Transcript Predicting clinical toxicity from in vitro assays

In Vitro Safety Profiling During
Lead Optimisation
Murray Brown
Manager, Data Interpretation and Business Process
Screening and Compound Profiling
Drug Discovery Process
Target
Selection
Basic
Research
Years
Candidate
Selection
Lead
Discovery
3
Preclinical
Development
1
IND
filing
NDA
filing
Clinical
Development
6
FDA
Filing
1.5
Once a candidate is selected the pharmacological properties of the
molecule are fixed
High Throughput Screening approaches apply within Lead Discovery to:
– Reduce the cycle time from target selection to candidate selection
– Increase the number of candidates per program
– Increase the quality of candidates selected
Strategies to Improve the Quality of Lead and
Candidate Generation
Robust screening infrastructure
– Automation quality control
– Statistical methods for hit selection
Quality “drug-like” compound libraries
– Low molecular weight and cLogP
New Screening Paradigms
– Fragment Screening
– Encoded Library technology
Relevant assay biology
– Native cellular systems
– Biophysical Screening
Pharmacology of lead series
– Ability to assess on-target and off-target activity
Causes of Attrition – Safety & Efficacy
Reasons For NME Termination By Stage
2005-2009 Industry Portrait
KMR Terminology
Early Dev: Preclin up to Ph III Start
Late Dev: Start Ph III to Launch
Termination Reasons
EARLY
LATE
Strategic
243
18
Resources
19
2
Efficacy
229
25
Safety
457
8
Technical
93
0
Unknow n
42
3
Total
1083
56
Strategic
Resources
Efficacy
GSK
EARLY
29
0
25
LATE
3
1
2
Safety
65
4
Technical
7
0
Unknow n
5
0
Total
131
10
KMR Group R&D General Metrics Study Final Report July 1, 2010
Addressing the Challenge of Drug Safety in Early
Discovery
Vision
• To increase candidate quality and probability of clinical success
through the identification and mitigation of safety hazards in chemical
series prior to candidate selection
Strategy
• Using high throughput techniques, implement panels of assays for use
in early discovery that identify likely safety liability in hits, leads and
candidates
Attrition Reduction Activities in GSK
Strategic Intent
– Implement assays during H2C to identify and manage compound series
likely to cause toxicity in preclinical or clinical studies
eXP
Cardiotoxicity
Hepatotoxicity
Genotoxicity
A bi-weekly panel of
50 molecular target
assays with known
clinical liability
A panel of Ion
Channel assays
enabled by high
throughput
electrophysiology
Cell Health assay
detects 70% of
known
hepatotoxicants
GreenScreen
assay licensed to
identify
Genotoxicants
Assays configured during 2009-2010 with capacity to screen 1200 hits, leads
and candidates/year
eXP (enhanced cross screen panel)
Neuronal:
Cardiac/vascular:
KCNQ1/minK
L-type Ca
VR4
M2
Adenosine 2a
β2 adrenergic
α1b adrenergic
α2a adrenergic
a1b3g2 GABA
SERT
DAT
NET
M1
MAO-B
μopioid
κopioid
Dopamine 1
Dopamine 2
Histamine 1
NK1
Hepatic:
OATP1B1
PXR
Gastro-intestinal:
5-HT3
PDE4B
GSK3b
PI3k
Immunological:
LCK
Cannabinoid 2
Nav1.5
Kv1.5
5-HT1B
5-HT2A
5-HT2C
COX2
V1a
Neuromuscular:
a1bgd nAChR
11 point dose response curve
Functional/activity assays
Interpharma Safety Profiling
Knowledge-Sharing - Secondary Pharmacology Screening
AstraZeneca
Outcomes:
Joanne Bowes
GlaxoSmithKline
2009-present
• Poster at SPS meeting:
Andrew Brown
Arun Sridhar
• What
• Rational design
of an inTargets?
vitro safety profiling panel to reduce
undesired secondary
pharmacology
of drug candidates.
• What
Technologies?
Steven Whitebread, Joanne Bowes, Andrew Brown, Jacques Hamon, Wolfgang G.
Jarolimek, Gareth Waldron and Arun Sridhar
Journal of Pharmacological and Toxicological Methods; 64(1), July-August 2011,
Page e18.
• What Process?
• Shared Case Studies
• Manuscript - in preparation
Pfizer
Gareth Waldron
Pharmaxis
Wolfgang Jarolimek
Novartis
Steven
Whitebread
Jacques Hamon
High Throughput Electrophysiology Assays to
predict Functional Cardiotoxicity
Cardiac Ion Channels
CNS
(GABAA)
(Barracuda)
hERG
NaV1.5
CaV1.2
KV1.5
KCNQ1
(IonWorks® and PatchXpress®)
See posters by Metul Patel et al on hERG IonWorks® population patch clamp
and Joanna Taylor et al on stem cell derived Cardiomyocytes
Genetic Toxicology: The GreenScreen Assay
Genotoxic agents either react directly with DNA or
disrupt the cellular apparatus which regulate the
fidelity of the genome
Regulations require a minimum of 3 GLP tests:
– a test for gene mutation in bacteria (for
example, the Ames test),
–
a test for chromosomal aberrations in vitro or the MLA
–
an in vivo test for chromosomal damage in
rodent haematopoietic cells.
The GADD45a gene is upregulated in response to
DNA damage in the GreenScreen assay (Gentronix)
Reporter transfected into Human p53 competent
lymphoblastoid cells
Genetic Toxicology: GreenScreen Assay
15% of pre-candidates are terminated due to Genotoxicity
GSK has licensed the GreenScreen HC genotoxicity assay for profiling of
hits, leads and candidates
110
3.5
3
90
80
2.5
70
60
2
50
1.5
40
30
Relative GFP Induction
31 of 34 known
genotoxic agents
induced GADD45a
reporter
Relative Suspention Growth
100
1
20
10
0.5
Blank 0.03 0.06 0.13 0.25 0.50 1.00 2.00 4.00 8.00
µg/ml Etoposide
110
3
90
2.5
80
70
2
60
50
1.5
40
30
1
Relative GFP Induction
100
Relative Suspention Growth
41 of 41 nongenotoxic agents
did not induce the
GADD45a reporter
20
10
0.5
Blank
7
14
28
57
114 228
µg/ml D-Mannitol
456
911 1822
Early stage (HitID and SoC) identification of GreenScreen HC actives
enable LO chemistry to focus on molecules without this liability
BlueScreen HC has now been implemented to allow higher throughput
See poster by Kate Simpson et al on BlueScreen assay validation
Cell Health Assay to Detect Hepatotoxicants
Drug-Induced Liver Injury (DILI) is a recurrent problem in pharmaceutical
development
Idiosyncratic hepatotoxicity is one of the leading causes of drug withdrawals,
non-approvals and warnings (Kaplovitz 2005)
Can we identify hepatotoxicants prior to candidate selection and reduce
attrition due to pre-clinical or clinical hepatotoxicity?
• 96well assay using HepG2
(Human liver carcinoma) cells
GSK Cell Health Assay Description
Measures cytotoxic effect of compounds in human liver-derived HepG2 cells
in 384-well format
3 parameter automated imaging assay
Using fluorescent staining, the key parameters measured in this assay are :  Nuclear Condensation
Hoechst 33342
Cell permeable DNA binding dye
 Mitochondrial membrane potential
TMRM
Accumulates in healthy Mitochondria but leaks out when
mitochondrial membrane potential is discharged
 Membrane permeability
TOTO-3
Cell membrane impermeable nuclear stain
Impaired mitochondrial function is an early indicator of cell injury
whereas loss of membrane integrity and changes in nuclear
morphology are indicators of acute or late stage cytotoxicity.
Quantification is carried out using the InCell
Example images
Nuclei
Mitochondrial
Potential
Membrane
Permeability
Negative
Control
Postive
Control
Typical dose response curves
Correlation between Cell Health readouts
Compounds usually show
very similar IC50s in all 3
readouts, but there are
exceptions where toxicity
is specific to a single
readout
Cell Health Assay to Detect Hepatotoxicants
The Cell Health assay for profiling of hits, leads and candidates
Negative compounds
Human and rat hepatotoxicants
Cytotoxicants
Idiosyncratic human hepatotoxicants
28/28
29/30
4/4
3/18
Early stage elimination of Cell Health actives enable LO chemistry to
focus on molecules without this liability
Compound A failed
due to liver toxicity.
A
B
C
150
125
100
No reported
hepatotoxicity for
Compounds B and C.
75
50
25
0
-25
-50
5E-7
1E-6
5E-6
1E-5
5E-5
0...
0.0...
5E-7
1E-6
5E-6
1E-5
Concentration
5E-5
0...
0.0...
5E-7
1E-6
5E-6
1E-5
5E-5
0...
0....
Frequency of toxicity in Cell Health for marketed
drugs and failed clinical candidates
100%
Failed Candidates twice as 90%
80%
likely to be active in Cell
Health than marketed drugs 70%
59
Inactive in
Cell Health
226
60%
Significant proportion of
marketed drugs show
toxicity in Cell Health
50%
40%
55
30%
20%
71
10%
0%
Drug
Drugs
FC
Failed
Development
Candidates
Active in
Cell Health
Toxic compounds? Toxic dose
Phillippus Aureolus
Theophrastus Bombastus
von Hohenheim
(1493-1541)
Paracelsus
Alle Ding' sind Gift, und nichts ohn' Gift; allein die Dosis macht, daß
ein Ding kein Gift ist.
"All things are poison and nothing is without poison, only the dose
permits something not to be poisonous."
Cell Health cytotoxicity vs normal and toxic exposure levels
Therapeutic or ‘normal’ blood concn
Toxic blood concn
Exposure level
100 uM
1 uM
10 nM
100 uM Cell Health pIC50
Therapeutic and toxic blood concentrations of more than 800 drugs and
other xenobiotics M. Schulz, A. Schmoldt Pharmazie 58(7) 2003 447-474
10 uM
http://fscimage.fishersci.com/webimages_FSC/downloads/winek.pdf
What drives cytotoxicity?
i) Physchem properties - clogP
What drives cytotoxicity?
ii) Physchem properties – rotatable bonds
What drives cytotoxicity?
iii) chemical series
Cell Health cytotoxicity by chemical cluster
Cell Health pIC50
clogP distribution for each cluster
clogP vs Cell Health pIC50
Cell Health Cytotoxicity is SAR-able in lead
optimisation
Physicochemical properties can be manipulated to reduce
likelihood of Cell Health cytotoxicity
– ↓clogP, ↓# aromatic rings, ↓heavy atom count (or ↑ >50!),
↑ heteroatoms, ↓ rotatable bonds
Cell Health cytotoxicity is a feature of chemical series beyond
their physicochemical properties (toxicophores)
– Early screening in Cell Health assay at HitID allows
selection of series with lower likelihood of cytotoxicity
Cell Health Assay Related to Promiscuity in eXP
1
100%
3
5
90%
80%
36
70%
60%
156
17
50%
19
24
40%
30%
19
20%
10%
28
0%
x ≤ 0.10
0.10 < x ≤ 0.20
0.20 < x ≤ 0.30
0.30 < x ≤ 0.40
Fraction assays with pXC50 >5
Green = Inactive in Cell Health
Red = Active in Cell Health
0.40 < x
In vitro cross screening profile of selected drugs
Low promiscuity, mechanism based
toxicity detected by eXP, non-toxic in
Cell Health
Non-promiscuous, highly tolerable,
non-toxic in Cell health
a1B
Moderately promiscuous and highly
tolerable, non-toxic in Cell health
CB2 Ag
Assay
a2C
b2
Highly promiscuous, low tolerability,
toxic in Cell Health
Attrition Reduction Toolkit: An annotated one-stopshop for all attrition reduction assays at GSK
Attrition Reduction Toolkit: An annotated one-stopshop for all attrition reduction assays at GSK
Compound
Structure
Profile similarity in eXP
Conclusions
We have implemented a panel of assays in early discovery to
assess toxicity hazards in hit and lead series
Assays are annotated according to likely clinical effect
Each assay is not decision making in isolation
– Data enables comparative decisions between chemical series
– Activity in multiple assays needs to be considered
Assays can be used to drive SAR
Cell Health assay in HepG2 cells concords well with
physicochemical properties shown to be important in clinical
attrition and clinical in vivo tolerability
Exposure levels are key for toxicology (as well as efficacy)
expected dose is important factor to be included in interpretation of
early Safety Profiling data
Acknowledgements
Steve Rees (formerly Screening and Compound Profiling)
Andrew Brown (Screening & Compound Profiling)
Dave Morris (Screening & Compound Profiling)
Wolfgang Jarolimek (formerly Screening and Compound Profiling)
Joanna Taylor (Screening & Compound Profiling)
Kate Simpson (Screening & Compound Profiling)
Metul Patel (Screening & Compound Profiling)
Rob Jepras (Screening & Compound Profiling)
Rob Eagle (Screening & Compound Profiling)
Darren Green (Computational & Structural Chemistry)
Cerys Lovatt (Safety Assessment)
Julie Holder (Safety Assessment/Stem Cells)
Nick McMahon (Safety Assessment)
Paul Hastwell (Safety Assessment)
Patrick Wier (Safety Assessment)
Steve Clarke (DMPK)
Bob Hertzberg (Screening & Compound Profiling)
Many other GSK scientists responsible for generating the assays and data