For years chemotherapy has been one of most common methods of treating cancer, but it comes with the substantial drawback of effecting healthy cells in the same way that it effects cancerous cells. This means that a subject of chemotherapy can experience great pain and sickness as a side effect of the potentially lifesaving treatment. A solution to this problem is targeted therapy, or the use of drugs, which more specifically targets cancer cells while ignoring nearby healthy cells. Targeted therapy is dependent on drugs which are tailored to inhibited cancer cell growth, proliferation, and viability, by targeting proteins found in the cells.
As of yet targeted therapy has been for the most part a supplement to more traditional chemotherapy. It can be effective, but not enough to stand on its own. One problem that is holding back targeted therapy is that many patients respond to these drugs differently and a personalized treatment must often be created on a case-by-case basis. Traditional live testing - which relies on trial and error - has been inefficient in identifying which drugs work best for which patients, but computer software derived from big data analysis may be able to make this process more efficient, and increase the effectiveness of targeted therapy.
The Johns Hopkins Based Bioinformatics firm InSilico Medicine has developed an algorithm which has the potential to do just that. "The algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues," said study author Artem Artemov. "It then predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormal, tumor promoting pathways."
To validate the effectiveness of the algorithm, it was tested against the predicted effectiveness of five drugs and seven different cancer types. The percentage that responded to the drug treatment displayed a significant correlation with the group that scored high on the algorithm, showing that this could be a quicker and more effective way to reach the same results.
"This could herald a big improvement in the quality of life of cancer patients as they undergo treatment," said Qingsong Zhu, Chief Operating Officer of InSilico Medicine, Inc. "The pain and sickness caused by chemotherapy has long been thought of as a necessary evil, but if we can more effectively tailor targeted therapy to the patient we can rely on it more than we already have. Targeted therapy may never replace chemo entirely, but we can move toward making it a bigger piece of the pie of cancer treatment, and allow patients to live more comfortable lives as they fight cancer."
The findings of this study will be presented at the 2015 Basel Life Science Week, a meeting of the minds on the cutting edge of life science held in Basel Switzerland from September 21st to the 24th as part of a forum on aging and drug discovery co-chaired by Alexander Zhavoronkov of Insillico Medicine and Bhupinder Bhullar of Novartis Pharmaceuticals.
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About Insilico Medicine
Insilico Medicine is a Baltimore-based company utilizing advances in genomics and big data analysis for in silico drug discovery and drug repurposing for aging and age-related. The company is utilizing the GeroScope™ and OncoFinder™ packages for aging and cancer research. Through internal expertise and extensive collaborations with brilliant scientists, institutions, and highly credible pharmaceutical companies, Insilico Medicine seeks to discover new drugs and drug combinations for personalized preventative medicine. For more information on Insilico Medicine, Inc. please visit http://www.insilicomedicine.com.