Functional NMDA receptor-based target engagement biomarkers for schizophrenia

research

Daniel C. Javitt, M.D., Ph.D.Professor & Director, Division of Experimental Therapeutics

Columbia University Medical Center

Director of Schizophrenia ResearchNathan Kline Institute

Disclosures

• Consultant: Pfizer, FORUM, Autifony, Glytech, Lundbeck, Concert, Cadence

• Scientific Advisory Board: Promentis, NeuroRx, Phytecs

• Equity: Glytech, AASI, NeuroRx

• Intellectual property rights: Glycine, D-serine and glycine transport inhibitors in Sz; D-cycloserine, combined NMDAR/5-HT2AR antagonism in depression & PTSD; visual ERP for early diagnosis of Alzheimer disease

• Off-label treatment: pomaglumetad

Functional target engagement biomarkers

The challenge

• Glutamatergic theories of schizophrenia have become increasingly established over the past 25 years

• Many glutamate-base pharmacological approaches show encouraging effects in preclinical models

• To date, none has translated into an effective medication

• Need target engagement biomarkers to permit better translation from animals to humans

• Allow “FAST fail” decisions regarding mechanism of action:• No target engagement - “fail” drug• Target engagement but no beneficial clinical effect – “fail” mechanism

• Permit informed dose selection

The solution

Academia, Government, and Pharma contributions

Sci Transl Med. 3:102mr2, 2011

TRANSLATION TYPE (Institute of Medicine, 2013)

NMDAR-based treatment development

N-methyl-D-aspartate (NMDA) receptor

- Javitt & Zukin, Am J Psychiatry, 148: 1301-8, 1991

Treatment targets

- Moghaddam & Javitt., Neuropsychopharmacol Rev, 2011

Glutamate synapse

Background

• NMDAR antagonists such as phencyclidine (PCP) and ketamine induce symptoms, neurocognitive deficits and neurophysiological deficits that closely resemble schizophrenia

• Acute NMDAR blockade is associated with an increase in presynaptic glutamate release (“glutamate surge”)

• Hypothesis 1: Symptoms/neurocognitive deficits results from NMDAR hypofunction• Hypothesis 2: Symptoms/neurocognitive deficits result from “glutamate surge”

NMDAR-based treatment development

Potential treatment approaches

Treatment targets

- Moghaddam & Javitt., Neuropsychopharmacol Rev, 2011

Glutamate synapse

Background

• NMDAR antagonists such as phencyclidine (PCP) and ketamine induce symptoms, neurocognitive deficits and neurophysiological deficits that closely resemble schizophrenia

• Acute NMDAR blockade is associated with an increase in presynaptic glutamate release (“glutamate surge”)

• Hypothesis 1: Symptoms/neurocognitive deficits results from NMDAR hypofunction• Hypothesis 2: Symptoms/neurocognitive deficits result from “glutamate surge”

Hypothesis 2: Desired solution -↓ presynaptic glutamate release

Hypothesis 1: Desired solution –↑ postsynaptic NMDAR activity

Effect of metabotropic glutamate receptors: preclinical models

Moghaddam et al., Science. 281:1349-52, 1998

• Treatment with an NMDAR antagonist (PCP) leads to significant increases in glutamate & dopamine release in prefrontal cortex, along with increases in locomotion

• Pretreatment with the mGluR2/3 agonist LY354740 blocks both the increases in glutamate and locomotion

• PCP-induced increases in dopamine release also inhibited but not blocked

Clinical effects of pomaglumetad (LY21400230)

Downing et al., BMC psychiatry. 14:351, 2014

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Subsequent failures to replicate

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Patil et al., Nat Med. 13:1102-7, 2007

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Initial positive result

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FAST-Fail: Psychotic disorders

Questions

• Why don’t mGluR2/3 agonists work in people, even though they work in rodent models?

• Were doses used in the clinical studies sufficient to adequately test the hypothesis?

• What biomarkers can be used to test target engagement?

NIMH FAST-psychosis spectrum (FAST-PS) biomarker project

• Phase I: Biomarker selection• Selected measures potentially sensitive to the glutamate “surge”• PharmacoBOLD, Glutamate MRS, task-based fMRI

• Phase II: Target engagement studies with pomaglumetad (healthy volunteers)

Phase I biomarker validation

JAMA Psychiatry. 75:11-19, 2018

• 65 Healthy volunteers• Randomized 2:1 to ketamine infusion vs. placebo• 2 MRI sessions per subject• Session 1: Glutamate 1H-MRS, task-based fMRI• Session 2: “PharmacoBOLD”• Psychosis ratings: CADSS, BPRS

Design

Magnetic resonance spectroscopy (MRS): Methods

Abdallah et al., Neuropsycho-pharmacology 43: 2154-2160, 2018.

Mechanism of action Example spectrum

• Increase in presynaptic glutamate release leads to a rapid increase in glutamate synthesis from glucose

• The increase in glutamate synthesis , in turn, leads to an increase in total glutamate+glutamine (“Glx”) in brain

Magnetic resonance spectroscopy (MRS): Results

Abdallah et al., Neuropsychopharmacology 43: 2154-2160, 2018.

Mechanism of action

• Increase in presynaptic glutamate release leads to a rapid increase in glutamate synthesis from glucose

• The increase in glutamate synthesis , in turn, leads to an increase in total glutamate+glutamine (“Glx”) in brain

*

Results

• Significant increase in Glx content at 15 min• BUT: Moderate effect size (d=.64)• Not sufficiently robust to be able to detect a

drug effect even if present

PharmacoBOLD

Abdallah et al., Neuropsycho-pharmacology 43: 2154-2160, 2018.

Mechanism of action

• Increase in presynaptic glutamate release leads to a rapid increase in glutamate synthesis from glucose

• The increased metabolic rate leads to an acute increase in BOLD reponse

Results

• Extremely large effect (d=5.4)• Sufficient to detect a change, if present

Phase 2 study: Design overview

• 81 healthy volunteer completers across 4 sites (Columbia, NYU, UAB, UCLA) (100 total subjects randomized)

• Randomized (1:1:1) double blind administration of a placebo, 40mg bid POMA, or 160mg bid POMA

• 40 mg BID = dose used in prior successful clinical trial

• 160 mg BID = maximum tolerated dose (limited by nausea, vomiting)

• Subjects took POMA or placebo for 10 days

• Administered ketamine or placebo on the final day of treatment

• Ketamine dose - 0.23 mg/kg bolus over 1 minute

• Ketamine-induced prefrontal glutamate activity as measured by resting BOLD fMRI (pharmacoBOLD)

• Inclusion criteria: BOLD fMRI response in dACC-ROI > 0.5% at Screening

Phase 2 Pomaglumetad study: results%

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Clinical ratings (BPRS)

d=-.14, p=.52vs. placebo

Main effect of treatment: p=.80

Placebo Low-dose High-dose(40 mg BID) (160 mg BID)

d=-.33, p=.15vs. placebo

Placebo Low-dose High-dose(40 mg BID) (160 mg BID)

Main effect of treatment: p=.33

mGluR/3 agonist development in Sz: Conclusions

Conclusions

• The good news is that the bad news may be wrong• At doses used in prior clinical studies, pomaglumetad does not show evidence of

significant functional target engagement• Other compounds are presently under investigation

• The bad news is that the mechanism may not be viable• Further dose escalation may be precluded by high rates of nausea/vomiting• HOWEVER: Side effects are likely due to local effects in stomach; could be blocked

by peripheral antagonists• Future studies with higher doses are needed

• “PharmacoBOLD” can be used for T1-type translation to healthy volunteers• Not suitable for T2-T4 translation involving patient groups

• Biomarker studies should probably be implemented before, rather than after, intensive phase 3 development

T2 translation: Mismatch negativity (MMN)

ERP Biomarker Qualification Consortium

www.erpbiomarkers.org

• Elicited in the context of an auditory “oddball” paradigm• Reflects information processing dysfunction at the level of

auditory sensory cortex• Consistent deficits in Sz related to impaired functional

outcome• Can be assessed in parallel in rodents, monkeys, & humans• Inhibited by NMDAR antagonists (e.g., ketamine) • Improved by putative NMDAR agonists (e.g. D-serine)

MMN Meta-analysis (Sz)

- Avissar et al., Schizophr Res. 191:25-34; 2018

Collaborators

Columbia

Jeff Lieberman (PI)Josh KantrowitzLarry KegelesJack GrinbandRagy GirgisMelanie WallTse Hswei ChooMarlene Carlson

Jim Robinson (NKI)

Biomarker validation

Yale UniversityJohn KrystalPhil CorlettGraeme MasonDouglas RothmanMaolin Qui

UC DavisCameron CarterJ. Daniel RaglandRichard MaddockCostin TanaseTyler Lesh

Pomaglumetad

UCLASteve MarderJunghee LeeMichael Green

NYUDon GoffFernando BoadaErica Diminich

UA BirminghamAdrian LahtiDavid WhiteMark Bolding

MMN Consortium