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Improving the specificity and precision of PANSS factors:
One approach to facilitate development of novel treatments in
schizophrenia
Seth C. Hopkins, PhDExecutive Director Translational MedicineSunovion Pharmaceuticals
1
• Industry-sponsored RCTs generate large clinical databases – which can be better examined to advance the field and
improve public health
Use of Clinical Trial Databases to Improve RCT Efficiency
tens of thousands of unique research subjects • acute studies
• long-term safety studies
• different compounds• range of doses
volume of clinical observations
2
• The potential for clinically-meaningful differentiation is an incentive for innovation, especially for a novel MoA
How to apply clinical trial databases to facilitate drug development, including drugs with novel mechanisms of action?
more accurate/specific descriptions of treatment effect across sub-domains of schizophrenia symptoms?
better understanding of effects in stable/specific patient types?
subsub-domains
subpopulations
sub-populations
3
Historical view of the accumulated database in schizophrenia drug development
Drug launches for schizophrenia
year of launchThompson Reuters | Integrity Database
19501960197019801990200020102020
Chlorpromazine Promazine
ThioridazineHaloperidolClopenthixol
ThiothixeneSulpirideSpiperonePimozide
ClozapineFluphenazine
Carpipramine Bromperidol
ZotepineAmisulpride
LevosulpirideEmonapride
RisperidoneOlanzapineQuetiapine
ZiprasidonePerospironeAripiprazole
SertindolePaliperidone
BlonanserinAsenapineIloperidoneLurasidoneBrexpiprazole
CariprazineCum
ulative drug launches (world-w
ide) for schizophrenia
year of launch
Dopamine D2Serotonin 5-HT2A
4
The cumulative number of research subjects is large
ClinTrials.orgindustry-sponsored | schizophrenia | phase 2 or phase 3 | randomized, placebo-controlled | primary endpoint efficacy
Dopamine D2 based mechanism
Subj
ects
enr
olle
d(c
umul
ativ
e) cumulative number of schizophrenia subjects enrolled in RCTs for industry-sponsored drug development programs (ClinTrials.org)
5
ClinTrials.org | industry-sponsored | schizophrenia | phase 2 or phase 3 |randomized, placebo-controlled
Total investment in clinical development for new schizophrenia compounds is large
all others
drug-development RCTs in schizophrenia (start dates)
Dopamine D2 based mechanism
Subj
ects
enr
olle
d(c
umul
ativ
e)
6
ClinTrials.org | industry-sponsored | schizophrenia | phase 2 or phase 3 |randomized, placebo-controlled
Total investment in compounds with novel mechanisms is also large
all others all others
Dopamine D2 based mechanism non-D2 mechanisms
Subj
ects
enr
olle
d(c
umul
ativ
e)
7
ClinTrials.org | industry-sponsored | schizophrenia | phase 2 or phase 3 |randomized, placebo-controlled
The success of compounds with non-D2 MoA’s has been poor relative to D2 compounds
all others all others
launches
Dopamine D2 based mechanism non-D2 mechanisms
Subj
ects
enr
olle
d(c
umul
ativ
e)
8
ClinTrials.org | industry-sponsored | schizophrenia | phase 2 or phase 3 |randomized, placebo-controlled
Development of compounds with non-D2 MoA’s has focused on unmet needs of Cognition and Negative Symptoms
Dopamine D2 based mechanism non-D2 mechanisms
all others all others
launches
PANSS totalCognition
Negative Symptoms
Relapse
RelapsePrimary Endpoints as portion of total enrolled subjects
PANSS total
Subj
ects
enr
olle
d(c
umul
ativ
e)
Drug development RCTs for new treatments in schizophrenia have incorporated new measurements of specific symptom domains
9
How to apply clinical trial databases to facilitate new treatments, including drugs with novel MoA’s?
Dopamine D2 based mechanism non-D2 mechanismsPANSS total
Cognition
Negative Symptoms
Relapse
Relapse
PANSS total
IMPROVEMEASUREMENTS
ACADEMIAPHARMA
NIMH/NIH
RDOC MATRICS
SCALES
Use the existing PANSS scale, to measure, with enhanced specificity, treatment effects across key symptom domains of schizophrenia
Drug development RCTs for new treatments in schizophrenia have incorporated new measurements of specified symptom domains
10
uncorrelatedscores UPSM factor scores
N=1,710 Sunovion dataset
acute schizophrenia, 6-weeks{lurasidone, placebo, olanzapine, quietiapine}
factor analysis of change-from item scoresretain score matrix coefficients
• (ORTHOGONAL) represent symptom change specific to each dimension
• (FACE VALID) corresponds to recognizable/established dimensions
• (APPLICABLE) UPSM can transform external PANSS data sets
UPSM
PANSS factors are correlatedCan we transform them to be more specific?
Uncorrelated PANSS Score Matrix (UPSM)
dom
ain
A
domain B
11
Pseudospecificity: A major confound in the assessment of efficacy in schizophrenia
SUNOVION DATA (N=1,710 patients from 5 placebo-controlled schizophrenia trials)Marder PANSS factor pos dis neg hos/exc anx/dep totPositive Symptoms 1Disorganized Thought 0.74 1Negative Symptoms 0.57 0.62 1Hostility/Excitement 0.64 0.59 0.43 1Anxiety/Depression 0.52 0.45 0.40 0.46 1PANSS Total 0.90 0.86 0.77 0.77 0.66 1
OTSUKA DATA (N=1,368 patients from 5 placebo-controlled schizophrenia trials)Marder PANSS factor pos dis neg hos/exc anx/dep totPositive Symptoms 1Disorganized Thought 0.73 1Negative Symptoms 0.59 0.67 1Hostility/Excitement 0.64 0.58 0.42 1Anxiety/Depression 0.58 0.51 0.49 0.48 1PANSS Total 0.89 0.87 0.81 0.75 0.71 1
TAKEDA DATA (N = 240 patients from 1 placebo-controlled schizophrenia trials 20 mg TK-063)Marder PANSS factor pos dis neg hos/exc anx/dep totPositive Symptoms 1Disorganized Thought 0.65 1Negative Symptoms 0.46 0.50 1Hostility/Excitement 0.46 0.41 0.23 1Anxiety/Depression 0.55 0.50 0.45 0.47 1PANSS Total 0.85 0.80 0.71 0.66 0.76 1
Correlations Among Marder PANSS Factor Scores (Week 6 Change from Baseline)
12
TAKEDA DATA (N = 240 patients from 1 placebo-controlled schizophrenia trials 20 mg TK-063)Transformed PANSS factors POS DIS NAA NDE HOS ANX DEPPOSITIVE 1DISORGANIZED 0.07 1NEG APATHY/AVOLITION 0.18 -0.07 1NEG DEFICIT OF EXPRESSION -0.02 -0.07 0.15 1HOSTILITY -0.01 -0.13 -0.15 -0.02 1ANXIETY 0.28 -0.01 0.24 -0.18 0.44 1DEPRESSION 0.29 -0.16 0.29 -0.06 0.09 0.36 1PANSS TOTAL SCORE 0.59 0.14 0.50 -0.23 0.38 0.61 0.65
UPSM transform reduces between‐factor correlations in endpoint PANSS factor change scores
SUNOVION DATA (N=1,710 patients from 5 placebo-controlled schizophrenia trials)Transformed PANSS factors POS DIS NAA NDE HOS ANX DEPPOSITIVE 1DISORGANIZED 0.20 1NEG APATHY/AVOLITION 0.10 0.08 1NEG DEFICIT OF EXPRESSION 0.04 0.12 0.22 1HOSTILITY 0.21 0.12 0.07 -0.02 1ANXIETY 0.09 0.04 -0.01 -0.08 0.13 1DEPRESSION 0.10 0.00 0.12 0.13 0.04 0.27 1PANSS TOTAL SCORE 0.60 0.45 0.45 0.36 0.53 0.45 0.46
OTSUKA DATA (N=1,368 patients from 5 placebo-controlled schizophrenia trials)Transformed PANSS factors POS DIS NAA NDE HOS ANX DEPPOSITIVE 1DISORGANIZED 0.17 1NEG APATHY/AVOLITION 0.12 0.12 1NEG DEFICIT OF EXPRESSION 0.03 0.22 0.37 1HOSTILITY 0.08 0.18 0.12 -0.04 1ANXIETY 0.06 0.12 0.05 -0.01 0.16 1DEPRESSION 0.21 0.08 0.26 0.28 0.07 0.27 1PANSS TOTAL SCORE 0.47 0.52 0.57 0.48 0.49 0.46 0.57
13
-0.9 -0.6 -0.3 0.0 -0.9 -0.6 -0.3 0.0
drug vs. placebo effect size ± 95%CI
worseningimprovement
POSITIVE
HOSTILITY
NEGATIVE
DISORGANIZED
DEPRESSION/ANXIETY
PANSS TOTAL TOTAL FACTOR SCORE
-0.38
-0.44
-0.32
-0.36
-0.33
-0.46
-0.35
-0.19
-0.22
-0.04
-0.27
-0.18
-0.14
-0.45
DEFICIT OF EXPRESSION
ANXIETY
DEPRESSION
APATHY/AVOLITION
worseningimprovement
MARDER PANSS FACTORS UPSM TRANSFORMED PANSS FACTORSoverlapping drug effects
Towards specificity in antipsychotic drug treatment effectsN=5 acute schizophrenia trials PANSS change from baseline, at Week 6 endpoint, lurasidone active doses vs. placebo
Hopkins et al. 2017 Schizophrenia Bulletin
subsub‐domains
more specificity
Attributions of specific treatment effects confounded by correlations among improvements in Marder PANSS Factor Scores
greater heterogeneity in effect size estimates across the sub-domains
14
Discussion Point: Treatment effects are separable among the dimensions of schizophrenia
If symptom dimensions can be separately identified and assessed even in the acute schizophrenia clinical trial setting...
...then therapeutics with novel efficacy profiles across the sub-dimensions of schizophrenia psychopathology can be evaluated
UPSM-transformation identified 2 PANSS-negative symptom sub-factors showing differential treatment effects, with larger effect sizes observed for the apathy/avolition sub-factor compared to the deficit of expression sub-factor
DRUG A DRUG B
subsub‐domains
15
Understanding of specificity within PANSS to advance the fieldand facilitate development of new treatments
more specific breakdown of total symptoms improvements according to the domains of most-prominent effects
Forest Forest Plots with specificity
• specificity among symptom sub-domains
subpopulations
sub-populations
Does an understanding of specificity of symptom change over time help to identify more-meaningful patient types?
Address issues of:• differentiation • dose-response• benefit/risk
Use during:• drug development
decisions• meta-analyses
Objective of this analysis direction:• examine failed/negative trials• test for differential treatment responses among types• develop “a priori” categories for future analysis plans of
novel MoA’s
16
are patient-types stable?do they persist post-baseline?
track response of patient-types post-baseline
PATIENT TYPES baselinePANSSbaselinePANSS
cluster(K-MEANS)
transform(UPSM)
Identified patient types at baseline who are prominent along specific UPSM factor scores
POS
HOS
DIS
ANX
DEP
NAA
NDE
subpopulations
sub-populations
PROMINENTLYPOSITIVE
POS
HOSTILE
DISORGANIZED
NEG
BASELINE
mean UPSMfactor scores
ANX DEP
train classifier(SVM)
post-baselinePANSS
post-baselinePANSS
post-baseline
PATIENT TYPES
apply classifier(SVM)
transform(UPSM)
17
Patient-types persist over time, even in the context of overall symptom (PANSS total) improvements
PROMINENTLYPOSITIVE
HOS
DIS
ANX
POS
HOS
DIS
ANX
DEP
NAA
NDE
NEG
DEP
PATIENT-TYPE PROMINENTLY POSITIVE
BASELINE SEQUENTIAL WEEKLY VISITS ENDPOINTN=1,710 subjects | 5 studies | acute schizophrenia RCTs
{lurasidone, placebo, olanzapine, quietiapine}
0 1 2 3 4 5 6
HOS
DIS
ANX
NEG
DEP
POS
DISCONTINUATION
Patient types persist over time and over treatment
POS
mean UPSMfactor scores
N=400
number of subjects
N=200
duration
Toward better definitions of patient-types within PANSS to better understand and characterize treatment response
Objectives of this analysis• examine failed/negative trials• test for differential treatment responses among types• develop “a priori” categories for future analysis plans of novel MoA’s
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• An understanding of the specificity of symptom change in PANSS ... can facilitate the evaluation of therapeutics with novel efficacy profiles across the sub-dimensions of schizophrenia psychopathology
Future directions in the use of clinical trial databases for improving RCT efficiency
subsub-domains
subpopulations
sub-populations
Towards collaborative analyses and shared research questions for our existing clinical trial databases
19