How to Accelerate the Search for Cancer’s Cure

There’s an experimental drug in the works that has been able to kill cancer cells. It’s called Dichloroacetate (DCA), and it’s being refined and perfected at the University of Alberta.

I’m no doctor or even a medical student, but this resonates with me. My grandfather died of lung cancer six years ago, and my grandmother died shortly after of pancreatic cancer.

Cancer is the leading cause of death in Canada, and according to Arbitrage Magazine, around 40% of women and 45% of men in Canada will develop cancer during their lifetimes. I’m sure there are many of us—too many—that have lost close friends and beloved family to cancer.

Drugs like DCA offer the glimmer of hope that so many people wish for: a chance to see a loved one return to a happier time. According to the University of Alberta, “as DCA is not patented, [Dr. Evangelos Michelakis] is concerned that it may be difficult to find funding from private investors to test DCA in clinical trials. He is grateful for the support he has already received from publicly funded agencies, such as the Canadian Institutes for Health Research (CIHR), and he is hopeful such support will continue and allow him to conduct clinical trials of DCA on cancer patients.”

As you may have gathered, DCA is far from perfect. It has made great strides in a few years, but it still has a ways to go before becoming a mainstream treatment.

Still, DCA is just one example of a drug that is still its beta stages, running through clinical trials and being tested for adverse effects. As the University of Alberta notes, it’s often difficult to find funding to keep research like the DCA project operating at full steam.

The startup costs and the operating costs required to keep clinical trials going are often too high to maintain, and slow down the progress of getting these drugs to shelves. That’s where London entrepreneurs Lijing Guo and Kartik Thakore hope to lend a hand.

“The main pain faced by a lot of people in the medical industry is that it costs a lot of time to manually data mine as well as a lot of money,” Guo explains. “With our two product lines Benedict and Danns, we hope to eliminate these time and financial constraints.”

In 2012, there is an abundance of data. Paco Underhill says in Why We Buy, “it is easier to collect data than to figure out what it means, much less map out what you can or should do about it.” AiMED, and software like it, creates opportunities to accelerate data mining and discover correlations within a chaotic set of data. 

“From all these correlations we can generate more sophisticated predictive algorithms (which essentially is what research is, trying to predict diseases better and quicker),” Guo elaborates. “In reference to clinical trials, what we can do is determine correlations between adverse events and drugs much faster and basically make sense of huge amounts of data quickly.”

AiMED’s programs aim to remove the huge startup costs faced by researchers, while making operating costs of data mining much more bearable. This will allow research projects like DCA to be able to do more while working with limited funds, and will accelerate the progress of many projects.

The flexibility of AiMED’s programs extends beyond the medical realm. “This workflow is not only limited to the medical industry,” Guo says. “Since data intake and data analysis is pervasive on all industries, we can quickly adapt our system to handle any industry. For example, we can analyze workflow data in a company and determine where bottlenecks are and find ways to make it more efficient.”

AiMED’s programs are currently being tested at the London Health Sciences Centre, and could very possibly remove a large part of the financial barrier that faces medical researchers. The company is seeking funding. These programs can also be calibrated and adapted to improve a company’s operations.

There are mountains of data now available to researchers and corporations. Companies like AiMED create products that are great catalysts in transforming raw data into useful information. This information can then be used to help us do awesome things.

Like cure cancer.