Cancer patients are often treated with chemotherapy and various types of drugs, but the results of these treatments aren’t uniform in effectiveness, which is why it’s imperative for hospitals, clinics, and doctors to make the best drug treatment choices for each individual patient. Getting drug therapies right is an area where digitized genomics data can help.
“The technique that we use for this is genomic sequencing,” explained Dr. Jurgi Camblong, cofounder of Sophia Genetics, a provider of artificial intelligence that pinpoints the genomic code mutations behind cancers and rare disorders to assist physicians and healthcare institutions in prescribing optimal drug treatments for their patients.
“What the technology does is spot variations in different genetic codes so we can use historical data that aids in prescribing the best combination of drugs to treat a particular cancer or condition in an individual patient,” said Camblong.
An example is lung cancer, where treatment in the past was prescribed based upon the patient’s tissue type instead of on a particular genetic mutation. By using genetic sequencing and mutation detection instead of tissue analysis, physicians can now identify the genetic events that caused the condition in the first place, and not just treat symptoms.
The GLP aggregated and excerpted this blog/article to reflect the diversity of news, opinion, and analysis. Read full, original post: How AI and next-generation genomic sequencing is helping cancer patients