How do you know that your mindfile will not be deleted, either on purpose or by accident? What would you do if your mindfile is stored in memory and not allowed to run? How would you know that you are not being run? Is not running the equivalent of being dead? How will you know that you are getting the processing power and bandwidth in your contract when reality is simulated and hardware test results could be simulated too?
There are at least two levels of challenges to address, akin to current physical world needs, first, survival needs and second, needs and rights when interacting with others.
Establishing rights for mindfiles
There will need to be ways to assure basic ‘human’ rights in a potential era of uploading brains to digital software files. There could be many misuses of massive databanks of mindfiles: they could be deleted at will (digital genocide) or by mistake by careless ISPs/data center managers, sold, kidnapped, copied, bred, hiveminded or discriminated against via less bandwidth and processing power. If the reality experienced by mindfiles is simulated, how would anyone know that the virtual reality they experience is the one they want to experience? A code or key could be created so that individual mindfiles could not be copied without the owners permission, agreement or knowing; perhaps like the telomere-shortening system used by biological cells. Pervasive externally run audit software could maintain lists of mindfile citizens (a future role for the nation-state) and periodically query each mindfile to determine its status and whether it is running. As usual, the white hats would need to stay ahead of the black hats.
Reducing naked Darwinism
With less transparency and social pressure, it is possible that the behavioral smoothing that has arisen in contemporary society would dissolve. Codes of conduct for mindfiles could be developed, probably with a much heightened awareness and refinement of the respectful treatment of consciousnesses. If virtuality is 100% sousveilled, this should not be a problem. In addition, mechanisms such as barriers, permissioning tiers and firewalled gardens could arise to prevent stronger minds from terrorizing and controlling weaker minds or different minds. The real goal would be to rearchitect social pressure in ways that are continually empowering to all individuals. Some mindfiles may prefer heavily controlled virtual environments, others may wish to venture onto the interstitial wildnets.
Sunday, June 28, 2009
Mindfile deletion
Sunday, June 21, 2009
Health Literacy Toolkit
With one key life sciences focus shifting to health as opposed to healthcare (as HealthCamp founder Mark Scrimshire exhorts) and to preventive, predictive health management as opposed to therapy and treatment, there should be the concept of a health literacy toolkit that would be a component of standardized knowledge, such as how to write, drive or get a job.
Definition of health literacy
Surprising but emblematic of the traditional health mentality (e.g.; treat illness) is the prevailing definition of health literacy…”a patient’s ability to acquire and understand information about a condition and options once diagnosed…” Moving into the preventive era, the definition of health literacy needs to shift from being backward-looking to forward-looking. Having health knowledge ahead of time could inform behaviors to prevent, slow or lessen the development of disease. Health literacy should be a general set of knowledge for everyone to know, not related to a condition once a patient has it.
Gap between health literacy and demand for health information
A U.S. Department of Health and Human Services (HHS) study finds that only 12% of adults have proficient health literacy (p. 26); that nearly 9 out of 10 adults may lack the skills needed to manage their health and prevent disease.
The biggest reason for low health literacy could be a lack of appropriately accessible and presented health information.A Pew Internet Study “The Social Life of Health Information” in June 2009 finds that 61% of U.S. adults are looking for health information online. The gap between health literacy and the demand for health information suggests that there is a substantial opportunity for a range of health information services and management tools, many of which could be fee-based such as the LIVESTRONG nutrition and exercise management program.
Health literacy toolkit
What should be the components of a standard health literacy toolkit? Many professionals (e.g.; physicians, academicians, etc.) believe that even HDL/LDL cholesterol information is too complicated for the lay public, but this just cannot be correct. When simple numeric information is presented clearly, people of any background and capability are often quite able to understand it and take action. For example, when utility bills started to provide straightforward quantitative data regarding power consumption, including day/night usage and costs, many people shifted their behavior in a positive informed way.
Figure 1 illustrates an example individual’s ongoing total cholesterol readings presented in a clear and informative way. Anyone inspecting the chart can easily identify the overall trend, down, which is good, wonder about the range of numeric measurements (157-185) vs. the average and how this translates into good or bad health tiers (e.g.; under 200 is generally good, but a rising trend that is still under 200 could be an indication of arising health issues for that individual), and inquisitively wonder about the peaks. The next level of information would be HDL and LDL readings, small lipids as is now de rigueur and triglycerides, but even this simple plot of total cholesterol measures is understandable, useful and potentially actionable. It is also the perfect level of information for individuals who are interested in being responsible for self-managing their health but from an efficient, easily-actionable level that does not require deep engagement of time or knowledge acquistion.
Some of the most obvious aspects to include in a health literacy toolkit would be nutritional information and its interpretation, caloric consumption and expenditure and ongoing quantitative measures of health from blood analysis and other tests (e.g.; blood pressure, glucose, cholesterol, BMI, weight, VO2 max, etc.). The data can be summarized (with detail available) and directly linked to actionable explanatory information (e.g.; measures may go up or down if they were not measured at the same time or situation, for example if a meal had been eaten before some but not all of the measurements). Other components of a standard health literacy toolkit could include where and how to obtain information and tools for self-tracking, how to integrate multiple data sources into a unified view, and how and what to expect when interacting with the medical community. Genomics is already part of the health literacy toolkit for early adopters and could become a standard toolkit component for everyone within five years, already helpful Genetics 101 sites are emerging.
Automated health monitoring tools
Health-self management in large quadrants of the population could accelerate with the advent of automated health monitoring tools that would capture frequent datapoints and aggregate the information into easily viewable web-based charts. Many devices such as blood pressure monitors, heart monitors and scales are now battery-intensive Bluetooth-enabled which is a nice intermediate step but what is really needed is for all of these monitoring devices to be directly on home WiFi networks. Where possible, having the monitoring applications directly on the smartphone is another obvious step rather than having separate devices. There are some WiFi-enabled devices, for example the FitBit calorimeter, which has been delayed in launching, and glucose monitors such as the GlucoMON, however its $75/month subscription fee appears exorbitant.
Sunday, June 14, 2009
Genomics: highest-impact near-term advance
Genomics is making faster progress than any other technology in recent history. Usually the vista from any point on an exponential curve looks flat to the experiencer but not so with consumer genomics, the field is exponentiating from any vantage point. Genomics scientific research and commercialization issues were discussed with excitement at the first-ever consumer genomics conference in Boston, June 9-11, 2009. (A PDF of this blogpost is available here.)
Summary
- Advent of the whole human genome: Automatic whole human genome sequencing of all individuals could likely be a reality in the next few years
- Medically actionable now: Genetic data is medically actionable now and becoming increasing more so, particularly in routing higher-risk individuals into earlier screening. It is estimated that each individual is in the upper 5% risk tier for at least one chronic disease.
- New ICT era (information and communications technology): Genomic data requires a significant new level of information processing, storage and transfer. One whole human genome can range from 6GB-8TB in terms of the data currently transferred between researchers.
- Social inevitability: Widespread genomic sequencing appears to be inevitable which has great benefits together with social challenges such as revealing non-paternity (10-15% in the U.S.), terminal disease conditions and reproductive issues (e.g.; recessive carrier status).
- Heightened role of the consumer: Consumers will have unprecedented access to health information about themselves and could take a much more active and self-directed role in their health management, more likely responding favorably than being consumed with their ‘incidentalome.’
- For some time, physicians have been ordering any number of one-off genetic tests for specific conditions such as Cystic Fibrosis, Huntington’s Disease, breast cancer (mutations in the BRCA1 and BRCA2 genes) and other conditions. Physicians can also order any of the below tests for patients.
- Single condition tests (DNA Direct, $200-1,000)
- SNP Chip risk assessment tests (23andme ($399, down from $1,000), DeCODEme ($985), Navigenics ($2,499))
- Whole genome scan (Knome ($99,500)) or whole exome scan (Knome ($24,500)) [The price just dropped from $350,000 to $99,000, but it would still seem silly to purchase now when a few more zeros might drop off within months]
- Personal Genome Project (PGP), Harvard Medical School, genome sequencing for free in exchange for open data publishing, now expanding from ten subjects to 100,000
- Family planning genetic screening: Counsyl
- Mate compatibility analysis based on immune system variation: ScientificMatch, GenePartner (The next obvious component would be including recessive disease carrier status in the back-end matching algorithms of dating services)
Current genomic testing issues: validity and utility
Validity
There are differing levels of data validity depending on which chip array and methodology is used to sequence the genomic data. Illumina reports being at two 9s now (e.g.; 99.99% error free; experiencing one error per 1,000 reads) and is hoping to move to four and then six 9s of quality. Sequencing is done at different levels of coverage ranging from 1x to 30x coverage, meaning how many times a sequence is read; 30x coverage is the most accurate and highest industry standard at present.
A few people who have tried multiple DTC (direct-to-consumer) SNP chip offerings have found consistent genotyping data (e.g.; having a ‘CT’ at a certain SNP), but different interpretations in lifetime risk probabilities as different markers are evaluated and rolled up into risk assessments across the companies. The risk of false negatives and false positives abounds.
Sources: Navigenics, DeCODEme, 23andme
Not only do different services map different markers to meta conditions like cardiovascular disease, but the most relevant medical SNPs are often not included in DTC SNP chips, probably due to patent and cost issues. A notable example is Myriad, which owns patents on the breast cancer-related BRCA1 and BRCA2 genes. This has become the focus of a timely lawsuit brought by the ACLU regarding the patentability of natural materials such as genes and industry norms of how genes are licensed for diagnosis and therapy.
Utility
There is ample room for risk interpretation mechanisms for polygenic conditions to become more sophisticated, right now the practice is a multiplicative technique, taking the risk value for each genotyped allele associated with the condition and multiplying them together; weighting and cluster-evaluation would be obvious refinements that research may support over time.
Genetic variation and disease causality
NHGRI and other GWAS (genome-wide association studies) researchers find that genes, as they have been studied so far, only account for a small percent of explaining disease. However, studies have been preliminary, the 1,000 genomes studied may not be enough for complete understanding, for example, about 35 common diseases have been found to have widely replicated common variants. One next step targeted by the NHGRI is to look at rare variants, low-frequency (e.g.; 1-2%) GWAS variants with intermediate penetrance, to possibly explain a larger percentage of disease causality. Simultaneously, our systemic understanding of biology is slowly improving, it seems that in many disease cases it may not be the gene or genotype, but rather the number of copies of the same gene (CNVs), translocations, inversions, and other problems with gene expression and DNA repair that are responsible for disease.
Knowledge gap
Genomic technology has been moving so fast that at present, most physicians do not have genetic training. The genetics community is the primary party helping to generate, interpret, present and monitor genomic data. Over time, other communities like physicians and genetic counselors (one of the world’s fastest-growing job categories) will hopefully become helpful in interpreting data together with patients. Genetic training is a key target area of CME (continuing medical education), for example the National Coalition for Professional Education in Genetics' "Genetics Education for Health Professionals: What are the Key Messages? How do we deliver them?” (Sep 2009) and Harvard Medical School’s “What the Primary Care Provider needs to know about the Genetic Basic of Adult Medicine” (Oct 2009).
That disease has a molecular basis is now undisputed and medicine is slowly shifting to reorganize around this. Presently, 1,400 genes can be tested to inform various clinical decisions, and 225 are deemed clinically significant. 100 new tests are being added annually. In some cases, medical information exists but is not being used, for example a straightforward marker for poor drug metabolizers, CYP2D6. About 10% of Caucasians are poor metabolizers however this is not routinely tested for ahead of time (nor in the DTC SNP chip tests mentioned above) and the same drugs are given to all patients in a trial and error process, sometimes in lower doses (e.g.; warfarin) due to fear of overdosing those for whom it could be harmful.
Another example of medical relevancy in genomic testing is the NHGRI’s GWAS study finding of the first nine genetic risk variants for type 2 diabetes: TCF7L2, IGF2BP2, CDKN2A/B, FTO, CDKAL1, KCNJ11, HHEX/IDE, SLC30A8 and PPARG; particularly the first one, TCF7L2. Higher-risk individuals identified early in life could receive targeted healthcare.
Additive statistical approach
So far, general genomic testing suggests that on average, each patient is in the upper 5% risk tier for at least one chronic disease (e.g.; cancer, cardiovascular disease, myocardial infarction, etc.) and that there is value in understanding genomic risk factors earlier in life. Whole human genome sequencing automatically at birth could mean a lifetime of personally relevant healthcare.
Although genomic tests do not predict polygenic disease definitively, they are medically actionably in taking conventional risk percentages (e.g.; American female lifetime breast cancer risk = 12%; American male lifetime prostate cancer risk = 16%) and layering on the specific genetic risk of the individual to route higher-risk individuals to screening and therapeutics earlier. Several researchers estimate that the earlier identification of higher risk patients could reduce overall healthcare costs by about ~$100,000 per person per condition.
Patient behavior: a key component of medical actionability
Although there is no known cure for Alzheimer’s Disease, and even a firm diagnosis can only be made at autopsy, Boston University’s REVEAL study has shown that people do change their behavior after receiving a positive diagnosis for Alzheimer’s Disease (mainly through purchasing supplements and some increase in exercise). It is also known that mid-life cholesterol levels correlate with Alzheimer’s Disease, so the highly actionable behavior for someone with an APO E4 positive allele could be more closely managing cholesterol intake.
Family history
The role of family history is another important component of disease prevention, diagnosis and management, and there are starting to be helpful web-based tools for consumers to assemble, manage and access family history data such as My Family Health Portrait.
Technology status
Technology advance has been the key enabler of the genomics revolution. The first genome sequencing project, completed in 2003 cost $3b. Now, the cost of genetic sequencing is dropping to the point where a $100 whole human genome may be available in the next few years, in 2010 according to Pacific Biosciences. There are several next-gen sequencing platforms in process now to supercede the current array-based method.
Next-gen sequencing platforms
Next-gen genomic sequencing platforms are generally falling into two categories, those using synthesis (specifically multiplex cyclic sequencing by synthesis) and those not using synthesis. Some of the most interesting next-gen companies using synthesis are Pacific Biosciences, Ion Torrent Systems and RainDance Technologies. Some of the most exciting non-synthesis-based next-gen sequencing companies are Oxford Nanopore Technologies, and NABsys and Halcyon. NABsys and Halcyon are electromagnetically-based rather than optically-based which means they are not dependent on light or fluorescence so the cameras can go much faster, perhaps 10,000 frames per second. Harvard Medical School maintains a nice overview of current and emerging gene sequencing technologies.
Transcriptome, proteome, metabolome, microbiome…
In addition to improving the cost and speed of existing genomic scanning, sequencing advances could open up the way to the eventual characterization of the whole cell and its interactions through the sequencing of the transcriptome, the proteome, the metabolome, the microbiome and other biological features. In the farther future, histone modification sequencing, DNA methylation, acetylation and phosphorylation are other characterization processes of interest that could be included.
Petabyte data era: processing, storage and transfer challenges
The biggest challenge consuming national genomic research labs at present is data processing and network communications. Genomic data is growing at 10x per year (vs. Moore’s Law growing at 1.5x per year). Research labs have problems with data storage, mapping and access, together with intra-site data transfer and external transfer. Shipping terabyte drives via fedex is the best current data transfer method, and at least one lab finds resequencing data cheaper than storing it.
The raw data of the 6b base pair whole human genome is 6GB, not challenging to store, but challenging to work with, it is not like just opening up and manipulating a word document. New data processing algorithms will need to be developed to interact with whole genome data, link it to reference tools and make it searchable and meaningful. Whole businesses can be formed to focus on genomic data curation alone (a second wind for Google?).
Even though the most basic raw data version of the whole human genome is 6GB, the full collection of files in use by researchers for one whole human genome may reach 8TB. The full works may include an intensity file, a BAN file (binary), a SAN file (searchable) and other files with coordinates, variations and other aspects. Part of the challenge is that appropriate data abstractions from the raw sequencing output are not yet known so all the data is kept. There is not yet a good reference model. Apparently, the Archeron X-Prize for genomics (sequencing 100 human genomes within 10 days or less at a maximum cost of $10,000 per genome) remains outstanding not because it cannot be done, but because the results cannot be recapitulated.
Testing inevitability and social implications
It seems quite possible that initial and ongoing whole human genome sequencing (and eventually, on-demand proteome, metabalome, microbiome, etc. sequencing) would be a routine component of everyone’s EMR (electronic medical record) available to both patients and physicians for ongoing predictive, preventive healthcare monitoring. There are some important social implications of widespread whole human genome testing, for example:
Non-paternity
One genetic issue is non-paternity (studies suggest 10-15% is the ongoing rate of non-paternity in the U.S.). In the era of whole human genome sequencing, paternity would be quite easy to trace. One possible impact is that the divorce rate could increase and single mothers could be stratified into lower economic tiers.
Right not to know
Another genetic issue is that of a person’s right not to know about their medical situation. With improving remedies, the right not to know becomes a lot less important. Also it may be quite straightforward for practitioners to deliver healthcare without breaching the patient’s right not to know their genetic information as they do currently. With more actionable treatments, it could become the social norm to know your genetic profile, to learn about potential conditions and work collaboratively with others with similar conditions in attempts to mobilize long-tail medicine, as PatientsLikeMe health social network participants are doing to run their own clinical trials.
Discrimination
GINA, the Genetic Information Nondiscrimination Act of 2008, protects U.S. citizens from discrimination by employers and insurance companies. It is a step in the right direction, but many are not reassured. The law has some holes, such as not covering long-term care providers, and will have to be strengthened via interpretation as real-life cases arise.
DNA Forensics – Gattaca?
In an age of inexpensive genomic testing, the on-demand testing of other people (such as a prospective mate, business partner, supervisor or tenant), as portrayed in the movie Gattaca, could easily occur; one such example provided decisive evidence in a recent divorce case. DNA privacy would become impossible as a practical matter. DNA privacy would become impossible as a practical matter. However, precisely because everyone would be subject to genetic openness and since the present world is not one of scarcity and control as the dystopian Gattaca, it may be that DNA testing and knowledge would not be a substantive issue. Already, several individuals in support of hastened scientific advance and open medicine have open-sourced their genomic data on the SNPedia or via the Personal Genome Project.
Venture capital investment opportunities
There are many exciting potential opportunities for venture capitalists, entrepreneurs and researchers in helping to realize the genomics revolution. The money is already arriving before the physicians as companies, backed by varying degrees of research, seek to monetize genetic risk. The potential demand for personal genomic products and services could be enormous, for example, the marker for weight-loss products is a $40b/year. Here are some potential opportunities:
- Personalized genetic testing, counseling, supplements and other action programs and remedies, for example, Inherent Health’s Weight Management, Heart Health and other tests, and the APO E Gene Diet.
- More DTC (direct-to-consumer) genetic testing and interpretation offerings stratified towards differing enduser tiers (e.g.; the aggressive early adopter, the lay person, the Boomer, the Gen Y’er)
- A line of genomic testing services to be offered by spas and private clinics; positioned as a luxury item vs. a medical necessity to accelerate adoption
- Next-gen sequencing, and next-next-gen sequencing, innovating the technology and the applications to commercialize the technology
- Web-based tools for integrating medical records, family history and genomic data, facilitating data collection, entry and access
- Genetic literacy products and services for physicians and consumers
- Web-based tools to appropriately and dynamically aggregate multiple risk alleles into chronic disease meta conditions such as cancer and cardiovascular disease
- Fee-based genomic data interpretation tools like the SNPedia’s Promethease
- Data processing algorithms to interact with whole genome data, making it searchable and meaningful with links to external reference databases
- Genomic data curation
- Cloud computing for genomic data analysis
- Health social networks or other tools for deep longitudinal monitoring over time by consumers/patients of many complex health factors
As our molecular understanding of disease progresses and genomic testing continues to decrease in cost and become increasingly medically relevant, adoption could become extremely widespread almost overnight. Physicians could start to see the additive, precise information conferred by genomic testing as a means of improving the care they now deliver, finding themselves initially encouraged and eventually forced into the genomic revolution. Pharmaceutical companies could start to use genomic testing and pharmacogenomics as a means of improving efficacy in drug discovery and delivery, providing some much-needed assistance to their ailing cost models. Consumers could be radically empowered to become curious about and responsible for self-managing their health with automated easy-to-use tools. Genomics as an enhanced approach to healthcare could transform the quality of life worldwide for all humanity.
Sunday, June 07, 2009
Aging is solvable
That aging is understandable and solvable, not necessarily immediately but ultimately, was one topic not seeing a lot of opposition at the American Aging Association (AGE) conference in Phoenix AZ May 29 – June 1, 2009. Key research highlights are below.
Aging is a key contemporary concern, on the order of climate change, as all countries worldwide have populations increasingly stratified towards aging. Aging is not just a medical condition but a key challenge to be resolved for advanced societies to be successful in the long-term. Productivity, healthcare costs and happiness and comfort could all be improved with advances in the remedy of aging. Aging has advanced from a nebulous concept to concrete mechanisms that can be understood and managed. Thematically, most of the bioparts impacted in aging (cells, genes, proteins, neurons, etc.) seem to still be present in older organisms, just not functioning the way they did when the organisms were younger, suggesting that it may be possible to manage and reverse aging processes, and confirming the systemic nature of aging including, for example, the role of a healthy microenvironment and cell-cell signaling. Reductionism as an approach has proved unsuccessful.
Aging is a multidisciplinary phenomenon, involving different deterioration processes in different tissues over time. Aging involves a variety of fields (immunology, cancer, regenerative medicine, cognition, micronutrients, etc.) and a variety of levels of research species (C. elegans (worms), Drosophila (flies), mice, rats and humans). At AGE, the organizational structure was a focus on systems pathways, particularly signaling and hormones, together with a look at the role of proteins in aging.
AGE was an excellent place to obtain a broad and deep comprehension of how aging works. The systemic rigor required to characterize the process-intensive nature of aging has been making significant progress, with a much more detailed understanding of the complex nested multifactor pathways now existing as compared with that of even a few years ago. It is clear that the painstaking characterization work could be further improved with automation and quantitative tools, especially for example, digital linkage of aging pathways across organisms.
As with other life sciences areas, the potential widespread quick and cheap availability of the sequencing of genomes, proteomes, etc. is likely to dramatically change how the science of aging is conducted, though not guarantee quick solutions. As pathways continue to be confirmed, they can be digitized into software and nearly indefinite simulated iterations could be run before conducting time-consuming and expensive bench experiments in confirmation.
Many interventions work for extending the lifespans and healthspans of lower order organisms, for example knocking out any one of 200 known genes may extend the lifespan of the C. elegans worm but the specifics and replicability of the mechanisms in higher order organisms are not known. It does not make sense to directly translate point solutions up to mammals given the systemic nature of the organisms and aging processes. Even moving one biomarker for alcohol consumption from monkeys to humans is not direct.
Exciting new research findings
Reference links below and conference abstracts here
Aging is a key contemporary issue. Research is advancing both incrementally and radically in every area of aging. The highest immediate impact could come from working on aging problems upstream at important fulcrum points that impact everything below them, such as genetics, epigenetics and the immune function. The research is progressing and it is starting to be time for VCs, big pharma and DIYbio’ers to take advantage of the many interesting and actionable possibilities.
Sunday, May 31, 2009
The future of computing – rotaxanes?
One of the great human endeavors at the moment is being able to work at the molecular scale (e.g.; 1-100 nm), using organic and inorganic materials for a variety of purposes ranging from basic materials to computing to electronics to life sciences therapeutics to energy. This includes the designed direction of existing molecular processes (e.g.; biology) and the synthesis of novel materials, structures and dynamic behavior.
Three of the most interesting advances in working at the molecular scale and examples of bio-infotech convergence are described below…
1) Hybrid organic-inorganic rotaxanes
First is the March 2009 work of David Leigh’s lab at the University of Edinburgh in creating hybrid organic-inorganic rotaxanes. A rotaxane (rota/wheel + axis) is a mechanically-interlocked molecular structure, essentially a dumbbell shape with a ring around its middle (Figure 1), often man-made but occasionally existing in nature. In this case, the dumbbell portion of the hybrid organic-inorganic rotaxane is an organic amine, the ring around the middle is a metal.
The benefit of metal-organic frameworks is that they have the properties of both organic and inorganic materials; structural and functional properties from organic materials and electronic, magnetic and catalytic properties from inorganic materials. This rotaxane molecule has directed shuttle-like behavior, where the metal ring around the center can be pushed to bind at either end, with its biggest potential application being in quantum computing.
2) Bio-inorganic interfaces
A second interesting example of molecular scale work and bio-infotech convergence is biocomposites/GEPIs (genetically-engineered peptides for inorganics) which regulate cell behavior and improve binding at bio-inorganic interfaces by modifying surface chemistry and immobilizing infection-causing bioactive molecules. Candan Tamerler’s lab at the University of Washington is doing some interesting work in this area. Improved bio-inorganic interfaces are needed for reduced infection and seamless interaction between human wetware and implants: heart, hip, prosthetics, eye, brain, etc.
3) DNA nanotechnology
The third interesting bio-infotech convergence example is DNA nanotechnology, the notion of using DNA as a structural building material (for example, for self-directed rapid templating) rather than as an information carrier. One key use is employing DNA as a programmable scaffolding for the self-assembly of nanoscale electronic components, meaning that scaffolds comprised of self-assembled DNA serve as templates for the targeted deposition of ordered nanoparticles and molecular arrays. DNA is formed into tubes and then metallized in solution to produce ultra-thin metal wires. John Reif’s lab at Duke University, Erik Winfree’s lab at Caltech and many other groups are working on DNA nanotechnology. Moving to the molecular scale for electronics manufacture is imperative for maintaining Moore’s Law computing performance improvements.
Future implications
It seems likely that working at the molecular scale and bio-infotech convergence will continue to grow. Organic-inorganic hybridization approaches could proliferate to exploit the full suite of properties afforded by organic and inorganic inputs, and as researchers suggest, lead to novel properties and the ability to harness molecular dynamics for human use.
Sunday, May 24, 2009
Expanding notion of Computing
As we push to extend inorganic Moore’s Law computing to ever-smaller nodes, and simultaneously attempt to understand and manipulate existing high-performance nanoscale computers known as biology, it is becoming obvious that the notion of computing is expanding. The definition, models and realms of computation are all being extended.
Computing models are growing
At the most basic level, how to do computing (the computing model) is certainly changing. As illustrated in Figure 1, the traditional linear Von Neumann model is being extended with new materials, 3D architectures, molecular electronics and solar transistors. Novel computing models are being investigated such as quantum computing, parallel architectures, cloud computing, liquid computing and the cell broadband architecture like that used in the IBM Roadrunner supercomputer. Biological computing models and biology as a substrate are also under exploration with 3D DNA nanotechnology, DNA computing, biosensors, synthetic biology, cellular colonies and bacterial intelligence, and the discovery of novel computing paradigms existing in biology such as the topological equations by which ciliate DNA is encrypted.
At another level, subtly but importantly, where to do computing is changing from specialized locations the size of a large room in the 1970s to the destktop to the laptop, netbook and mobile device and smartphone. At present computers are still made of inorganic materials but introducing a variety of organic materials computing mechisms helps to expand the definition of what computing is. Ubiquitous sensors, personalized home electricity monitors, self-adjusting biofuels, molecular motors and biological computers do not sound like the traditional concept of computing. True next-generation drugs could be in the form of molecular machines. Organic components or organic/inorganic hybrid components, as the distinction dissolves, could be added to many object such as the smartphone. A mini-NMR or mini-Imager for mobile medical diagnostics from a disposable finger-prick blood sample would be an obvious addition.
Sunday, May 17, 2009
Synthetic biology – what is next?
Synthetic biology is the engineering of biology, re-designing existing biological systems and designing new ones, for a myriad of purposes. The most obvious killer apps are the improved synthesis of drugs and other medicines and the synthetic generation of biofuels.
Right now the most exciting aspect of synthetic biology –suggesting that the field is getting some traction – is that three key community constituents are getting more heavily involved: traditional academic researchers (SB 4.0 conference videos and agenda), undergraduates and high school students through the annual iGEM (international genetically engineered machines) competition (1200 students from 112 teams are expected at this fall’s iGEM Jamboree at MIT, and a growing group of non-institutionally affiliated enthusiasts, diybio’ers, the 2000s version of the Homebrew Computer Club, for both wetlab (an interesting recent example) and computer modeling, simulation and data management projects.
Other waves in the history of biotechnology have shown that life sciences problems tend to be much more complex, take much longer than expected to solve and ultimately underdeliver results. There is no reason to think that synthetic biology would be any different, but it is obviously not futile to work on the challenges. When the synbio community analogizes their status to the heterogeneous screws and bolts of the construction industry circa 1864, they are not kidding.
The DNA synthesis process is astonishingly unautomated, unstandardized and expensive ($0.50-$1.00 per base pair) at present (it would be $15-30 billion to synthesize the full genome of a human (ignoring ethical, legal, etc. issues)).Synthetic biology is a new field and the demand for synthesized DNA is still small; the 2,000 or so iGEM community members are the biggest market. Ginkgo Bioworks is working to deliver robotic synthesized DNA assembly and other startups would be likely to spring up in this area. Ginkgo has also helped to expand and improve one of the main synbio tools, the Registry of Standard Biological Parts.
Sunday, May 10, 2009
Status of cancer detection
The Canary Foundation’s annual symposium held May 4-6, 2009 indicated progress in two dimensions of a systemic approach to cancer detection: blood biomarker identification and molecular imaging analysis.
Systems approach to cancer detection
A systems approach is required for effective cancer detection as assays show that many proteins, miRNAs, gene variants and other biomarkers found in cancer are also present in healthy organisms. The two current methods are one, looking comprehensively at the full suite of genes and proteins, checking for over-expression, under-expression, mutation, quantity, proximity and other factors in a tapestry of biological interactions and two, seeking to identify biomarkers that are truly unique to cancer, for example resulting from post-translational modifications like glycosylation and phosphorylation. Establishing mathematical simulation models has also been an important step in identifying baseline normal variation, treatment windows and cost trade-offs.
Blood biomarker analysis
There are several innovative approaches to blood biomarker analysis including blood-based protein-assays (identifying and quantifying novel proteins related to cancer), methylation analysis (looking at abnormal methylation as a cancer biomarker) and miRNA biomarker studies (distinguishing miRNAs which originated from tumors). Creating antibodies and assays for better discovery is also advancing particularly protein detection approaches using zero, one and two antibodies.
Molecular Imaging
The techniques for imaging have been improving to molecular level resolution. It is becoming possible to dial-in to any set of 3D coordinates in the body with high-frequency, increase the temperature and destroy only that area of tissue. Three molecular imaging technologies appear especially promising: targeted microbubble ultrasound imaging (where targeted proteins attach to cancer cells and microbubbles are attached to the proteins which make the cancerous cells visible via ultrasound; a 10-20x cheaper technology than the CT scan alternative), Raman spectroscopy (adding light-based imaging to endoscopes) and a new imaging strategy using photoacoustics (light in/sound out).
Tools: Cancer Genome Atlas and nextgen sequencing
As with other high-growth science and technology areas, tools and research findings evolve in lockstep. The next generation of tools for cancer detection includes a vast cataloging of baseline and abnormal data and a more detailed level of assaying and sequencing. In the U.S., the NIH’s Cancer Genome Atlas is completing a pilot phase and being expanded to include 50 tumor types (vs. the pilot phase’s three types: glioblastoma, ovarian and lung) and abnormalities in 25,000 tumors. The project performs a whole genomic scan of cancer tumors, analyzing mutations, methylation, coordination, pathways, copy number, miRNAs and expression. A key tool is sequencing technology itself which is starting to broaden out from basic genomic scanning to targeted sequencing, whole RNA sequencing, methylome sequencing, histone modification sequencing, DNA methylation by arrays and RNA analysis by arrays. The next level would be including another layer of detail, areas such as acetylation and phosphorylation.
Future paradigm shifts: prevention, omnisequencing, nanoscience and synthetic biology
Only small percentages of annual cancer research budgets are spent on detection vs. treatment, but it is possible that the focus will be further upstreamed to prevention and health maintenance as more is understood about the disease mechanisms of cancer. Life sciences technology is not just moving at Moore’s Law paces but there are probably also some paradigm shifts coming.
The three most suggestive areas for coming life science discontinuities are genomic sequencing, nanoscience and synthetic biology.Genomic sequencing contemplates the routine scanning of each individual and tumor at multiple levels: genomic, proteomic, methylomic, etc. Nanoscience is the ability to design, construct and render mobile a large variety of molecular [biological] devices. Synthetic biology is designing new or modifying existing biological pathways in order to produce systems with superior or different properties, exercised by both traditional practitioners (recent conferences: Advances in Synthetic Biology, Synthetic Biology 4.0) and diybio’ers.
Sunday, May 03, 2009
Opportunities in level-two nanoscience
The April 20-24, 2009 Foundations of Nanoscience conference at Snowbird UT provided an interesting look at the wide variety of subfields and applications for nanoscience in thirteen tracks roughly organized into five areas: principles, materials, nanostructures, components and processes (Taxonomy, Quick Reference Guide to Current Research). Many of the nanoscience subfields have been in existence for five to ten years, however the different nanotechnology science and commerical efforts are still fairly isolated (for example, there could be an NNI roadmapping initiative). Nanoscience is largely still at the stage of experimental demos rather than quick advances to commercialization. The diversity of approaches demonstrates creativity and the increasing complexity, refinement and sophistication signals that nanoscience could be moving into a more mature era.
Definition and applications
Nanoscience is the interdisciplinary nexus of several fields including chemistry, physics, electronics, biology and materials - a convergence hub between life and technology, organics and inorganics, biotic and abiotic, top-down engineering and bottom-up nature. Researchers exhibit substrate agnosticism as approaches, techniques, tools and applications may be organic, inorganic or synthetic; the focus is on properties, functionality and requirements.
Nanoscience also encompasses fundamental understandings such as the definition of life, for example, it can be argued that self-replicating crystals constitute organic life. The potential uses of nanoscience are manifold, particularly in electronics, medicine, sensors and materials.
Drug delivery and bridging the gap from end-of-the-roadmap Moore’s Law computing to molecular electronics are the most urgent potential applications.
The central issue is working with today’s top-down engineered approaches which are specific but limited, to reach the molecular scale, by either extending existing methods or integrating or substituting them with molecular (organic) methods. Biology is a molecular system that works, in fact many interlinked systems. While it is messy to characterize and direct, it has tremendous potential both in its existing mechanisms and novel constructions. However, new materials and processes could be challenging to bring into the existing electronics fabrication value chain.
Status: increasing complexity and working with trade-offs
Broadly, nanoscience is currently in the phase of building on basic configurations to achieve more complex design motifs, for example scaling up circuit arrays from single to double digits, generating 3D construction materials such as 3D nanocrystals, making molecular motors from biological parts, producing active vs. static building blocks and a variety of structurally strong shapes such as icosahedra and other polyhedra. In addition to increasing complexity, another major theme is the sophisticated design trade-offs amongst a variety of parameters such as chirality, charge, planarity, time scale dynamics, thermodynamics, binding, distance, solubility, aggregation, functionalization and materials.
Wonder tools: DNA and CNTs
DNA and CNTs are the most widely used materials in nanoscience. DNA is a tremendously versatile tool not just as an information carrier and material for building structures but also as an external tagging agent on particles and as a template for directing the growth of nanocrystals and metal wires. As has long been realized, carbon nanotubes have many desirable properties for a wide range of applications but still prove elusive to manufacture to spec in large quantities.
Conclusion: moving nanoscience to nanotechnology
Many fields of science now operate at the nano or molecular scale and it is clearly useful to have a foundational characterization and established toolkit for molecular science. One next phase would be moving nanoscience to nanotechnology, seeing a tight linkage between the emerging novel materials, nanostructures and architectures to the engineering and realization of applications.
Sunday, April 26, 2009
Ultimate possibilities for life and technology
Thinking really long term, what would it be like if all matter, including life, could be designed and built to specification with nanotechnology and synthetic biology? Form factor could become ephemeral and purpose-driven. An intelligence could embody as a human, as a fleet of starships, as a crane, as a school of nanoparticles, or remain digital.
Some interesting issues could come up, say from having multiple persistent copies of one intelligence. What would the social, legal, economic etiquette and governing laws be? Or would these words even make sense anymore? The notion of the distinct individual may become obsolete.
Transhumanism will be an interesting and certainly divisive step, when groups or all humans have radically enhanced capabilities as compared with today. Posthumanism, the moment of speciation, may be quite a shock.
What about utility functions? In a digital format, traditional biological functions make a lot less sense. And what about emotion? Is there a relevant adaptation for the digital substrate or is emotion just another biology-based information system?
What is intelligence and is it reflected differently in a digital medium without the sensory input context of the physical world? Maybe intelligence is nothing more than manipulating patterns of information.
Finally, what are the ultimate possibilities for life and technology once joined? What if any would the activity be? Would the focus be on aesthetics? Analytics?
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