The medical field has been making considerable advances in cancer research. The number of approved therapies continues to increase at an accelerated pace. Thanks to bold investments and innovation, patients are living longer with the disease than ever before. But greater treatment options and a higher number of patients living longer means a vastly greater dataset for researchers and doctors to draw inferences from. What to do with this cancer-specific “big data”? The answer is, of course, to merge big data and cancer research. Now is the perfect time to explore more solutions through big data oncology.

How Big Data is Transforming Oncology

To stay ahead in the fight against cancer, institutions are undergoing a digital transformation. Big data is at the core of this technological revolution. Its usage involves tapping into large pools of clinical, biological, and genomic information. As a result, researchers have been able to make advances in treatment and diagnosis.

“We are now capable of collecting amounts of data that we never thought were possible before,” said Dr. Bissan Al-Lazikani, head of data science at The Institute of Cancer Research. “We are starting to really understand the complexities of cancer at a level that is unprecedented. This has really revolutionized the way we do drug discovery.”

Using big data in cancer research is needed for better machine learning. As technology systems gather more data and profile more patients, the smarter the computer algorithms get.  Artificial intelligence allows medical institutions to gain real-time insights. Such insights from big data oncology can ultimately improve cancer care and outcomes even more.

Carmela Dantas Barbosa discusses Decades of cancer research has created a huge data pool - and a need for big data oncology.
The marriage of big data and oncology means greater opportunity for treatment advances.

Leaders in Using Big Data for Immuno-Oncology

In 2017, biotech company F1 Oncology raised $37 million for its work in immuno-oncology. Last January, the company announced an additional $10 million investment for two CAR-T products. These will be tested on patients with refractory, metastatic cancer. Big data will power the precision medicine-directed trial.

The company uses analytics for big data in cancer research instead of building off assumptions. This allows F1 to freely innovate and take more intellectual risks. Also, the company’s infrastructure and data transfer platform allow a wider selection of CAR constructs. This helps in choosing optimal compositions from thousands of options.

Gregory Frost, Ph.D. Chairman & CEO of F1 Oncology is hopeful about the company’s contribution to immuno-oncology. “The clinical investigation of these first tumor microenvironment-controlled CAR-T products, each with unique targets and activating domains and properties, will advance the field towards the objective of making CAR-T more broadly applicable to patients suffering from solid tumor malignancies,” he said.

Another company leveraging big data and artificial intelligence is Sophia Genetics. Along with DNA Sequencing, big data and AI help detect certain types of cancer. Results are then compared using machine learning. Through this process of big data oncology, patients are able to receive suggested treatment.

Mixing big data and cancer research has yielded positive results.
Big data and cancer research have come together to produce great strides in treating the disease.

Recent Milestones in Cancer Research

In the past couple of years, there are more choices for treating a range of cancers.  And there’s no stopping the growth of treatment options. In fact, the U.S. market for oncology therapeutic medicines will reach as much as $100 billion by 2022.

With the rise of immuno-oncology, researchers are testing different combinations of immune-boosting treatments. Combinations include either several similar drugs or drugs and older treatments like chemotherapy. These experiments can lead to more innovative developments.

The entry of novel cures guided by precision medicine is also notable.  Chimeric Antigen Receptor T-cell  (CAR-T) treatments resulted in 70% or higher cure rates for previously untreatable blood cancers.

All of this stems from the merging of big data and cancer research.

The Promising Future of Big Data Oncology

The healthcare industry is embracing the use of technology for finding cures. Even tech giant Google is exploring the medical applications of artificial intelligence.  This indicates that digital solutions have helped speed up progress in the field. With more innovations by bold institutions, society can have a better understanding of cancer treatment.

Melding big data and cancer research involves more than just processing the info according to Carmela Dantas Barbosa
Big data oncology means not only processing all the cancer research but sharing it as well.

Experts must look at solutions on how to widen the acceptance of data sharing. This can take cancer research to the next level. Right now, more and more patients are opening up to the idea of releasing their data for analysis. Despite the negative perceptions, this can help researchers create better-personalized treatments.

The use of mobile apps and wearable devices to gather information is also likely to increase in the coming years. These can track activities of cancer patients and even help make day-to-day management easier.

Analysts say that medical applications of big data and cancer research remain in their infancy. Still, if improvements continue at the rate they’re currently going, the future of big data oncology seems promising. More and more patients will be able to get individualized, less invasive treatments that can improve their odds of survival.

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