We always hear about cures for cancer, but what does that really mean? Cancer is not one disease and there will never be one silver bullet treatment. It is a blanket term for a potentially unlimited number of unique diseases that share one common feature: uncontrolled cellular growth.
Cancer is a leading cause of death worldwide and will soon be the leading cause of death as our population continues to age. Almost everyone has had a friend or family member who has had cancer or has died from cancer.
Treating cancer is tricky because patients with seemingly similar cancers can have wildly different responses to the same treatment. Every individual’s cancer is unique and his or her treatment should also be. Until recently, sequencing individual cancer genomes was prohibitively expensive.
Just 15 years ago, it cost $2.7 billion to sequence the first human genome. A decade ago, the cost was still in the 10s of millions of dollars. In 2016, we are looking at about $1,000 to sequence a genome and it should be less than $100 quite soon. The cost of sequencing is decreasing significantly faster than Moore’s law, its computational sibling.
Of course, sequencing the genome is only half the solution. We also need to analyze and interpret the genomes to match patients with the best treatments.
That’s where big data comes in.
Machine learning has made massive advances in the last decade due to new algorithms and increases in computing power.
We can finally crunch the huge amount of genomic data being produced and match drugs to the specific vulnerabilities of an individual’s cancer.
These personalized and tailored therapies target specific mutations of the cancerous cells so healthy normal cells can survive unscathed. A welcomed change from the traditional multiple rounds of combination chemotherapy, which are toxic to normal cells that divide quickly such as hair and those lining the digestive tract and in bone marrow.
Machines are also way better than doctors at sifting through the massive flood of genomic studies coming out everyday. Doctors are incredibly busy and can’t spend all day reading through all the latest studies in genomics. No human ever could, but machines are built for it.
By comparing a patient’s unique cancer genome to a database of millions of cancer research papers, Tempus can deliver a report to doctors with a tailored treatment plan based on the most relevant scientific literature and clinical trials.
We are empowering physicians to make real-time data-driven decisions based on a patient’s unique pathology. There are hidden patterns in the vast trove of genomic cancer data and we are on the verge of finding them.
It’s about time.
To learn more about how Tempus can help, please reach out here.