Founded Year



Series B | Alive

Total Raised


Last Raised

$17M | 2 yrs ago

About Cyclica

Cyclica is a global biotechnology company that leverages artificial intelligence and computational biophysics to reshape the drug discovery process. Cyclica's structure-based and AI-augmented drug discovery platform includes Ligand Design for multi-targeted and multi-objective drug design, and Ligand Express for off-target profiling, systems biology linkages, and structural pharmacogenomic insights.

Cyclica Headquarter Location

207 Queens Quay West Suite 420

Toronto, Ontario, M5J 1A7,



ESPs containing Cyclica

The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.

Healthcare / Biopharmaceuticals

AI drug discovery vendors are analyzing data (e.g., clinical trials data, EHRs, omics data, cellular images, and more) to develop novel drugs.

Cyclica named as Outperformer among 9 other companies, including Atomwise, Insilico Medicine, and insitro.

Predict your next investment

The CB Insights tech market intelligence platform analyzes millions of data points on venture capital, startups, patents , partnerships and news mentions to help you see tomorrow's opportunities, today.

Cyclica's Products & Differentiation

See Cyclica's products and how their products differentiate from alternatives and competitors

  • Ligand Express

    Ligand Express® is a cloud-based platform that provides insights into the polypharmacology of small molecule ligands.


    The platform identifies significant protein targets using an innovative structure-based and drug-centric technology that leverages artificial intelligence to determine the drug's effect on those tar… 

  • Subscribe to see more

    We're on a mission to enable every organization to make smarter decisions about tech. Whether it's finding a new game-changing vendor or understanding a new market, it's easier, faster and smarter with CB Insights. All made possible by the smartest, hardest-working team in tech. Subscribe to see more.


    We're on a mission to enable every organization to make smarter decisions about tech. Whether it's finding a new game-changing vendor or understanding a new market, it's easier, faster and smarter with CB Insights. All made possible by the smartest, hardest-working team in tech. Subscribe to see more.

Research containing Cyclica

Get data-driven expert analysis from the CB Insights Intelligence Unit.

CB Insights Intelligence Analysts have mentioned Cyclica in 2 CB Insights research briefs, most recently on Mar 3, 2020.

Expert Collections containing Cyclica

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

Cyclica is included in 4 Expert Collections, including Artificial Intelligence.


Artificial Intelligence

9,051 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.


AI 100

100 items

The winners of the 4th annual CB Insights AI 100.


Digital Health

13,070 items

Technologies, platforms, and systems that engage consumers for lifestyle, wellness, or health-related purposes; capture, store, or transmit health data; and/or support life science and clinical operations. (DiME, DTA, HealthXL, & NODE.Health)


Biopharma Tech

838 items

Cyclica Patents

Cyclica has filed 4 patents.

The 3 most popular patent topics include:

  • Bioinformatics
  • Biological databases
  • Cheminformatics
patents chart

Application Date

Grant Date


Related Topics



Properties of chemical elements, Mass spectrometry, Cheminformatics, Chemistry, Oxidizing agents


Application Date


Grant Date


Related Topics

Properties of chemical elements, Mass spectrometry, Cheminformatics, Chemistry, Oxidizing agents



Latest Cyclica News

Cancer Therapeutics Target the Undruggable, Confront Other Bugbears

May 2, 2022

Orum Therapeutics develops tumor-directed protein degraders (TPDs). Each TPD consists of an antibody conjugated to a payload, specifically, a small-molecule protein degrader. The antibody directs the TPD to the cytosol of target cells, where the payload exerts its catalytic mechanism of action. (The TPD shown here is based on a 1IGY antibody structure: gray: variable heavy chain of the antibody; peach: variable light chain; yellow: linker–molecular glue degrader.) Orum Therapeutics develops tumor-directed protein degraders (TPDs). Each TPD consists of an antibody conjugated to a payload, specifically, a small-molecule protein degrader. The antibody directs the TPD to the cytosol of target cells, where the payload exerts its catalytic mechanism of action. (The TPD shown here is based on a 1IGY antibody structure: gray: variable heavy chain of the antibody; peach: variable light chain; yellow: linker–molecular glue degrader.) Share Although cancer drug pipelines have produced the occasional gusher in recent years, there have been even more blockages. Indeed, many of the blockages suggest that existing small-molecule and biologic modalities may be unsuitable for certain cancers. In any case, conventional methods for drugging oncogenes and screening compounds have been showing their limitations. Consequently, new methods are being explored. Biotechnology companies are constructing new discovery platforms and developing completely novel types of drugs. Some of the companies are convinced that innovative methods will show that supposedly undruggable targets are, in fact, druggable. And other companies are interested in showing that targets that have already been “drugged” can be, well, “better drugged.” Leveraging mRNA Strand Therapeutics is attacking cancer through the use of mRNA therapeutics combined with synthetic biology principles. The company’s platform is focused around addressing three problems with first-generation mRNA therapeutics, says Jake Becraft, PhD, Strand’s CEO and co-founder. The first problem is rapid degradation. Messenger RNA lasts only a day or two in cells. Strand is working with longer-lasting types of mRNA. These include self-replicating mRNAs that not only extend the lifetime of the molecule, but also increase the level of expression. The second problem is lack of specificity. According to Becraft, elevated levels of expression require the ability to control expression. “We design different sorts of genetic circuits which allow us to control where in the body or in which types of tissues the mRNA will be active,” he says. He adds that the genetic circuits also allow the mRNA to be inactive in nontarget tissues. Strand is addressing the third problem—toxicity—through computational biology techniques and innovative manufacturing approaches. “We’re able to make ultralow immunogenicity molecules of mRNA and actually control how they interact with the different immunological sensors within the body,” Becraft explains. “[Doing so] allows us to drop the immunogenicity down orders of magnitude lower than similar vectors.” Target-wise, Strand is currently working with well-validated targets, with the potential later to build out its pipeline with targets discovered in-house. For its first drug, Strand is targeting tumors with mRNAs encoded with cytokines that express at a high level inside the cell, leading to a systemic immune reaction against the tumor. Cytokines have been used against tumors before, but they have been delivered from outside the cell. Becraft says this is one of the first approaches using the cell machinery to produce cytokines inside the tumor cell from an mRNA therapeutic. The idea is to achieve a higher concentration and duration of exposure to the cytokines using the localized mRNA-mediated expression. Strand expects that its lead therapeutic candidate, an intratumorally administered mRNA packaged in a lipid nanoparticle, will enter the clinic in 2023. In a mouse model, treatment with this drug led to what Becraft calls “massive” suppression of tumor growth, with 60–80% of mice showing complete tumor eradication. In a follow-up study in which the drug was administered in combination with an anti-PD1 agent, 100% of mice were cured. The so-called undruggable target Some of the most attractive targets in the field of oncology are classified as “undruggable” due to a lack of potential binding pockets. Notable examples include RAS and MYC. To discover compounds that can bind to such targets, Perturba Therapeutics is using live-cell-based platforms for mammalian membrane two-hybrid (MaMTH) and split-intein-mediated protein ligation (SIMPL) assays. These platforms leverage artificial intelligence (AI)-augmented discovery technology from Cyclica, Perturba’s parent company. Pertuba Therapeutics, a Cyclica spinout from the University of Toronto laboratory of Igor Stagljar, PhD, addresses “undrugged cancers” by finding ways to modulate protein-protein interactions (PPIs). The company’s development workflow integrates Cyclica’s AI-augmented drug discovery platform with sensitive, live-cell drug screening assays from the Stagljar laboratory. At present, the company is advancing two inhibitors for EGFR triple-mutant non-small cell lung cancer and four programs targeting small GTPases for various intractable cancers. Perturba is using the assays to learn how to drug formerly undruggable targets, including protein-protein interactions (PPIs), and to shorten the discovery time from an average of three to five years to several months. “With these two live-cell assays,” says Igor Stagljar, PhD, chief science officer at Perturba, “we can take any druggable PPI and run it through Cyclica’s AI platform, identify compounds, and then see whether these compounds are inhibiting PPIs or not.” According to Stagljar, the assays offer a speed advantage. MaMTH and SIMPL select for permeability and toxicity of the compounds, avoiding a time- and labor-intensive follow-up procedure. Cyclica’s machine learning engines marry knowledge- and structure-based approaches to generate high-quality drug-target interaction (DTI) predictions. For example, Cyclica’s MatchMaker engine takes a panoramic view of the proteome and can systematically map DTIs to observed or inferred ligand-binding sites from experimentally determined protein structures and homology models. In addition, MatchMaker considers the polypharmacology of small molecules, looking at dozens to hundreds of off-target effects that could be exploited to optimize therapies for selectivity and off-target toxicity. MatchMaker provides the largest, fastest, and most predictive proteome-wide screening capability in the market, asserts Naheed Kurji, co-founder, president, and CEO of Cyclica and president and CEO of Perturba. “Perturba combines Cyclica’s AI drug design platform and drug discovery expertise with experimental live-cell phenotypic assays from the Stagljar laboratory at the University of Toronto,” Kurji adds. “[This approach] represents a paradigm shift in drugging targets that have been recalcitrant to other approaches, and it offers unparalleled speed.” Perturba is advancing two programs for osimertinib-resistant triple-mutant EGFR non-small cell lung cancer, and recently kicked off multiple programs targeting small GTPases mutated in pancreatic, colon, and non-small cell lung cancer. Antibody-guided protein degraders Orum Therapeutics develops tumor-directed targeted protein degraders (TPDs) to treat cancer. These TPDs reflect the company’s TPD2 approach, which addresses undruggable targets by combining the power of protein degradation and the precise tumor cell delivery mechanism of an antibody. The TPD2 approach is realized in several Orum platforms, including the Antibody neoDegrader Conjugate (AnDC) platform, which generates first-in-class antibody-drug conjugates. According to Orum, the AnDC platform offers an advantage over existing TPD platforms in that the delivery of protein degrader drug conjugates is limited to the target cell. Once in the cell, the mechanism of action is catalytic and can be used many times within the cell. Tumor-directed TPDs need to outperform conventional small-molecule TPDs with respect to efficacy pharmacokinetics, and safety, says Sung Joo Lee, PhD, CEO of Orum. He relates that the inspiration for Orum’s platform originated from the observation that protein degraders have the potential to address many undruggable targets. Although Orum’s scientists were intrigued by protein degraders, they recognized that existing approaches would face significant toxicity issues. For example, Lee was aware that a Phase I trial of protein degrader CC-90009 (Celgene/Bristol Myers Squibb) in acute myeloid leukemia and myelodysplastic syndrome had been suspended due to an “adverse change in the risk/benefit.” That insight led Orum to invest in antibody-drug conjugate tools for TPD delivery. “It was a steep learning curve,” Lee recalls. “The concept is simple, but technically there are a lot of things that need to be considered.” That process involved testing multiple methods of conjugation with multiple versions of the degrader on multiple types of antibodies to determine the best combination. Orum settled on GSPT1, a translation termination factor, as its first target. When GSPT1 is degraded, translational termination is disrupted and stress on the cell increases, leading to apoptosis. The company’s GSPT1 degrader, ORM-6151, is intended to treat CD33-positive acute myeloid leukemia. Orum plans to file an IND application for ORM-6151 next year. In solid tumors, Orum is developing a HER2/HER3-targeted protein degrader (ORM-5029) using pertuzumab as the linked antibody. In HER2-expressing cell lines, ORM-5029 showed 10- to 100-fold superior potency compared to HER2 ADCs or GSPT1 degraders. The virus-like drug conjugate Another company pioneering its own class of drugs is Aura Biosciences. Aura is developing novel biologic drugs called virus-like drug conjugates (VDCs) made of virus-like particles (VLPs) derived from human papillomavirus, linked with cytotoxic drug compounds. In this case, the VLP acts as the targeting system, as the antibody does in an antibody-drug conjugate (ADC), while also providing a secondary mechanism of action by stimulating an immune response. According to Aura’s CEO, Elisabet de los Pinos, PhD, the inspiration for the company’s platform was the relationship between viruses and cancers. She recalls, “I thought that we should use the affinity and avidity of viruses to cancer cells to basically deliver weapons against them.” Aura Biosciences develops virus-like drug conjugates for the treatment of multiple oncology indications. Virus-like drug conjugates, which consist of virus-like particles that can be loaded or conjugated with cytotoxic drugs, are derived from the human papillomavirus. They selectively bind to the modified and overexpressed heparin sulfate proteoglycans (HSPGs) that are present on many tumor types. Back in 2015, when Aura was founded, other companies were trying to develop the first viral therapies based on oncolytic viruses. Such therapies, however, rely on viral replication to infect cancer cells, require intratumoral administration, and lead to viral shedding. In contrast, VLPs are very safe as they are made only of the capsid of the virus and cannot replicate. The key innovation was to incorporate the tools of ADCs to create a VDC. “One of the advantages of this type of drug is that in an ADC you can usually conjugate five to seven cytotoxic drugs,” de los Pinos remarks. “With a VDC, we’ve been able to conjugate up to 400 molecules.” She adds that VLPs bind the cancer cell in a unique way. Typically, ADCs target receptors such as the epidermal growth factor receptor. But VLPs bind to heparan sulfate proteoglycans, a surface protein commonly overexpressed on cancer cells. This panel shows how Aura Biosciences generates virus-like drug conjugates (VDCs) by combining virus-like particles (VLPs; blue spheres) and cytotoxic drug molecules (orange circles). A single VDC can deliver hundreds of cytotoxic molecules conjugated to its capsid proteins. Besides inducing acute necrosis of tumor cells, VDCs can create a highly immunogenic milieu, triggering an antitumor-specific immune response. Aura’s lead product is a VDC for early-stage primary choroidal melanoma, a cancer of the eye. In the early stages of disease, the tumor is confined to the eye, and the standard-of-care treatment, radiotherapy, typically leaves the patient blind. “We have the clinical data now to show that it works,” de los Pinos asserts. “It preserves vision.” She adds that if it is administered early, it could, given its mechanism of action, “prevent patients from developing metastatic disease.” Aura is also planning a Phase I trial in non-muscle-invasive bladder cancer. This is another indication where a treatment exists, but leaves the patient with significant morbidity, with the loss of the bladder. De los Pinos declares that she is optimistic about the platform potential for VDCs. “We can deliver nucleic acids,” she explains, “and we’re going to be looking at the platform and the growth of the platform broadly, not limited by a particular cytotoxic payload.” Share

Cyclica Web Traffic

Page Views per User (PVPU)
Page Views per Million (PVPM)
Reach per Million (RPM)
CBI Logo

Cyclica Rank

  • When was Cyclica founded?

    Cyclica was founded in 2013.

  • Where is Cyclica's headquarters?

    Cyclica's headquarters is located at 207 Queens Quay West, Toronto.

  • What is Cyclica's latest funding round?

    Cyclica's latest funding round is Series B.

  • How much did Cyclica raise?

    Cyclica raised a total of $20.65M.

  • Who are the investors of Cyclica?

    Investors of Cyclica include GreenSky Capital, Chiesi Farmaceutici, Drive Capital, Grants4Apps, JLabs and 6 more.

  • Who are Cyclica's competitors?

    Competitors of Cyclica include Insilico Medicine, BenevolentAI, Exscientia, Standigm, Recursion and 13 more.

  • What products does Cyclica offer?

    Cyclica's products include Ligand Express and 1 more.

  • Who are Cyclica's customers?

    Customers of Cyclica include Merck KGaA, Yuhan Pharmaceuticals, Bayer, FMC and Cerevel Therapeutics.

You May Also Like

Insilico Medicine Logo
Insilico Medicine

Insilico Medicine develops a range of generative adversarial networks (GANs) and reinforcement learning approaches to identify protein targets, generate molecular structures with specified properties, and generate synthetic data. The company provides pharmaceutical and biotechnology companies with artificial intelligence solutions that transform the way innovative medicines and treatments are discovered and accelerate research and development. The company was founded in 2014 and is based in Hong Kong.

insitro Logo

insitro is a data-driven drug discovery and development company that leverages machine learning and high-throughput biology to transform the way medicines are created to help patients.

Atomwise Logo

Atomwise uses deep learning neural networks to help discover new medicines. Atomwise achieves results for new drug hit discovery, binding affinity prediction, and toxicity detection. Atomwise predicts drug candidates for pharmaceutical companies, start-ups, and research institutions. It is currently using computational drug design to design drugs against COVID.

Aria Pharmaceuticals Logo
Aria Pharmaceuticals

Aria Pharmaceuticals is a preclinical-stage pharmaceutical company that discovers and develops novel small molecule therapies for complex and hard-to-treat diseases

Standigm Logo

Standigm is an AI and systems biology-based startup that aims to expedite the drug discovery process. Standigm develops a computer modeling technology that learns medical and biological information and predicts the action mechanism of pharmaceutics in advance. This technology can improve the pharmaceutical development process by tailoring the application of previous know-hows, come up with possible combinations of pharmaceuticals, and optimize the selection of candidates and participants for clinical trials.


BERG is a Boston-based biopharma company focused on taking a bold "back to biology" approach to therapeutic discovery using its unique AI-based Interrogative Biology platform. This platform combines patient biology and artificial intelligence-based analytics to engage the differences between healthy and disease environments. The patient's own biology drives the platform's results and guides the company in the discovery and development of drugs, diagnostics and healthcare applications. Its platform utilizes patient population health data to bring actionable Patient Intelligence to precision medicine applications. This means faster discovery and development of treatments, more effective precision treatments for individuals as well as a reduction in costs to our healthcare systems.

Discover the right solution for your team

The CB Insights tech market intelligence platform analyzes millions of data points on vendors, products, partnerships, and patents to help your team find their next technology solution.

Request a demo

CBI websites generally use certain cookies to enable better interactions with our sites and services. Use of these cookies, which may be stored on your device, permits us to improve and customize your experience. You can read more about your cookie choices at our privacy policy here. By continuing to use this site you are consenting to these choices.