoma)
Fit parallel linear and non-linear binding elimination pathways
Assume Vmax and Km are predictive of humans
Residual clearance allometrically scaled
Simulate human PK profiles
Ignores neutralisationhttp://www.abgenix.com/documents/ASCPT2004%20poster.pdf
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Define the right dose Large molecules bind to a target at nanomolar
concentrations– 150kD implies equates to 0.15µg/ml for 50% binding
That’s about 0.01 mg/kg
Antibody binding is normally antagonistic– High binding required to suppress signaling pathways– 80-90% binding equates to 1 – 2µg for biological effect
That’s about 0.1 mg/kg
Guiding simplification– Starting dose of Kd[nM]/200Kd[nM]/200 [mg/kg] will give about 50% binding
[Duff pg. 29] Scale for smaller proteins according to MWT and Vdss
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Define the right dose
Proposed (and approved) Suggested (for agonist)
100x lower starting dose and smaller escalations*Assumes Cmax/Kd is correlated with functional responseRo ~ (Cmax/Kd)/(1+(Cmax/Kd))
*
Dose (mg/kg)
Cmax (ug/ml)
AUC(0-inf)
(ug.h/ml)Cover DOSE
Ratio Cmax
Kd Ro
0.1 2.309 428 500x 8.2 89%
0.5 11.55 2142 100x 40.9 98%
2 46.2 8567 25x 163.8 99%
5 115.5 21418 10x 409.5 100%
Dose (mg/kg)
Cmax (ug/ml)
AUC(0-inf)
(ug.h/ml)Cover DOSE
Ratio Cmax
Kd Ro
0.001 0.023 4.28 50000x 0.08 8%
0.003 0.069 12.8 16667x 0.25 20%
0.008 0.185 34.2 6250x 0.7 40%
0.012 0.277 51.4 4167x 1.0 50%
0.025 0.577 107 2000x 2.0 67%
0.05 1.155 214 1000x 4.1 80%
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Understand the population ICH guidelines Benefit outweighs the risk
– HVTs do not benefit– Risk must be managed
accordingly
Mixed populations?– HVTs (S&T/PK) then
escalate in patients
Mild patients?– Neither HVTs nor mild
patients may predict eventual populationhttp://www.noaddedsugar.org/images/gordon/crowd.jpg
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Healthy subjects or patients?
Points to consider Comments
Expression of target protein Healthy subjects may not predict safety and tolerability
Safety profile in patients may vary with disease severity
Determination of optimal biological dose
May only be possible in patients
Presence of co-morbidities Detection and interpretation of safety signals more difficult
Long half life Extended follow-up not always feasible in healthy volunteers
Opportunity for investigating pharmacodynamic activity
Risk assessment May preclude healthy subjects
Immunogenicity May limit future choice of therapy
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Not all created equal …
Intrinsic variability– drug-target interactiondrug-target interaction
– type of transduction
– drug access at biophase
– delivery & input rate
– metabolism pheno/genotype
– disease & homeostasis
– placebo response
Extrinsic variability– drug-drug interactions
– interactions with endogenous substances
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Part 1 – Healthy subjectsSafety, tolerability
PK
Part 2 – PatientSafety, tolerabilityPK, PD
Increasing dose
Bridging dose
Mixed study population
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Design the right study (practice)
Stronger drive to deliver more information earlier: MTD with Proof of PharmacologyProof of Pharmacology– early call on therapeutic index– define MTD in relevant populations (target expression?)– early go/no-go decisions
Fusion designs in Phase I– combination of study objectives
Adaptive designs in Phase I– say how you will decide to do something
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Proof of pharmacology
Safety signalSafety signal from known class of compounds (e.g. cortisol suppression)
Receptor occupancy signaloccupancy signal from ex vivo assay (e.g. CD11B from neutrophils)
Imaging signalImaging signal (e.g. fMRI or PET studies) Transcriptomics for evidence of signal transductionsignal transduction Clinical surrogateClinical surrogate signal (e.g. airway conductance) Clinical signalClinical signal (e.g., fasting plasma glucose)
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Design the right study: Phase I Fusion designs
FTIH
SingleDose
RepeatDose
FoodEffect
Drug-DrugInteraction
PatientPopulation
HumanPharmacology
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Safe and well-tolerated?FTIH study objectives
Part A To investigate the safety and tolerability of single escalating doses of
GSK123456 in healthy subjects. To characterize the preliminary pharmacokinetics of single escalating
doses of GSK123456 in healthy subjects.Part B To investigate the safety and tolerability of a single oral dose of
GSK123456 in mild to moderate patients To characterize the preliminary pharmacodynamics of single and repeat
doses of GSK123456 as assessed by in an appropriate model
…GSK123456 is safe, well-tolerated, pharmacokinetics, response in patients…
Summarise and report results of Part A and justify doses in Part B
Will we establish a Maximum Tolerated Dose?
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Summary biopharmCEDD FTIH/FTIP studies
Criteria Syncra® GSK1 GSK2 GSK4
Indication Diabetes Rheumatoid arthritis
Severe asthma Neuro-degeneration
Target GLP-1 Soluble cytokine Soluble cytokine Soluble protein
Precedence Yes No Semi No
Population HVT HVT HVT/Patients Patients
Design Parallel 2-dose adaptive AUC-
based escalation
Parallel SDadaptive follow-up
Parallel SD/RDPart A/B
Parallel SD/RD D-optimal adaptive
dose escalation on target inhibition
Escalation 416x 10,000x 10,000x 800x
Proof of Pharmacology
Fasting glucose compared to active control (enabling)
Target binding and ex vivo LPS
inhibition
Allergen challenge Target binding and inhibition
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GSK123456 Pop-PK analysis (0.03 – 1.0 mg/kg) during ongoing trial
10
100
1000
10000
100000
1000000
0 7 14 21 28 35 42
Time [days]
Co
nc
en
tra
tio
n [
ng
/ml]
Population Mean Individual Predictions GSK123456
Population PK analysis ongoing to predict time to follow-up
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Conduct the study rightEnsure clinical excellence
All FTIH studies conducted in a
hospital based Unit
Integrated emergency response system and access
to ITU
Determine if additional measures or clinical expertise is needed
Assure staff training and experience
Shared medical accountability between site (PI) and sponsor
(medical monitor)
Dosing staggeredInterval hrs -
days
Staff and facilities to handle medical
emergencies
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Summary Understand the mechanism
– Translational medicine plan
Understand the pharmacology– Same principles, different size, High/Low risk molecule?
Design the right study (theory)
– Think escalations not doses, start low, end slow
Define the right dose– MABEL, Cmax/Kd, Preclinical PKPD, Allometry
Understand the population– HVTs and/or/then Patients? Target? MTD?
Design the right study (practice)– Fusion designs with Proof of Pharmacology for FIM expected
Conduct the study right– Hospital site, staggered dosing
27/04/2007 AGAH/Club Phase I Annual Mtg 40
Acknowledgements GSK biopharmCEDD GSK riCEDD Ruth Oliver, CPDM Colin Dollery, GSK
“Laugh when you can, it’s good medicine” Lord Byron
© Mike Baldwin