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Canada's Cyclica Targets Pharma with Drug-Protein Interaction Search Software


NEW YORK (GenomeWeb) – Canadian informatics firm Cyclica is seeking to build a business around Ligand Express, a proprietary system for indexing and searching drug-protein interactions that the company believes could help pharmaceutical companies save time, maximize their investments, and keep their drug discovery pipelines fresh.

Incorporated in 2010, Cyclica officially opened its doors in late 2012 after raising approximately C$2 million (over $1.6 million) and hiring its first employee. The company, which is headquartered in Toronto and has a second office in New Haven, Connecticut, has spent the last few years developing its flagship offering as well as building up its team — it currently has 11 employees on staff.

Ligand Express uses a combination of biological, chemical, and protein structure data to identify small molecule candidates for possible development and testing, potential problems for compounds, mechanisms of action, and opportunities for drug repurposing. More specifically, it looks at all possible physical interactions between proteins found in the human body and small molecules at both the molecular and systems level, Stephen MacKinnon, a structural bioinformatician at Cyclica, told GenomeWeb.

Given a list of compounds, he explained, Ligand Express first examines all of their known possible interactions with proteins as well as known interactions between similar compounds and proteins. It then selects from this smaller pool drug-protein interactions that are more likely than others and uses those as a template to explore much larger sets of proteins for other possible interactions, he said. As it finds new interactions, it uses a proprietary algorithm to select those that are more likely to be good candidates for further research and development.

The software draws on internal databases of known and predicted protein structures and protein conformation data as well as databases of drug information and peer-reviewed scientific literature to make predictions about potential clinical outcomes of drug candidates such as side effects, toxicity, and therapeutic effects.

According to Cyclica, its software improves on traditional compute-intensive and slower protein docking methods, offering a shorter time to results than these existing methods — days as opposed to months — without corresponding compromises in accuracy. This can potentially help drug manufacturers slash years off their current drug development timeframes and save millions of dollars in failed clinical trials, Paul Angelico, the company's president and CEO, said.

Moreover, many existing commercial solutions tend to explore drug-protein interactions in the context of a pre-selected group of proteins, meaning that the insights and analysis they provide are limited to a small pool of candidates focused on specific targets or receptors, Naheed Kurji, the company's co-founder and CFO, told GenomeWeb.

Since Ligand Express searches a much wider space of potential proteins it can provide more comprehensive reports that cover not just effects on specific targets but also possible off-target effects which could be, for example, opportunities for drug repurposing that may help pharma companies expand the patent life cycle of existing products, he said. The system could also help manufacturers answer questions about drugs already in development, MacKinnon added. For instance, if a drug in clinical testing has an adverse effect on a subset of the test population, Ligand Express could help developers identify the molecular root of the effect and take steps to work around it or they could use the information to select candidates for whom the drug would be most efficacious, he said.

Cyclica's target market is primarily pharma but it is also targeting firms that are developing nutraceuticals and other consumer goods such as cosmetics and creams, Angelico said. It also hopes to eventually tap into the personalized medicine arena, oncology in particular, and use its system there to help oncologists and other clinicians select more efficacious treatments for their patients. Kurji said that the company is currently in discussions with a number of large pharmaceutical, nutraceutical, and consumer goods companies who are interested in using its solution but he could not disclose specific names for confidentiality reasons.

Cyclcia plans to make Ligand Express available under a software-as-a-service model starting possibly next quarter, Kurji said. The company will also offer consulting services that will support customers of the SaaS software. For now, it works with clients on a project basis where clients submit groups of compounds for analysis and company scientists run the data through the software themselves. At the end, clients receive project reports that detail the company's assessment of the input compounds and its findings. Cyclica opted for a project-based approach as its initial business model, he explained, so that it could continue to improve and refine its technology in collaboration with customers. It was also a way to introduce clients to the system and its capabilities before transitioning them to the more enterprise SaaS offering.

Cyclica is still mulling its pricing structure but the company currently charges customers about $15,000 to $20,000 per compound for projects — the exact cost varies depending on client's needs. Pricing for licenses to the planned SaaS is yet to be determined but it will also vary some depending on factors such as how much work clients want to handle themselves, what sort of services they access with the software, and what sort of customizations are included in their systems.

Cyclica competes with firms such as NuMedii, a Stanford University spin-off that uses proprietary network-based algorithms to find both drug candidates and predictive biomarkers, and Numerate, whose Numatix software uses machine learning algorithms to generate in silico small molecule drug leads for specific disease targets. It also competes with Biovia — formerly Accelrys — which was acquired by Dassault Systèmes last year.