Transcript view slides - PFF Summit 2015

INTEGRATING BIOMARKERS IN CLINICAL
STUDIES TO AFFECT PATIENT CARE
FERNANDO J. MARTINEZ, MD, MS
TRANSLATIONAL SCIENCE: PROGRESS TOWARDS PERSONALIZED
MEDICINE FOR IPF - BIG DATA MEETS PATIENT CARE
NOVEMBER 13, 2015
This slide has been removed at the request of the
presenter because it contains unpublished data.
How can biomarkers be
used in drug development?
Use
Drug Development
Target validation
Demonstrate potential target plays biological
role
Early compound screening
Identifies most promising compounds
Pharmacodynamics assays
Determines drug activity/dose selection
Patientused
selection
Biomarkers
to confirm
the MOA ideally need to be
Surrogate endpoint
available at the initiation of
clinical development
(Phase I) in order to be
most useful*
Defines inclusion/exclusion criteria
Allows short-term outcome measures in
place of long-term primary endpoint
Michele
C & Ball J. Evaluation of biomarkers and surrogate endpoints
*Groves et al,
Quintiles
In chronic disease; 2010
This slide has been removed at the request of the
presenter because it contains unpublished data.
This slide has been removed at the request of the
presenter because it contains unpublished data.
This slide has been removed at the request of the
presenter because it contains unpublished data.
How can biomarkers be
used in drug development?
Biomarkers for patient
selection can be developed
prospectively with drug
and
biomarker
Use
Drug
Development
development occurring in
parallel,
or they canpotential
be
Target validation
Demonstrate
targetCan
playsinclude
biological
developed
Can include
role by effectively
pathway specific
playing “catch-up” at a
general prognostic
enrichment
later stage *
Early
compound screening
Identifies most promising compounds
markers
markers
*Groves et al, Quintiles
Pharmacodynamics assays Determines drug activity/dose selection
Patient selection
Defines inclusion/exclusion criteria
Surrogate endpoint
Allows short-term outcome measures in
place of long-term primary endpoint
Michele C & Ball J. Evaluation of biomarkers and surrogate endpoints
In chronic disease; 2010
Biomarker Enrichment Strategies:
Borrowing from Oncology
 Treatment targeting molecular pathways may
benefit only a subset of patients
 Treatment heterogeneity requires biomarker
development
 Multiple Phase III designs are available in this
setting
 The choice of trial design should be guided by
the strength of the biomarker’s credentials
Freidlin & Korn Nat Rev Clin Oncol 2014;
11:81-90
Trial Options for Biomarkers
with Varying Strength
Freidlin & Korn Nat Rev Clin Oncol 2014;
11:81-90
‘Fall-back’ Design for Biomarkers
With Weak Credentials
Freidlin & Korn Nat Rev Clin Oncol 2014;
11:81-90
Disease Progression in IPF is
Associated with Altered Lung Microbiome
Variable
Age (per 10 yrs)
Male gender
Smoking Status
FVC 10%
DLCO 10% increase
Desaturation <88%
GERD
Shannon Diversity Index
Streptococcus > 4%
Staphylococcus > 2%
Concordance Index
Parameter Estimate
-0.388
-0.059
0.174
0.286
-0.034
2.03
1.15
-0.629
2.375
1.59
SE
HR (95%CI)
0.36
0.68 (0.33,1.36)
0.45 0.94 (0.391,2.27)
0.35
1.19 (0.6,2.36)
0.16
1.33 (0.97,1.83)
0.25
0.97 (0.59,1.58)
0.58
7.59 (2.41,23.9)
0.49
3.16 (1.21,8.29)
0.24
0.53 (0.33,0.85)
0.63 10.75 (3.15,36.68)
0.55 4.89 (1.67,14.27)
0.766
P-value
0.28
0.89
0.62
0.076
0.89
<0.001*
0.019*
0.0087*
<0.001*
0.0037*
Han et al; Lancet Respir Med 2014; 2: 548-56
This slide has been removed at the request of the
presenter because it contains unpublished data.
This slide has been removed at the request of the
presenter because it contains unpublished data.
Co-trimoxazole decreases all cause
mortality in per protocol analysis in
181 fibrotic IIP (89% IPF)
Shulgina et al; Thorax 2013; 68: 155-62
CLEAN UP IPF
Fernando J. Martinez, M.D., M.S. (contact PI)
Weill Cornell Medical Center
University of Michigan Health System
Kevin Anstrom, PhD (co-PI)
Michael Durheim, MD (co-I)
Duke University
Imre Noth, MD (co-PI)
University of Chicago
Robert Kaner, MD (co-I)
Xiaoping Wu, MD (co-I)
Weill Cornell Medical Center
Kevin Flaherty, MD, MS (co-I)
University of Michigan Health System
Ganesh Raghu, MD (co-I)
University of Washington
What is CLEAN UP IPF hypothesis?
Our principal hypothesis is that
antimicrobial therapy in IPF
patients will improve clinical
outcomes
17
CLEAN UP IPF inclusion/exclusion
Inclusion
Exclusion
Age > 40
Local IPF diagnosis
Able to provide informed consent
Currently on regular antibiotic therapy
Antibiotic therapy contraindication
Pregnancy or planning pregnancy
CLEAN UP IPF additional
components
Included in current study
 Baseline genotyping
Proposed
 Bronchoscopic substudy
 Baseline PBMC genomic
 Microbiome analysis of
signature in subset
bronch, oral, poop
samples
 Circulating inflammatory
cell subtypes
Response segregated by pre-alert and
post-alert enrollment status
Martinez et al NEJM 2014; 370: 2093-101
This slide has been removed at the request of the
presenter because it contains unpublished data.
NAC effectiveness by TOLLIP genotype sets up
another opportunity for biomarker driven trial
Oldham et al AJRCCM Articles in press
Published on 02-September-2015 as
10.1164/rccm.201505-1010)C
How can biomarkers be
used in drug development?
Use
Drug Development
Target validation
Demonstrate potential target plays biological
role
Early compound screening
Identifies most promising compounds
Pharmacodynamics assays
Determines drug activity/dose selection
Patient selection
Defines inclusion/exclusion criteria
Surrogate endpoint
Allows short-term outcome measures in
place of long-term primary endpoint
Michele C & Ball J. Evaluation of biomarkers and surrogate endpoints
In chronic disease; 2010
This slide has been removed at the request of the
presenter because it contains unpublished data.
Biomarker Strategy for
Therapeutics in IPF Development
Target
Therapeutic
Biomarker
strategy
αvβ6
STX-100 mAb
TGF-β activity (pSMAD2 and
gene changes) in BAL
IL-2
Sirolimus
Change in peripheral blood
CXCR4+ fibrocytes
IL-4/IL-13
SAR156597 IL-4/IL-13
bispecific mAb (Sanofi)
Peripheral blood biomarkers
IL-13
QAX576 mAb
TBD
IL-13
Tralokinumab mAb
Peripheral blood biomarkers
LPA1
BMS-986202 mAb
TBD
CTGF (antagonist)
FG-3019 mAb
TBD
LOXL2 (antagonist)
GS6624
Prognostic value of baseline
level of LOXL-2in peripheral
blood
PDGF/FGF-2/VEGF
BIBF-1120
TBD
PI3K/mTor
GSK2126458
pAKT in plasma and BAL cells
Serum amyloid protein
PRM-151
Fibrocytes, IL-6, other peripheral
biomarkers
Carbon monoxide
Serum MMP7
Pirfenidone
-
Anti-inflammatory/anti-fibrotic
One final thought from the
PFF Summit….

In the first study, company researchers presented data suggesting that
Veracyte's molecular classifier, which is in development, has the
potential to accurately distinguish IPF from other ILDs without the need
for surgery… The classifier is being developed using whole-genome,
deep RNA sequencing and with training by histopathology “truth.” These
results reinforce previous findings*.
* Kim, SY. (June 2015). Classification of usual interstitial pneumonia in
patients with interstitial lung disease: assessment of a machine learning
approach using high-dimensional transcriptional data. Lancet Resp.
Med., 2015; 3(6): 473–482.
Veracyte press release
Integrating biomarkers in
clinical studies to affect patient care:
Conclusions
 Biomarkers have the potential to
– limit treatment heterogeneity
– identify new and highly promising therapeutic
targets
– enhance efficiency of future therapeutic
development
 Biological samples should be routinely collected in all
therapeutic trials
 Linking to molecular diagnostics may be optimal
 Companion diagnostic strategies should be
considered in future development