Can you provide an overview of the mission and structure of PsychoGenics’ business?

PsychoGenics’ mission is to transform CNS drug discovery and deliver much needed treatments to patients suffering from severely disabling neuropsychiatric conditions. To do this we employ our proprietary, high throughput, AI-driven phenotypic discovery platforms, which we use in combination with our broad pre-clinical discovery capabilities and mouse disease models. We employ our platforms and capabilities in three distinct ways:

1. Fee-for-service: A profitable growing business with relationships with more than 400 companies and more than 90% of our business coming from repeat clients. Our capabilities include behavioral testing, electrophysiology, translational EEG, quantitative histology, molecular biology, and bioanalysis. In addition, offer our clients access to rodent disease models for a variety of neuropsychiatric disorders and pain to help them understand the therapeutic utility of their treatments.

2. Partnered drug discovery where we enter into shared-risk partnerships that deliver upfront fees, milestones and royalties.  Our partnered drug discovery relies heavily on our phenotypic AI-driven platforms and has delivered four clinical compounds, the most advanced of which is a novel first-in-class treatment for schizophrenia in Phase 3 clinical studies; and multiple advanced preclinical candidates.  We currently have four partners; Sunovion, Roche, Karuna, and Blue Oak, and are in discussions with others.

3. Internal drug discovery, which is a more recent endeavor.  In 2020, we hired a team of drug hunters to mine our compound library consisting of thousands of chemically diverse, CNS active compounds collected over more than a decade.  This library delivers hits (starting points), and together with our platforms and other capabilities, we are building a pipeline of wholly owned drug candidates.  Our two most advanced programs will enter IND-enabling studies this year. 

Can you describe your AI-driven platforms?

Almost two decades ago, during the height of the genomic revolution when companies were looking for disease targets, PsychoGenics recognized that the target-driven approach to neuropsychiatric drug discovery, which biopharmaceutical companies were pursuing to the exclusion of other approaches, had serious flaws; confirmed decades later by the sparsity of new first-in-class treatments.  Instead, we pioneered an alternative phenotypic approach that captures hundreds-of-thousands of behavioral and physiological data points from mice and employs machine learning to predict therapeutic applications for novel compounds.  Not only has this target-agnostic approach delivered novel first-in-class clinical compounds, such as SEP-363856, with improved efficacy and side effect profiles for unmet neuropsychiatric needs, but it has also proven to be highly efficient delivering clinical candidates ready for preclinical development – some two- to three-years faster and requiring only a fraction of new analogs than target-driven approaches.  In the Sunovion partnership, we jointly discovered several new drug candidates with novel modes of action, including SEP-363856, which has shown statistically significant and clinically meaningful improvement in multiple symptoms of schizophrenia with a side effect profile similar to placebo, differentiating it from existing antipsychotics.  SEP-363856, now in Phase 3, has received Breakthrough Therapy Designation.

What are the keys to improving attrition rate in CNS clinical trials?

Typically, one looks for target engagement in the brain as an indication that one’s compound is doing what it was designed to do.  However, since we are using a phenotypic platform, the compounds we discover act through multiple mechanisms, or through novel or unknown mechanisms, so target engagement via PET tracers is not an option.   Having a robust understanding of the efficacy and side effect profiles of a compound in preclinical in vivo models is very important so we know what to look out for clinically. Our platform, plus all the other capabilities that we employ, allows us to understand the potential of a compound, along with its potential liabilities. We also look for translational biomarkers, so we can assess translation from preclinical to clinical. Examples include EEG patterns such as increased or decreased REM sleep or functional MRI to show how a treatment activates the same brain regions across species, especially higher species prior to going into humans.  It is extremely important in offsetting clinical risk to know that you are showing similar effects in humans to rodents and/or non-human primates.

What has the influx of capital into neuropsychiatric drug discovery meant for PsychoGenics’ growth?

Neuropsychiatric drug discovery has seen more money flow into it in 2020 than ever before and almost double 2019, both in terms of institutional investment and partnering.  I think it was inevitable that we would see a resurgence of interest in CNS disorders as these are severely disabling conditions with poor or no available treatments that impact huge numbers of people worldwide.  There is a general sense that CNS may be the next oncology.  This influx of capital is best reflected in our service business which grew significantly in 2020 as a result of many newly formed, venture backed companies requesting our services.   We are also seeing more opportunities for partnerships, driven in part by the clinical success of SEP-363856 in schizophrenia, which validates our AI-driven discovery platforms, and in part by the renewed interest in CNS and the need to explore new approaches to discover new and improved treatments.  Finally, we were able to secure funding to build our own internal drug discovery team in 2020.