Big Data Archives - Sanford Burnham Prebys
Institute News

The Cancer Letter covers collaboration between Sanford Burnham Prebys and the National Cancer Institute to precisely prescribe cancer drugs

AuthorGreg Calhoun
Date

May 14, 2024

The May 10 issue of The Cancer Letter details a recent publication explaining the investigation of a new AI tool that may be able to match cancer drugs more precisely to patients.

The Cancer Letter—a news organization and weekly publication based in Washington, D.C., that focuses on cancer research and clinical care—included an article in its May 10 issue about a partnership between scientists at Sanford Burnham Prebys and the National Cancer Institute (NCI).

Authored by Sanju Sinha, PhD, assistant professor in the Cancer Molecular Therapeutics Program at Sanford Burnham Prebys, and the NCI’s Eytan Ruppin, MD, PhD, the “Trials & Tribulations” feature describes a first-of-its-kind computational tool to systematically predict patient response to cancer drugs at single-cell resolution. The study regarding this new tool was published on April 18, 2024, in the journal  Nature Cancer.

The Cancer Letter was founded in 1973 and focuses its coverage on the development of cancer therapies, drug regulation, legislation, cancer research funding, health care finance and public health.

Institute News

NIH director highlights Sanford Burnham Prebys and National Cancer Institute project to improve precision oncology

AuthorGreg Calhoun
Date

May 9, 2024

The NIH director’s blog features a recent publication detailing the study of a new AI tool that may be able to match cancer drugs more precisely to patients.

Monica M. Bertagnolli, MD, director of the National Institutes of Health (NIH), highlighted a collaboration between scientists at Sanford Burnham Prebys and the National Cancer Institute (NCI) on the NIH director’s blog. Bertagnoli noted advances that have been made in precision oncology approaches using a growing array of tests to uncover molecular or genetic profiles of tumors that can help guide treatments. She also recognizes that much more research is needed to realize the full potential of precision oncology.  

The spotlighted Nature Cancer study demonstrates the potential to better predict how patients will respond to cancer drugs by using a new AI tool to analyze the sequences of the RNA within each cell of a tumor sample. Current precision oncology methods take an average of the DNA and RNA in all the cells in a tumor sample, which the research team hypothesized could hide certain subpopulations of cells—known as clones—that are more resistant to specific drugs.  

Bertagnoli said, “Interestingly, their research shows that having just one clone in a tumor that is resistant to a particular drug is enough to thwart a response to that drug. As a result, the clone with the worst response in a tumor will best explain a person’s overall treatment response.” 

More of Bertagnoli’s thoughts on this collaboration between scientists at Sanford Burnham Prebys and the NCI are available on the NIH director’s blog

Sanju Sinha, PhD, assistant professor in the Cancer Molecular Therapeutics Program at Sanford Burnham Prebys, is the first author on the featured study. 

Institute News

Media coverage of AI study predicting responses to cancer therapy ranks top 5% among published research

AuthorScott LaFee, Susan Gammon and Greg Calhoun
Date

April 29, 2024

Last week, Sanford Burnham Prebys and the National Cancer Institute shared findings regarding a first-of-its-kind computational tool to systematically predict patient response to cancer drugs at single-cell resolution.

Many news outlets and trade publications took note of this study and the computational tool’s potential future use in hospitals and clinics. This coverage placed the paper in the top 5% of all manuscripts ranked by Altmetric—a service that tracks and analyzes online attention of published research to improve the understanding and value of research and how it affects people and communities.

The results from the highlighted study were published on April 18, 2024, in the journal Nature Cancer.

“Our goal is to create a clinical tool that can predict the treatment response of individual cancer patients in a systematic, data-driven manner. We hope these findings spur more data and more such studies, sooner rather than later,” says first author Sanju Sinha, PhD, assistant professor in the Cancer Molecular Therapeutics Program at Sanford Burnham Prebys.

Here are a few of the venues that helped spread the word about this research: 

  • AP News: “Researchers … suggest that such single-cell RNA sequencing data could one day be used to help doctors more precisely match cancer patients with drugs that will be effective for their cancer.”
  • Politico, fourth story in Future Pulse newsletter: “Our hope is that being able to characterize the tumors on a single-cell resolution will enable us to treat and target potentially the most resistant and aggressive [cells], which are currently missed.”
  • NIH.gov: “The researchers discovered that if just one clone were resistant to a particular drug, the patient would not respond to that drug, even if all the other clones responded.”
  • Inside Precision Medicine: “The model was validated by predicting the response to monotherapy and combination treatment in three independent, recently published clinical trials for multiple myeloma, breast, and lung cancer.”

“I’m very pleased with how many news outlets covered our work,” Sinha says. “It is important and will help us continue improving the tool with more data so it can one day benefit cancer patients.”

Institute News

Why share data from clinical trials? SBP’s CEO Perry Nisen weighs in

AuthorKristen Cusato
Date

September 26, 2016

Sharing clinical trial data with researchers who weren’t involved in the original study maximizes the value of patients’ participation, allowing more research questions to be answered than those of the original study. However, figuring out what data should be shared and how to do it has proven to be difficult.

The most recent issue of the New England Journal of Medicine devoted three perspective articles and an editorial on the topic of data sharing. Perry Nisen, MD, PhD, CEO of Sanford Burnham Prebys Medical Discovery Institute (SBP) and his colleagues discuss efforts to share clinical trial data and the hurdles that investigators still face.

“One of the risks is that there will not be a single simple system where these data can be accessed and analyzed, and the benefits of meta-analyzing data from multiple studies will be limited by cost and complexities,” said Nisen.

GlaxoSmithKline was a first mover in making anonymized patient-level data available from clinical trials. In 2013, the Clinical Study Data Request was established. The site is now managed by the Wellcome Trust, an independent, non-sponsor safe harbor, and includes more than 3,000 trials from 13 industry sponsors.

 

Nisen answers key questions about the future of clinical data sharing:

Q: Why should research sponsors go to the expense of sharing data?

Clinical data sharing is the right thing to do for science and society. First, it increases transparency of clinical trial data. It maximizes the contribution of trial participants to new knowledge and understanding. This allows researchers to confirm or refute findings, and enables them to generate other hypotheses. Scientific research globally is moving toward more transparency in clinical trial reporting and this is an important step toward building trust.

 

Q: What are the challenges to a one-stop shop for sharing all clinical trials data?

Protecting patient privacy and confidentiality is a major concern. Also, ensuring the data are used for valid scientific investigation, preventing erroneous claims of benefit or risk, and controlling the cost associated with anonymizing data in formats investigators can utilize effectively.

Other challenges inherent in data sharing include patient consent, data standards, standards for re-use, conflicts of interest, and intellectual property.

 

The editorial, also co-authored by Frank Rockhold, PhD, professor of biostatistics and bioinformatics at the Duke Clinical Research Institute, and Andrew Freeman, BSc, head of medical policy at GlaxoSmithKline, is available online here.

Institute News

Will you be part of the largest-ever clinical research study?

Authorjmoore
Date

March 23, 2016

It’s called the Precision Medicine Initiative (PMI) Cohort Program, and it was just announced in February by President Obama. If you join the cohort (group of subjects tracked over a long period of time), you can help researchers improve precision medicine, in which doctors select the treatments and preventive strategies that will work best for each patient. This program is just one component of the larger Precision Medicine Initiative announced during last year’s State of the Union address.

What’s the goal? According to NIH Director Francis Collins, the cohort program “seeks to extend precision medicine to all diseases by building a national research cohort of one million or more U.S. participants,” all enrolled by 2019.

Why recruit so many people? Since the program is intended to benefit people affected by many diseases and conditions, it must include large, representative samples of people with each type. Large samples increase the likelihood that studies using these data will find new associations and interactions among genes, environmental factors, and disease risk.

What will participants do? Volunteers will share their health records, complete surveys on lifestyle and environmental exposures, undergo a physical, and provide a biological sample (e.g. blood) for genetic testing.

How will people benefit? Participants will be considered partners in research—they’ll have access to their genetic data and, where possible, how their genes, surroundings, and habits affect their health. They’ll also have a say in how the research is conducted and what questions it should address.

Who’s running it? The NIH is overseeing the whole program, but it will be directly run from multiple institutions (which are currently being selected). The pilot phase will be led by Vanderbilt University and Verily (formerly Google Life Sciences).

What’s the cost? $130 million has been allotted in this fiscal year, but more money will be needed to keep the program going.

Should I be excited about it? Maybe. Some leaders in the health field have criticized the program for throwing money at the latest big thing instead of more low-tech problems like unequal access to healthcare, but such a huge data resource is bound to lead to answers to many important questions. 

What are the challenges for the PMI?

  • Scale—The program will generate one of the largest clinical databases yet, and it’s not clear how difficult it will be to make systems that can store and analyze it.
  • Privacy—Data will be anonymized, but keeping the health information of a million people in one place might represent a target for hackers sophisticated enough to figure out participants’ identities.
  • Interoperability—Health record systems are notoriously incompatible with one another. Though the PMI also has provisions to correct this, it likely won’t be a quick fix.

How can I sign up? Enrollment has not yet begun, but the NIH will announce when the public can get involved. So stay tuned…