Jan 19 2016

Cancer ‘Moonshot’ needs Informatics

by at 10:33 am

Many of us who work in the interface of Cancer Clinical Research and Biomedical informatics were thrilled to hear about the cancer moonshot program from President Obama announced in his final State of the Union Address on Tuesday, Jan 12’16.

VP Biden, the nominated leader for this effort, has pledged to increase the resources available to combat the disease, and to find ways for the cancer community to work together and share information, the operative word being “share” (after ‘resources’).

In this post, I briefly review (by no means comprehensive; just a Saturday morning project while brunch cooks in the Instant pot) four thematic areas where informatics is already playing a key role to help realize cancer moonshot goals and identify challenges and opportunities.

  • Immunotherapies: Recent approvals of ipilimumab (Yervoy), sipuleucel-T (Provenge), Nivolmab (Opdivo) and Pembrolizumab (Keytruda) represent important clinical advances for the field of active immunotherapy in oncology and for patients with melanoma and prostate cancer, respectively. Immunoinformatics has played a critical role in B- and T- cell epitope prediction during the course of development of these therapies. New predictive computational models to describe the time-dependent relationships of cancer, immunity, and immunotherapies have emerged over the last few years. Using next gen sequencing approaches such as whole genome, exome and RNA sequencing, it is now possible to characterize with high accuracy the individual set of Human Lymphocyte Antigen (HLA) alleles of an individual patient leading to personalized immunotherapies. The biggest challenge in immunoinformatics arises from the routine sequencing of individual human genomes. We need new informatics tools to study the impact of natural genomic variation on the immune system and how to tap into it for new therapies. Click here for further reading.
  • Precision medicine: President Obama’s precision medicine initiative and the $215M investment have brought precision medicine to the forefront of many organizations. The cost of cancer care is estimated at $200 Billion each year and only on the rise as our population increases and lives longer. Many pundits see Precision Medicine as a way to deliver value-based cancer care. Thanks to high throughput technology, including genomic testing of each tumor, and each patient’s inherited DNA— along with proteomics in the future—oncologists are able to tailor regimens for gene mutations in each patient thus avoiding high cost of drugs that may not work. A key informatics challenge is to figure out which of the thousands of mutations in a patient’s tumor are drivers or actionable markers. There is a race in both academic and commercial space to develop software that will tease out the ‘drivers’ from the ‘passengers’. Furthermore, mutations have to be categorized by levels of evidence: high evidence – where the gene mutation has been tested in a randomized controlled trial (RCT) setting, medium evidence – retrospective gene mutation analysis of RCTs- and finally low level evidence with pre-clinical data only on the mutation. We need better evidence modeling approaches to categorize actionable mutations if clinicians are to use these in routine patient care. Click here for further reading.
  • Cell free DNA/blood tests: While molecular profiling in solid tumors remains routine practice in cancer diagnostics, modern technologies have enabled detection of biomarkers in stray cells, exosomes and traces of DNA in blood and other body fluids. This offers a low cost method to obtain cancer-profiling data for diagnosis and treatment when invasive tissue biopsies may be clinically difficult. While technologies and informatics methods for detecting very small amounts of tumor DNA are on the rise, there are many biological issues that need to be addressed. If the tumor cell did not shed a single piece of variant DNA, even the most sensitive technology will be unable to detect it. Commercial interest in this space is enormous. The Genomics/Informatics Company Illumina has just launched a new startup, GRAIL, in collaboration with Jeff Bezos and Bill Gates to develop a single blood test that could detect cancer early. Now, that is a moonshot goal! Click here for further reading.
  • Organizing cancer data: Now on to my favorite topic of organizing cancer data to power new discovery. Secondary use of EHR data for observational studies is improving through clinical research networks. As large biorepositories linked to electronic health records become more common, informatics is enabling researchers to identify cohorts that meet study criteria and have requisite consents.
    Modified from Thomas Wilckens, MD

    Modified from Thomas Wilckens, MD

    While there have been significant efforts in sharing molecular data sets publicly, less progress has been made on sharing healthcare data. Many standards exist today to facilitate data sharing and interoperability. We need more training of existing standards to consumers (app developers, scientists) of standards. We also need a comprehensive knowledgebase ecosystem that supports federated queries across cancer subtypes, risk, molecular features, diagnosis, therapy and outcomes at an individual level to advance biomarker discovery and better clinical decision support. Real-world Big Data on claims, outcomes, drug labels, research publications, clinical trials are now available and ready to be linked and analyzed to develop better cancer treatments. NCI’s TCGA and Rembrandt, Georgetown Lombardi Cancer Center’s G-DOC, Global Alliance for Genomic Health (GA4GH), ASCO’s CancerLinQ are all efforts in this direction. Let’s unleash cancer big data in effective ways to collectively make the moonshot program a reality! Click here for further reading.

Programs such as the cancer moonshot are a journey, not a destination and if directed appropriately, can inevitably better the practice of cancer medicine.

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Nov 03 2015

Quantified Self, GenomeFirst and a trip to the White House – A busy week for Biomedical informatics

by at 11:22 pm

“You are over pronating!” bleeps Bluetooth enabled, sensor-infused smart socks just 10 minutes into your daily running routine.

Or, “check your blood pressure, temperature and heart rate using Scanadusm, with no cuffs, in just 15 seconds!” quips Kevin Maloy of MedStar Institute for Innovation during our fourth annual Georgetown Biomedical Informatics Symposium on October 16, organized and hosted by the Innovation Center for Biomedical Informatics. Emerging trends in informatics and health IT were demonstrated and discussed with over 350 attendees from academia, industry and government. The event benefited from strong support of institutional and industry sponsors. Find out more about the symposium’2015 here. I present Cliff Notes version of four major themes here for your quick browsing.

  1. Quantified Self

We are increasingly wearing bands to track how much we move, strapping on watches to listen to our heartbeat, and logging what we eat and drink. The underlying proposal is that describing ourselves with these numbers will put healthcare back in the hands of people. Will the “quantified self” become a major driver in how diseases are prevented or treated? This is one of the intriguing questions that our symposium explored.

Informatics opportunity: Design in healthcare is an opportunity to improve signal and reduce noise in a system that is over stretched, under utilized and very expensive.

  1. EHRs and other emerging health technologies

Digitized health is a dream come true for many. But are electronic health records (EHRs) actually getting in the way of physician productivity? At our symposium, Mike Hogarth of University of California, Davis presented results from a survey of 410 internists that estimated that 42 minutes are lost each day by physicians due to EHRs. About 80% of key clinical data are in the form of unstructured narratives – a mess he referred to “dirta,” instead of data. This information requires enormous quality control, structuring, and integration – a reality that raises the question: can practice-based evidence be generated through retrospective studies of EHR datasets?

Informatics opportunity: Nigam Shah of Stanford University suggested that enterprise wide data governance at hospital systems, or a green button function within EHRs, could help clinicians use aggregate patient data to support decisions at the point of care. Ben Schneiderman of University of Maryland demo’ed EventFlow, a tool for visual analysis of temporal events within patient records to enable advanced healthcare discovery. Zak Kohane of Harvard University, in his keynote lecture, cited clinical research data integration software such as i2b2, tranSMART, and SMART Health IT apps as solutions to the “dirta” problem in healthcare innovation.

  1. Trends in Precision Medicine

A lot of the excitement at the symposium – amplified by the talks on targeted therapies in pancreatic cancers and a panel discussion on Next Generation Sequencing (NGS) in the clinic – was focused on Precision Medicine.

Mike Pishvaian of Georgetown University and Dr. Jon Brody of TJU discussed PANCan’s “Know your tumor” program. This program has found that 43% of patients had actionable findings from molecular profiling, resulting in modified treatment recommendations and better responses.

Regeneron’s Rick Dewey asked a provocative question: what if everybody’s genome was available in his or her medical record? Rick and Marc Williams of Geisinger described a collaboration between Regeneron and Geisinger to use EHRs and exome sequencing data from over 200,000 individuals for faster drug discovery. It was a treat to hearabout Geisinger’s GenomeFirst initiative, which is implementing genome inference engines – clinical decision support and predictive models to enable Precision Medicine in a unique way with teams of clinicians, genetic counselors, nurse practitioners and informaticians.

No scientific symposium is complete without an award! The (iPAD winning) best poster award went to Ao Yuan, graduate student in Biostatistics at GU for his work on a semi parametric model for the analysis of patient sub-groups in precision medicine trials.

The Precision Medicine journey is underway, and is already improving medicine. Informaticians are vital to this journey. More work is needed to collect the right patient cohorts for research, to identify the right markers to test, and to develop the appropriate targeted therapies.

The Symposium explored what’s next for all of us in this important journey?

Informatics opportunity: Curating evidence of biomarker association with drug response, novel data wrangling approaches to extract and analyze useful clinical and genomic data to drive new hypothesis generation and clinical decision support, and data science approaches to connect genotypes to phenotypes are a few of many opportunities for informaticians to meaningfully participate in the precision medicine revolution.

  1. Security, Privacy and Trust principles for patient-centered studies

The symposium was a perfect lead-in to a great roundtable discussion on a much-needed security framework for President Obama’s Precision Medicine Initiative at the White House OSTP. I was humbled by the discussion with experts in cyber security, patient privacy, trust principles, and data breach. Will “white hat hacking” help? How can we use it in the context of protecting healthcare data and participants from willful misuse?

Informatics opportunity: DJ Patil, US Chief Data Science Officer emphasized the need for IT teams to focus on data infrastructure, auditing and monitoring of patient genomic data, data transmission and access infrastructure, including tiered data access.

It is so gratifying to see informaticians providing thought leadership across the full spectrum of clinical research and care. Let’s continue the conversation – find me on e-mail at subha.madhavan@georgetown.edu or on twitter at @subhamadhavan.

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