The term of art for the onscreen workspaces containing the sophisticated tools used by software developers and engineers is called the application programming interface (API).¹ It is where code is written, assembled, tested and revised.
Scientists working on various aspects of the human genome have recently expressed a comparable need for the development of specialized APIs to assist in a wide range of projects in their field.² A very informative and compelling piece about this by Prakash Menon (CEO of BaseHealth) entitled Developing An Application Programming Interface for the Genome was posted on VentureBeat.com on June 27, 2015. I will sum up, annotate, and then pose some questions that will not require their own specialized API to be considered.
The article begins by citing to a quote from Gholson Lyon, a genomics scientist at the Cold Spring Harbor Laboratory in New York, about the existing lack of a “killer app to interact” with DNA. He very recently raised this in another article entitled Apple Has Plans for your DNA by Antonio Regalado, posted on May 5, 2015 on MIT’s technologyreview.com. (The article appears in print in the July/August 2015 issue of MIT’s Technology Review.) This fascinating piece is about Apple’s new ResearchKit, an open source medical research framework for researchers to create iPhone apps for medical studies.³ Such an API technology, as Gholson described it, would make access and interpretation the genome universal, as well as make it more “programmable”. (I highly recommend reading both Menon’s and Regalato’s articles together in their entirety.)
Menon parses the three waves of genomics computing in the following manner:
- First Wave: During the 1990’s, this was the “sequencing era” when the human genome was first fully mapped. Rapid technological advances have enabled scientists to do this increasingly faster and cheaper. This has resulted in the emergence of the field of personalized medicine where diagnostics and treatments are designed by using more accurate genomic data of patients.
- Second Wave: The current state of genomic technologies with faster (termed “high-throughput”), more accurate, and less expensive genome sequencing for treating diseases.
- Third Wave: This is currently evolving with an emphasis is upon “integrating genomic data with other types of data”. This will soon permit advances such as “connect variants to environmental, lifestyle, dietary, and activity” data for the benefit of people who are well as well as those who are suffering from genetically based illnesses.
He believes that creating APIs for genomic science to be used by “developers everywhere” would put genomic data into a “wider context” and, in turn, enable new insights to be integrated into daily medical practice. Furthermore, timely innovations become more likely. As he sees this situation, the genome is a “database that we have constructed and curated”, and as such requires new interfaces to obtain the most value from its vast contents.
This also raises the prospect of genomic APIs becoming yet another addition in a growing conceptual framework dubbed the “API Economy”. (See Six Ways to Get a Grip on the API Economy by Serdar Yegulap, posted on InfoWorld.com on April 20, 2015, for a concise summary and the latest indicators of this emerging trend.)
Perhaps the Fourth Wave of genomics computing will be ushered in by a new generation of software and hardware developers who will “think about personalization at the molecular level”, and not require any further involvement by skilled bioinformatics specialists.
The author acknowledges the need for “privacy, security and the ethical implications” of his proposals, but believes that the potential benefits will result in these concerns being resolved.
Potential new software-driven innovations from Menon’s proposed genomic APIs include:
- Pharmacy systems that integrate with a patient’s genomic data so that prescribed drugs are the best choices for the individual, including a reduction in side effects.
- Improved organ and bone marrow donor matching systems.
- Optimizing food ingredients, supplements and diets, as well as activity and rest periods.
- Adding genomic data to “build worlds around each player” in online games.
In Menon’s assessment of these four waves, he sees the third wave presently “playing out” and the fourth wave arriving but “it’s not yet widely distributed”.4 Today, the first genomic APIs are starting to appear. In the US, developers are immersing themselves in the key concepts of molecular biology to more fully enable their work. He further predicts that in the next wave of “billion-dollar businesses” will involve the human genome, only some of which will be specifically in health care.
As to the needs and desires of individuals concerning their genomic data, Menon believes that they want to use it for their own advantage, combine and compare it with the data of others, and to create “wholly new capabilities”. Indeed, we have seen already numerous applications of genomic data that could not possibly have been imagined by James Watson and Francis Crick, the Nobel Prize winning discoverers of the structure of DNA.
My questions are as follows:
- Should genomics APIs be developed and circulated on a fully open source basis? If so, what intellectual property issues may still arise and how, and by whom, should they be settled, arbitrated or litigated?5
- Will developers from other fields, as well as non-affiliated scientifically curious individuals, be drawn into using the APIs for original research and development projects?
- What, if any, scientific, ethical and regulatory guidelines might be needed as oversight for genomic APIs?
- Will such APIs lead to a surge in startup company formation in genomics and other related biotechnology businesses?
- Are there unique elements of design and functionality in genomic APIs that might lead to innovations in API development in other fields? That is, is there some form of beneficial and/or symbiotic effect that may emerge?
1. An API for the depository of TED Talks was recently discussed in the May 13, 2015 Subway Fold post entitled IBM’s Watson is Now Data Mining TED Talks to Extract New Forms of Knowledge.
2. See also the June 12, 2015 Subway Fold post entitled Scientists Are Developing Massive Storage Systems Based Upon Minute Amounts of DNA and Polymers for a related story on using DNA as a dramatically different information storage medium.
3. For a full exploration of current efforts and proposals to use smartphones as medical platforms, please see the March 3, 2015 Subway Fold post entitled Book Review of “The Patient Will See You Now”. To follow this area of development on a daily basis I highly recommend following the book’s author, Dr. Eric Topol, on Twitter at @EricTopol.
4. This point invokes master sci-fi writer William Gibson’s often quoted line “The future is here already — it’s just not very evenly distributed.”
5. The United States Supreme Court declined to hear an appeal of a case involving Google and Oracle concerning the ownership of an API . See Supreme Court Declines to Hear Appeal in Google-Oracle Copyright Fight by Quentin Hardy, in the June 29, 2015 edition of The New York Times for full coverage.