BlackThorn Therapeutics Reports New Insights into Neurobehavioral Disorders at the 49th Annual Meeting of the Society for Neuroscience

SAN FRANCISCO, October 23, 2019 –BlackThorn Therapeutics, Inc., today announced that the company presented new data science research into the underlying biology of neurobehavioral disorders at the 49th annual meeting of the Society for Neuroscience (SfN) taking place October 19-23 in Chicago.

“CNS drug discovery and development needs biology-based, data-driven strategies to achieve better treatment outcomes for people with neurobehavioral disorders,” said Bill Martin, Ph.D., BlackThorn’s chief executive officer. “Our data science research presented at SfN highlights key technological advances we are making to process brain imaging data at scale which yields insights into the biological basis of behavior as well as treatment response. We are applying our learnings to advance our pipeline of targeted therapeutics starting with a phase 2 trial of our KOR antagonist, BTRX-140, in patients with major depressive disorder, which is on track to start by year-end.”

BlackThorn’s presentations at SfN highlighted research enabled by pathfinder™, the company’s cloud-based computational psychiatry platform for multimodal data collection, integration and analysis at scale. Leveraging pathfinder™, the company creates a quantitative, brain-based understanding of neurobehavioral disorders. BlackThorn applies these data-driven insights to create treatments targeted to biologically-based subtypes of patients with the goal of increasing the precision of therapeutic intervention.

BlackThorn’s Data Science Presentations at SfN
Mellem, M. et al. “Resting-state functional MRI outperforms structural MRI in predicting transdiagnostic depression severity”
Session 704.06 / CC66 – Biomarker and Drug Discovery: Neuropsychiatric Diseases
Wed, Oct. 23, 2019 09:00 AM – 10:00 AM

Summary: Depressed mood is a symptom present in many neurobehavioral disorders. This research sought to identify a “depressive brain signature” across diagnostic categories from the Consortium for Neuropsychiatric Phenomics dataset, which includes resting-state functional MRI (rs-fMRI) and structural-MRI (sMRI) imaging measures from patients with schizophrenia, bipolar disorder, and attention deficit and hyperactivity disorder. An algorithm was developed that reliably predicted severity of depression across disorders and identified that functional brain connectivity, rather than solely anatomic features, provided a “depressive brain signature.”

Liu, Y. et al. “Machine learning identifies large-scale reward-related activity modulated by dopaminergic enhancement in major depression”
Session 684.10/ V22 Depression: Physiology, Pharmacology, and Treatment
Wed, Oct. 23, 2019 09:00 AM – 10:00 AM

Summary: An independent study evaluated whether enhancing dopaminergic signaling can normalize dysregulated patterns of brain activity associated with major depressive disorder (MDD) and hypothesized that specific brain regions associated with reward processing would be involved. Using machine learning, BlackThorn developed predictive models that could discriminate MDD patterns of brain activity from healthy patterns of brain activity. The best models were based whole-brain connectivity rather than single brain regions, which highlights the power of data-driven vs. hypothesis-driven classification methodologies.

Kollada M, et al. “Automated parameter search for fMRI preprocessing pipeline quality control using functional connectivity matrix clustering”
092.01 / BB52 – Connectomics Analytics II
Sat, Oct. 19, 2019 1:00 PM – 2:00 PM

Summary: Quality Control (QC) of fMRI preprocessing has become a bottleneck to analyzing large-scale fMRI datasets. An automated search method for selecting the optimal fMRI preprocessing pipeline parameters was developed and validated on two independent datasets. The method allows for generation of parameter set recommendations for each subject, which dramatically reduces the turnaround time and effort required of an expert reviewer to fully QC a dataset.

Gonzalez, H. et al. “Cloud-enabled massively parallel structural and functional MRI preprocessing pipeline”
Session 525.08 / DD41 – Software Tools: Imaging
October 22, 2019, 8:00 AM

Summary: The preprocessing of structural and functional MRI scans is a computationally-intensive operation, typically taking several hours per subject. This results in prohibitively long waits between MRI data acquisition and analysis, particularly in large datasets with many hundreds of subjects. A cloud-enabled, massively parallel approach was developed that significantly reduced the end-to-end preprocessing time for complete MRI datasets, and holds promise in enabling scientists to study the effect and sensitivity of parameter changes across datasets with many thousands of subjects.

About BlackThorn’s Lead Clinical Program: BTRX-140
BTRX-140 is a potent, selective small molecule antagonist of the kappa opioid receptor (KOR), which was discovered as part of a research collaboration with The Scripps Research Institute. The KOR/dynorphin system is known to be a major stress response signaling pathway in the brain. KOR/dynorphin ‘tone’ contributes significantly to regulating brain circuits involved in motivation and emotion, and recently BlackThorn demonstrated the involvement of KOR/dynorphin in executive functions. Dysfunction of the KOR/dynorphin system is associated with anhedonia, anxiety and cognitive impairment, which are key drivers of disability in numerous psychiatric and neurological disorders. BTRX-140 is intended to normalize dysregulated brain networks by altering activity of KOR through dynorphin blockade. BTRX-140 was found to be well tolerated in single and multiple ascending dose studies in healthy volunteers.

About BlackThorn Therapeutics
BlackThorn Therapeutics, Inc., is a clinical-stage, neurobehavioral health company committed to improving the lives of people with neurobehavioral disorders through the discovery and development of novel, targeted therapeutics. Our goal is to empower patients and physicians to make treatment decisions and plans based on an individual’s profile across the spectrum of neurobehavioral health. In order to address historical challenges in CNS drug development, we have engineered pathfinder™, a proprietary computational psychiatry platform to capture, quantify and model multiple data types. We use pathfinder™ to better understand how networks of brain activity relate to normal and disordered behavior, and we employ high performance computing, predictive models and artificial intelligence (AI) technology to accelerate the entire process. We apply pathfinder™ outputs to identify novel targets, small molecule drug candidates and biologically-based patient subgroups. Our lead clinical program is focused on BTRX-140, a selective KOR antagonist, for which a phase 2 trial in major depressive disorder is expected to begin in 4Q:19. Our second clinical program is focused on a selective V1aR antagonist for the potential treatment of autism spectrum disorder, for which a phase 1 trial is expected to begin in early 2020. Both molecules were discovered in collaboration with The Scripps Research Institute. BlackThorn is headquartered in San Francisco, California. For more information, please visit

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Laura Hansen, Ph.D., VP, Corporate Affairs
tel: 650-703-6523

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