Improving the specificity and precision of PANSS factors:

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1 Improving the specificity and precision of PANSS factors: One approach to facilitate development of novel treatments in schizophrenia Seth C. Hopkins, PhD Executive Director Translational Medicine Sunovion Pharmaceuticals 1

2 Use of Clinical Trial Databases to Improve RCT Efficiency Industry-sponsored RCTs generate large clinical databases which can be better examined to advance the field and improve public health volume of clinical observations different compounds range of doses tens of thousands of unique research subjects acute studies long-term safety studies 2

3 How to apply clinical trial databases to facilitate drug development, including drugs with novel mechanisms of action? The potential for clinically-meaningful differentiation is an incentive for innovation, especially for a novel MoA subdomains subpopulations better understanding of effects in stable/specific patient types? more accurate/specific descriptions of treatment effect across sub-domains of schizophrenia symptoms? 3

4 Historical view of the accumulated database in schizophrenia drug development Drug launches for schizophrenia Serotonin 5-HT2A Dopamine D2 Cariprazine Brexpiprazole Lurasidone Iloperidone Asenapine Blonanserin Paliperidone Sertindole Aripiprazole Perospirone Ziprasidone Quetiapine Olanzapine Risperidone Emonapride Levosulpiride Amisulpride Zotepine Bromperidol Carpipramine Fluphenazine Clozapine Pimozide Spiperone Sulpiride Thiothixene Clopenthixol Haloperidol Thioridazine Promazine Chlorpromazine Cumulative drug launches (world-wide) for schizophrenia Thompson Reuters Integrity Database year of launch

5 The cumulative number of research subjects is large Dopamine D2 based mechanism Subjects enrolled (cumulative) cumulative number of schizophrenia subjects enrolled in RCTs for industry-sponsored drug development programs (ClinTrials.org) ClinTrials.org industry-sponsored schizophrenia phase 2 or phase 3 randomized, placebo-controlled primary endpoint efficacy 5

6 Total investment in clinical development for new schizophrenia compounds is large Dopamine D2 based mechanism Subjects enrolled (cumulative) all others drug-development RCTs in schizophrenia (start dates) ClinTrials.org industry-sponsored schizophrenia phase 2 or phase 3 randomized, placebo-controlled 6

7 Total investment in compounds with novel mechanisms is also large Dopamine D2 based mechanism non-d2 mechanisms Subjects enrolled (cumulative) all others all others ClinTrials.org industry-sponsored schizophrenia phase 2 or phase 3 randomized, placebo-controlled 7

8 The success of compounds with non-d2 MoA s has been poor relative to D2 compounds Dopamine D2 based mechanism non-d2 mechanisms Subjects enrolled (cumulative) launches all others all others ClinTrials.org industry-sponsored schizophrenia phase 2 or phase 3 randomized, placebo-controlled 8

9 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 Subjects enrolled (cumulative) launches all others all others Relapse PANSS total Cognition PANSS total Primary Endpoints as portion of total enrolled subjects Negative Symptoms Relapse Drug development RCTs for new treatments in schizophrenia have incorporated new measurements of specific symptom domains ClinTrials.org industry-sponsored schizophrenia phase 2 or phase 3 randomized, placebo-controlled 9

10 How to apply clinical trial databases to facilitate new treatments, including drugs with novel MoA s? Dopamine D2 based mechanism Relapse PANSS total Cognition non-d2 mechanisms PANSS total Negative Symptoms Relapse RDOC MATRICS SCALES IMPROVE MEASUREMENTS Use the existing PANSS scale, to measure, with enhanced specificity, treatment effects across key symptom domains of schizophrenia ACADEMIA PHARMA NIMH/NIH Drug development RCTs for new treatments in schizophrenia have incorporated new measurements of specified symptom domains 10

11 PANSS factors are correlated Can we transform them to be more specific? N=1,710 Sunovion dataset acute schizophrenia, 6-weeks {lurasidone, placebo, olanzapine, quietiapine} factor analysis of change-from item scores retain score matrix coefficients domain A UPSM UPSM uncorrelated factor scores scores domain B (ORTHOGONAL) represent symptom change specific to each dimension (FACE VALID) corresponds to recognizable/established dimensions (APPLICABLE) UPSM can transform external PANSS data sets Uncorrelated PANSS Score Matrix (UPSM) 11

12 Pseudospecificity: A major confound in the assessment of efficacy in schizophrenia Correlations Among Marder PANSS Factor Scores (Week 6 Change from Baseline) SUNOVION DATA (N=1,710 patients from 5 placebo-controlled schizophrenia trials) Marder PANSS factor pos dis neg hos/exc anx/dep tot Positive Symptoms 1 Disorganized Thought Negative Symptoms Hostility/Excitement Anxiety/Depression PANSS Total OTSUKA DATA (N=1,368 patients from 5 placebo-controlled schizophrenia trials) Marder PANSS factor pos dis neg hos/exc anx/dep tot Positive Symptoms 1 Disorganized Thought Negative Symptoms Hostility/Excitement Anxiety/Depression PANSS Total 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 tot Positive Symptoms 1 Disorganized Thought Negative Symptoms Hostility/Excitement Anxiety/Depression PANSS Total

13 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 DEP POSITIVE 1 DISORGANIZED NEG APATHY/AVOLITION NEG DEFICIT OF EXPRESSION HOSTILITY ANXIETY DEPRESSION PANSS TOTAL SCORE OTSUKA DATA (N=1,368 patients from 5 placebo-controlled schizophrenia trials) Transformed PANSS factors POS DIS NAA NDE HOS ANX DEP POSITIVE 1 DISORGANIZED NEG APATHY/AVOLITION NEG DEFICIT OF EXPRESSION HOSTILITY ANXIETY DEPRESSION PANSS TOTAL SCORE TAKEDA DATA (N = 240 patients from 1 placebo-controlled schizophrenia trials 20 mg TK-063) Transformed PANSS factors POS DIS NAA NDE HOS ANX DEP POSITIVE 1 DISORGANIZED NEG APATHY/AVOLITION NEG DEFICIT OF EXPRESSION HOSTILITY ANXIETY DEPRESSION PANSS TOTAL SCORE

14 Towards specificity in antipsychotic drug treatment effects N=5 acute schizophrenia trials PANSS change from baseline, at Week 6 endpoint, lurasidone active doses vs. placebo MARDER PANSS FACTORS overlapping drug effects POSITIVE UPSM TRANSFORMED PANSS FACTORS more specificity subdomains Attributions of specific treatment effects confounded by correlations among improvements in Marder PANSS Factor Scores DISORGANIZED NEGATIVE APATHY/AVOLITION DEFICIT OF EXPRESSION greater heterogeneity in effect size estimates across the sub-domains HOSTILITY DEPRESSION/ANXIETY ANXIETY DEPRESSION PANSS TOTAL TOTAL FACTOR SCORE improvement worsening improvement worsening Hopkins et al Schizophrenia Bulletin drug vs. placebo effect size ± 95%CI 14

15 Discussion Point: Treatment effects are separable among the dimensions of schizophrenia subdomains 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 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 subdimensions of schizophrenia psychopathology can be evaluated 15

16 Understanding of specificity within PANSS to advance the field and facilitate development of new treatments specificity among symptom sub-domains subpopulations Does an understanding of specificity of symptom change over time help to identify more-meaningful patient types? 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 Address issues of: differentiation dose-response benefit/risk Use during: drug development decisions meta-analyses Forest Plots with specificity more specific breakdown of total symptoms improvements according to the domains of most-prominent effects 16

17 Identified patient types at baseline who are prominent along specific UPSM factor scores are patient-types stable? do they persist post-baseline? subpopulations post-baseline PROMINENTLY POSITIVE track response of patienttypes post-baseline POS HOSTILE PATIENT TYPES baseline PANSS post-baseline PANSS mean UPSM factor scores DISORGANIZED ANX DEP NEG transform (UPSM) cluster (K-MEANS) train classifier (SVM) transform (UPSM) apply classifier (SVM) PATIENT TYPES POS HOS DIS ANX DEP NAA BASELINE NDE 17

18 Patient-types persist over time, even in the context of overall symptom (PANSS total) improvements 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 PROMINENTLY POSITIVE duration Patient types persist over time and over treatment PATIENT-TYPE PROMINENTLY POSITIVE POS POS HOS HOS DIS ANXDEP number of subjects DIS N=200 N=400 NEG mean UPSM factor scores ANX DEP NEG DISCONTINUATION POS HOS DIS ANX DEP NAA NDE BASELINE SEQUENTIAL WEEKLY VISITS ENDPOINT N=1,710 subjects 5 studies acute schizophrenia RCTs {lurasidone, placebo, olanzapine, quietiapine} 18

19 Future directions in the use of clinical trial databases for improving RCT efficiency 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 subdomains subpopulations Towards collaborative analyses and shared research questions for our existing clinical trial databases 19