This presentation was developed for Dr. Anna Durbin's vaccine class at Johns Hopkins. It was delivered simultaneously to my vaccine class at URI. Both classes had their first introductory lecture at the same time, so we joined them by webinar. The slides cover the EpiVax approach to computational vaccinology, which is relatively novel as compared to other groups working in the field. A number of case studies, including H7N9, are provided.

1. Using
Computa.onal
Vaccinology
to
Design
Genome-­‐Derived
Vaccines
for
Infec.ous
Diseases,
Cancer,
Allergy
and
Autoimmune
Disease
22
January
2014
Anne
S.
De
Groot,
Lenny
Moise,
Leslie
Cousens,
Frances
Terry,
William
Mar<n
Ins<tute
for
Immunology
and
Informa<cs,
University
of
Rhode
Island
and
EpiVax,
Inc.
www.epvax.com
www.immunome.org
1

2. Your
Speaker
–
Annie
De
Groot
MD
2

3. The
Company:
EpiVax
hOp://bit.ly/EpiPubs
3

4. EpiVax
Collaborates
with
the
Ins*tute
for
Immunology
and
Informa*cs
@
URI
Collabora<ve
Research
on
Immunome-­‐Derived
Accelerated
Vaccine
Design
and
Development
Funded
by
the
NIH
CCHI
U19,
COBRE,
and
P01
awards.
www.immunome.org
hOp://bit.ly/EpiPubs
4

5. Addi.onal
Collaborators
Bill
Mar<n
Lenny
Moise
Frances
Terry
Leslie
Cousens
Ryan
Tassone
Howie
La<mer
Mindy
Cote
Lauren
Levitz
Chris<ne
Boyle
Mark
Poznansky
Tim
Brauns
Pierre
LeBlanc
Ted
Ross
Don
Drake,
Brian
Schanen
AI058326,
AI058376,
AI078800,
AI082642
Alan
Rothman
Carey
Medin
Andres
Gui<errez
Danielle
Aguirre
Joe
Desrosiers
Thomas
Mather
Wendy
Coy
Loren
Fast
Hardy
Kornfeld
Jinhee
Lee
Liisa
Selin
Sharon
Frey
Mark
Buller
hOp://bit.ly/EpiPubs
Jill
Schreiwer
Connie
Schmaljohn
Lesley
C.
Dupuy
5

6. Outline
• Why Computational Immunology
• Tools to Produce IDVs
– Antigen selection
– Vaccine design
– New concepts
• Case Studies
6

7. Predic<ng
the
future
is
something
that
weather
experts
do
with
the
assistance
of
informa<cs
models.
These
forecasts
enable
us
to
make
decisions
on
a
daily
basis,
and
they
are
accurate
enough
to
mobilize
millions
if
and
when
severe
storms
are
predicted.
Why
then,
are
we
so
slow
to
use
informa<cs
in
vaccine
and
protein
therapeu<cs
design?

8. In
todays
talk,
I
will
discuss
the
use
of
immunoinforma<cs
tools
for
vaccine
design,
mechanism
of
ac<on
studies,
and
efficacy
evalua<ons.
I
believe
that
the
<me
is
ripe
for
vaccine
developers
to
ac<vely
apply,
evaluate
and
improve
vaccines
through
the
use
of
computa<onal
immunogenicity
predic<on
tools.

9. “Old
Style”
Vaccines
Grow
.
.
.
and
use
whole
pathogen

10. The
focus
of
our
work
Can
we
make
vaccines
beJer/faster
BeOer
understanding
of
vaccine
MOA
Whole
(live/
killed)
vaccines
Subunit
vaccines
(Flu,
Hepa<<s
B,
HPV
vaccines,
for
example)
Genome-­‐
Derived,
Epitope
Driven
(GD-­‐ED)
Vaccines
Improve
vaccine
safety
and
efficacy
Accelerate
Vaccine
Design
hOp://bit.ly/EpiPubs
10

11. iVAX
Vaccine
Design
Toolkit

12. Why?
New
Vaccines
Needed
• For Example:
– HIV
– HCV
– Malaria
– Universal Influenza Vaccine
– Vaccines against Cancer
– Vaccines for immunotherapy of AI
– Vaccines for diseases affecting food animals

13. Why?
Unacceptable
Delays
• For Example: Pandemic influenza 2009
– Traditional flu vaccine production methods
require large lead time
– 20 weeks to first vaccine dose
– “Pandemic” influenza had already peaked by
the time the first shots were being delivered.
– Vaccine manufacturing failed the test.
– Is H7N9 the next pandemic? If so, we are
worried. . .

14. Emergent
H7N9
disease
in
China
hOp://bit.ly/EpiPubs
14

15. Spread
to
Beijing
on
4/13/13
.
.
.
Spread
to
Hong
Kong
on
12/6/
13
15

16. Markedly
Increased
ac.vity
in
late
2013
and
early
2014!
hOp://bit.ly/EpiPubs
16

17. Con.nuing
Expansion
of
H7N9
First
confirmed
cases
occurred
in
Shanghai
(3/30/13)
but
case
ac<vity
rapidly
increased
in
Zheijang
and
Jiangsu
provinces
shortly
aier.
Now,
we
have
a
problem!
hOp://bit.ly/EpiPubs
17
Image
credit
to
VDU
and
Dr.
Ian
M
Mackay
hOp://www.uq.edu.au/vdu/VDUInfluenza_H7N9.htm

18. Ci.es
that
are
one
stop
from
H7N9
An
es<mated
70%
of
the
world
popula<on
resides
within
two
hours’
travel
<me
of
des<na<on
airports
(calculated
using
gridded
popula<on-­‐density
maps
and
a
data
set
of
global
travel
<mes,
map
supplied
by
A.
J.
Tatem,
Z.
Huang
and
S.
I.
Hay
(2013).

19. H7N9
Morbidity
and
Mortality
Quick
numbers...
• Total
confirmed
human
cases
of
influenza
A
virus
H7N9:
>
200
•
Total
deaths
aOributed
to
infec<on
with
influenza
A
virus
H7N9:
>
50
•
Case
Fatality
Rate
(CFR):
29%
(current)
•
Average
<me
from
illness
onset
to
first
confirma<on
of
H7N9
(days):
<10
•
Median
age
of
the
H7N9-­‐confirmed
cases
(including
deaths;
years):
63
•
Males:
71%
of
cases,
74%
of
deaths
•
Younger
pa<ents
are
recovering
.
.
.
hOp://pandemicinforma<onnews.blogspot.com
hOp://www.uq.edu.au/vdu/VDUInfluenza_H7N9.htm
19

20. Virus
Transmission
Mechanism
–
source
is
s.ll
at
large
• Human
to
human
transmission
has
not
been
proved
(or
disproved)
many
cases
show
uninfected
family
members
• Poultry
iden<fied
as
poten<al
natural
host
and
H7N9
samples
were
found
in
poultry
market
environment
in
Shanghai.
However
not
many
poultry
vendors
infected
and
many
cases
have
no
indica<on
of
poultry
exposure
hOp://bit.ly/EpiPubs
Image
credit
to
VDU
and
Dr.
Ian
M
Mackay
hOp://
20
www.uq.edu.au/vdu/VDUInfluenza_H7N9.htm

21. Distribu.on
of
Cases
This
picture
shows
the
geographically
wide
distribu<on
of
flu
cases
-­‐
sugges<ng
widespread
distribu<on
of
the
virus
rather
than
a
point
outbreak.
hOp://bit.ly/EpiPubs
21

22. Why
are
immunoinforma.cs
tools
important
in
this
sedng?
• Immunoinforma<cs
predicted
low
immunogenicity
of
‘cri<cal
an<gen’
H7
HA
• hOp://bit.ly/H7N9_2013

23. (reminder)
Flu
Vaccine
–
HA
protein
Ian
Mackey
hOp://www.uq.edu.au/vduVDUInfluenza_H7N9.htm
hOp://bit.ly/EpiPubs
23

24. What
Can
We
Learn
About
H7N9?
HA
(hemagglu<nin)
is
the
‘Cri<cal
An<gen’
used
for
Flu
vaccines,
especially
recombinant
vaccines
–
–
which
are
currently
in
produc*on.
hOp://bit.ly/EpiPubs
24

25. H7N9
is
a
unique
virus
• Low
conserva<on
of
HA,
NA
surface
proteins
is
not
surprising
• Internal
proteins
are
more
conserved
hOp://bit.ly/EpiPubs
25

26. New
H7N9
Flu
is
Predicted
to
be
80
POORLY
IMMUNOGENIC
Thrombopoietin
70
-
60
-
-
50
-
-
40
-
HA
A/California/07/2009
(H1N1)
Tetanus Toxin
-
30
-
Influenza-HA
HA
A/Victoria/361/2011
(H3N2)
-
20
-
-
10
-
-
00
-
-
-10
-
-
-20
-
IgG FC Region
-
-30
-
Fibrinogen-Alpha
-
-40
-
-
-50
-
-
-60
-
-
-70
-
-
-80
H7
HA
Immunogenic
Poten.al
-
Human EPO
EBV-BKRF3
HA
A/Texas/50/2012
(H3N2)
Albumin
Follitropin-Beta
Random
Expecta.on
HA
A/chicken/Italy/13474/1999
(H7N1)
.
.
.
.
.
.
.
.
.
-­‐6.23
HA
A/Shanghai/1/2013
(H7N9)
.
.
.
.
.
.
.
..
.
.
.
.
.
.
.
-­‐8.11
HA
A/mallard/Netherlands/09/2005
(H7N7)
.
.
.
.
.
.
-­‐8.63
gB-2 (EPX Score: -24.56)
HA
A/mallard/Netherlands/12/2000
(H7N3)
..
.
.
.
.
.-­‐9.91
hOp://bit.ly/EpiPubs

27. Why
are
immunoinforma.cs
tools
important
in
this
sedng?
• Immunoinforma<cs
predicted
low
immunogenicity
of
‘cri<cal
an<gen’
H7
HA
• Vaccine
was
developed
but
is
low
immunogenicity
as
predicted.
hOp://bit.ly/H7N9_NovaVax

28. Unadjuvanted Influenza
Vaccine Effectiveness

29. Why
are
immunoinforma.cs
tools
important
in
this
sedng?
.
.
.
Low
and
S predicted
• Immunoinforma<cs
low
.
.
.
low
immunogenicity
of
‘cri<cal
an<gen’
H7
HA
• Vaccine
was
developed
but
is
low
immunogenicity
as
predicted
• Sero-­‐conversion
is
delayed,
diminished
in
pa<ents
infected
with
H7N9.
hOp://bit.ly/H7N9_Serology

30. Why
are
immunoinforma.cs
tools
important
in
this
sedng?
• Immunoinforma<cs
predicted
low
immunogenicity
of
‘cri<cal
an<gen’
H7
HA
• Vaccine
was
developed
but
is
low
immunogenicity
as
predicted
• Sero-­‐conversion
is
delayed,
diminished
in
pa<ents
infected
with
H7N9.
• New
vaccine
approaches
are
needed.
• .
.
.
Now
that
you
are
convinced,
let’s
talk
about
computa<onal
vaccine
design

31. Outline
• Why Computational Immunology
• Tools to Produce IDVs
– Antigen selection
– Vaccine design
– New concepts
• Case Studies
31

32. Computational Vaccinology:
Genomes-to-Vaccines

33. Selection of vaccine antigens is key
• Lots of Genomes now Published!
• On line tools for Pathogen Gene finding
(GLIMMER, ORPHEUS, GeneMark)
• Tools for selecting subsets of protein –
such as subcellular localization of
hypothetical proteins (PSORTb, CELLO,
Proteome Analyst)

34. Comparative Genomics Impacts
Vaccine Immunogen Selection
Strain 1
dispensable
genes
core
genome
Strain 2
pangenome
Strain 3
strain-­‐specific
genes

35. Immunome-Derived Vaccines . . .
Payload
Adjuvant
Delivery
Vehicle
.
.
.
Need
“informa*on”
=
T
cell
and
B
cell
epitopes
.
.
.
And
the
correct
“milieu”
=
delivery
vehicle,
adjuvants/TLR
ligands
“Fine
tune”
the
immune
response?
Vaccine
. . And there is ample evidence that this approach
to vaccine design produces protective immunity

36. Payload:
Predic.ng
Epitopes
that
Drive
Immune
Response
is
our
Exper.se
Protein
MHC II Pocket
Peptide
Epitope
HLA (Human MHC), are comprised of
peptide specific pockets
EpiMatrix predicts how well a peptide
sequence will bind to a specific pocket.
Binding is the prerequisite for
immunogenicity
8 class II HLA supertypes which taken
together incorporate 95% of human
populations (and pockets) worldwide.
Mature
APC
Each 9-mer/10-mer is analyzed for
binding potential to each of those 8
allele matrices.
The
EpiMatrix
Score
describes
the
binding
affinity
.
of
the
pep<de
sequence
to
the
HLA
complex
Southwood et al. J. Immunology 1998
Sturniolo et al. Nature Biotechnology, 1999
hOp://bit.ly/EpiPubs
37

37. How
do
we
measure
Immunogenicity?
Vaccine
an<gen
epitope
epitope
epitope
1
+
1
+
1
=
Response
Immune
response
to
a
vaccine
an<gen
can
be
predicted
by
measuring
the
number
of
T
cell
epitopes
contained
in
the
an<gen
with
immunoinforma<cs
tools.
hOp://bit.ly/EpiPubs

38. “Immunogenicity
Scale”
Immunogenic
proteins
Non
Immunogenic
proteins
hOp://bit.ly/EpiPubs
41

39. Easy
easy
to
deliver
as
pep<des
ClustiMer: Screen for Epitope Clusters
DRB1*0101
DRB1*0301
DRB1*0401
DRB1*0701
DRB1*0801
DRB1*1101
DRB1*1301
DRB1*1501
42

40. Conservatrix:
Overcome the Challenge of Variability
HIV
HCV
Influenza
43

41. Conservatrix Finds Conserved 9-mers
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
Conserved
epitope
Identifying the most conserved 9-mers allows for protection
against more strains with fewer epitopes
44

42. BlastiMer: Epitope Exclusion
Foreign
Self
In
all
of
our
vaccines
we
eliminate
cross-­‐reac<ve
epitopes
Confidential
45

43. Epitope
Cross-­‐Reac<vity
Impacts
Vaccine
Immunogen
Selec<on
Human
Poten.ally
detrimental
cross-­‐
reac.ve
epitopes
Human
Microbiome
Pathogen
Protec.ve
epitopes
Poten.ally
detrimental
cross-­‐
reac.ve
epitopes
hOp://bit.ly/EpiPubs
46

44. JanusMatrix
TCR
Each MHC ligand has two faces,
The MHC-binding face (aggretope),
and the TCR-interacting face (epitope)
The JanusMatrix algorithm searches for putative MHC
ligands which are identical at the contact residues but
may vary at the MHC-binding residues.
http://bit.ly/JanusMatrix
MHC
TCR
Find predicted 9-mer ligands with:
• Identical T cell-facing residues
• Same HLA allele and minimally
different MHC-facing residues
48
MHC/HLA

45. HCV
T
Effector
Epitopes
HCV_G1_NS2_732
HCV_G1_1941
HCV_G1_DEXDC_1246
HCV_G1_1605
HCV_G1_NS2_748
HCV_G1_NS4B_1769
HCV_G1_2941
HCV_G1_2440
HCV_G1_2898
HCV_G1_NS4B_1725
HCV_G1_ENV_359
HCV_G1_2485
HCV_G1_NS4B_1876
HCV_G1_NS4B_1910
HCV_G1_ENV_255
HCV_G1_2879
HCV_G1_NS4B_1790
HCV_G1_NS4b_1798
HCV_G1_2913
HCV_G1_NS5A_1988
HCV_G1_2840
HCV_G1_NS2_909

46. Treg-­‐like-­‐Epitope:
HCV
HC
V_
G
1_
NS
2_
79
4

47. Outline
• Why Computational Immunology
• Tools to Produce IDVs
– Antigen selection
– Vaccine design
• Case Studies
51

48. EpiAssembler Constructs
Immunogenic Consensus Sequences
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
CTRPNNTRK
Epi-Assembler
Immunogenic consensus

49. EpiAssembler: Core Epitope
STRAIN 01
STRAIN 02
STRAIN 03
STRAIN 04
STRAIN 05
STRAIN 06
STRAIN 07
STRAIN 08
STRAIN 09
STRAIN 10
STRAIN 11
STRAIN 12
STRAIN 13
STRAIN 14
STRAIN 15
STRAIN 16
STRAIN 17
STRAIN 18
STRAIN 19
STRAIN 20
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
X
A
X
A
X
A
X
A
X
A
A
A
A
A
A
X
A
X
A
A
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
P
P
P
X
P
P
P
X
P
P
P
X
P
X
P
P
X
P
X
P
K
K
K
K
K
K
K
K
K
R
x
K
K
K
K
K
K
K
K
K
K
V
V
X
V
V
X
V
V
X
V
V
V
V
X
V
V
V
X
V
V
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
Q
X
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
Q
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
A
A
A
A
A
A
A
A
A
A
A
A
A
A
X
A
A
A
A
A
K
K
K
K
K
X
K
K
K
K
K
X
K
K
K
K
K
K
K
X
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
X
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
W
W
W
W
W
W
X
W
W
W
W
W
W
W
W
W
W
W
W
W
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
X
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
X
F
F
F W A K H M W N F
I
I
I
X
I
I
I
I
X
I
I
I
I
I
I
I
I
I
I
I
S
S
S
S
S
S
S
S
S
X
S
S
S
S
S
X
S
S
S
S
X
G
G
X
G
G
G
G
X
G
G
G
G
X
G
G
G
G
X
G
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
L
L
X
L
L
X
L
L
X
L
L
X
L
L
L
L
X
L
L
L

50. EpiAssembler: Flanking Epitopes
STRAIN 01
STRAIN 02
STRAIN 03
STRAIN 04
STRAIN 05
STRAIN 06
STRAIN 07
STRAIN 08
STRAIN 09
STRAIN 10
STRAIN 11
STRAIN 12
STRAIN 13
STRAIN 14
STRAIN 15
STRAIN 16
STRAIN 17
STRAIN 18
STRAIN 19
STRAIN 20
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
X
A
X
A
X
A
X
A
X
A
A
A
A
A
A
X
A
X
A
A
A
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
P
P
P
X
P
P
P
X
P
P
P
X
P
X
P
P
X
P
X
P
K
K
K
K
K
K
K
K
K
R
x
K
K
K
K
K
K
K
K
K
K
V
V
X
V
V
X
V
V
X
V
V
V
V
X
V
V
V
X
V
V
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
Q
X
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
Q
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
A
A
A
A
A
A
A
A
A
A
A
A
A
A
X
A
A
A
A
A
K
K
K
K
K
X
K
K
K
K
K
X
K
K
K
K
K
K
K
X
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
X
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
W
W
W
W
W
W
X
W
W
W
W
W
W
W
W
W
W
W
W
W
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
X
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
X
F
F
I
I
I
X
I
I
I
I
X
I
I
I
I
I
I
I
I
I
I
I
S
S
S
S
S
S
S
S
S
X
S
S
S
S
S
X
S
S
S
S
X
G
G
X
G
G
G
G
X
G
G
G
G
X
G
G
G
G
X
G
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
F W A K H M W N F
M W N F I S G I Q
W P K V E Q F W A
W
P
K
V
E
Q
N
F
I
S
G
I
Q
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
L
L
X
L
L
X
L
L
X
L
L
X
L
L
L
L
X
L
L
L
Y
L

51. EpiAssembler:
Final Immunogenic Consensus Sequence
STRAIN 01
STRAIN 02
STRAIN 03
STRAIN 04
STRAIN 05
STRAIN 06
STRAIN 07
STRAIN 08
STRAIN 09
STRAIN 10
STRAIN 11
STRAIN 12
STRAIN 13
STRAIN 14
STRAIN 15
STRAIN 16
STRAIN 17
STRAIN 18
STRAIN 19
STRAIN 20
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
X
A
X
A
X
A
X
A
X
A
A
A
A
A
A
X
A
X
A
A
A
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
P
P
P
X
P
P
P
X
P
P
P
X
P
X
P
P
X
P
X
P
K
K
K
K
K
K
K
K
K
R
x
K
K
K
K
K
K
K
K
K
K
V
V
X
V
V
X
V
V
X
V
V
V
V
X
V
V
V
X
V
V
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
Q
X
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
Q
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
W
A
A
A
A
A
A
A
A
A
A
A
A
A
A
X
A
A
A
A
A
K
K
K
K
K
X
K
K
K
K
K
X
K
K
K
K
K
K
K
X
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
X
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
W
W
W
W
W
W
X
W
W
W
W
W
W
W
W
W
W
W
W
W
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
X
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
X
F
F
I
I
I
X
I
I
I
I
X
I
I
I
I
I
I
I
I
I
I
I
S
S
S
S
S
S
S
S
S
X
S
S
S
S
S
X
S
S
S
S
X
G
G
X
G
G
G
G
X
G
G
G
G
X
G
G
G
G
X
G
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
Q
Q
Q
Q
Q
Q
Q
Q
X
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
F W A K H M W N F
M W N F I S G I Q
W P K V E Q F W A
W
P
K
V
E
Q
N
F
I
S
G
I
Q
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
L
L
X
L
L
X
L
L
X
L
L
X
L
L
L
L
X
L
L
L
Y
L
Q A S W P K V E Q F W A K H M W N F I S G I Q Y L

52. VaxCAD Identifies and
Eliminates Junctional Epitopes
VaxCAD will identify junctional epitopes and rearrange chosen epitopes to reduce
junctional epitope formation

53. -10
Epitope Cluster Score
Junctional Cluster Score
20
10
0
Peptides in Default order in construct HP_IIB
50
40
-10
HP4117
HP4061
HP4181
HP4111
HP4018
HP4070
HP4060
HP4157
HP4065
HP4001
HP4193
HP4034
HP4068
HP4168
HP4160
HP4175
HP4127
HP4126
HP4007
HP4154
HP4164
HP4119
HP4100
HP4120
HP4179
30
EpiMatrix Cluster Score
50
HP4117
HP4179
HP4007
HP4111
HP4018
HP4070
HP4034
HP4193
HP4065
HP4181
HP4157
HP4060
HP4068
HP4164
HP4160
HP4175
HP4127
HP4120
HP4126
HP4154
HP4168
HP4119
HP4100
HP4001
HP4061
EpiMatrix Cluster Score
VaxCAD Example
Epitope Cluster Score
Junctional Cluster Score
40
30
20
10
0
Peptides in Optimized order in construct HP_IIB
57

54. Multi-Epitope Gene Design
Intended Protein Product: Many epitopes strung together in a “String-of-Beads”
DNA insert
DNA
Vector
Protein
product
(folded)
58

55. Immunogenic Consensus Sequence
Formulations
DNA
–
chain
of
epitopes,
or
pep<de
in
liposomes
ICS-­‐op<mized
whole
proteins
ICS-­‐op<mized
proteins
in
VLP

56. In Vivo Model for Validation:
HLA Transgenic Mice






HLA A2
HLA B7
HLA A2/DR1
HLA DR2
HLA DR3
HLA DR4

57. Outline
• Why Computational Immunology
• Tools to Produce IDVs
• Case Studies
– Tularemia
– Smallpox
– H. pylori
– VEEV (multi-pathogen vaccine)
– Influenza
61

58. Current
Vaccine
Design
Pipeline
Burk/Tuly/
MP
Epitope
Discovery
Epitope
Validation
Construct
Design
Immunogenicity
Animal Model
Validation
Epitope
Discovery
Epitope
Validation
Construct
Design
Immunogenicity
Animal Model
Validation
Tularemia
Epitope
Discovery
Epitope
Validation
Construct
Design
Immunogenicity
Animal Model
Validation
Smallpox
Epitope
Discovery
Epitope
Validation
Construct
Design
Immunogenicity
Animal Model
Validation
H. pylori
Epitope
Discovery
Epitope
Validation
Construct
Design
Immunogenicity
Animal Model
Validation
VEEV
Epitope
Discovery
Epitope
Validation
Construct
Design
Immunogenicity
Animal Model
Validation
Influenza
Epitope
Discovery
Epitope
Validation
Construct
Design
Immunogenicity
Animal Model
Validation
HIV/TB
62

59. GDV
Approach
Applied
to
F.
tularensis
In 24 months:
• Took one genome
• Mapped class I + Class II
• Selected 165 epitopes
• Confirmed in human
• Cloned into vaccine
• Performed Challenge studies. . .
McMurry
JA,
Gregory
SH,
Moise
L,
Rivera
DS,
Buus
S,
and
De
Groot
AS.
Diversity
of
Francisella
tularensis
Schu4
an<gens
recognized
by
T
lymphocytes
aier
natural
infec<ons
in
humans:
Iden<fica<on
of
candidate
epitopes
for
inclusion
in
a
ra<onally
designed
tularemia
vaccine.
Vaccine
2007
Apr
20;25(16):3179-­‐91.
63

60. High
Responder
Frequency
to
Class
II
Epitopes
in
Pa.ents
with
Prior
Exposure
22/25
pep<des;
Average
response
to
the
pool
was
over
1,000
gamma
producing
cells
per
million
above
background.
Percent
of
subjects
responding
by
IFN
gamma
ELISpot
Significant
Spot
Forming
Cells
averaged
across
subjects
64

61. TulyVax:
6
epitope
in
LVS
Challenge
Strain

62. IFN-g SFC/10^6 splenocytes
over background
TulyVax
Immunogenicity
in
HLA
Tg
Epitope-­‐specific
IFNγ
Response
950 300
Placebo-immunized
250
900 -
FT_II_v1-immunized
200
150
100
50
Schu4 peptides
with perfect LVS match
Schu4 peptides
with partial LVS match
3025
3024
3023
3007
3019
3015
3003
3001
F176
F102
3018
3017
3005
3004
0
Schu4 peptides
without LVS match
Nearly identical immunogenicity profile observed in HLA DR3 mouse
immunizations performed in collaboration with Dr. Terry Wu (UNM), illustrating
broad reactivity of immunoinformatic predicted epitopes.

63. TulyVax Efficacy
100%
TuliVax Immunized Mice
Placebo Recipient Mice
Percent Survival
80%
60%
57%
Rapidity:
from
genome
to
candidate
vaccine
in
24
months
.
.
.
40%
Efficacy:
14
epitope
vaccine
protects
against
live
challenge
20%
0%
0%
0
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21
Days after lethal bacterial challenge
14
epitopes:
T
cell-­‐epitope-­‐immunized
mice
were
protected
against
live
challenge
with
tularemia.
Placebo-­‐recipient
mice
died
within
10
days.
McMurry et al. Vaccine 2007;25:3179-91 and Gregory et al. Vaccine 2009 27:5299-306

64. Immunome-Derived Smallpox Vaccine:
VennVax
vaccinia
smallpox
Immunogenic
Epitopes
Vaccine
Shared
Immunogenic
Epitopes

65. VennVax Class II Epitopes are
Antigenic in Dryvax Vaccinees
20
88%
of
predicted
T
cell
epitopes
confirmed
in
vitro
using
hu
PBMC
Moise et al. Vaccine. 2009 27:6471-9

66. VennVax Immunization
in HLA DR3 Transgenic Mice
Immunizations
Days 0, 14, 28, 42
1. epitope DNA vaccine prime (IM)
2. epitope peptide boost (IN)
Moise L et al. Vaccine. 2011;29:501-11
Immunogenicity
Day 56
Challenge
Day 65

67. Survival
of
VennVax-­‐Vaccinated
Mice
Aqer
Aerosol
Challenge
100%
survival
of
Vaccinated
mice
vs.
17%
of
placebo
100
90
Percent Survival
80
Placebo
70
Vaccinated
60
50
40
30
20
10
0
DNA
00
100
boost
DNA
520
boost
Challenge
10 40
15
60
Day Post Immunization
17%
20
80
25
73
Moise et al. Vaccine. 2011; 29:501-11

68. Protection Without
Vaccine-Induced Antibodies
3
Pre-challenge Placebo
Pre-challenge Vaccine
2.5
Post-challenge Placebo
Post-challenge Vaccine
OD 490
2
1.5
Post-challenge
1
0.5
Pre-challenge
0
100
200
400
800
1600
1/Dilution Factor
3200
6400
12800

69. Therapeutic H. pylori Vaccination
Week 0
Week 6
Week 12-19
H. pylori
SS1
H. pylori SS1 lysate IN
H. pylori
SS1
Week 51
1. epitope DNA vaccine prime IN
2. epitope peptide boost IN
IFN-gamma
and IL-4 ELISpot
H. pylori
SS1
1. epitope DNA vaccine prime IM
2. epitope peptide boost IN
Histology
H. pylori
SS1
1. control DNA prime IN
2. control peptide boost IN

70. HelicoVax: Broad Epitope Recognition
IFN-gamma Secretion in Response to Splenocyte Restimulation following immunization
Average Helico-Vax
Average SS1
600
500
400
300
200
100
SS1 (whole lysate-immunized mice) recognized few epitopes (white bars);
HelicoVax-immunized mice recognized 45 of 50 (dark bars). 45/50 were immunogenic.
ConA
HP POO L 6
HP POO L 5
HP POO L 4
HP 4179
HP 4175
HP 4164
HP 4160
HP 4157
HP 4154
HP 4127
HP 4120
HP 4119
HP 4117
HP 4111
HP 4070
HP 4068
HP 4060
HP 4018
HP POO L 3
HP POO L 2
HP POO L 1
HP 4199
HP 4197
HP 4189
HP 4174
HP 4165
HP 4156
HP 4153
HP 4152
HP 4077
HP 4071
HP 4067
HP 4055
HP 4054
HP 4040
HP 4032
HP 4029
0
HP 4009
SFC/10^6 over background
700

71. HelicoVax Eradicates H. pylori Infection
***
P<0.001
**
P<0.01
***
P<0.001
800
600
H. pylori qPCR
(SSA/GAPDH)
180
160
140
120
This result accomplished in just over 24 months . . .
100
80
60
40
20
0
Lysate
pVAX
DNA IM
DNA IN
Moss et al, Vaccine 2011;29:2085-91

72. VEEV IDV Development:
Comparison with Whole Antigen Vaccine
Two Whole Gene Constructs
– Ebola Zaire GP
– VEEV 26S*
– subcloned into pWRG-7077
VS.
One Multi-Epitope Construct
– Ebola Zaire/Sudan GP epitopes
– VEEV 26S epitopes
– subcloned into pWRG-7077
*Dupuy LC, Richards MJ, Ellefsen B, Chau L, Luxembourg A, Hannaman D, Livingston BD,
Schmaljohn CS. A DNA Vaccine for Venezuelan Equine Encephalitis Virus Delivered by
Intramuscular Electro-poration Elicits High Levels of Neutralizing Antibodies in Multiple
Animal Models and Provides Protective Immunity to Mice and Nonhuman Primates. Clin
Vaccine Immunol. 2011 Mar 30.

73. IFNγ ELISpot responses to
VEEV peptide pools
VEEV E1
VEEV E2

74. VEEV IDV Elicits Antibody Response
USAMRIID DR3 Mouse Study
VEEV Challenge Group ELISA
Day 56 Serum Samples
5
Log10 Titer
4
3
2
1
0
Neg Con Arm Pos Con Arm Vaccine Arm
Whole Antigen Epitope-Driven
Negative
Control
Vaccine
Vaccine

75. VEEV IDV Protects
Against Lethal Challenge
100
90
80
70
60
50
40
30
20
10
0
USAMRIID DR3 Mouse Study
VEEV Challenge Weights
% Mean Starting Weight
Percent survival
USAMRIID DR3 Mouse Study
VEEV Challenge Survival
0
5
10
Days postchallenge
Neg Con Arm
100
Pos Con Arm
Vaccine Arm
90
Neg Con Control
Negative Arm
Pos Con Arm
Whole Antigen
Epitope-Driven
Vaccine Arm
80
70
60
50
Vaccine
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Days Postchallenge

76. What Drives Protection?
T
helper
Epitopes
B
cell
epitopes
Other?
CTL?
Th2?
Negative
Control
Whole Antigen
Vaccine
Subset of Th epitopes
stimulate IFNγ secretion"
"
Combination of immunogenic
Th epitopes that overlap B cell
epitopes???"
"
Contribution from other Th
epitopes (stimulate other
cytokines) that overlap with Bcell epitopes"
"
"
"
Th epitopes that stimulate
different subpopulations"
"
Epitope-Driven
"
Vaccine
"
What is clear: that whole Ag is
not necessary for protection"

77. T
cells
=
Immune
System
Body
Armor
T
cell
response
cannot
prevent
Infec<on
but
.
.
.
T
cell
response
can
arm
against
Disease

78. The "New" Flu
(H1N1 2009 California)
hOp://bit.ly/EpiPubs
84

79. 2009
Worry:
CDC
–
No
Cross-­‐reac.ve
Ab
•
•
•
Preliminary
studies
of
individuals
showed
that
an<bodies
induced
by
seasonal
influenza
vaccina<on
were
not
cross-­‐reac<ve
with
novel
H1N1.
What
if
the
T
cell
epitopes
were
cross-­‐reac<ve?
Would
that
help?
(Note
that
the
situa<on
is
very
similar
for
H7N9
–
no
cross-­‐reac<ve
an<body).
Centers
for
Disease
Control
and
Preven<on.
Serum
an<body
response
to
a
novel
influenza
A
(H1N1)
virus
aier
vaccina<on
with
seasonal
influenza
vaccine.
MMWR
Morb
Mortal
Wkly
Rep
2009;58(19):521–4.
hOp://bit.ly/EpiPubs
85

80. 2009
H1N1
contains
conserved
epitope
Sequences
–
Predicted
Cross
Protec.on
Immunogenic
T cell
epitopes
Enough
Cross-­‐
protec<ve
Epitopes
that
Seasonal
Flu
vaccina<on
or
exposure
may
protect
Conserved
T-Cell
Epitopes
hOp://bit.ly/EpiPubs
86
De Groot et al. Vaccine 2009;27:5740-7

81. EpiVax
Predicted
Cross-­‐Protec.on
hOp://www.ncbi.nlm.nih.gov/pubmed/19660593
hOp://bit.ly/EpiPubs
87

82. Immuniza.on
with
FluVax
cross-­‐conserved
T
cell
epitopes
decreases
lung
viral
load
10
8
1.00E+08
P=
0.002
PFU/ml
*
10
1.00E+07
7
10
A
handful
of
conserved
epitopes
protected
against
disease
6
1.00E+06
Placebo
FluVax
2009
Placebo
2
Days
hOp://bit.ly/H1N1_DR3_2013
hOp://bit.ly/Moise_Universal_Flu
Post-­‐Infec.on
hOp://bit.ly/EpiPubs
FluVax
2009
4
Days
90

83. H1N1
Conclusions
• This work recapitulates other projects already completed:
Complete protection using ONLY T cell epitopes (H. pylori,
Tularemia, VennVax)
• Results of our published studies demonstrate that conserved
T cell epitope sequences, important to viral fitness, also may
be immunologically significant contributors to protection
against newly emerging influenza strains.
• The conserved epitope approach promises to answer the
need for prompt preparedness and delivery of a safe,
efficacious vaccine without requiring a new vaccine for every
emergent influenza strain.
hOp://bit.ly/H1N1_DR3_2013
hOp://bit.ly/Moise_Universal_Flu
hOp://bit.ly/EpiPubs
91

84. What about H7N9?
hOp://bit.ly/EpiPubs
92

85. What
Can
We
Learn
About
H7N9?
Epitopes
Novel
or
Conserved?
H7N9
Circula<ng
Flu
As
it
turns
out
-­‐
-­‐
-­‐
Very
Poor
Cross-­‐Conserva<on
–
Only
within
Internal
Proteins
hOp://bit.ly/EpiPubs
93

86. New
H7N9
Flu
is
Predicted
to
be
80
POORLY
IMMUNOGENIC
Thrombopoietin
70
-
60
-
-
50
-
-
40
-
HA
A/California/07/2009
(H1N1)
Tetanus Toxin
-
30
-
Influenza-HA
HA
A/Victoria/361/2011
(H3N2)
-
20
-
-
10
-
-
00
-
-
-10
-
-
-20
-
IgG FC Region
-
-30
-
Fibrinogen-Alpha
-
-40
-
-
-50
-
-
-60
-
-
-70
-
-
-80
-
H7
HA
Immunogenic
Poten.al
Human EPO
EBV-BKRF3
HA
A/Texas/50/2012
(H3N2)
Albumin
Follitropin-Beta
hOp://bit.ly/H7N9_HVandI
Random
Expecta.on
HA
A/chicken/Italy/13474/1999
(H7N1)
.
.
.
.
.
.
.
.
.
-­‐6.23
HA
A/Shanghai/1/2013
(H7N9)
.
.
.
.
.
.
.
..
.
.
.
.
.
.
.
-­‐8.11
HA
A/mallard/Netherlands/09/2005
(H7N7)
.
.
.
.
.
.
-­‐8.63
gB-2 (EPX Score: -24.56)
HA
A/mallard/Netherlands/12/2000
(H7N3)
..
.
.
.
.
.-­‐9.91

87. This
is
a
unique
virus
• Low
conserva<on
of
HA,
NA
surface
proteins
is
not
surprising
• Internal
proteins
are
more
conserved
• And
–
HA
is
has
unusually
low
immunogenicity
• Could
that
explain
why
infec<on
is
widespread?
• Difficult
to
make
an<bodies
to
the
HA
hOp://bit.ly/EpiPubs
96

88. Differen<al
Cross-­‐reac<vity
with
the
human
genome-­‐
significance?
New
and
unpublished:
The
“Classic
Epitope”
Is
much
more
cross-­‐conserve
with
the
human
genome
in
the
case
of
H7N9.
H1N1
H7N9
hOp://bit.ly/EpiPubs
97

89. This
is
a
unique
virus
• Unusually
low
immunogenicity
• Cross-­‐reac<vity
with
human
genome
• How
do
we
overcome
this
problem?
hOp://bit.ly/EpiPubs
98

90. hOp://bit.ly/EpiPubs
99

91. Immunoinforma.cs
Toolkit
• EpiMatrix – maps T cell epitopes
• ClustiMer - Promiscuous / Supertype Epitopes
Seamless
Vaccine
• BlastiMer - Avoiding “self” - autoimmunity
Design
• Conservatrix – Identifies Conserved Segments
Integrated
toolkit
is
• EpiAssembler - Immunogenic Consensus Sequences
unique
to
iVax
• Aggregatrix – Optimizing the coverage of vaccines
• VaxCAD - Processing and Assembly
hOp://bit.ly/EpiPubs
100

92. FastVax: Vaccines on demand
• High throughput computing
• Immunoinformatics
• Vaccine design algorithms
Rapid
deployment
when
genome
sequence
is
in
hand
• Vaccine Production
• Delivery device
• Animal safety/tox/immunogenicity/validation
• Deployment by established distribution systems
Pilot
program
Funded
by
DARPA
Prebuilt
hOp://bit.ly/EpiPubs
101

93. 20
hours
-­‐
April
05
–
April
06
2013
Extremely
Rapid
H7N9
Vaccine
Design
April
05,
2013:
Obtain
H7N9
Sequences
(4
human-­‐sourced;
GISAID)
Obtain
all
available
H7N9
sequences
EpiMatrix
Analysis:
Iden<fica<on
of
H7N9
Class
I
and
Class
II
Epitopes
Compare
with
previous
epitopes
(IEDB)
And
other
H7N9
strains;
create
final
list
20
hours
(Logged).
101
H7N9
ICS*
Class
II
Epitopes
+
586
Class
I
Epitopes
Eliminate
Epitopes
highly
conserved
with
Human
Design
vaccine:
12
hours
(Logged).
April
06,
2013:
H7N9
Vaccine:
Two
Constructs,
Class
I
and
Class
II
hOp://bit.ly/EpiPubs
102

94. Gedng
FastVax
into
the
clinic:
4
Steps
Emergency
use
authoriza<on
1.
In
silico
Design
2.
Produc<on
and
Packaging
3.
Clinical
Trial
(correlates
of
immunity)
4.
Deployment
Regulatory
Agency
approval
As
Currently
Proposed
with
Genome-­‐derived
Epitope-­‐driven
Influenza
Vaccines
(R21
/
NIAID
/
NIH)
hOp://bit.ly/EpiPubs
104

95. H7N9
at
EpiVax
• String-­‐of-­‐epitopes
DNA
vaccine
(Doug
Lowrie)
• String-­‐of-­‐epitopes
Phage
vaccine
(Ft.
Detrick)
• Op<mized
HA
(fix
epitopes)
recombinant
(TBD?)
• Op<mized
HA
+
epitope
string
VLP
(Ted
Ross)
• Collabora<on
with
NIID/Japan
–
in
progress
EpiVax
Contacts:
Anthony
Marcello,
BDA,
amarcello@epivax.com
Anne
S.
De
Groot
CEO/CSO
annied@epivax.com
105

96. H7N9 Delivery vehicles
DNA
–
chain
of
epitopes,
or
pep<de
in
liposomes
ICS-­‐op<mized
whole
proteins
ICS-­‐op<mized
proteins
in
VLP

97. And
.
.
.
Cancer,
Allergy
and
Autoimmune
Disease?
•
Payload+Adjuvant+
Delivery
vehicle
=
Vaccine
• Cancer
Vax
=
Epitopes
+
Adjuvant
+
?
• Tregitope
=
Novel
“adjuvant”
that
induces
tolerance
• Allergy
Vax
=
Epitopes
+Tregitope+Delivery
vehicle
• Autoimmunity
Vax=
AutoAg+Tregitope+Del.
vehicle
107

98. Outline
• Why Computational Immunology
• Tools to Produce IDVs
– Antigen selection
– Vaccine design
– New concepts
• Case Studies
• . . . Questions?
108

99. EpiVax:
Four
Core
Strengths
Contact:
Anthony
Marcello,
BDA,
amarcello@epivax.com
Confiden<al