Investigating Target Identification and Validation Modelling in Neurodegenerative Disease
Target identification and validation modelling are critical steps along the drug discovery process for neurodegenerative disease. Molecules that play a role in disease pathogenesis must be identified and then verified to have a modulating effect on the disease before hits can be found and optimised. Oxford Global had the pleasure of hosting an online panel discussion at our Neuroscience Discovery Symposium.
Chris Winrow, VP and Head of Translational Medicine at Cyclerion Therapeutics, moderated the panel. He spent 15 years working on drug discovery at Merck before moving to Ironwood Pharmaceuticals which spun out his current company. Cyclerion is a clinical stage biopharmaceutical company based in Cambridge, MA which investigates the nitric oxide, soluble guanylate cyclase, cyclic GMP (NO-sGC-cGMP) pathway in the CNS.
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Shane Hegarty initially trained as a neuroscientist working on neurotrophic factors for neurodegenerative diseases. He joined Boston Children’s Hospital, Harvard Medical School at Zhigang He’s lab to identify novel targets for neuroprotection, axion regeneration, and reactivation of spare tissue in degenerative conditions. Axonis Therapeutics span out of the He lab where Hegarty is now the Chief Scientific Officer and Co-Founder.
Strategies for Target Identification
Winrow first asked the panel what strategies they used to identify targets for neurodegenerative disorders. Here, a combination of investigative techniques can be employed. Furthermore, type of model system used is important, animal models are not predictive enough of the human disease to solely rely upon.
Hegarty noted that the ideal target is validated in human biology or genetically linked to a disorder. He observed that the field was currently limited by models, “that’s an absolute fact.” Current available tools make it difficult to translate targets, but Hegarty is hopeful that new techniques like induced pluripotent stem cells can better recapitulate human disease phenotypes. He advised that scientists should be aware of the limitations of their tools, “one model can’t answer all your questions.”
“In terms of target identification, you have to study something – to try to find the best model for the phenotype of interest,” said Hegarty, adding that those models should strive for reproducibility, fidelity, and translatability. “We need to be open minded and ask ourselves, is what we’re studying relevant to the patient?”
Validation Models
Having had substantial experience working with animal models, Winrow sees their utility in building toward translational endpoints. He asked the group if they thought there were any particular aspects of animal modelling that they found compelling.
One perspective is that some working in model validation rely on animal models than others. Models for neurodegenerative diseases, particularly neuroinflammation, have a very specific use case, and are not intended to fully recapitulate the human disease. Often, animal models are used as a stepping-stone, along with other methods to investigate neuroinflammation.
Hegarty agreed with this point, “you can’t fall in love with a model, that’s a very dangerous thing to do.” He added that because scientists spend a lot of time optimising their model, which can be like a fine art, that often people can get too attached to their model. Ideally, multiple models will be used to cross-validate the therapeutic potential of a new target, each of which would reproducibly model a different aspect of the pathology.
In translation, Hegarty said that the more reproducible a model is, the more confidence can be gained from it. “However, this is just another step on the de-risking process, you’ll never have the full answer until you enter late-stage clinical trials,” he said. The best case scenario is to use pharmacodynamic biomarkers with a direct connection to the disease, such as neurofilament light chain. Hegarty also specified that ideal PK/PD biomarkers could be tested in early development and then translated from animal in vivo studies into the clinic for proof of target engagement or proof of biology early readouts in patient trials.
As a first time-founder, Hegarty also warned against being overly ambitious. He said that it may not be productive to aim to make a monumental impact early on. “Starting out you could think, ‘my therapy is neuroprotective; maybe it could be used to treat Alzheimer’s.’ But it can be more prudent to focus in on a smaller patient group that shows the pathology that you’re treating.”
What Factors Constitute a Validated Target?
When considering what factors constitutes a validated target, it can depend on perspective. An academic might consider validation to be something as simple as a cellular model, whereas an MD or clinician would consider validation to mean a clinically validated model. Therefore, when discussing validation, it is important to keep in mind what that word might mean to them.
The cornerstone of validation is a specific understanding of a relationship between an expression and a clinical manifestation. Herein, the minimum level of validation that a scientist should observe is some evidence of a connection to a disease. However, even this benchmark understanding of validation can miss important aspects of disease via post-transcriptional translation.
Introducing the clinician’s perspective, Hegarty gave the example of anti-VEGF treatment for certain retinal disorders that cause the growth of new blood vessels and swelling in the eye. While being reasonably effective, the treatment is not an optimal modality as it can require repeated injections in the eye. Biotech company Regenxbio developed a solution to aid in this problem: a one-time gene therapy to safely and effectively deliver the therapeutic persistently over time.
When it comes to the validation of this approach, Hegarty said: “They’re probably working with a validated therapeutic approach because it has already been effective in patients with retinal disorders. However, there’s not going to be a genome-wide association study (GWAS), or other patient datasets linking VEGF to these conditions. We just know that there’s a huge problem with neovascularisation in these disorders. That for me is a reliable form of target validation.”
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Join and network with over 400 industry leaders at the renowned Drug Discovery Summit in Berlin, where we will address the latest advancements in target identification, validation and HIT optimisation. Exploring the latest advancements in phenotypic and target-based discovery, chemical biology as well as drug design at our two-day summit. The event will bring together leading experts in the fields of Organoid Discovery, Phenotypic Screening, Targeted Protein Degradation, AI Computational Drug Design and Lead Optimisation.
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